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Augusto AM, Raposeira H, Horta P, Mata VA, Aizpurua O, Alberdi A, Jones G, Razgour O, Santos SAP, Russo D, Rebelo H. Bat diversity boosts ecosystem services: Evidence from pine processionary moth predation. Sci Total Environ 2024; 912:169387. [PMID: 38110100 DOI: 10.1016/j.scitotenv.2023.169387] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Revised: 12/12/2023] [Accepted: 12/12/2023] [Indexed: 12/20/2023]
Abstract
Coniferous forests contribute to the European economy; however, they have experienced a decline since the late 1990s due to an invasive pest known as the pine processionary moth, Thaumetopoea pityocampa. The impacts of this pest are increasingly exacerbated by climate change. Traditional control strategies involving pesticides have had negative effects on public health and the environment. Instead, forest managers seek a more ecological and sustainable approach to management that promotes the natural actions of pest control agents. This study aims to evaluate the role of bats in suppressing pine processionary moths in pine forests and examine how the bat community composition and abundance influence pest consumption. Bats were sampled in the mountainous environment of the Serra da Estrela in central Portugal to collect faecal samples for DNA meta-barcoding analysis. We assessed the relationship between a) bat richness, b) bat relative abundance, c) bat diet richness, and the frequency of pine processionary moth consumption. Our findings indicate that sites with the highest bat species richness and abundance exhibit the highest levels of pine processionary moth consumption. The intensity of pine processionary moth consumption is independent of insect diversity within the site. The highest occurrence of pine processionary moth presence in bat diets is primarily observed in species that forage in cluttered habitats. A typical predator of pine processionary moths among bats is likely to be a forest-dwelling species that specialises in consuming Lepidoptera. These species primarily use short-range echolocation calls, which are relatively inaudible to tympanate moths, suitable for locating prey in cluttered environments, employing a gleaning hunting strategy. Examples include species from the genera Plecotus, Myotis, and Rhinolophus. This study enhances our understanding of the potential pest consumption services provided by bats in pine forests. The insights gained from this research can inform integrated pest management practices in forestry.
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Affiliation(s)
- A M Augusto
- ICS, Instituto de Ciências Sociais, Universidade de Lisboa, Av. Professor Aníbal de Bettencourt, 9, 1600-189 Lisboa, Portugal.
| | - H Raposeira
- CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório Associado, Campus de Vairão, 4485-661 Vairão, Portugal; BIOPOLIS Program in Genomics, Biodiversity and Land Planning, CIBIO, Campus de Vairão, 4485-661 Vairão, Portugal; Departamento de Biologia, Faculdade de Ciências, Universidade do Porto, Porto 4099-002, Portugal
| | - P Horta
- CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório Associado, Campus de Vairão, 4485-661 Vairão, Portugal; BIOPOLIS Program in Genomics, Biodiversity and Land Planning, CIBIO, Campus de Vairão, 4485-661 Vairão, Portugal; Departamento de Biologia, Faculdade de Ciências, Universidade do Porto, Porto 4099-002, Portugal
| | - V A Mata
- CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório Associado, Campus de Vairão, 4485-661 Vairão, Portugal; BIOPOLIS Program in Genomics, Biodiversity and Land Planning, CIBIO, Campus de Vairão, 4485-661 Vairão, Portugal
| | - O Aizpurua
- Globe Institute, University of Copenhagen, 1350 Copenhagen, Denmark
| | - A Alberdi
- Globe Institute, University of Copenhagen, 1350 Copenhagen, Denmark
| | - G Jones
- School of Biological Sciences, University of Bristol, 24 Tyndall Avenue, Bristol BS8 1TQ, UK
| | - O Razgour
- Biosciences, University of Exeter, Hatherly Laboratories, Prince of Wales Road, Exeter EX4 4PS, UK
| | - S A P Santos
- Instituto Politécnico de Setúbal, ESTBarreiro, Rua Américo da Silva Marinho, 2839-001 Lavradio, Portugal; LEAF-Linking Landscape, Environment, Agriculture and Food Research Center, Associate Laboratory TERRA, Instituto Superior de Agronomia, Universidade de Lisboa, Tapada da Ajuda, 1349-017 Lisboa, Portugal
| | - D Russo
- Laboratory of Animal Ecology and Evolution (AnEcoEvo), Dipartimento di Agraria, Università degli Studi di Napoli Federico II, via Università 100, I-80055 Portici, Napoli, Italy
| | - H Rebelo
- CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório Associado, Campus de Vairão, 4485-661 Vairão, Portugal; BIOPOLIS Program in Genomics, Biodiversity and Land Planning, CIBIO, Campus de Vairão, 4485-661 Vairão, Portugal; Instituto Politécnico de Setúbal, ESS, Campus da Estefanilha, Setúbal, Portugal; NBI, Natural Business Intelligence, Régia Douro Park, 5000-033 Andrães, Vila Real, Portugal
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Tian J, Jones G, Lin X, Zhou Y, King A, Vickers J, Pan F. Letter to the Editor: Chronic Pain in Multiple Sites and Dementia: A Vicious Cycle? J Prev Alzheimers Dis 2024; 11:527-528. [PMID: 38374760 DOI: 10.14283/jpad.2023.120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/21/2024]
Affiliation(s)
- J Tian
- Feng Pan, Menzies Institute for Medical Research, University of Tasmania, Private Bag 23, Hobart, Tasmania 7000, Australia. Phone: +61 3 6220 5943; Fax: +61 3 6226 7704; E-mail:
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Kanis JA, Johansson H, McCloskey EV, Liu E, Åkesson KE, Anderson FA, Azagra R, Bager CL, Beaudart C, Bischoff-Ferrari HA, Biver E, Bruyère O, Cauley JA, Center JR, Chapurlat R, Christiansen C, Cooper C, Crandall CJ, Cummings SR, da Silva JAP, Dawson-Hughes B, Diez-Perez A, Dufour AB, Eisman JA, Elders PJM, Ferrari S, Fujita Y, Fujiwara S, Glüer CC, Goldshtein I, Goltzman D, Gudnason V, Hall J, Hans D, Hoff M, Hollick RJ, Huisman M, Iki M, Ish-Shalom S, Jones G, Karlsson MK, Khosla S, Kiel DP, Koh WP, Koromani F, Kotowicz MA, Kröger H, Kwok T, Lamy O, Langhammer A, Larijani B, Lippuner K, Mellström D, Merlijn T, Nordström A, Nordström P, O'Neill TW, Obermayer-Pietsch B, Ohlsson C, Orwoll ES, Pasco JA, Rivadeneira F, Schott AM, Shiroma EJ, Siggeirsdottir K, Simonsick EM, Sornay-Rendu E, Sund R, Swart KMA, Szulc P, Tamaki J, Torgerson DJ, van Schoor NM, van Staa TP, Vila J, Wareham NJ, Wright NC, Yoshimura N, Zillikens MC, Zwart M, Vandenput L, Harvey NC, Lorentzon M, Leslie WD. Previous fracture and subsequent fracture risk: a meta-analysis to update FRAX. Osteoporos Int 2023; 34:2027-2045. [PMID: 37566158 PMCID: PMC7615305 DOI: 10.1007/s00198-023-06870-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Accepted: 07/22/2023] [Indexed: 08/12/2023]
Abstract
A large international meta-analysis using primary data from 64 cohorts has quantified the increased risk of fracture associated with a previous history of fracture for future use in FRAX. INTRODUCTION The aim of this study was to quantify the fracture risk associated with a prior fracture on an international basis and to explore the relationship of this risk with age, sex, time since baseline and bone mineral density (BMD). METHODS We studied 665,971 men and 1,438,535 women from 64 cohorts in 32 countries followed for a total of 19.5 million person-years. The effect of a prior history of fracture on the risk of any clinical fracture, any osteoporotic fracture, major osteoporotic fracture, and hip fracture alone was examined using an extended Poisson model in each cohort. Covariates examined were age, sex, BMD, and duration of follow-up. The results of the different studies were merged by using the weighted β-coefficients. RESULTS A previous fracture history, compared with individuals without a prior fracture, was associated with a significantly increased risk of any clinical fracture (hazard ratio, HR = 1.88; 95% CI = 1.72-2.07). The risk ratio was similar for the outcome of osteoporotic fracture (HR = 1.87; 95% CI = 1.69-2.07), major osteoporotic fracture (HR = 1.83; 95% CI = 1.63-2.06), or for hip fracture (HR = 1.82; 95% CI = 1.62-2.06). There was no significant difference in risk ratio between men and women. Subsequent fracture risk was marginally downward adjusted when account was taken of BMD. Low BMD explained a minority of the risk for any clinical fracture (14%), osteoporotic fracture (17%), and for hip fracture (33%). The risk ratio for all fracture outcomes related to prior fracture decreased significantly with adjustment for age and time since baseline examination. CONCLUSION A previous history of fracture confers an increased risk of fracture of substantial importance beyond that explained by BMD. The effect is similar in men and women. Its quantitation on an international basis permits the more accurate use of this risk factor in case finding strategies.
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Affiliation(s)
- J A Kanis
- Mary McKillop Institute for Health Research, Australian Catholic University, Melbourne, Australia.
- Centre for Metabolic Bone Diseases, University of Sheffield, Sheffield, UK.
| | - H Johansson
- Mary McKillop Institute for Health Research, Australian Catholic University, Melbourne, Australia
- Sahlgrenska Osteoporosis Centre, Institute of Medicine, University of Gothenburg, Gothenburg, Sweden
| | - E V McCloskey
- Centre for Metabolic Bone Diseases, University of Sheffield, Sheffield, UK
- MRC Versus Arthritis Centre for Integrated research in Musculoskeletal Ageing, Mellanby Centre for Musculoskeletal Research, University of Sheffield, Sheffield, UK
| | - E Liu
- Mary McKillop Institute for Health Research, Australian Catholic University, Melbourne, Australia
| | - K E Åkesson
- Clinical and Molecular Osteoporosis Research Unit, Department of Clinical Sciences, Lund University, Lund, Sweden
- Department of Orthopedics, Skåne University Hospital, Malmö, Sweden
| | - F A Anderson
- GLOW Coordinating Center, Center for Outcomes Research, University of Massachusetts Medical School, Worcester, MA, USA
| | - R Azagra
- Department of Medicine, Autonomous University of Barcelona, Barcelona, Spain
- Health Centre Badia del Valles, Catalan Institute of Health, Barcelona, Spain
- PRECIOSA-Fundación para la investigación, Barberà del Vallés, Barcelona, Spain
| | - C L Bager
- Nordic Bioscience A/S, Herlev, Denmark
| | - C Beaudart
- WHO Collaborating Centre for Public Health Aspects of Musculoskeletal Health and Aging, Division of Public Health, Epidemiology and Health Economics, University of Liège, Liège, Belgium
- Department of Health Services Research, University of Maastricht, Maastricht, the Netherlands
| | - H A Bischoff-Ferrari
- Department of Aging Medicine and Aging Research, University Hospital, Zurich, and University of Zurich, Zurich, Switzerland
- Centre on Aging and Mobility, University of Zurich and City Hospital, Zurich, Switzerland
| | - E Biver
- Division of Bone Diseases, Department of Medicine, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - O Bruyère
- WHO Collaborating Centre for Public Health Aspects of Musculoskeletal Health and Aging, Division of Public Health, Epidemiology and Health Economics, University of Liège, Liège, Belgium
| | - J A Cauley
- Department of Epidemiology, School of Public Health, University of Pittsburgh, Pittsburgh, Philadelphia, USA
| | - J R Center
- Skeletal Diseases Program, Garvan Institute of Medical Research, Sydney, NSW, Australia
- St Vincent's Clinical School, School of Medicine and Health, University of New South Wales Sydney, Sydney, NSW, Australia
- School of Medicine Sydney, University of Notre Dame Australia, Sydney, NSW, Australia
| | - R Chapurlat
- INSERM UMR 1033, Université Claude Bernard-Lyon1, Hôpital Edouard Herriot, Lyon, France
| | | | - C Cooper
- MRC Lifecourse Epidemiology Centre, University of Southampton, Southampton, UK
- NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospitals Southampton NHS Foundation Trust, Southampton, UK
- NIHR Oxford Biomedical Research Unit, University of Oxford, Oxford, UK
| | - C J Crandall
- Division of General Internal Medicine and Health Services Research, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
| | - S R Cummings
- San Francisco Coordinating Center, California Pacific Medical Center Research Institute, San Francisco, CA, USA
| | - J A P da Silva
- Coimbra Institute for Clinical and Biomedical Research, Faculty of Medicine, University of Coimbra, Coimbra, Portugal
- Rheumatology Department, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
| | - B Dawson-Hughes
- Bone Metabolism Laboratory, Jean Mayer US Department of Agriculture Human Nutrition Research Center on Aging, Tufts University, Boston, MA, USA
| | - A Diez-Perez
- Department of Internal Medicine, Hospital del Mar and CIBERFES, Autonomous University of Barcelona, Barcelona, Spain
| | - A B Dufour
- Marcus Institute for Aging Research, Hebrew Senior Life, Boston, MA, USA
- Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - J A Eisman
- Skeletal Diseases Program, Garvan Institute of Medical Research, Sydney, NSW, Australia
- St Vincent's Clinical School, School of Medicine and Health, University of New South Wales Sydney, Sydney, NSW, Australia
- School of Medicine Sydney, University of Notre Dame Australia, Sydney, NSW, Australia
| | - P J M Elders
- Petra JM Elders Department of General Practice, Amsterdam UMC, location AMC, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - S Ferrari
- Division of Bone Diseases, Department of Medicine, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Y Fujita
- Center for Medical Education and Clinical Training, Kindai University Faculty of Medicine, Osaka, Japan
| | - S Fujiwara
- Department of Pharmacy, Yasuda Women's University, Hiroshima, Japan
| | - C-C Glüer
- Section Biomedical Imaging, Molecular Imaging North Competence Center, Department of Radiology and Neuroradiology, University Medical Center Schleswig-Holstein Kiel, Kiel University, Kiel, Germany
| | - I Goldshtein
- Maccabitech Institute of Research and Innovation, Maccabi Healthcare Services, Tel Aviv, Israel
- Department of Epidemiology and Preventive Medicine, School of Public Health, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - D Goltzman
- Department of Medicine, McGill University and McGill University Health Centre, Montreal, Canada
| | - V Gudnason
- Icelandic Heart Association, Kopavogur, Iceland
- University of Iceland, Reykjavik, Iceland
| | - J Hall
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh, UK
| | - D Hans
- Interdisciplinary Centre of Bone Diseases, Bone and Joint Department, Lausanne University Hospital (CHUV) & University of Lausanne, Lausanne, Switzerland
| | - M Hoff
- Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Rheumatology, St Olavs Hospital, Trondheim, Norway
| | - R J Hollick
- Aberdeen Centre for Arthritis and Musculoskeletal Health, Epidemiology Group, University of Aberdeen, Aberdeen, UK
| | - M Huisman
- Department of Epidemiology and Data Science, Amsterdam Public Health Research Institute, VU University Medical Center, Amsterdam, The Netherlands
- Department of Sociology, VU University, Amsterdam, The Netherlands
| | - M Iki
- Department of Public Health, Kindai University Faculty of Medicine, Osaka, Japan
| | - S Ish-Shalom
- Endocrine Clinic, Elisha Hospital, Haifa, Israel
| | - G Jones
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Australia
| | - M K Karlsson
- Clinical and Molecular Osteoporosis Research Unit, Department of Clinical Sciences, Lund University, Lund, Sweden
- Department of Orthopedics, Skåne University Hospital, Malmö, Sweden
| | - S Khosla
- Robert and Arlene Kogod Center on Aging and Division of Endocrinology, Mayo Clinic College of Medicine, Mayo Clinic, Rochester, MN, USA
| | - D P Kiel
- Marcus Institute for Aging Research, Hebrew Senior Life, Boston, MA, USA
- Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - W-P Koh
- Healthy Longevity Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Singapore Institute for Clinical Sciences, Agency for Science Technology and Research (A*STAR), Singapore, Singapore
| | - F Koromani
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
- Department of Radiology and Nuclear Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - M A Kotowicz
- IMPACT (Institute for Mental and Physical Health and Clinical Translation), Deakin University, Geelong, Victoria, Australia
- Barwon Health, Geelong, Victoria, Australia
- Department of Medicine -Western Health, The University of Melbourne, St Albans, Victoria, Australia
| | - H Kröger
- Department of Orthopedics and Traumatology, Kuopio University Hospital, Kuopio, Finland
- Kuopio Musculoskeletal Research Unit, University of Eastern Finland, Kuopio, Finland
| | - T Kwok
- Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, Hong Kong
- Jockey Club Centre for Osteoporosis Care and Control, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, Hong Kong
| | - O Lamy
- Centre of Bone Diseases, Lausanne University Hospital, Lausanne, Switzerland
- Service of Internal Medicine, Lausanne University Hospital, Lausanne, Switzerland
| | - A Langhammer
- HUNT Research Centre, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
| | - B Larijani
- Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - K Lippuner
- Department of Osteoporosis, Bern University Hospital, University of Bern, Bern, Switzerland
| | - D Mellström
- Geriatric Medicine, Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Geriatric Medicine, Sahlgrenska University Hospital Mölndal, Mölndal, Sweden
| | - T Merlijn
- Department of General Practice, Amsterdam UMC, location AMC, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - A Nordström
- School of Sport Sciences, UiT The Arctic University of Norway, Tromsø, Norway
- Department of Health Sciences, Swedish Winter Sports Research Centre, Mid Sweden University, Östersund, Sweden
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - P Nordström
- Department of Public Health and Caring Sciences, Uppsala University, Uppsala, Sweden
| | - T W O'Neill
- National Institute for Health Research Manchester Biomedical Research Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
- Centre for Epidemiology Versus Arthritis, University of Manchester, Manchester, UK
| | - B Obermayer-Pietsch
- Department of Internal Medicine, Division of Endocrinology and Diabetology, Medical University Graz, Graz, Austria
- Center for Biomarker Research in Medicine, Graz, Austria
| | - C Ohlsson
- Sahlgrenska Osteoporosis Centre, Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Drug Treatment, Sahlgrenska University Hospital, Region Västra Götaland, Gothenburg, Sweden
| | - E S Orwoll
- Department of Medicine, Oregon Health and Science University, Portland, OR, USA
| | - J A Pasco
- IMPACT (Institute for Mental and Physical Health and Clinical Translation), Deakin University, Geelong, Victoria, Australia
- Barwon Health, Geelong, Victoria, Australia
- Department of Medicine -Western Health, The University of Melbourne, St Albans, Victoria, Australia
- Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia
| | - F Rivadeneira
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - A-M Schott
- Université Claude Bernard Lyon 1, U INSERM 1290 RESHAPE, Lyon, France
| | - E J Shiroma
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Baltimore, MD, USA
| | - K Siggeirsdottir
- Icelandic Heart Association, Kopavogur, Iceland
- Janus Rehabilitation, Reykjavik, Iceland
| | - E M Simonsick
- Translational Gerontology Branch, National Institute on Aging Intramural Research Program, Baltimore, MD, USA
| | - E Sornay-Rendu
- INSERM UMR 1033, University of Lyon, Hôpital Edouard Herriot, Lyon, France
| | - R Sund
- Kuopio Musculoskeletal Research Unit, University of Eastern Finland, Kuopio, Finland
| | - K M A Swart
- Petra JM Elders Department of General Practice, Amsterdam UMC, location AMC, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
- PHARMO Institute for Drug Outcomes Research, Utrecht, The Netherlands
| | - P Szulc
- INSERM UMR 1033, University of Lyon, Hôpital Edouard Herriot, Lyon, France
| | - J Tamaki
- Department of Hygiene and Public Health, Faculty of Medicine, Educational Foundation of Osaka Medical and Pharmaceutical University, Osaka, Japan
| | - D J Torgerson
- York Trials Unit, Department of Health Sciences, University of York, York, UK
| | - N M van Schoor
- Department of Epidemiology and Data Science, Amsterdam Public Health Research Institute, VU University Medical Center, Amsterdam, The Netherlands
| | - T P van Staa
- Centre for Health Informatics, Faculty of Biology, Medicine and Health, School of Health Sciences, University of Manchester, Manchester, UK
| | - J Vila
- Statistics Support Unit, Hospital del Mar Medical Research Institute, CIBER Epidemiology and Public Health (CIBERESP), Barcelona, Spain
| | - N J Wareham
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - N C Wright
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - N Yoshimura
- Department of Preventive Medicine for Locomotive Organ Disorders, The University of Tokyo Hospital, Tokyo, Japan
| | - M C Zillikens
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - M Zwart
- PRECIOSA-Fundación para la investigación, Barberà del Vallés, Barcelona, Spain
- Health Center Can Gibert del Plà, Catalan Institute of Health, Girona, Spain
- Department of Medical Sciences, University of Girona, Girona, Spain
- GROIMAP/GROICAP (research groups), Unitat de Suport a la Recerca Girona, Institut Universitari d'Investigació en Atenció Primària Jordi Gol, Girona, Spain
| | - L Vandenput
- Mary McKillop Institute for Health Research, Australian Catholic University, Melbourne, Australia
- Sahlgrenska Osteoporosis Centre, Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - N C Harvey
- MRC Lifecourse Epidemiology Centre, University of Southampton, Southampton, UK
- NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospitals Southampton NHS Foundation Trust, Southampton, UK
| | - M Lorentzon
- Mary McKillop Institute for Health Research, Australian Catholic University, Melbourne, Australia
- Sahlgrenska Osteoporosis Centre, Institute of Medicine, University of Gothenburg, Gothenburg, Sweden
| | - W D Leslie
- Department of Medicine, University of Manitoba, Winnipeg, Manitoba, Canada
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Lu AT, Fei Z, Haghani A, Robeck TR, Zoller JA, Li CZ, Lowe R, Yan Q, Zhang J, Vu H, Ablaeva J, Acosta-Rodriguez VA, Adams DM, Almunia J, Aloysius A, Ardehali R, Arneson A, Baker CS, Banks G, Belov K, Bennett NC, Black P, Blumstein DT, Bors EK, Breeze CE, Brooke RT, Brown JL, Carter GG, Caulton A, Cavin JM, Chakrabarti L, Chatzistamou I, Chen H, Cheng K, Chiavellini P, Choi OW, Clarke SM, Cooper LN, Cossette ML, Day J, DeYoung J, DiRocco S, Dold C, Ehmke EE, Emmons CK, Emmrich S, Erbay E, Erlacher-Reid C, Faulkes CG, Ferguson SH, Finno CJ, Flower JE, Gaillard JM, Garde E, Gerber L, Gladyshev VN, Gorbunova V, Goya RG, Grant MJ, Green CB, Hales EN, Hanson MB, Hart DW, Haulena M, Herrick K, Hogan AN, Hogg CJ, Hore TA, Huang T, Izpisua Belmonte JC, Jasinska AJ, Jones G, Jourdain E, Kashpur O, Katcher H, Katsumata E, Kaza V, Kiaris H, Kobor MS, Kordowitzki P, Koski WR, Krützen M, Kwon SB, Larison B, Lee SG, Lehmann M, Lemaitre JF, Levine AJ, Li C, Li X, Lim AR, Lin DTS, Lindemann DM, Little TJ, Macoretta N, Maddox D, Matkin CO, Mattison JA, McClure M, Mergl J, Meudt JJ, Montano GA, Mozhui K, Munshi-South J, Naderi A, Nagy M, Narayan P, Nathanielsz PW, Nguyen NB, Niehrs C, O'Brien JK, O'Tierney Ginn P, Odom DT, Ophir AG, Osborn S, Ostrander EA, Parsons KM, Paul KC, Pellegrini M, Peters KJ, Pedersen AB, Petersen JL, Pietersen DW, Pinho GM, Plassais J, Poganik JR, Prado NA, Reddy P, Rey B, Ritz BR, Robbins J, Rodriguez M, Russell J, Rydkina E, Sailer LL, Salmon AB, Sanghavi A, Schachtschneider KM, Schmitt D, Schmitt T, Schomacher L, Schook LB, Sears KE, Seifert AW, Seluanov A, Shafer ABA, Shanmuganayagam D, Shindyapina AV, Simmons M, Singh K, Sinha I, Slone J, Snell RG, Soltanmaohammadi E, Spangler ML, Spriggs MC, Staggs L, Stedman N, Steinman KJ, Stewart DT, Sugrue VJ, Szladovits B, Takahashi JS, Takasugi M, Teeling EC, Thompson MJ, Van Bonn B, Vernes SC, Villar D, Vinters HV, Wallingford MC, Wang N, Wayne RK, Wilkinson GS, Williams CK, Williams RW, Yang XW, Yao M, Young BG, Zhang B, Zhang Z, Zhao P, Zhao Y, Zhou W, Zimmermann J, Ernst J, Raj K, Horvath S. Author Correction: Universal DNA methylation age across mammalian tissues. Nat Aging 2023; 3:1462. [PMID: 37674040 PMCID: PMC10645586 DOI: 10.1038/s43587-023-00499-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/08/2023]
Affiliation(s)
- A T Lu
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Altos Labs, San Diego Institute of Science, San Diego, CA, USA
| | - Z Fei
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Statistics, University of California, Riverside, Riverside, CA, USA
| | - A Haghani
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Altos Labs, San Diego Institute of Science, San Diego, CA, USA
| | - T R Robeck
- Zoological SeaWorld Parks and Entertainment, Orlando, FL, USA
| | - J A Zoller
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
| | - C Z Li
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
| | - R Lowe
- Altos Labs, Cambridge Institute of Science, Cambridge, UK
| | - Q Yan
- Altos Labs, San Diego Institute of Science, San Diego, CA, USA
| | - J Zhang
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - H Vu
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | - J Ablaeva
- Department of Biology, University of Rochester, Rochester, NY, USA
| | - V A Acosta-Rodriguez
- Department of Neuroscience, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - D M Adams
- Department of Biology, University of Maryland, College Park, MD, USA
| | - J Almunia
- Loro Parque Fundacion, Puerto de la Cruz, Spain
| | - A Aloysius
- Department of Biology, University of Kentucky, Lexington, KY, USA
| | - R Ardehali
- Division of Cardiology, Department of Internal Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - A Arneson
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | - C S Baker
- Marine Mammal Institute, Oregon State University, Newport, OR, USA
| | - G Banks
- School of Science and Technology, Clifton Campus, Nottingham Trent University, Nottingham, UK
| | - K Belov
- School of Life and Environmental Sciences, the University of Sydney, Sydney, New South Wales, Australia
| | - N C Bennett
- Department of Zoology and Entomology, University of Pretoria, Hatfield, South Africa
| | - P Black
- Busch Gardens Tampa, Tampa, FL, USA
| | - D T Blumstein
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, CA, USA
- Rocky Mountain Biological Laboratory, Crested Butte, CO, USA
| | - E K Bors
- Marine Mammal Institute, Oregon State University, Newport, OR, USA
| | - C E Breeze
- Altius Institute for Biomedical Sciences, Seattle, WA, USA
| | - R T Brooke
- Epigenetic Clock Development Foundation, Los Angeles, CA, USA
| | - J L Brown
- Center for Species Survival, Smithsonian Conservation Biology Institute, Front Royal, VA, USA
| | - G G Carter
- Department of Evolution, Ecology and Organismal Biology, The Ohio State University, Columbus, OH, USA
| | - A Caulton
- AgResearch, Invermay Agricultural Centre, Mosgiel, New Zealand
- Department of Biochemistry, University of Otago, Dunedin, New Zealand
| | - J M Cavin
- Gulf World, Dolphin Company, Panama City Beach, FL, USA
| | - L Chakrabarti
- School of Veterinary Medicine and Science, University of Nottingham, Nottingham, UK
| | - I Chatzistamou
- Department of Pathology, Microbiology and Immunology, School of Medicine, University of South Carolina, Columbia, SC, USA
| | - H Chen
- Department of Pharmacology, Addiction Science and Toxicology, the University of Tennessee Health Science Center, Memphis, TN, USA
| | - K Cheng
- Medical Informatics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - P Chiavellini
- Biochemistry Research Institute of La Plata, Histology and Pathology, School of Medicine, University of La Plata, La Plata, Argentina
| | - O W Choi
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - S M Clarke
- AgResearch, Invermay Agricultural Centre, Mosgiel, New Zealand
| | - L N Cooper
- Department of Anatomy and Neurobiology, Northeast Ohio Medical University, Rootstown, OH, USA
| | - M L Cossette
- Department of Environmental and Life Sciences, Trent University, Peterborough, Ontario, Canada
| | - J Day
- Taronga Institute of Science and Learning, Taronga Conservation Society Australia, Mosman, New South Wales, Australia
| | - J DeYoung
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - S DiRocco
- SeaWorld of Florida, Orlando, FL, USA
| | - C Dold
- Zoological Operations, SeaWorld Parks and Entertainment, Orlando, FL, USA
| | | | - C K Emmons
- Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, USA
| | - S Emmrich
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - E Erbay
- Altos Labs, San Francisco, CA, USA
| | - C Erlacher-Reid
- SeaWorld of Florida, Orlando, FL, USA
- SeaWorld Orlando, Orlando, FL, USA
| | - C G Faulkes
- School of Biological and Behavioural Sciences, Queen Mary University of London, London, UK
| | - S H Ferguson
- Fisheries and Oceans Canada, Freshwater Institute, Winnipeg, Manitoba, Canada
- Department of Biological Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - C J Finno
- Department of Population Health and Reproduction, University of California, Davis School of Veterinary Medicine, Davis, CA, USA
| | | | - J M Gaillard
- Universite de Lyon, Universite Lyon 1, CNRS, Laboratoire de Biometrie et Biologie Evolutive, Villeurbanne, France
| | - E Garde
- Greenland Institute of Natural Resources, Nuuk, Greenland
| | - L Gerber
- Evolution and Ecology Research Centre, School of Biological, Earth and Environmental Sciences, UNSW Sydney, Sydney, New South Wales, Australia
| | - V N Gladyshev
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - V Gorbunova
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - R G Goya
- Biochemistry Research Institute of La Plata, Histology and Pathology, School of Medicine, University of La Plata, La Plata, Argentina
| | - M J Grant
- Applied Translational Genetics Group, School of Biological Sciences, Centre for Brain Research, the University of Auckland, Auckland, New Zealand
| | - C B Green
- Department of Neuroscience, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - E N Hales
- Department of Population Health and Reproduction, University of California, Davis School of Veterinary Medicine, Davis, CA, USA
| | - M B Hanson
- Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, USA
| | - D W Hart
- Department of Zoology and Entomology, University of Pretoria, Hatfield, South Africa
| | - M Haulena
- Vancouver Aquarium, Vancouver, British Columbia, Canada
| | - K Herrick
- SeaWorld of California, San Diego, CA, USA
| | - A N Hogan
- Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - C J Hogg
- School of Life and Environmental Sciences, the University of Sydney, Sydney, New South Wales, Australia
| | - T A Hore
- Department of Anatomy, University of Otago, Dunedin, New Zealand
| | - T Huang
- Division of Human Genetics, Department of Pediatrics, University at Buffalo, Buffalo, NY, USA
- Division of Genetics and Metabolism, Oishei Children's Hospital, Buffalo, NY, USA
| | | | - A J Jasinska
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - G Jones
- School of Biological Sciences, University of Bristol, Bristol, UK
| | | | - O Kashpur
- Mother Infant Research Institute, Tufts Medical Center, Boston, MA, USA
| | - H Katcher
- Yuvan Research, Mountain View, CA, USA
| | | | - V Kaza
- Peromyscus Genetic Stock Center, University of South Carolina, Columbia, SC, USA
| | - H Kiaris
- Peromyscus Genetic Stock Center, University of South Carolina, Columbia, SC, USA
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, SC, USA
| | - M S Kobor
- Edwin S.H. Leong Healthy Aging Program, Centre for Molecular Medicine and Therapeutics, University of British Columbia, Vancouver, British Columbia, Canada
| | - P Kordowitzki
- Institute of Animal Reproduction and Food Research of the Polish Academy of Sciences, Olsztyn, Poland
- Institute for Veterinary Medicine, Nicolaus Copernicus University, Torun, Poland
| | - W R Koski
- LGL Limited, King City, Ontario, Canada
| | - M Krützen
- Evolutionary Genetics Group, Department of Evolutionary Anthropology, University of Zurich, Zurich, Switzerland
| | - S B Kwon
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | - B Larison
- Department of Ecology and Evolutionary Biology, UCLA, Los Angeles, CA, USA
- Center for Tropical Research, Institute for the Environment and Sustainability, UCLA, Los Angeles, CA, USA
| | - S G Lee
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - M Lehmann
- Biochemistry Research Institute of La Plata, Histology and Pathology, School of Medicine, University of La Plata, La Plata, Argentina
| | - J F Lemaitre
- Universite de Lyon, Universite Lyon 1, CNRS, Laboratoire de Biometrie et Biologie Evolutive, Villeurbanne, France
| | - A J Levine
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - C Li
- Texas Pregnancy and Life-course Health Center, Southwest National Primate Research Center, San Antonio, TX, USA
- Department of Animal Science, College of Agriculture and Natural Resources, Laramie, WY, USA
| | - X Li
- Technology Center for Genomics and Bioinformatics, Department of Pathology and Laboratory Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - A R Lim
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - D T S Lin
- Centre for Molecular Medicine and Therapeutics, BC Children's Hospital Research Institute, University of British Columbia, Vancouver, British Columbia, Canada
| | | | - T J Little
- Institute of Ecology and Evolution, School of Biological Sciences, University of Edinburgh, Edinburgh, UK
| | - N Macoretta
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - D Maddox
- White Oak Conservation, Yulee, FL, USA
| | - C O Matkin
- North Gulf Oceanic Society, Homer, AK, USA
| | - J A Mattison
- Translational Gerontology Branch, National Institute on Aging Intramural Research Program, National Institutes of Health, Baltimore, MD, USA
| | | | - J Mergl
- Marineland of Canada, Niagara Falls, Ontario, Canada
| | - J J Meudt
- Biomedical and Genomic Research Group, Department of Animal and Dairy Sciences, University of Wisconsin-Madison, Madison, WI, USA
| | - G A Montano
- Zoological Operations, SeaWorld Parks and Entertainment, Orlando, FL, USA
| | - K Mozhui
- Department of Preventive Medicine, University of Tennessee Health Science Center, College of Medicine, Memphis, TN, USA
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, College of Medicine, Memphis, TN, USA
| | - J Munshi-South
- Louis Calder Center-Biological Field Station, Department of Biological Sciences, Fordham University, Armonk, NY, USA
| | - A Naderi
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, SC, USA
| | - M Nagy
- Museum fur Naturkunde, Leibniz Institute for Evolution and Biodiversity Science, Berlin, Germany
| | - P Narayan
- Applied Translational Genetics Group, School of Biological Sciences, Centre for Brain Research, the University of Auckland, Auckland, New Zealand
| | - P W Nathanielsz
- Texas Pregnancy and Life-course Health Center, Southwest National Primate Research Center, San Antonio, TX, USA
- Department of Animal Science, College of Agriculture and Natural Resources, Laramie, WY, USA
| | - N B Nguyen
- Division of Cardiology, Department of Internal Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - C Niehrs
- Institute of Molecular Biology, Mainz, Germany
- Division of Molecular Embryology, DKFZ-ZMBH Alliance, Heidelberg, Germany
| | - J K O'Brien
- Taronga Institute of Science and Learning, Taronga Conservation Society Australia, Mosman, New South Wales, Australia
| | - P O'Tierney Ginn
- Mother Infant Research Institute, Tufts Medical Center, Boston, MA, USA
- Department of Obstetrics and Gynecology, Tufts University School of Medicine, Boston, MA, USA
| | - D T Odom
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
- Division of Regulatory Genomics and Cancer Evolution, Deutsches Krebsforschungszentrum, Heidelberg, Germany
| | - A G Ophir
- Department of Psychology, Cornell University, Ithaca, NY, USA
| | - S Osborn
- SeaWorld of Texas, San Antonio, TX, USA
| | - E A Ostrander
- Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - K M Parsons
- Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, USA
| | - K C Paul
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - M Pellegrini
- Department of Molecular Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, USA
| | - K J Peters
- Evolutionary Genetics Group, Department of Evolutionary Anthropology, University of Zurich, Zurich, Switzerland
- School of Earth, Atmospheric and Life Sciences, University of Wollongong, Wollongong, Australia
| | - A B Pedersen
- Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, Edinburgh, UK
| | - J L Petersen
- Department of Animal Science, University of Nebraska, Lincoln, NE, USA
| | - D W Pietersen
- Mammal Research Institute, Department of Zoology and Entomology, University of Pretoria, Hatfield, South Africa
| | - G M Pinho
- Department of Ecology and Evolutionary Biology, UCLA, Los Angeles, CA, USA
| | - J Plassais
- Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - J R Poganik
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - N A Prado
- Department of Biology, College of Arts and Science, Adelphi University, Garden City, NY, USA
| | - P Reddy
- Altos Labs, San Diego Institute of Science, San Diego, CA, USA
- Salk Institute for Biological Studies, La Jolla, CA, USA
| | - B Rey
- Universite de Lyon, Universite Lyon 1, CNRS, Laboratoire de Biometrie et Biologie Evolutive, Villeurbanne, France
| | - B R Ritz
- Department of Epidemiology, UCLA Fielding School of Public Health, Los Angeles, CA, USA
- Department of Environmental Health Sciences, UCLA Fielding School of Public Health, Los Angeles, CA, USA
- Department of Neurology, UCLA David Geffen School of Medicine, Los Angeles, CA, USA
| | - J Robbins
- Center for Coastal Studies, Provincetown, MA, USA
| | | | - J Russell
- SeaWorld of California, San Diego, CA, USA
| | - E Rydkina
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - L L Sailer
- Department of Psychology, Cornell University, Ithaca, NY, USA
| | - A B Salmon
- The Sam and Ann Barshop Institute for Longevity and Aging Studies and Department of Molecular Medicine, UT Health San Antonio and the Geriatric Research Education and Clinical Center, South Texas Veterans Healthcare System, San Antonio, TX, USA
| | | | - K M Schachtschneider
- Department of Radiology, University of Illinois at Chicago, Chicago, IL, USA
- Department of Biochemistry and Molecular Genetics, University of Illinois at Chicago, Chicago, IL, USA
- National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - D Schmitt
- College of Agriculture, Missouri State University, Springfield, MO, USA
| | - T Schmitt
- SeaWorld of California, San Diego, CA, USA
| | | | - L B Schook
- Department of Radiology, University of Illinois at Chicago, Chicago, IL, USA
- Department of Animal Sciences, University of Illinois at Urbana-Champaign, Champaign, IL, USA
| | - K E Sears
- Department of Ecology and Evolutionary Biology, UCLA, Los Angeles, CA, USA
- Department of Molecular Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, USA
| | - A W Seifert
- Department of Biology, University of Kentucky, Lexington, KY, USA
| | - A Seluanov
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - A B A Shafer
- Department of Forensic Science, Environmental and Life Sciences, Trent University, Peterborough, Ontario, Canada
| | - D Shanmuganayagam
- Biomedical and Genomic Research Group, Department of Animal and Dairy Sciences, University of Wisconsin-Madison, Madison, WI, USA
- Department of Surgery, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - A V Shindyapina
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | | | - K Singh
- Shobhaben Pratapbhai Patel School of Pharmacy and Technology Management, SVKM'S NMIMS University, Mumbai, India
| | - I Sinha
- Department of Ecology and Evolutionary Biology, UCLA, Los Angeles, CA, USA
| | - J Slone
- Division of Human Genetics, Department of Pediatrics, University at Buffalo, Buffalo, NY, USA
| | - R G Snell
- Applied Translational Genetics Group, School of Biological Sciences, Centre for Brain Research, the University of Auckland, Auckland, New Zealand
| | - E Soltanmaohammadi
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, SC, USA
| | - M L Spangler
- Department of Animal Science, University of Nebraska, Lincoln, NE, USA
| | | | - L Staggs
- SeaWorld of Florida, Orlando, FL, USA
| | | | - K J Steinman
- Species Preservation Laboratory, SeaWorld San Diego, San Diego, CA, USA
| | - D T Stewart
- Biology Department, Acadia University, Wolfville, Nova Scotia, Canada
| | - V J Sugrue
- Department of Anatomy, University of Otago, Dunedin, New Zealand
| | - B Szladovits
- Department of Pathobiology and Population Sciences, Royal Veterinary College, Hatfield, UK
| | - J S Takahashi
- Department of Neuroscience, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Howard Hughes Medical Institute, Department of Neuroscience, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - M Takasugi
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - E C Teeling
- School of Biology and Environmental Science, University College Dublin, Dublin, Ireland
| | - M J Thompson
- Department of Molecular Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, USA
| | - B Van Bonn
- John G. Shedd Aquarium, Chicago, IL, USA
| | - S C Vernes
- School of Biology, the University of St Andrews, Fife, UK
- Neurogenetics of Vocal Communication Group, Max Planck Institute for Psycholinguistics, Nijmegen, the Netherlands
| | - D Villar
- Blizard Institute, Faculty of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - H V Vinters
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - M C Wallingford
- Mother Infant Research Institute, Tufts Medical Center, Boston, MA, USA
- Division of Obstetrics and Gynecology, Tufts University School of Medicine, Boston, MA, USA
| | - N Wang
- Center for Neurobehavioral Genetics, Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - R K Wayne
- Department of Ecology and Evolutionary Biology, UCLA, Los Angeles, CA, USA
| | - G S Wilkinson
- Department of Biology, University of Maryland, College Park, MD, USA
| | - C K Williams
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - R W Williams
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, College of Medicine, Memphis, TN, USA
| | - X W Yang
- Center for Neurobehavioral Genetics, Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - M Yao
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
| | - B G Young
- Fisheries and Oceans Canada, Winnipeg, Manitoba, Canada
| | - B Zhang
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Z Zhang
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - P Zhao
- Division of Cardiology, Department of Internal Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research, University of California, Los Angeles, CA, USA
| | - Y Zhao
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - W Zhou
- Center for Computational and Genomic Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - J Zimmermann
- Department of Mathematics and Technology, University of Applied Sciences Koblenz, Koblenz, Germany
| | - J Ernst
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | - K Raj
- Altos Labs, Cambridge Institute of Science, Cambridge, UK
| | - S Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
- Altos Labs, San Diego Institute of Science, San Diego, CA, USA.
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA.
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Raman B, McCracken C, Cassar MP, Moss AJ, Finnigan L, Samat AHA, Ogbole G, Tunnicliffe EM, Alfaro-Almagro F, Menke R, Xie C, Gleeson F, Lukaschuk E, Lamlum H, McGlynn K, Popescu IA, Sanders ZB, Saunders LC, Piechnik SK, Ferreira VM, Nikolaidou C, Rahman NM, Ho LP, Harris VC, Shikotra A, Singapuri A, Pfeffer P, Manisty C, Kon OM, Beggs M, O'Regan DP, Fuld J, Weir-McCall JR, Parekh D, Steeds R, Poinasamy K, Cuthbertson DJ, Kemp GJ, Semple MG, Horsley A, Miller CA, O'Brien C, Shah AM, Chiribiri A, Leavy OC, Richardson M, Elneima O, McAuley HJC, Sereno M, Saunders RM, Houchen-Wolloff L, Greening NJ, Bolton CE, Brown JS, Choudhury G, Diar Bakerly N, Easom N, Echevarria C, Marks M, Hurst JR, Jones MG, Wootton DG, Chalder T, Davies MJ, De Soyza A, Geddes JR, Greenhalf W, Howard LS, Jacob J, Man WDC, Openshaw PJM, Porter JC, Rowland MJ, Scott JT, Singh SJ, Thomas DC, Toshner M, Lewis KE, Heaney LG, Harrison EM, Kerr S, Docherty AB, Lone NI, Quint J, Sheikh A, Zheng B, Jenkins RG, Cox E, Francis S, Halling-Brown M, Chalmers JD, Greenwood JP, Plein S, Hughes PJC, Thompson AAR, Rowland-Jones SL, Wild JM, Kelly M, Treibel TA, Bandula S, Aul R, Miller K, Jezzard P, Smith S, Nichols TE, McCann GP, Evans RA, Wain LV, Brightling CE, Neubauer S, Baillie JK, Shaw A, Hairsine B, Kurasz C, Henson H, Armstrong L, Shenton L, Dobson H, Dell A, Lucey A, Price A, Storrie A, Pennington C, Price C, Mallison G, Willis G, Nassa H, Haworth J, Hoare M, Hawkings N, Fairbairn S, Young S, Walker S, Jarrold I, Sanderson A, David C, Chong-James K, Zongo O, James WY, Martineau A, King B, Armour C, McAulay D, Major E, McGinness J, McGarvey L, Magee N, Stone R, Drain S, Craig T, Bolger A, Haggar A, Lloyd A, Subbe C, Menzies D, Southern D, McIvor E, Roberts K, Manley R, Whitehead V, Saxon W, Bularga A, Mills NL, El-Taweel H, Dawson J, Robinson L, Saralaya D, Regan K, Storton K, Brear L, Amoils S, Bermperi A, Elmer A, Ribeiro C, Cruz I, Taylor J, Worsley J, Dempsey K, Watson L, Jose S, Marciniak S, Parkes M, McQueen A, Oliver C, Williams J, Paradowski K, Broad L, Knibbs L, Haynes M, Sabit R, Milligan L, Sampson C, Hancock A, Evenden C, Lynch C, Hancock K, Roche L, Rees M, Stroud N, Thomas-Woods T, Heller S, Robertson E, Young B, Wassall H, Babores M, Holland M, Keenan N, Shashaa S, Price C, Beranova E, Ramos H, Weston H, Deery J, Austin L, Solly R, Turney S, Cosier T, Hazelton T, Ralser M, Wilson A, Pearce L, Pugmire S, Stoker W, McCormick W, Dewar A, Arbane G, Kaltsakas G, Kerslake H, Rossdale J, Bisnauthsing K, Aguilar Jimenez LA, Martinez LM, Ostermann M, Magtoto MM, Hart N, Marino P, Betts S, Solano TS, Arias AM, Prabhu A, Reed A, Wrey Brown C, Griffin D, Bevan E, Martin J, Owen J, Alvarez Corral M, Williams N, Payne S, Storrar W, Layton A, Lawson C, Mills C, Featherstone J, Stephenson L, Burdett T, Ellis Y, Richards A, Wright C, Sykes DL, Brindle K, Drury K, Holdsworth L, Crooks MG, Atkin P, Flockton R, Thackray-Nocera S, Mohamed A, Taylor A, Perkins E, Ross G, McGuinness H, Tench H, Phipps J, Loosley R, Wolf-Roberts R, Coetzee S, Omar Z, Ross A, Card B, Carr C, King C, Wood C, Copeland D, Calvelo E, Chilvers ER, Russell E, Gordon H, Nunag JL, Schronce J, March K, Samuel K, Burden L, Evison L, McLeavey L, Orriss-Dib L, Tarusan L, Mariveles M, Roy M, Mohamed N, Simpson N, Yasmin N, Cullinan P, Daly P, Haq S, Moriera S, Fayzan T, Munawar U, Nwanguma U, Lingford-Hughes A, Altmann D, Johnston D, Mitchell J, Valabhji J, Price L, Molyneaux PL, Thwaites RS, Walsh S, Frankel A, Lightstone L, Wilkins M, Willicombe M, McAdoo S, Touyz R, Guerdette AM, Warwick K, Hewitt M, Reddy R, White S, McMahon A, Hoare A, Knighton A, Ramos A, Te A, Jolley CJ, Speranza F, Assefa-Kebede H, Peralta I, Breeze J, Shevket K, Powell N, Adeyemi O, Dulawan P, Adrego R, Byrne S, Patale S, Hayday A, Malim M, Pariante C, Sharpe C, Whitney J, Bramham K, Ismail K, Wessely S, Nicholson T, Ashworth A, Humphries A, Tan AL, Whittam B, Coupland C, Favager C, Peckham D, Wade E, Saalmink G, Clarke J, Glossop J, Murira J, Rangeley J, Woods J, Hall L, Dalton M, Window N, Beirne P, Hardy T, Coakley G, Turtle L, Berridge A, Cross A, Key AL, Rowe A, Allt AM, Mears C, Malein F, Madzamba G, Hardwick HE, Earley J, Hawkes J, Pratt J, Wyles J, Tripp KA, Hainey K, Allerton L, Lavelle-Langham L, Melling L, Wajero LO, Poll L, Noonan MJ, French N, Lewis-Burke N, Williams-Howard SA, Cooper S, Kaprowska S, Dobson SL, Marsh S, Highett V, Shaw V, Beadsworth M, Defres S, Watson E, Tiongson GF, Papineni P, Gurram S, Diwanji SN, Quaid S, Briggs A, Hastie C, Rogers N, Stensel D, Bishop L, McIvor K, Rivera-Ortega P, Al-Sheklly B, Avram C, Faluyi D, Blaikely J, Piper Hanley K, Radhakrishnan K, Buch M, Hanley NA, Odell N, Osbourne R, Stockdale S, Felton T, Gorsuch T, Hussell T, Kausar Z, Kabir T, McAllister-Williams H, Paddick S, Burn D, Ayoub A, Greenhalgh A, Sayer A, Young A, Price D, Burns G, MacGowan G, Fisher H, Tedd H, Simpson J, Jiwa K, Witham M, Hogarth P, West S, Wright S, McMahon MJ, Neill P, Dougherty A, Morrow A, Anderson D, Grieve D, Bayes H, Fallon K, Mangion K, Gilmour L, Basu N, Sykes R, Berry C, McInnes IB, Donaldson A, Sage EK, Barrett F, Welsh B, Bell M, Quigley J, Leitch K, Macliver L, Patel M, Hamil R, Deans A, Furniss J, Clohisey S, Elliott A, Solstice AR, Deas C, Tee C, Connell D, Sutherland D, George J, Mohammed S, Bunker J, Holmes K, Dipper A, Morley A, Arnold D, Adamali H, Welch H, Morrison L, Stadon L, Maskell N, Barratt S, Dunn S, Waterson S, Jayaraman B, Light T, Selby N, Hosseini A, Shaw K, Almeida P, Needham R, Thomas AK, Matthews L, Gupta A, Nikolaidis A, Dupont C, Bonnington J, Chrystal M, Greenhaff PL, Linford S, Prosper S, Jang W, Alamoudi A, Bloss A, Megson C, Nicoll D, Fraser E, Pacpaco E, Conneh F, Ogg G, McShane H, Koychev I, Chen J, Pimm J, Ainsworth M, Pavlides M, Sharpe M, Havinden-Williams M, Petousi N, Talbot N, Carter P, Kurupati P, Dong T, Peng Y, Burns A, Kanellakis N, Korszun A, Connolly B, Busby J, Peto T, Patel B, Nolan CM, Cristiano D, Walsh JA, Liyanage K, Gummadi M, Dormand N, Polgar O, George P, Barker RE, Patel S, Price L, Gibbons M, Matila D, Jarvis H, Lim L, Olaosebikan O, Ahmad S, Brill S, Mandal S, Laing C, Michael A, Reddy A, Johnson C, Baxendale H, Parfrey H, Mackie J, Newman J, Pack J, Parmar J, Paques K, Garner L, Harvey A, Summersgill C, Holgate D, Hardy E, Oxton J, Pendlebury J, McMorrow L, Mairs N, Majeed N, Dark P, Ugwuoke R, Knight S, Whittaker S, Strong-Sheldrake S, Matimba-Mupaya W, Chowienczyk P, Pattenadk D, Hurditch E, Chan F, Carborn H, Foot H, Bagshaw J, Hockridge J, Sidebottom J, Lee JH, Birchall K, Turner K, Haslam L, Holt L, Milner L, Begum M, Marshall M, Steele N, Tinker N, Ravencroft P, Butcher R, Misra S, Walker S, Coburn Z, Fairman A, Ford A, Holbourn A, Howell A, Lawrie A, Lye A, Mbuyisa A, Zawia A, Holroyd-Hind B, Thamu B, Clark C, Jarman C, Norman C, Roddis C, Foote D, Lee E, Ilyas F, Stephens G, Newell H, Turton H, Macharia I, Wilson I, Cole J, McNeill J, Meiring J, Rodger J, Watson J, Chapman K, Harrington K, Chetham L, Hesselden L, Nwafor L, Dixon M, Plowright M, Wade P, Gregory R, Lenagh R, Stimpson R, Megson S, Newman T, Cheng Y, Goodwin C, Heeley C, Sissons D, Sowter D, Gregory H, Wynter I, Hutchinson J, Kirk J, Bennett K, Slack K, Allsop L, Holloway L, Flynn M, Gill M, Greatorex M, Holmes M, Buckley P, Shelton S, Turner S, Sewell TA, Whitworth V, Lovegrove W, Tomlinson J, Warburton L, Painter S, Vickers C, Redwood D, Tilley J, Palmer S, Wainwright T, Breen G, Hotopf M, Dunleavy A, Teixeira J, Ali M, Mencias M, Msimanga N, Siddique S, Samakomva T, Tavoukjian V, Forton D, Ahmed R, Cook A, Thaivalappil F, Connor L, Rees T, McNarry M, Williams N, McCormick J, McIntosh J, Vere J, Coulding M, Kilroy S, Turner V, Butt AT, Savill H, Fraile E, Ugoji J, Landers G, Lota H, Portukhay S, Nasseri M, Daniels A, Hormis A, Ingham J, Zeidan L, Osborne L, Chablani M, Banerjee A, David A, Pakzad A, Rangelov B, Williams B, Denneny E, Willoughby J, Xu M, Mehta P, Batterham R, Bell R, Aslani S, Lilaonitkul W, Checkley A, Bang D, Basire D, Lomas D, Wall E, Plant H, Roy K, Heightman M, Lipman M, Merida Morillas M, Ahwireng N, Chambers RC, Jastrub R, Logan S, Hillman T, Botkai A, Casey A, Neal A, Newton-Cox A, Cooper B, Atkin C, McGee C, Welch C, Wilson D, Sapey E, Qureshi H, Hazeldine J, Lord JM, Nyaboko J, Short J, Stockley J, Dasgin J, Draxlbauer K, Isaacs K, Mcgee K, Yip KP, Ratcliffe L, Bates M, Ventura M, Ahmad Haider N, Gautam N, Baggott R, Holden S, Madathil S, Walder S, Yasmin S, Hiwot T, Jackson T, Soulsby T, Kamwa V, Peterkin Z, Suleiman Z, Chaudhuri N, Wheeler H, Djukanovic R, Samuel R, Sass T, Wallis T, Marshall B, Childs C, Marouzet E, Harvey M, Fletcher S, Dickens C, Beckett P, Nanda U, Daynes E, Charalambou A, Yousuf AJ, Lea A, Prickett A, Gooptu B, Hargadon B, Bourne C, Christie C, Edwardson C, Lee D, Baldry E, Stringer E, Woodhead F, Mills G, Arnold H, Aung H, Qureshi IN, Finch J, Skeemer J, Hadley K, Khunti K, Carr L, Ingram L, Aljaroof M, Bakali M, Bakau M, Baldwin M, Bourne M, Pareek M, Soares M, Tobin M, Armstrong N, Brunskill N, Goodman N, Cairns P, Haldar P, McCourt P, Dowling R, Russell R, Diver S, Edwards S, Glover S, Parker S, Siddiqui S, Ward TJC, Mcnally T, Thornton T, Yates T, Ibrahim W, Monteiro W, Thickett D, Wilkinson D, Broome M, McArdle P, Upthegrove R, Wraith D, Langenberg C, Summers C, Bullmore E, Heeney JL, Schwaeble W, Sudlow CL, Adeloye D, Newby DE, Rudan I, Shankar-Hari M, Thorpe M, Pius R, Walmsley S, McGovern A, Ballard C, Allan L, Dennis J, Cavanagh J, Petrie J, O'Donnell K, Spears M, Sattar N, MacDonald S, Guthrie E, Henderson M, Guillen Guio B, Zhao B, Lawson C, Overton C, Taylor C, Tong C, Mukaetova-Ladinska E, Turner E, Pearl JE, Sargant J, Wormleighton J, Bingham M, Sharma M, Steiner M, Samani N, Novotny P, Free R, Allen RJ, Finney S, Terry S, Brugha T, Plekhanova T, McArdle A, Vinson B, Spencer LG, Reynolds W, Ashworth M, Deakin B, Chinoy H, Abel K, Harvie M, Stanel S, Rostron A, Coleman C, Baguley D, Hufton E, Khan F, Hall I, Stewart I, Fabbri L, Wright L, Kitterick P, Morriss R, Johnson S, Bates A, Antoniades C, Clark D, Bhui K, Channon KM, Motohashi K, Sigfrid L, Husain M, Webster M, Fu X, Li X, Kingham L, Klenerman P, Miiler K, Carson G, Simons G, Huneke N, Calder PC, Baldwin D, Bain S, Lasserson D, Daines L, Bright E, Stern M, Crisp P, Dharmagunawardena R, Reddington A, Wight A, Bailey L, Ashish A, Robinson E, Cooper J, Broadley A, Turnbull A, Brookes C, Sarginson C, Ionita D, Redfearn H, Elliott K, Barman L, Griffiths L, Guy Z, Gill R, Nathu R, Harris E, Moss P, Finnigan J, Saunders K, Saunders P, Kon S, Kon SS, O'Brien L, Shah K, Shah P, Richardson E, Brown V, Brown M, Brown J, Brown J, Brown A, Brown A, Brown M, Choudhury N, Jones S, Jones H, Jones L, Jones I, Jones G, Jones H, Jones D, Davies F, Davies E, Davies K, Davies G, Davies GA, Howard K, Porter J, Rowland J, Rowland A, Scott K, Singh S, Singh C, Thomas S, Thomas C, Lewis V, Lewis J, Lewis D, Harrison P, Francis C, Francis R, Hughes RA, Hughes J, Hughes AD, Thompson T, Kelly S, Smith D, Smith N, Smith A, Smith J, Smith L, Smith S, Evans T, Evans RI, Evans D, Evans R, Evans H, Evans J. Multiorgan MRI findings after hospitalisation with COVID-19 in the UK (C-MORE): a prospective, multicentre, observational cohort study. Lancet Respir Med 2023; 11:1003-1019. [PMID: 37748493 PMCID: PMC7615263 DOI: 10.1016/s2213-2600(23)00262-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Revised: 06/16/2023] [Accepted: 06/30/2023] [Indexed: 09/27/2023]
Abstract
INTRODUCTION The multiorgan impact of moderate to severe coronavirus infections in the post-acute phase is still poorly understood. We aimed to evaluate the excess burden of multiorgan abnormalities after hospitalisation with COVID-19, evaluate their determinants, and explore associations with patient-related outcome measures. METHODS In a prospective, UK-wide, multicentre MRI follow-up study (C-MORE), adults (aged ≥18 years) discharged from hospital following COVID-19 who were included in Tier 2 of the Post-hospitalisation COVID-19 study (PHOSP-COVID) and contemporary controls with no evidence of previous COVID-19 (SARS-CoV-2 nucleocapsid antibody negative) underwent multiorgan MRI (lungs, heart, brain, liver, and kidneys) with quantitative and qualitative assessment of images and clinical adjudication when relevant. Individuals with end-stage renal failure or contraindications to MRI were excluded. Participants also underwent detailed recording of symptoms, and physiological and biochemical tests. The primary outcome was the excess burden of multiorgan abnormalities (two or more organs) relative to controls, with further adjustments for potential confounders. The C-MORE study is ongoing and is registered with ClinicalTrials.gov, NCT04510025. FINDINGS Of 2710 participants in Tier 2 of PHOSP-COVID, 531 were recruited across 13 UK-wide C-MORE sites. After exclusions, 259 C-MORE patients (mean age 57 years [SD 12]; 158 [61%] male and 101 [39%] female) who were discharged from hospital with PCR-confirmed or clinically diagnosed COVID-19 between March 1, 2020, and Nov 1, 2021, and 52 non-COVID-19 controls from the community (mean age 49 years [SD 14]; 30 [58%] male and 22 [42%] female) were included in the analysis. Patients were assessed at a median of 5·0 months (IQR 4·2-6·3) after hospital discharge. Compared with non-COVID-19 controls, patients were older, living with more obesity, and had more comorbidities. Multiorgan abnormalities on MRI were more frequent in patients than in controls (157 [61%] of 259 vs 14 [27%] of 52; p<0·0001) and independently associated with COVID-19 status (odds ratio [OR] 2·9 [95% CI 1·5-5·8]; padjusted=0·0023) after adjusting for relevant confounders. Compared with controls, patients were more likely to have MRI evidence of lung abnormalities (p=0·0001; parenchymal abnormalities), brain abnormalities (p<0·0001; more white matter hyperintensities and regional brain volume reduction), and kidney abnormalities (p=0·014; lower medullary T1 and loss of corticomedullary differentiation), whereas cardiac and liver MRI abnormalities were similar between patients and controls. Patients with multiorgan abnormalities were older (difference in mean age 7 years [95% CI 4-10]; mean age of 59·8 years [SD 11·7] with multiorgan abnormalities vs mean age of 52·8 years [11·9] without multiorgan abnormalities; p<0·0001), more likely to have three or more comorbidities (OR 2·47 [1·32-4·82]; padjusted=0·0059), and more likely to have a more severe acute infection (acute CRP >5mg/L, OR 3·55 [1·23-11·88]; padjusted=0·025) than those without multiorgan abnormalities. Presence of lung MRI abnormalities was associated with a two-fold higher risk of chest tightness, and multiorgan MRI abnormalities were associated with severe and very severe persistent physical and mental health impairment (PHOSP-COVID symptom clusters) after hospitalisation. INTERPRETATION After hospitalisation for COVID-19, people are at risk of multiorgan abnormalities in the medium term. Our findings emphasise the need for proactive multidisciplinary care pathways, with the potential for imaging to guide surveillance frequency and therapeutic stratification. FUNDING UK Research and Innovation and National Institute for Health Research.
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Shorthouse FM, Griffin N, McNicholas C, Spahr N, Jones G. Agreement and consistency in the triaging of musculoskeletal primary care referrals by vetting clinicians using a knowledge-based triage tool. Prim Health Care Res Dev 2023; 24:e63. [PMID: 37881880 PMCID: PMC10790367 DOI: 10.1017/s1463423623000361] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Revised: 06/09/2023] [Accepted: 06/10/2023] [Indexed: 10/27/2023] Open
Abstract
BACKGROUND Primary care referrals received by secondary care services are vetted or triaged to pathways best suited for patients' needs. If knowledge-based triaging is used by vetting clinicians, accuracy is required to avoid incorrect decisions being made. With limited evidence to support best practice, we aimed to evaluate consistency across vetting clinicians' decisions and their agreement with a criterion decision. METHODS Twenty-nine trained vetting clinicians (18 female) representative of pay grades independently triaged five musculoskeletal physiotherapy referral cases into one of 10 decisions using an internally developed triage tool. Agreement across clinicians' decisions between and within cases was assessed using Fleiss's kappa overall and within pay grade. Proportions of triage decisions consistent with criterion decisions were assessed using Cochran's Q test. RESULTS Clinician agreement was fair for all cases (κ = 0.385) irrespective of pay grade but varied within clinical cases (κ = -0.014-0.786). Proportions of correct triage decisions were significantly different across cases [Q(4) = 33.80, P < 0.001] ranging from 17% to 83%. CONCLUSIONS Agreement and consistency in decisions were variable using the tool. Ensuring referrer information is accurate is vital, as is developing, automating and auditing standards for certain referrals with clear pathways. But we argue that variable vetting outcomes might represent healthy pathway abundance and should not simply be automated in response to perceived inefficiencies.
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Affiliation(s)
- F. M. Shorthouse
- Musculoskeletal Physiotherapy Service, Guys and St Thomas’ NHS Foundation Trust, Westminster Bridge Road, SE1 7EH, UK
| | - N. Griffin
- Musculoskeletal Physiotherapy Service, Guys and St Thomas’ NHS Foundation Trust, Westminster Bridge Road, SE1 7EH, UK
| | - C. McNicholas
- Musculoskeletal Physiotherapy Service, Guys and St Thomas’ NHS Foundation Trust, Westminster Bridge Road, SE1 7EH, UK
| | - N. Spahr
- Musculoskeletal Physiotherapy Service, Guys and St Thomas’ NHS Foundation Trust, Westminster Bridge Road, SE1 7EH, UK
| | - G. Jones
- Physiotherapy Service, Guys and St Thomas’ NHS Foundation Trust, Westminster Bridge Road, SE1 7EH, UK
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Lu AT, Fei Z, Haghani A, Robeck TR, Zoller JA, Li CZ, Lowe R, Yan Q, Zhang J, Vu H, Ablaeva J, Acosta-Rodriguez VA, Adams DM, Almunia J, Aloysius A, Ardehali R, Arneson A, Baker CS, Banks G, Belov K, Bennett NC, Black P, Blumstein DT, Bors EK, Breeze CE, Brooke RT, Brown JL, Carter GG, Caulton A, Cavin JM, Chakrabarti L, Chatzistamou I, Chen H, Cheng K, Chiavellini P, Choi OW, Clarke SM, Cooper LN, Cossette ML, Day J, DeYoung J, DiRocco S, Dold C, Ehmke EE, Emmons CK, Emmrich S, Erbay E, Erlacher-Reid C, Faulkes CG, Ferguson SH, Finno CJ, Flower JE, Gaillard JM, Garde E, Gerber L, Gladyshev VN, Gorbunova V, Goya RG, Grant MJ, Green CB, Hales EN, Hanson MB, Hart DW, Haulena M, Herrick K, Hogan AN, Hogg CJ, Hore TA, Huang T, Izpisua Belmonte JC, Jasinska AJ, Jones G, Jourdain E, Kashpur O, Katcher H, Katsumata E, Kaza V, Kiaris H, Kobor MS, Kordowitzki P, Koski WR, Krützen M, Kwon SB, Larison B, Lee SG, Lehmann M, Lemaitre JF, Levine AJ, Li C, Li X, Lim AR, Lin DTS, Lindemann DM, Little TJ, Macoretta N, Maddox D, Matkin CO, Mattison JA, McClure M, Mergl J, Meudt JJ, Montano GA, Mozhui K, Munshi-South J, Naderi A, Nagy M, Narayan P, Nathanielsz PW, Nguyen NB, Niehrs C, O'Brien JK, O'Tierney Ginn P, Odom DT, Ophir AG, Osborn S, Ostrander EA, Parsons KM, Paul KC, Pellegrini M, Peters KJ, Pedersen AB, Petersen JL, Pietersen DW, Pinho GM, Plassais J, Poganik JR, Prado NA, Reddy P, Rey B, Ritz BR, Robbins J, Rodriguez M, Russell J, Rydkina E, Sailer LL, Salmon AB, Sanghavi A, Schachtschneider KM, Schmitt D, Schmitt T, Schomacher L, Schook LB, Sears KE, Seifert AW, Seluanov A, Shafer ABA, Shanmuganayagam D, Shindyapina AV, Simmons M, Singh K, Sinha I, Slone J, Snell RG, Soltanmaohammadi E, Spangler ML, Spriggs MC, Staggs L, Stedman N, Steinman KJ, Stewart DT, Sugrue VJ, Szladovits B, Takahashi JS, Takasugi M, Teeling EC, Thompson MJ, Van Bonn B, Vernes SC, Villar D, Vinters HV, Wallingford MC, Wang N, Wayne RK, Wilkinson GS, Williams CK, Williams RW, Yang XW, Yao M, Young BG, Zhang B, Zhang Z, Zhao P, Zhao Y, Zhou W, Zimmermann J, Ernst J, Raj K, Horvath S. Universal DNA methylation age across mammalian tissues. Nat Aging 2023; 3:1144-1166. [PMID: 37563227 PMCID: PMC10501909 DOI: 10.1038/s43587-023-00462-6] [Citation(s) in RCA: 28] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Accepted: 06/21/2023] [Indexed: 08/12/2023]
Abstract
Aging, often considered a result of random cellular damage, can be accurately estimated using DNA methylation profiles, the foundation of pan-tissue epigenetic clocks. Here, we demonstrate the development of universal pan-mammalian clocks, using 11,754 methylation arrays from our Mammalian Methylation Consortium, which encompass 59 tissue types across 185 mammalian species. These predictive models estimate mammalian tissue age with high accuracy (r > 0.96). Age deviations correlate with human mortality risk, mouse somatotropic axis mutations and caloric restriction. We identified specific cytosines with methylation levels that change with age across numerous species. These sites, highly enriched in polycomb repressive complex 2-binding locations, are near genes implicated in mammalian development, cancer, obesity and longevity. Our findings offer new evidence suggesting that aging is evolutionarily conserved and intertwined with developmental processes across all mammals.
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Affiliation(s)
- A T Lu
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Altos Labs, San Diego Institute of Science, San Diego, CA, USA
| | - Z Fei
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Statistics, University of California, Riverside, Riverside, CA, USA
| | - A Haghani
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Altos Labs, San Diego Institute of Science, San Diego, CA, USA
| | - T R Robeck
- Zoological SeaWorld Parks and Entertainment, Orlando, FL, USA
| | - J A Zoller
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
| | - C Z Li
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
| | - R Lowe
- Altos Labs, Cambridge Institute of Science, Cambridge, UK
| | - Q Yan
- Altos Labs, San Diego Institute of Science, San Diego, CA, USA
| | - J Zhang
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - H Vu
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | - J Ablaeva
- Department of Biology, University of Rochester, Rochester, NY, USA
| | - V A Acosta-Rodriguez
- Department of Neuroscience, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - D M Adams
- Department of Biology, University of Maryland, College Park, MD, USA
| | - J Almunia
- Loro Parque Fundacion, Puerto de la Cruz, Spain
| | - A Aloysius
- Department of Biology, University of Kentucky, Lexington, KY, USA
| | - R Ardehali
- Division of Cardiology, Department of Internal Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - A Arneson
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | - C S Baker
- Marine Mammal Institute, Oregon State University, Newport, OR, USA
| | - G Banks
- School of Science and Technology, Clifton Campus, Nottingham Trent University, Nottingham, UK
| | - K Belov
- School of Life and Environmental Sciences, the University of Sydney, Sydney, New South Wales, Australia
| | - N C Bennett
- Department of Zoology and Entomology, University of Pretoria, Hatfield, South Africa
| | - P Black
- Busch Gardens Tampa, Tampa, FL, USA
| | - D T Blumstein
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, CA, USA
- Rocky Mountain Biological Laboratory, Crested Butte, CO, USA
| | - E K Bors
- Marine Mammal Institute, Oregon State University, Newport, OR, USA
| | - C E Breeze
- Altius Institute for Biomedical Sciences, Seattle, WA, USA
| | - R T Brooke
- Epigenetic Clock Development Foundation, Los Angeles, CA, USA
| | - J L Brown
- Center for Species Survival, Smithsonian Conservation Biology Institute, Front Royal, VA, USA
| | - G G Carter
- Department of Evolution, Ecology and Organismal Biology, The Ohio State University, Columbus, OH, USA
| | - A Caulton
- AgResearch, Invermay Agricultural Centre, Mosgiel, New Zealand
- Department of Biochemistry, University of Otago, Dunedin, New Zealand
| | - J M Cavin
- Gulf World, Dolphin Company, Panama City Beach, FL, USA
| | - L Chakrabarti
- School of Veterinary Medicine and Science, University of Nottingham, Nottingham, UK
| | - I Chatzistamou
- Department of Pathology, Microbiology and Immunology, School of Medicine, University of South Carolina, Columbia, SC, USA
| | - H Chen
- Department of Pharmacology, Addiction Science and Toxicology, the University of Tennessee Health Science Center, Memphis, TN, USA
| | - K Cheng
- Medical Informatics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - P Chiavellini
- Biochemistry Research Institute of La Plata, Histology and Pathology, School of Medicine, University of La Plata, La Plata, Argentina
| | - O W Choi
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - S M Clarke
- AgResearch, Invermay Agricultural Centre, Mosgiel, New Zealand
| | - L N Cooper
- Department of Anatomy and Neurobiology, Northeast Ohio Medical University, Rootstown, OH, USA
| | - M L Cossette
- Department of Environmental and Life Sciences, Trent University, Peterborough, Ontario, Canada
| | - J Day
- Taronga Institute of Science and Learning, Taronga Conservation Society Australia, Mosman, New South Wales, Australia
| | - J DeYoung
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - S DiRocco
- SeaWorld of Florida, Orlando, FL, USA
| | - C Dold
- Zoological Operations, SeaWorld Parks and Entertainment, Orlando, FL, USA
| | | | - C K Emmons
- Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, USA
| | - S Emmrich
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - E Erbay
- Altos Labs, San Francisco, CA, USA
| | - C Erlacher-Reid
- SeaWorld of Florida, Orlando, FL, USA
- SeaWorld Orlando, Orlando, FL, USA
| | - C G Faulkes
- School of Biological and Behavioural Sciences, Queen Mary University of London, London, UK
| | - S H Ferguson
- Fisheries and Oceans Canada, Freshwater Institute, Winnipeg, Manitoba, Canada
- Department of Biological Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - C J Finno
- Department of Population Health and Reproduction, University of California, Davis School of Veterinary Medicine, Davis, CA, USA
| | | | - J M Gaillard
- Universite de Lyon, Universite Lyon 1, CNRS, Laboratoire de Biometrie et Biologie Evolutive, Villeurbanne, France
| | - E Garde
- Greenland Institute of Natural Resources, Nuuk, Greenland
| | - L Gerber
- Evolution and Ecology Research Centre, School of Biological, Earth and Environmental Sciences, UNSW Sydney, Sydney, New South Wales, Australia
| | - V N Gladyshev
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - V Gorbunova
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - R G Goya
- Biochemistry Research Institute of La Plata, Histology and Pathology, School of Medicine, University of La Plata, La Plata, Argentina
| | - M J Grant
- Applied Translational Genetics Group, School of Biological Sciences, Centre for Brain Research, the University of Auckland, Auckland, New Zealand
| | - C B Green
- Department of Neuroscience, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - E N Hales
- Department of Population Health and Reproduction, University of California, Davis School of Veterinary Medicine, Davis, CA, USA
| | - M B Hanson
- Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, USA
| | - D W Hart
- Department of Zoology and Entomology, University of Pretoria, Hatfield, South Africa
| | - M Haulena
- Vancouver Aquarium, Vancouver, British Columbia, Canada
| | - K Herrick
- SeaWorld of California, San Diego, CA, USA
| | - A N Hogan
- Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - C J Hogg
- School of Life and Environmental Sciences, the University of Sydney, Sydney, New South Wales, Australia
| | - T A Hore
- Department of Anatomy, University of Otago, Dunedin, New Zealand
| | - T Huang
- Division of Human Genetics, Department of Pediatrics, University at Buffalo, Buffalo, NY, USA
- Division of Genetics and Metabolism, Oishei Children's Hospital, Buffalo, NY, USA
| | | | - A J Jasinska
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - G Jones
- School of Biological Sciences, University of Bristol, Bristol, UK
| | | | - O Kashpur
- Mother Infant Research Institute, Tufts Medical Center, Boston, MA, USA
| | - H Katcher
- Yuvan Research, Mountain View, CA, USA
| | | | - V Kaza
- Peromyscus Genetic Stock Center, University of South Carolina, Columbia, SC, USA
| | - H Kiaris
- Peromyscus Genetic Stock Center, University of South Carolina, Columbia, SC, USA
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, SC, USA
| | - M S Kobor
- Edwin S.H. Leong Healthy Aging Program, Centre for Molecular Medicine and Therapeutics, University of British Columbia, Vancouver, British Columbia, Canada
| | - P Kordowitzki
- Institute of Animal Reproduction and Food Research of the Polish Academy of Sciences, Olsztyn, Poland
- Institute for Veterinary Medicine, Nicolaus Copernicus University, Torun, Poland
| | - W R Koski
- LGL Limited, King City, Ontario, Canada
| | - M Krützen
- Evolutionary Genetics Group, Department of Evolutionary Anthropology, University of Zurich, Zurich, Switzerland
| | - S B Kwon
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | - B Larison
- Department of Ecology and Evolutionary Biology, UCLA, Los Angeles, CA, USA
- Center for Tropical Research, Institute for the Environment and Sustainability, UCLA, Los Angeles, CA, USA
| | - S G Lee
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - M Lehmann
- Biochemistry Research Institute of La Plata, Histology and Pathology, School of Medicine, University of La Plata, La Plata, Argentina
| | - J F Lemaitre
- Universite de Lyon, Universite Lyon 1, CNRS, Laboratoire de Biometrie et Biologie Evolutive, Villeurbanne, France
| | - A J Levine
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - C Li
- Texas Pregnancy and Life-course Health Center, Southwest National Primate Research Center, San Antonio, TX, USA
- Department of Animal Science, College of Agriculture and Natural Resources, Laramie, WY, USA
| | - X Li
- Technology Center for Genomics and Bioinformatics, Department of Pathology and Laboratory Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - A R Lim
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - D T S Lin
- Centre for Molecular Medicine and Therapeutics, BC Children's Hospital Research Institute, University of British Columbia, Vancouver, British Columbia, Canada
| | | | - T J Little
- Institute of Ecology and Evolution, School of Biological Sciences, University of Edinburgh, Edinburgh, UK
| | - N Macoretta
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - D Maddox
- White Oak Conservation, Yulee, FL, USA
| | - C O Matkin
- North Gulf Oceanic Society, Homer, AK, USA
| | - J A Mattison
- Translational Gerontology Branch, National Institute on Aging Intramural Research Program, National Institutes of Health, Baltimore, MD, USA
| | | | - J Mergl
- Marineland of Canada, Niagara Falls, Ontario, Canada
| | - J J Meudt
- Biomedical and Genomic Research Group, Department of Animal and Dairy Sciences, University of Wisconsin-Madison, Madison, WI, USA
| | - G A Montano
- Zoological Operations, SeaWorld Parks and Entertainment, Orlando, FL, USA
| | - K Mozhui
- Department of Preventive Medicine, University of Tennessee Health Science Center, College of Medicine, Memphis, TN, USA
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, College of Medicine, Memphis, TN, USA
| | - J Munshi-South
- Louis Calder Center-Biological Field Station, Department of Biological Sciences, Fordham University, Armonk, NY, USA
| | - A Naderi
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, SC, USA
| | - M Nagy
- Museum fur Naturkunde, Leibniz Institute for Evolution and Biodiversity Science, Berlin, Germany
| | - P Narayan
- Applied Translational Genetics Group, School of Biological Sciences, Centre for Brain Research, the University of Auckland, Auckland, New Zealand
| | - P W Nathanielsz
- Texas Pregnancy and Life-course Health Center, Southwest National Primate Research Center, San Antonio, TX, USA
- Department of Animal Science, College of Agriculture and Natural Resources, Laramie, WY, USA
| | - N B Nguyen
- Division of Cardiology, Department of Internal Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - C Niehrs
- Institute of Molecular Biology, Mainz, Germany
- Division of Molecular Embryology, DKFZ-ZMBH Alliance, Heidelberg, Germany
| | - J K O'Brien
- Taronga Institute of Science and Learning, Taronga Conservation Society Australia, Mosman, New South Wales, Australia
| | - P O'Tierney Ginn
- Mother Infant Research Institute, Tufts Medical Center, Boston, MA, USA
- Department of Obstetrics and Gynecology, Tufts University School of Medicine, Boston, MA, USA
| | - D T Odom
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
- Division of Regulatory Genomics and Cancer Evolution, Deutsches Krebsforschungszentrum, Heidelberg, Germany
| | - A G Ophir
- Department of Psychology, Cornell University, Ithaca, NY, USA
| | - S Osborn
- SeaWorld of Texas, San Antonio, TX, USA
| | - E A Ostrander
- Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - K M Parsons
- Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, USA
| | - K C Paul
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - M Pellegrini
- Department of Molecular Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, USA
| | - K J Peters
- Evolutionary Genetics Group, Department of Evolutionary Anthropology, University of Zurich, Zurich, Switzerland
- School of Earth, Atmospheric and Life Sciences, University of Wollongong, Wollongong, Australia
| | - A B Pedersen
- Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, Edinburgh, UK
| | - J L Petersen
- Department of Animal Science, University of Nebraska, Lincoln, NE, USA
| | - D W Pietersen
- Mammal Research Institute, Department of Zoology and Entomology, University of Pretoria, Hatfield, South Africa
| | - G M Pinho
- Department of Ecology and Evolutionary Biology, UCLA, Los Angeles, CA, USA
| | - J Plassais
- Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - J R Poganik
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - N A Prado
- Department of Biology, College of Arts and Science, Adelphi University, Garden City, NY, USA
| | - P Reddy
- Altos Labs, San Diego Institute of Science, San Diego, CA, USA
- Salk Institute for Biological Studies, La Jolla, CA, USA
| | - B Rey
- Universite de Lyon, Universite Lyon 1, CNRS, Laboratoire de Biometrie et Biologie Evolutive, Villeurbanne, France
| | - B R Ritz
- Department of Epidemiology, UCLA Fielding School of Public Health, Los Angeles, CA, USA
- Department of Environmental Health Sciences, UCLA Fielding School of Public Health, Los Angeles, CA, USA
- Department of Neurology, UCLA David Geffen School of Medicine, Los Angeles, CA, USA
| | - J Robbins
- Center for Coastal Studies, Provincetown, MA, USA
| | | | - J Russell
- SeaWorld of California, San Diego, CA, USA
| | - E Rydkina
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - L L Sailer
- Department of Psychology, Cornell University, Ithaca, NY, USA
| | - A B Salmon
- The Sam and Ann Barshop Institute for Longevity and Aging Studies and Department of Molecular Medicine, UT Health San Antonio and the Geriatric Research Education and Clinical Center, South Texas Veterans Healthcare System, San Antonio, TX, USA
| | | | - K M Schachtschneider
- Department of Radiology, University of Illinois at Chicago, Chicago, IL, USA
- Department of Biochemistry and Molecular Genetics, University of Illinois at Chicago, Chicago, IL, USA
- National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - D Schmitt
- College of Agriculture, Missouri State University, Springfield, MO, USA
| | - T Schmitt
- SeaWorld of California, San Diego, CA, USA
| | | | - L B Schook
- Department of Radiology, University of Illinois at Chicago, Chicago, IL, USA
- Department of Animal Sciences, University of Illinois at Urbana-Champaign, Champaign, IL, USA
| | - K E Sears
- Department of Ecology and Evolutionary Biology, UCLA, Los Angeles, CA, USA
- Department of Molecular Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, USA
| | - A W Seifert
- Department of Biology, University of Kentucky, Lexington, KY, USA
| | - A Seluanov
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - A B A Shafer
- Department of Forensic Science, Environmental and Life Sciences, Trent University, Peterborough, Ontario, Canada
| | - D Shanmuganayagam
- Biomedical and Genomic Research Group, Department of Animal and Dairy Sciences, University of Wisconsin-Madison, Madison, WI, USA
- Department of Surgery, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - A V Shindyapina
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | | | - K Singh
- Shobhaben Pratapbhai Patel School of Pharmacy and Technology Management, SVKM'S NMIMS University, Mumbai, India
| | - I Sinha
- Department of Ecology and Evolutionary Biology, UCLA, Los Angeles, CA, USA
| | - J Slone
- Division of Human Genetics, Department of Pediatrics, University at Buffalo, Buffalo, NY, USA
| | - R G Snell
- Applied Translational Genetics Group, School of Biological Sciences, Centre for Brain Research, the University of Auckland, Auckland, New Zealand
| | - E Soltanmaohammadi
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, SC, USA
| | - M L Spangler
- Department of Animal Science, University of Nebraska, Lincoln, NE, USA
| | | | - L Staggs
- SeaWorld of Florida, Orlando, FL, USA
| | | | - K J Steinman
- Species Preservation Laboratory, SeaWorld San Diego, San Diego, CA, USA
| | - D T Stewart
- Biology Department, Acadia University, Wolfville, Nova Scotia, Canada
| | - V J Sugrue
- Department of Anatomy, University of Otago, Dunedin, New Zealand
| | - B Szladovits
- Department of Pathobiology and Population Sciences, Royal Veterinary College, Hatfield, UK
| | - J S Takahashi
- Department of Neuroscience, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Howard Hughes Medical Institute, Department of Neuroscience, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - M Takasugi
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - E C Teeling
- School of Biology and Environmental Science, University College Dublin, Dublin, Ireland
| | - M J Thompson
- Department of Molecular Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, USA
| | - B Van Bonn
- John G. Shedd Aquarium, Chicago, IL, USA
| | - S C Vernes
- School of Biology, the University of St Andrews, Fife, UK
- Neurogenetics of Vocal Communication Group, Max Planck Institute for Psycholinguistics, Nijmegen, the Netherlands
| | - D Villar
- Blizard Institute, Faculty of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - H V Vinters
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - M C Wallingford
- Mother Infant Research Institute, Tufts Medical Center, Boston, MA, USA
- Division of Obstetrics and Gynecology, Tufts University School of Medicine, Boston, MA, USA
| | - N Wang
- Center for Neurobehavioral Genetics, Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - R K Wayne
- Department of Ecology and Evolutionary Biology, UCLA, Los Angeles, CA, USA
| | - G S Wilkinson
- Department of Biology, University of Maryland, College Park, MD, USA
| | - C K Williams
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - R W Williams
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, College of Medicine, Memphis, TN, USA
| | - X W Yang
- Center for Neurobehavioral Genetics, Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - M Yao
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
| | - B G Young
- Fisheries and Oceans Canada, Winnipeg, Manitoba, Canada
| | - B Zhang
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Z Zhang
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - P Zhao
- Division of Cardiology, Department of Internal Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research, University of California, Los Angeles, CA, USA
| | - Y Zhao
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - W Zhou
- Center for Computational and Genomic Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - J Zimmermann
- Department of Mathematics and Technology, University of Applied Sciences Koblenz, Koblenz, Germany
| | - J Ernst
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | - K Raj
- Altos Labs, Cambridge Institute of Science, Cambridge, UK
| | - S Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
- Altos Labs, San Diego Institute of Science, San Diego, CA, USA.
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA.
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8
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Drummen SJJ, Balogun S, Lahham A, Bennell K, Hinman RS, Callisaya M, Cai G, Otahal P, Winzenberg T, Wang Z, Antony B, Munugoda IP, Martel-Pelletier J, Pelletier JP, Abram F, Jones G, Aitken D. A pilot randomized controlled trial evaluating outdoor community walking for knee osteoarthritis: walk. Clin Rheumatol 2023; 42:1409-1421. [PMID: 36692651 PMCID: PMC10102100 DOI: 10.1007/s10067-022-06477-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2022] [Revised: 12/01/2022] [Accepted: 12/08/2022] [Indexed: 01/25/2023]
Abstract
OBJECTIVES To determine the feasibility of a randomized controlled trial (RCT) examining outdoor walking on knee osteoarthritis (KOA) clinical outcomes and magnetic resonance imaging (MRI) structural changes. METHOD This was a 24-week parallel two-arm pilot RCT in Tasmania, Australia. KOA participants were randomized to either a walking plus usual care group or a usual care control group. The walking group trained 3 days/week. The primary outcome was feasibility assessed by changes being required to the study design, recruitment, randomization, program adherence, safety, and retention. Exploratory outcomes were changes in symptoms, physical performance/activity, and MRI measures. RESULTS Forty participants (mean age 66 years (SD 1.4) and 60% female) were randomized to walking (n = 24) or usual care (n = 16). Simple randomization resulted in a difference in numbers randomized to the two groups. During the study, class sizes were reduced from 10 to 8 participants to improve supervision, and exclusion criteria were added to facilitate program adherence. In the walking group, total program adherence was 70.0% and retention 70.8% at 24 weeks. The walking group had a higher number of mild adverse events and experienced clinically important improvements in symptoms (e.g., visual analogue scale (VAS) knee pain change in the walking group: - 38.7 mm [95% CI - 47.1 to - 30.3] versus usual care group: 4.3 mm [- 4.9 to 13.4]). CONCLUSIONS This study supports the feasibility of a full-scale RCT given acceptable adherence, retention, randomization, and safety, and recruitment challenges have been identified. Large symptomatic benefits support the clinical usefulness of a subsequent trial. TRIAL REGISTRATION NUMBER 12618001097235. Key Points • This pilot study is the first to investigate the effects of an outdoor walking program on knee osteoarthritis clinical outcomes and MRI joint structure, and it indicates that a full-scale RCT is feasible. • The outdoor walking program (plus usual care) resulted in large improvements in self-reported knee osteoarthritis symptoms compared to usual care alone. • The study identified recruitment challenges, and the manuscript explores these in more details and provides recommendations for future studies.
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Affiliation(s)
- S J J Drummen
- Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, 7000, Australia.
| | - S Balogun
- Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, 7000, Australia
- Australian National University, Canberra, Australia
| | - A Lahham
- Monash University, Melbourne, Australia
| | - K Bennell
- The University of Melbourne, Melbourne, Australia
| | - R S Hinman
- The University of Melbourne, Melbourne, Australia
| | - M Callisaya
- Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, 7000, Australia
- Monash University, Melbourne, Australia
| | - G Cai
- Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, 7000, Australia
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China
| | - P Otahal
- Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, 7000, Australia
| | - T Winzenberg
- Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, 7000, Australia
| | - Z Wang
- Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, 7000, Australia
| | - B Antony
- Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, 7000, Australia
| | - I P Munugoda
- Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, 7000, Australia
| | - J Martel-Pelletier
- Osteoarthritis Research Unit, University of Montreal Hospital Research Centre (CRCHUM), Montreal, QC, Canada
| | - J P Pelletier
- Osteoarthritis Research Unit, University of Montreal Hospital Research Centre (CRCHUM), Montreal, QC, Canada
| | - F Abram
- Medical Imaging Research & Development, ArthroLab Inc, Montreal, QC, Canada
| | - G Jones
- Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, 7000, Australia
| | - D Aitken
- Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, 7000, Australia
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9
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Vandenput L, Johansson H, McCloskey EV, Liu E, Åkesson KE, Anderson FA, Azagra R, Bager CL, Beaudart C, Bischoff-Ferrari HA, Biver E, Bruyère O, Cauley JA, Center JR, Chapurlat R, Christiansen C, Cooper C, Crandall CJ, Cummings SR, da Silva JAP, Dawson-Hughes B, Diez-Perez A, Dufour AB, Eisman JA, Elders PJM, Ferrari S, Fujita Y, Fujiwara S, Glüer CC, Goldshtein I, Goltzman D, Gudnason V, Hall J, Hans D, Hoff M, Hollick RJ, Huisman M, Iki M, Ish-Shalom S, Jones G, Karlsson MK, Khosla S, Kiel DP, Koh WP, Koromani F, Kotowicz MA, Kröger H, Kwok T, Lamy O, Langhammer A, Larijani B, Lippuner K, Mellström D, Merlijn T, Nordström A, Nordström P, O'Neill TW, Obermayer-Pietsch B, Ohlsson C, Orwoll ES, Pasco JA, Rivadeneira F, Schei B, Schott AM, Shiroma EJ, Siggeirsdottir K, Simonsick EM, Sornay-Rendu E, Sund R, Swart KMA, Szulc P, Tamaki J, Torgerson DJ, van Schoor NM, van Staa TP, Vila J, Wareham NJ, Wright NC, Yoshimura N, Zillikens MC, Zwart M, Harvey NC, Lorentzon M, Leslie WD, Kanis JA. Update of the fracture risk prediction tool FRAX: a systematic review of potential cohorts and analysis plan. Osteoporos Int 2022; 33:2103-2136. [PMID: 35639106 DOI: 10.1007/s00198-022-06435-6] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Accepted: 05/18/2022] [Indexed: 12/15/2022]
Abstract
UNLABELLED We describe the collection of cohorts together with the analysis plan for an update of the fracture risk prediction tool FRAX with respect to current and novel risk factors. The resource comprises 2,138,428 participants with a follow-up of approximately 20 million person-years and 116,117 documented incident major osteoporotic fractures. INTRODUCTION The availability of the fracture risk assessment tool FRAX® has substantially enhanced the targeting of treatment to those at high risk of fracture with FRAX now incorporated into more than 100 clinical osteoporosis guidelines worldwide. The aim of this study is to determine whether the current algorithms can be further optimised with respect to current and novel risk factors. METHODS A computerised literature search was performed in PubMed from inception until May 17, 2019, to identify eligible cohorts for updating the FRAX coefficients. Additionally, we searched the abstracts of conference proceedings of the American Society for Bone and Mineral Research, European Calcified Tissue Society and World Congress of Osteoporosis. Prospective cohort studies with data on baseline clinical risk factors and incident fractures were eligible. RESULTS Of the 836 records retrieved, 53 were selected for full-text assessment after screening on title and abstract. Twelve cohorts were deemed eligible and of these, 4 novel cohorts were identified. These cohorts, together with 60 previously identified cohorts, will provide the resource for constructing an updated version of FRAX comprising 2,138,428 participants with a follow-up of approximately 20 million person-years and 116,117 documented incident major osteoporotic fractures. For each known and candidate risk factor, multivariate hazard functions for hip fracture, major osteoporotic fracture and death will be tested using extended Poisson regression. Sex- and/or ethnicity-specific differences in the weights of the risk factors will be investigated. After meta-analyses of the cohort-specific beta coefficients for each risk factor, models comprising 10-year probability of hip and major osteoporotic fracture, with or without femoral neck bone mineral density, will be computed. CONCLUSIONS These assembled cohorts and described models will provide the framework for an updated FRAX tool enabling enhanced assessment of fracture risk (PROSPERO (CRD42021227266)).
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Affiliation(s)
- L Vandenput
- Mary McKillop Institute for Health Research, Australian Catholic University, Melbourne, Australia
- Sahlgrenska Osteoporosis Centre, Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - H Johansson
- Mary McKillop Institute for Health Research, Australian Catholic University, Melbourne, Australia
- Centre for Metabolic Bone Diseases, University of Sheffield, Sheffield, UK
| | - E V McCloskey
- Centre for Metabolic Bone Diseases, University of Sheffield, Sheffield, UK
- MRC Versus Arthritis Centre for Integrated Research in Musculoskeletal Ageing, Mellanby Centre for Musculoskeletal Research, University of Sheffield, Sheffield, UK
| | - E Liu
- Mary McKillop Institute for Health Research, Australian Catholic University, Melbourne, Australia
| | - K E Åkesson
- Clinical and Molecular Osteoporosis Research Unit, Department of Clinical Sciences, Lund University, Lund, Sweden
- Department of Orthopedics, Skåne University Hospital, Malmö, Sweden
| | - F A Anderson
- GLOW Coordinating Center, Center for Outcomes Research, University of Massachusetts Medical School, Worcester, MA, USA
| | - R Azagra
- Department of Medicine, Autonomous University of Barcelona, Barcelona, Spain
- Health Center Badia del Valles, Catalan Institute of Health, Barcelona, Spain
- GROIMAP (Research Group), Unitat de Suport a La Recerca Metropolitana Nord, Institut Universitari d'Investigació en Atenció Primària Jordi Gol, Santa Coloma de Gramenet, Barcelona, Spain
| | - C L Bager
- Nordic Bioscience A/S, Herlev, Denmark
| | - C Beaudart
- WHO Collaborating Centre for Public Health Aspects of Musculoskeletal Health and Aging, Division of Public Health, Epidemiology and Health Economics, University of Liège, Liège, Belgium
| | - H A Bischoff-Ferrari
- Department of Aging Medicine and Aging Research, University Hospital, Zurich, and University of Zurich, Zurich, Switzerland
- Centre On Aging and Mobility, University of Zurich and City Hospital, Zurich, Switzerland
| | - E Biver
- Division of Bone Diseases, Department of Medicine, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - O Bruyère
- WHO Collaborating Centre for Public Health Aspects of Musculoskeletal Health and Aging, Division of Public Health, Epidemiology and Health Economics, University of Liège, Liège, Belgium
| | - J A Cauley
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Philadelphia, USA
| | - J R Center
- Bone Biology, Healthy Ageing Theme, Garvan Institute of Medical Research, Sydney, NSW, Australia
- St Vincent's Clinical School, Faculty of Medicine, University of New South Wales Sydney, Sydney, NSW, Australia
- School of Medicine Sydney, University of Notre Dame Australia, Sydney, NSW, Australia
| | - R Chapurlat
- INSERM UMR 1033, University of Lyon, Hôpital Edouard Herriot, Lyon, France
| | | | - C Cooper
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK
- National Institute for Health Research Southampton Biomedical Research Centre, University of Southampton and University Hospitals Southampton NHS Foundation Trust, Southampton, UK
- National Institute for Health Research Oxford Biomedical Research Unit, , University of Oxford, Oxford, UK
| | - C J Crandall
- Division of General Internal Medicine and Health Services Research, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
| | - S R Cummings
- San Francisco Coordinating Center, California Pacific Medical Center Research Institute, San Francisco, CA, USA
| | - J A P da Silva
- Coimbra Institute for Clinical and Biomedical Research, Faculty of Medicine, University of Coimbra, Coimbra, Portugal
- Rheumatology Department, University Hospital and University of Coimbra, Coimbra, Portugal
| | - B Dawson-Hughes
- Bone Metabolism Laboratory, Jean Mayer US Department of Agriculture Human Nutrition Research Center On Aging, Tufts University, Boston, MA, USA
| | - A Diez-Perez
- Department of Internal Medicine, Hospital del Mar and CIBERFES, Autonomous University of Barcelona, Barcelona, Spain
| | - A B Dufour
- Marcus Institute for Aging Research, Hebrew SeniorLife, Boston, MA, USA
- Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - J A Eisman
- St Vincent's Clinical School, Faculty of Medicine, University of New South Wales Sydney, Sydney, NSW, Australia
- School of Medicine Sydney, University of Notre Dame Australia, Sydney, NSW, Australia
- Osteoporosis and Bone Biology Division, Garvan Institute of Medical Research, Sydney, NSW, Australia
| | - P J M Elders
- Department of General Practice, Amsterdam UMC, Location VUmc, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - S Ferrari
- Division of Bone Diseases, Department of Medicine, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Y Fujita
- Department of Public Health, Faculty of Medicine, Kindai University, Osaka, Japan
| | - S Fujiwara
- Department of Pharmacy, Yasuda Women's University, Hiroshima, Japan
| | - C-C Glüer
- Section Biomedical Imaging, Molecular Imaging North Competence Center, Department of Radiology and Neuroradiology, University Medical Center Schleswig-Holstein Kiel, Kiel University, Kiel, Germany
| | - I Goldshtein
- Maccabitech Institute of Research and Innovation, Maccabi Healthcare Services, Tel Aviv, Israel
- Department of Epidemiology and Preventive Medicine, School of Public Health, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - D Goltzman
- Department of Medicine, McGill University and McGill University Health Centre, Montreal, Canada
| | - V Gudnason
- Icelandic Heart Association, Kopavogur, Iceland
- University of Iceland, Reykjavik, Iceland
| | - J Hall
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh, UK
| | - D Hans
- Centre of Bone Diseases, Bone and Joint Department, Lausanne University Hospital, Lausanne, Switzerland
| | - M Hoff
- Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Rheumatology, St Olavs Hospital, Trondheim, Norway
| | - R J Hollick
- Aberdeen Centre for Arthritis and Musculoskeletal Health, Epidemiology Group, University of Aberdeen, Aberdeen, UK
| | - M Huisman
- Department of Epidemiology and Data Science, Amsterdam Public Health Research Institute, VU University Medical Center, Amsterdam, The Netherlands
- Department of Sociology, VU University, Amsterdam, The Netherlands
| | - M Iki
- Department of Public Health, Faculty of Medicine, Kindai University, Osaka, Japan
| | - S Ish-Shalom
- Endocrine Clinic, Elisha Hospital, Haifa, Israel
| | - G Jones
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Australia
| | - M K Karlsson
- Clinical and Molecular Osteoporosis Research Unit, Department of Clinical Sciences, Lund University, Lund, Sweden
- Department of Orthopaedics, Skåne University Hospital, Malmö, Sweden
| | - S Khosla
- Robert and Arlene Kogod Center On Aging and Division of Endocrinology, Mayo Clinic College of Medicine, Mayo Clinic, Rochester, MN, USA
| | - D P Kiel
- Marcus Institute for Aging Research, Hebrew SeniorLife, Boston, MA, USA
- Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - W-P Koh
- Healthy Longevity Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Singapore Institute for Clinical Sciences, Agency for Science Technology and Research (A*STAR), Singapore, Singapore
| | - F Koromani
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
- Department of Radiology and Nuclear Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - M A Kotowicz
- IMPACT (Institute for Mental and Physical Health and Clinical Translation), Deakin University, Geelong, VIC, Australia
- Barwon Health, Geelong, VIC, Australia
- Department of Medicine - Western Health, The University of Melbourne, St Albans, Victoria, Australia
| | - H Kröger
- Department of Orthopedics and Traumatology, Kuopio University Hospital, Kuopio, Finland
- Kuopio Musculoskeletal Research Unit, University of Eastern Finland, Kuopio, Finland
| | - T Kwok
- Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, Hong Kong
- Jockey Club Centre for Osteoporosis Care and Control, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, Hong Kong
| | - O Lamy
- Centre of Bone Diseases, Lausanne University Hospital, Lausanne, Switzerland
- Service of Internal Medicine, Lausanne University Hospital, Lausanne, Switzerland
| | - A Langhammer
- Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, HUNT Research Centre, Norwegian University of Science and Technology, Trondheim, Norway
| | - B Larijani
- Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - K Lippuner
- Department of Osteoporosis, Bern University Hospital, University of Bern, Bern, Switzerland
| | - D Mellström
- Geriatric Medicine, Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Geriatric Medicine, Sahlgrenska University Hospital Mölndal, Mölndal, Sweden
| | - T Merlijn
- Department of General Practice, Amsterdam UMC, Location VUmc, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - A Nordström
- Division of Sustainable Health, Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
- School of Sport Sciences, Arctic University of Norway, Tromsø, Norway
| | - P Nordström
- Unit of Geriatric Medicine, Department of Community Medicine and Rehabilitation, Umeå University, Umeå, Sweden
| | - T W O'Neill
- National Institute for Health Research Manchester Biomedical Research Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
- Centre for Epidemiology Versus Arthritis, University of Manchester, Manchester, UK
| | - B Obermayer-Pietsch
- Department of Internal Medicine, Division of Endocrinology and Diabetology, Medical University Graz, Graz, Austria
- Center for Biomarker Research in Medicine, Graz, Austria
| | - C Ohlsson
- Sahlgrenska Osteoporosis Centre, Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Drug Treatment, Sahlgrenska University Hospital, Region Västra Götaland, Gothenburg, Sweden
| | - E S Orwoll
- Department of Medicine, Oregon Health and Science University, Portland, OR, USA
| | - J A Pasco
- Institute for Physical and Mental Health and Clinical Translation (IMPACT), Deakin University, Geelong, Australia
- Department of Medicine-Western Health, The University of Melbourne, St Albans, Australia
- Barwon Health, Geelong, Australia
- Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia
| | - F Rivadeneira
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - B Schei
- Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Gynecology, St Olavs Hospital, Trondheim, Norway
| | - A-M Schott
- Université Claude Bernard Lyon 1, U INSERM 1290 RESHAPE, Lyon, France
| | - E J Shiroma
- Laboratory of Epidemiology and Population Sciences, National Institute On Aging, Baltimore, MD, USA
| | - K Siggeirsdottir
- Icelandic Heart Association, Kopavogur, Iceland
- Janus Rehabilitation, Reykjavik, Iceland
| | - E M Simonsick
- Translational Gerontology Branch, National Institute On Aging Intramural Research Program, Baltimore, MD, USA
| | | | - R Sund
- Kuopio Musculoskeletal Research Unit, University of Eastern Finland, Kuopio, Finland
| | - K M A Swart
- Department of General Practice, Amsterdam UMC, Location VUmc, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - P Szulc
- INSERM UMR 1033, University of Lyon, Hôpital Edouard Herriot, Lyon, France
| | - J Tamaki
- Department of Hygiene and Public Health, Faculty of Medicine, Educational Foundation of Osaka Medical and Pharmaceutical University, Osaka, Japan
| | - D J Torgerson
- York Trials Unit, Department of Health Sciences, University of York, York, UK
| | - N M van Schoor
- Department of Epidemiology and Data Science, Amsterdam Public Health Research Institute, VU University Medical Center, Amsterdam, The Netherlands
| | - T P van Staa
- Centre for Health Informatics, Faculty of Biology, Medicine and Health, School of Health Sciences, University of Manchester, Manchester, UK
| | - J Vila
- Statistics Support Unit, Hospital del Mar Medical Research Institute, CIBER Epidemiology and Public Health (CIBERESP), Barcelona, Spain
| | - N J Wareham
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - N C Wright
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - N Yoshimura
- Department of Preventive Medicine for Locomotive Organ Disorders, The University of Tokyo Hospital, Tokyo, Japan
| | - M C Zillikens
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - M Zwart
- Health Center Can Gibert del Plà, Catalan Institute of Health, Girona, Spain
- Department of Medical Sciences, University of Girona, Girona, Spain
- GROIMAP (Research Group), Institut Universitari d'Investigació en Atenció Primària Jordi Gol, Barcelona, Spain
| | - N C Harvey
- MRC Lifecourse Epidemiology Centre, University of Southampton, Southampton, UK
- NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, UK
| | - M Lorentzon
- Mary McKillop Institute for Health Research, Australian Catholic University, Melbourne, Australia
- Sahlgrenska Osteoporosis Centre, Institute of Medicine, University of Gothenburg, Gothenburg, Sweden
- Geriatric Medicine, Region Västra Götaland, Sahlgrenska University Hospital, Mölndal, Sweden
| | - W D Leslie
- Department of Medicine, University of Manitoba, Winnipeg, MB, Canada
| | - J A Kanis
- Mary McKillop Institute for Health Research, Australian Catholic University, Melbourne, Australia.
- Centre for Metabolic Bone Diseases, University of Sheffield, Sheffield, UK.
- Centre for Metabolic Bone Diseases, University of Sheffield Medical School, Sheffield, UK.
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Fergusson M, Wijayarathna R, Coupe S, Jones G. How fast is too fast? post-operative & physical function milestones for patients undergoing maxillofacial surgery with free flap reconstruction. Clin Nutr ESPEN 2022. [DOI: 10.1016/j.clnesp.2022.06.033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Allsop L, Almeida P, Altmann D, Alvarez Corral M, Amoils S, Anderson D, Antoniades C, Arbane G, Arias A, Armour C, Armstrong L, Armstrong N, Arnold D, Arnold H, Ashish A, Ashworth A, Ashworth M, Aslani S, Assefa-Kebede H, Atkin C, Atkin P, Aung H, Austin L, Avram C, Ayoub A, Babores M, Baggott R, Bagshaw J, Baguley D, Bailey L, Baillie JK, Bain S, Bakali M, Bakau M, Baldry E, Baldwin D, Ballard C, Banerjee A, Bang B, Barker RE, Barman L, Barratt S, Barrett F, Basire D, Basu N, Bates M, Bates A, Batterham R, Baxendale H, Bayes H, Beadsworth M, Beckett P, Beggs M, Begum M, Bell D, Bell R, Bennett K, Beranova E, Bermperi A, Berridge A, Berry C, Betts S, Bevan E, Bhui K, Bingham M, Birchall K, Bishop L, Bisnauthsing K, Blaikely J, Bloss A, Bolger A, Bonnington J, Botkai A, Bourne C, Bourne M, Bramham K, Brear L, Breen G, Breeze J, Bright E, Brill S, Brindle K, Broad L, Broadley A, Brookes C, Broome M, Brown A, Brown A, Brown J, Brown J, Brown M, Brown M, Brown V, Brugha T, Brunskill N, Buch M, Buckley P, Bularga A, Bullmore E, Burden L, Burdett T, Burn D, Burns G, Burns A, Busby J, Butcher R, Butt A, Byrne S, Cairns P, Calder PC, Calvelo E, Carborn H, Card B, Carr C, Carr L, Carson G, Carter P, Casey A, Cassar M, Cavanagh J, Chablani M, Chambers RC, Chan F, Channon KM, Chapman K, Charalambou A, Chaudhuri N, Checkley A, Chen J, Cheng Y, Chetham L, Childs C, Chilvers ER, Chinoy H, Chiribiri A, Chong-James K, Choudhury N, Chowienczyk P, Christie C, Chrystal M, Clark D, Clark C, Clarke J, Clohisey S, Coakley G, Coburn Z, Coetzee S, Cole J, Coleman C, Conneh F, Connell D, Connolly B, Connor L, Cook A, Cooper B, Cooper J, Cooper S, Copeland D, Cosier T, Coulding M, Coupland C, Cox E, Craig T, Crisp P, Cristiano D, Crooks MG, Cross A, Cruz I, Cullinan P, Cuthbertson D, Daines L, Dalton M, Daly P, Daniels A, Dark P, Dasgin J, David A, David C, Davies E, Davies F, Davies G, Davies GA, Davies K, Dawson J, Daynes E, Deakin B, Deans A, Deas C, Deery J, Defres S, Dell A, Dempsey K, Denneny E, Dennis J, Dewar A, Dharmagunawardena R, Dickens C, Dipper A, Diver S, Diwanji SN, Dixon M, Djukanovic R, Dobson H, Dobson SL, Donaldson A, Dong T, Dormand N, Dougherty A, Dowling R, Drain S, Draxlbauer K, Drury K, Dulawan P, Dunleavy A, Dunn S, Earley J, Edwards S, Edwardson C, El-Taweel H, Elliott A, Elliott K, Ellis Y, Elmer A, Evans D, Evans H, Evans J, Evans R, Evans RI, Evans T, Evenden C, Evison L, Fabbri L, Fairbairn S, Fairman A, Fallon K, Faluyi D, Favager C, Fayzan T, Featherstone J, Felton T, Finch J, Finney S, Finnigan J, Finnigan L, Fisher H, Fletcher S, Flockton R, Flynn M, Foot H, Foote D, Ford A, Forton D, Fraile E, Francis C, Francis R, Francis S, Frankel A, Fraser E, Free R, French N, Fu X, Furniss J, Garner L, Gautam N, George J, George P, Gibbons M, Gill M, Gilmour L, Gleeson F, Glossop J, Glover S, Goodman N, Goodwin C, Gooptu B, Gordon H, Gorsuch T, Greatorex M, Greenhaff PL, Greenhalgh A, Greenwood J, Gregory H, Gregory R, Grieve D, Griffin D, Griffiths L, Guerdette AM, Guillen Guio B, Gummadi M, Gupta A, Gurram S, Guthrie E, Guy Z, H Henson H, Hadley K, Haggar A, Hainey K, Hairsine B, Haldar P, Hall I, Hall L, Halling-Brown M, Hamil R, Hancock A, Hancock K, Hanley NA, Haq S, Hardwick HE, Hardy E, Hardy T, Hargadon B, Harrington K, Harris E, Harrison P, Harvey A, Harvey M, Harvie M, Haslam L, Havinden-Williams M, Hawkes J, Hawkings N, Haworth J, Hayday A, Haynes M, Hazeldine J, Hazelton T, Heeley C, Heeney JL, Heightman M, Henderson M, Hesselden L, Hewitt M, Highett V, Hillman T, Hiwot T, Hoare A, Hoare M, Hockridge J, Hogarth P, Holbourn A, Holden S, Holdsworth L, Holgate D, Holland M, Holloway L, Holmes K, Holmes M, Holroyd-Hind B, Holt L, Hormis A, Hosseini A, Hotopf M, Howard K, Howell A, Hufton E, Hughes AD, Hughes J, Hughes R, Humphries A, Huneke N, Hurditch E, Husain M, Hussell T, Hutchinson J, Ibrahim W, Ilyas F, Ingham J, Ingram L, Ionita D, Isaacs K, Ismail K, Jackson T, James WY, Jarman C, Jarrold I, Jarvis H, Jastrub R, Jayaraman B, Jezzard P, Jiwa K, Johnson C, Johnson S, Johnston D, Jolley CJ, Jones D, Jones G, Jones H, Jones H, Jones I, Jones L, Jones S, Jose S, Kabir T, Kaltsakas G, Kamwa V, Kanellakis N, Kaprowska S, Kausar Z, Keenan N, Kelly S, Kemp G, Kerslake H, Key AL, Khan F, Khunti K, Kilroy S, King B, King C, Kingham L, Kirk J, Kitterick P, Klenerman P, Knibbs L, Knight S, Knighton A, Kon O, Kon S, Kon SS, Koprowska S, Korszun A, Koychev I, Kurasz C, Kurupati P, Laing C, Lamlum H, Landers G, Langenberg C, Lasserson D, Lavelle-Langham L, Lawrie A, Lawson C, Lawson C, Layton A, Lea A, Lee D, Lee JH, Lee E, Leitch K, Lenagh R, Lewis D, Lewis J, Lewis V, Lewis-Burke N, Li X, Light T, Lightstone L, Lilaonitkul W, Lim L, Linford S, Lingford-Hughes A, Lipman M, Liyanage K, Lloyd A, Logan S, Lomas D, Loosley R, Lota H, Lovegrove W, Lucey A, Lukaschuk E, Lye A, Lynch C, MacDonald S, MacGowan G, Macharia I, Mackie J, Macliver L, Madathil S, Madzamba G, Magee N, Magtoto MM, Mairs N, Majeed N, Major E, Malein F, Malim M, Mallison G, Mandal S, Mangion K, Manisty C, Manley R, March K, Marciniak S, Marino P, Mariveles M, Marouzet E, Marsh S, Marshall B, Marshall M, Martin J, Martineau A, Martinez LM, Maskell N, Matila D, Matimba-Mupaya W, Matthews L, Mbuyisa A, McAdoo S, Weir McCall J, McAllister-Williams H, McArdle A, McArdle P, McAulay D, McCormick J, McCormick W, McCourt P, McGarvey L, McGee C, Mcgee K, McGinness J, McGlynn K, McGovern A, McGuinness H, McInnes IB, McIntosh J, McIvor E, McIvor K, McLeavey L, McMahon A, McMahon MJ, McMorrow L, Mcnally T, McNarry M, McNeill J, McQueen A, McShane H, Mears C, Megson C, Megson S, Mehta P, Meiring J, Melling L, Mencias M, Menzies D, Merida Morillas M, Michael A, Milligan L, Miller C, Mills C, Mills NL, Milner L, Misra S, Mitchell J, Mohamed A, Mohamed N, Mohammed S, Molyneaux PL, Monteiro W, Moriera S, Morley A, Morrison L, Morriss R, Morrow A, Moss AJ, Moss P, Motohashi K, Msimanga N, Mukaetova-Ladinska E, Munawar U, Murira J, 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Qureshi H, Qureshi IN, Radhakrishnan K, Ralser M, Ramos A, Ramos H, Rangeley J, Rangelov B, Ratcliffe L, Ravencroft P, Reddington A, Reddy R, Redfearn H, Redwood D, Reed A, Rees M, Rees T, Regan K, Reynolds W, Ribeiro C, Richards A, Richardson E, Rivera-Ortega P, Roberts K, Robertson E, Robinson E, Robinson L, Roche L, Roddis C, Rodger J, Ross A, Ross G, Rossdale J, Rostron A, Rowe A, Rowland A, Rowland J, Roy K, Roy M, Rudan I, Russell R, Russell E, Saalmink G, Sabit R, Sage EK, Samakomva T, Samani N, Sampson C, Samuel K, Samuel R, Sanderson A, Sapey E, Saralaya D, Sargant J, Sarginson C, Sass T, Sattar N, Saunders K, Saunders P, Saunders LC, Savill H, Saxon W, Sayer A, Schronce J, Schwaeble W, Scott K, Selby N, Sewell TA, Shah K, Shah P, Shankar-Hari M, Sharma M, Sharpe C, Sharpe M, Shashaa S, Shaw A, Shaw K, Shaw V, Shelton S, Shenton L, Shevket K, Short J, Siddique S, Siddiqui S, Sidebottom J, Sigfrid L, Simons G, Simpson J, Simpson N, Singh C, Singh S, Sissons D, Skeemer J, Slack K, Smith A, Smith D, Smith S, Smith J, Smith L, Soares M, Solano TS, Solly R, Solstice AR, Soulsby T, Southern D, Sowter D, Spears M, Spencer LG, Speranza F, Stadon L, Stanel S, Steele N, Steiner M, Stensel D, Stephens G, Stephenson L, Stern M, Stewart I, Stimpson R, Stockdale S, Stockley J, Stoker W, Stone R, Storrar W, Storrie A, Storton K, Stringer E, Strong-Sheldrake S, Stroud N, Subbe C, Sudlow CL, Suleiman Z, Summers C, Summersgill C, Sutherland D, Sykes DL, Sykes R, Talbot N, Tan AL, Tarusan L, Tavoukjian V, Taylor A, Taylor C, Taylor J, Te A, Tedd H, Tee CJ, Teixeira J, Tench H, Terry S, Thackray-Nocera S, Thaivalappil F, Thamu B, Thickett D, Thomas C, Thomas S, Thomas AK, Thomas-Woods T, Thompson T, Thompson AAR, Thornton T, Tilley J, Tinker N, Tiongson GF, Tobin M, Tomlinson J, Tong C, Touyz R, Tripp KA, Tunnicliffe E, Turnbull A, Turner E, Turner S, Turner V, Turner K, Turney S, Turtle L, Turton H, Ugoji J, Ugwuoke R, Upthegrove R, Valabhji J, Ventura M, Vere J, Vickers C, Vinson B, Wade E, Wade P, Wainwright T, Wajero LO, Walder S, Walker S, Walker S, Wall E, Wallis T, Walmsley S, Walsh JA, Walsh S, Warburton L, Ward TJC, Warwick K, Wassall H, Waterson S, Watson E, Watson L, Watson J, Welch C, Welch H, Welsh B, Wessely S, West S, Weston H, Wheeler H, White S, Whitehead V, Whitney J, Whittaker S, Whittam B, Whitworth V, Wight A, Wild J, Wilkins M, Wilkinson D, Williams N, Williams N, Williams J, Williams-Howard SA, Willicombe M, Willis G, Willoughby J, Wilson A, Wilson D, Wilson I, Window N, Witham M, Wolf-Roberts R, Wood C, Woodhead F, Woods J, Wormleighton J, Worsley J, Wraith D, Wrey Brown C, Wright C, Wright L, Wright S, Wyles J, Wynter I, Xu M, Yasmin N, Yasmin S, Yates T, Yip KP, Young B, Young S, Young A, Yousuf AJ, Zawia A, Zeidan L, Zhao B, Zongo O. Clinical characteristics with inflammation profiling of long COVID and association with 1-year recovery following hospitalisation in the UK: a prospective observational study. Lancet Respir Med 2022; 10:761-775. [PMID: 35472304 PMCID: PMC9034855 DOI: 10.1016/s2213-2600(22)00127-8] [Citation(s) in RCA: 144] [Impact Index Per Article: 72.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 03/23/2022] [Accepted: 03/31/2022] [Indexed: 11/25/2022]
Abstract
BACKGROUND No effective pharmacological or non-pharmacological interventions exist for patients with long COVID. We aimed to describe recovery 1 year after hospital discharge for COVID-19, identify factors associated with patient-perceived recovery, and identify potential therapeutic targets by describing the underlying inflammatory profiles of the previously described recovery clusters at 5 months after hospital discharge. METHODS The Post-hospitalisation COVID-19 study (PHOSP-COVID) is a prospective, longitudinal cohort study recruiting adults (aged ≥18 years) discharged from hospital with COVID-19 across the UK. Recovery was assessed using patient-reported outcome measures, physical performance, and organ function at 5 months and 1 year after hospital discharge, and stratified by both patient-perceived recovery and recovery cluster. Hierarchical logistic regression modelling was performed for patient-perceived recovery at 1 year. Cluster analysis was done using the clustering large applications k-medoids approach using clinical outcomes at 5 months. Inflammatory protein profiling was analysed from plasma at the 5-month visit. This study is registered on the ISRCTN Registry, ISRCTN10980107, and recruitment is ongoing. FINDINGS 2320 participants discharged from hospital between March 7, 2020, and April 18, 2021, were assessed at 5 months after discharge and 807 (32·7%) participants completed both the 5-month and 1-year visits. 279 (35·6%) of these 807 patients were women and 505 (64·4%) were men, with a mean age of 58·7 (SD 12·5) years, and 224 (27·8%) had received invasive mechanical ventilation (WHO class 7-9). The proportion of patients reporting full recovery was unchanged between 5 months (501 [25·5%] of 1965) and 1 year (232 [28·9%] of 804). Factors associated with being less likely to report full recovery at 1 year were female sex (odds ratio 0·68 [95% CI 0·46-0·99]), obesity (0·50 [0·34-0·74]) and invasive mechanical ventilation (0·42 [0·23-0·76]). Cluster analysis (n=1636) corroborated the previously reported four clusters: very severe, severe, moderate with cognitive impairment, and mild, relating to the severity of physical health, mental health, and cognitive impairment at 5 months. We found increased inflammatory mediators of tissue damage and repair in both the very severe and the moderate with cognitive impairment clusters compared with the mild cluster, including IL-6 concentration, which was increased in both comparisons (n=626 participants). We found a substantial deficit in median EQ-5D-5L utility index from before COVID-19 (retrospective assessment; 0·88 [IQR 0·74-1·00]), at 5 months (0·74 [0·64-0·88]) to 1 year (0·75 [0·62-0·88]), with minimal improvements across all outcome measures at 1 year after discharge in the whole cohort and within each of the four clusters. INTERPRETATION The sequelae of a hospital admission with COVID-19 were substantial 1 year after discharge across a range of health domains, with the minority in our cohort feeling fully recovered. Patient-perceived health-related quality of life was reduced at 1 year compared with before hospital admission. Systematic inflammation and obesity are potential treatable traits that warrant further investigation in clinical trials. FUNDING UK Research and Innovation and National Institute for Health Research.
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Host LV, Keen HI, Laslett LL, Black DM, Jones G. Zoledronic acid does not slow spinal radiographic progression of osteoarthritis in postmenopausal women with osteoporosis and radiographic osteoarthritis. Ther Adv Musculoskelet Dis 2022; 14:1759720X221081652. [PMID: 35844267 PMCID: PMC9283639 DOI: 10.1177/1759720x221081652] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Accepted: 01/25/2022] [Indexed: 11/17/2022] Open
Abstract
Introduction: Post hoc analyses of osteoporosis trials have suggested that
alendronate and strontium ranelate may be associated with a reduction in the
progression of spinal radiographic osteoarthritis (OA). We performed an
analysis on a subgroup of participants in the horizon PFT trial (a 3-year
randomized controlled trial (RCT) of yearly zoledronic acid (ZA) in
postmenopausal women with osteoporosis), to evaluate the effect of ZA on the
structural progression of spinal osteophytes (OPh) and disk space narrowing
(DN). Methods: Paired lateral spinal X-rays (baseline and 36 months) were selected from the
horizon PFT trial records restricted to those with radiographic OA at
baseline. The X-rays were analyzed by two readers blinded to the treatment
allocation. OPh and DN were scored separately using the Lane atlas (0–3 for
increasing severity at each vertebral level) at all evaluable levels from
T4–12 and L1–5. Results: A total of 504 sets of paired radiographs were included in the analysis, 245
in the ZA group and 259 in the placebo group. Overall, the rates of change
of OPh and DN scores were low, and they were not statistically different
between the groups (change in the whole spine OPh ZA 1.0 ± 1.6, placebo
0.8 ± 1.3, p = 0.1; DN ZA 0.3 ± 1.0, placebo 0.3 ± 0.8,
p = 0.7). Conclusion: Yearly ZA for 3 years was not associated with a slowing of progression of OPh
or DN in the thoracolumbar spine in patients with pre-existing radiographic
OA.
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Affiliation(s)
- L V Host
- Rheumatology Department, Fiona Stanley Hospital, Murdoch, WA, Australia
| | - H I Keen
- Rheumatology Department, Fiona Stanley Hospital, Murdoch, WA, AustraliaSchool of Medicine, University of Western Australia, Perkins South Building, FSH, Murdoch Drive, Murdoch, WA 6150, Australia
| | - L L Laslett
- Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, Australia
| | - D M Black
- Division of Clinical Trials & Multicenter Studies, University of California, San Francisco, CA, USA
| | - G Jones
- Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, Australia
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Minary K, Tanne C, Kwon T, Faudeux C, Clave S, Langevin L, Pietrement C, Enoch C, Parmentier C, Mariani-Kurkdjian P, Weill FX, Jones G, Djouadi N, Morin D, Fila M. Outbreak of hemolytic uremic syndrome with unusually severe clinical presentation caused by Shiga toxin-producing Escherichia coli O26:H11 in France. Arch Pediatr 2022; 29:448-452. [DOI: 10.1016/j.arcped.2022.05.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 04/04/2022] [Accepted: 05/12/2022] [Indexed: 12/01/2022]
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Lim Y, Cicuttini F, Wluka A, Jones G, Hill C, Forbes A, Tonkin A, Berezovskaya S, Tan L, Ding C, Wang Y. AB0978 Effect of atorvastatin on skeletal muscles of patients with knee osteoarthritis: post-hoc analysis of a randomised controlled trial. Ann Rheum Dis 2022. [DOI: 10.1136/annrheumdis-2022-eular.2213] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
BackgroundStatins are often discontinued due to muscle-related side effects. The effect of statin on skeletal muscles in populations with osteoarthritis is unknown.ObjectivesThis study aims to examine the effect of atorvastatin on skeletal muscle biochemistry, strength, size and symptoms in patients with symptomatic knee osteoarthritis.MethodsThis is a post-hoc analysis of a multicentre randomised, double-blind, placebo-controlled trial over 2 years in which participants with knee osteoarthritis who met the American College of Rheumatology clinical criteria received atorvastatin 40mg daily (n=151) or placebo (n=153). Outcomes included levels of creatinine kinase (CK), aspartate transaminases (AST) and alanine transaminases (ALT) at baseline, 4 weeks, 6, 12 and 24 months; muscle strength measured by dynamometry at baseline, 12 and 24 months; vastus medialis cross-sectional area (CSA) on magnetic resonance imaging at baseline and 24 months; and self-reported myalgia during the trial.Results304 participants [mean age 55.7 (SD 7.6) years, 55.6% female] were randomised. There were no significant differences in CK and AST levels between atorvastatin and placebo groups at 4 weeks (CK median 107 vs 110, p=0.76; AST 22 vs 21, p=0.14), 6 (CK 109 vs 101.5, p=0.37; AST 21 vs 20, p=0.45), 12 (CK 103 vs 103, p=0.93; AST 22 vs 21, p=0.99), and 24 (CK 103 vs 93.5, p=0.17; AST 22 vs 21, p=0.34) months. The atorvastatin group had higher ALT levels than the placebo group at 4 weeks [26 vs 21, p=0.0004] and 6 months [25 vs 22, p=0.007] but no between-group differences at 12 [24 vs 21, p=0.08] and 24 [24 vs 21, p=0.053] months. Muscle strength significantly increased in the atorvastatin group but not the placebo group over 24 months with no between-group differences [mean 8.5 (95% CI 2.6,14.4) vs 5.6 (-0.3,11.5), p=0.50]. Change in vastus medialis CSA over 24 months showed between-group differences favouring the atorvastatin group [+0.12 (-0.09,0.34) vs -0.24 (-0.48,0.01), p=0.03] but of uncertain clinical significance. There was a trend for more myalgia in the atorvastatin group over 2 years (8/151 vs 2/153, p=0.06), mostly occurring within 6 months (7/151 vs 1/153, p=0.04). Of the 10 participants with myalgia, there was no relationship between the incidence of myalgia and CK levels.ConclusionIn those with symptomatic knee osteoarthritis, despite a trend for more myalgia, there was no clear evidence of an adverse effect of atorvastatin on skeletal muscles, including those most relevant to knee joint health.Disclosure of InterestsYuan Lim: None declared, Flavia Cicuttini: None declared, Anita Wluka: None declared, Graeme Jones Speakers bureau: GJ received honoraria for talks from BMS, Roche, AbbVie, Amgen, Lilly, Novartis, and Janssen, Grant/research support from: GJ received grant for a clinical trial from Covance, Catherine Hill: None declared, Andrew Forbes: None declared, Andrew Tonkin Speakers bureau: AT received honoraria for lectures from Pfizer; honoraria for lectures and advisory board participation from Amgen, Consultant of: AT received honoraria for lectures and advisory board participation from Amgen, honoraria for data and safety monitoring board participation from Merck, and honoraria for data and safety monitoring board participation from Novartis, Sofia Berezovskaya: None declared, Lynn Tan: None declared, Changhai Ding: None declared, Yuanyuan Wang: None declared
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Pan F, Tian J, Cervo M, Scott D, Cicuttini F, Jones G. POS1116 DIETARY INFLAMMATORY INDEX AND KNEE STRUCTURES ON MRI AND PAIN: A PROSPECTIVE COHORT STUDY. Ann Rheum Dis 2022. [DOI: 10.1136/annrheumdis-2022-eular.1920] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
BackgroundWhile some individual dietary nutrients/components have been shown to be associated with knee osteoarthritis (OA) progression, the associations of the dietary inflammatory index (DII), which reflects the overall inflammatory potential of a diet, with MRI-detected structural changes and pain have not been investigated.ObjectivesThis longitudinal study aimed to determine whether DII scores are associated with knee structural changes and pain over a 10.7-year follow-up in community-dwelling older adults.MethodsThis study utilised the data from a prospective population-based cohort study (mean age 63 years, 51% women) in which 1,099, 875, 768 and 563 participants completed assessments at baseline, 2.6, 5.1 and 10.7 years, respectively. T1-weighted or T2-weighted MRI of the right knee was performed to measure cartilage volume (CV) and bone marrow lesions (BMLs) at baseline and 10.7 years. The Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain questionnaire was used to measure knee pain at all assessments. Baseline energy-adjusted DII (E-DII) scores were calculated using a validated Food Frequency Questionnaire. X-ray was performed to assess radiographic knee osteoarthritis (ROA). Linear, log-binomial regression and linear mixed-effects modelling with adjustments for covariates were used to examine the associations of E-DII with CV loss, BML size increase and knee pain, respectively. Pain trajectories (i.e., ‘Minimal Pain’, ‘Mild Pain’, and ‘Moderate Pain’) were previously identified in this cohort using group-based trajectory modelling [1]. Multi-nominal logistic regression was used to examine the association between E-DII and pain trajectory groups.ResultsThe mean E-DII at baseline was -0.48±1.39. In multivariable analyses, E-DII score was not associated with tibial CV loss and BML size increase [CV loss: β=0.03% per annum, 95%CI -0.01–0.06; BML size increase: relative risk (RR)=0.94, 95%CI 0.84–1.05;]. Higher E-DII was associated with greater pain score over 10.7 years (β=0.21, 95%CI 0.004-0.43) and an increased risk of belonging to ‘Moderate pain’ as compared to ‘Minimal Pain’ trajectory group [relative risk ratio (RRR): 1.19, 95%CI 1.02-1.39] after adjustment for age, body mass index, physical activity, education level, employment, emotional problems, comorbidities, and ROA.ConclusionHigher DII was associated with greater pain score and higher risk of more severe pain trajectory, but not structural changes, suggesting discordance between effects of diet on structural damage and pain, and that targeting pro-inflammatory diets may be beneficial to reduce pain.References[1]Pan F, Tian J, Aitken D, Cicuttini F, Jones G. Predictors of pain severity trajectory in older adults: a 10.7-year follow-up study. Osteoarthritis Cartilage. 2018;26(12):1619-26.Disclosure of InterestsNone declared
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Drummen S, Balogun S, Scheepers L, Munugoda I, Lahham A, Bennell K, Hinman R, Callisaya M, Cai G, Otahal P, Winzenberg T, Wang Z, Antony B, Martel-Pelletier J, Pelletier JP, Abram F, Jones G, Aitken D. AB0994 Exploring knee osteoarthritis pain trajectories and movement-evoked pain changes during a 24-week outdoor walking program (WALK). Ann Rheum Dis 2022. [DOI: 10.1136/annrheumdis-2022-eular.4090] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
BackgroundExercise therapy is recommended as first line treatment for knee osteoarthritis (OA), but it remains to be sub-optimally applied (1). Movement-evoked pain is a potential barrier to exercise adherence, but recent evidence suggests that such pain can be improved by training (2). Walking programs are low-cost, easily adopted and can be performed outdoors which can minimize the risk of SARS-CoV-2 transmission when in a group (3).ObjectivesTo explore the acute pain trajectories of individuals with knee OA during a 24-week outdoor walking intervention. In addition, to explore the effect of pain trajectories and/or baseline characteristics on retention and adherence.MethodsIndividuals with clinical knee OA and bone marrow lesions (BMLs) on magnetic resonance imaging (MRI) were asked to follow a 24-week walking program. Every week consisted of two one hour supervised group sessions at various outdoor locations and one unsupervised session. At the start and end of every supervised group walk, knee pain was self-reported by participants to their trainer using a numerical rating scale (NRS) (0-10). The difference between the NRS pain values was considered as an acute pain change evoked by that walk. At baseline, the most affected knee of each participant was assessed using the Visual Analogue Scale (VAS) pain, the Western Ontario and McMasters Universities Osteoarthritis Index (WOMAC) pain, stiffness and function, wellbeing (3 questionnaires) and the Osteoarthritis Research Society International (OARSI) recommended strength and performance measures.ResultsIn total, N = 24 participants started the program of whom N = 7 (29%) withdrew. Pain at the start of each walk decreased from NRS 2.5 (SD 1.6) at the first walk (N = 24) to NRS 0.9 (SD 0.8) at the final walk (N = 17). This pain was estimated to decrease on NRS by -0.04 (95% CI -0.05 to -0.02) per supervised session, p < 0.001 during the first 12 weeks and -0.01 (95% CI -0.02 to -0.004), p = 0.004 during the second twelve weeks of the program. The number (%) of participants who experienced an acute increase in pain decreased from 11 (45.8%) at the first walk to 4 (23.5%) at the last walk.At baseline, non-adherent participants (<70% of group sessions) (N = 11) had lower physical performance scores, including the 30s Chair Stand Test (mean 10 (SD 1.7) stands versus mean 12.0 (SD 1.7) stands, p = 0.011), Fast Past Walk Test (1.23 (SD 0.14) meter per seconds (m/s) vs 1.50 (SD 0.20) m/s, p = 0.001), Six Minute Walk Test (418.8 (SD 75.9) m vs 529 (SD 72.6) m, p = 0.002), compared to adherent participants (N = 13). Non-adherent participants also had less severe self-reported symptoms including WOMAC stiffness (90.7 (SD 44.5) mm vs 121.5 (SD 17.0) mm, p = 0.031), compared to adherent participants. During the first two weeks of walking, acute increases in pain on average (mean ≥0.5 NRS) were reported by a greater number of non-adherent (N = 5 (45.5%)) than adherent participants (n = 4 (30.8%)).ConclusionThis was an exploratory study and results need to be interpreted with caution due to the small sample size. The walking program resulted in clinically important improvements (MCIIs) (≥ 1 on NRS) (4) in start pain and acute pain changes. Improvements in start pain during the first 12-weeks were comparable to improvements measured in the NEMEX program (2) and may suggest that 12 weeks of exercise is sufficient to achieve MCIIs in pain. Improvements in acute changes in pain were smaller, which may have been related to a floor effect (5). Lower physical performance scores at baseline and more acute increases in pain during the first two weeks was associated with non-adherence. Participants with these characteristics may benefit from a lighter introduction to exercise.References[1]Bennell KL, et al. The Lancet Regional Health-Western Pacific. 2021;12:100187.[2]Sandal LF, et al. Osteoarthritis and cartilage. 2016;24(4):589-92.[3]Bulfone TC, et al. The Journal of infectious diseases. 2021;223(4):550-61.[4]Perrot S, et al. Pain. 2013;154(2):248-56.[5]McHorney CA, et al. Quality of life research. 1995;4(4):293-307.AcknowledgementsWe thank the participants who made this study possible. We would like to acknowledge the research staff, Kate Probert, Lizzy Reid, Simone Fitzgerald, Claire Roberts, Jasmin Ritchie, Dawn Simpson, and Tim Albion. We also thank Hamish Newsham-West for his contribution to the study design.Disclosure of InterestsStan Drummen: None declared, Saliu Balogun: None declared, Lieke Scheepers Grant/research support from: Competitive Grant Program Inflammation ASPIRE 2020 Rheumatology International Developed Markets from Pfizer, Employee of: previously worked as an Associate Director Epidemiology at the Medical Evidence Observational Research Department at AstraZeneca., Ishanka Munugoda: None declared, aroub lahham: None declared, Kim Bennell: None declared, Rana Hinman: None declared, Michele Callisaya: None declared, Guoqi Cai: None declared, Petr Otahal: None declared, Tania Winzenberg Consultant of: received payment to create educational material by AMGEN, Zhiqiang Wang: None declared, Benny Antony: None declared, Johanne Martel-Pelletier Shareholder of: ArthroLab Inc., Jean-Pierre Pelletier Shareholder of: ArthroLab Inc., François Abram Consultant of: ArthroLab Inc., Employee of: Arthrolab Inc., Graeme Jones Speakers bureau: received payment for a speakers bureau from Novartis, Dawn Aitken: None declared
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Ma C, Liu M, Tian J, Zhai G, Cicuttini F, Schooneveldt Y, Meikle P, Jones G, Pan F. AB1474 LIPIDOMIC PROFILING IDENTIFIES SERUM LIPIDS ASSOCIATED WITH PERSISTENT MULTISITE MUSCULOSKELETAL PAIN. Ann Rheum Dis 2022. [DOI: 10.1136/annrheumdis-2022-eular.1922] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
BackgroundLipid mediators have been suggested to have a role in pain sensitivity and response; however, longitudinal data on lipid metabolites and persistent multisite musculoskeletal pain (MSMP) are lacking.ObjectivesThis study was to identify lipid metabolic markers for persistent MSMP.MethodsLipidomic profiling of 807 lipid species was performed on serum samples of 536 participants from a cohort study. MSMP was measured by a questionnaire and defined as painful sites ≥4. Persistent MSMP was defined as having MSMP at every visit. Logistic regression was used with adjustment for potential confounders. The Benjamini Hochberg method was used to control for multiple testing.ResultsA total of 530 samples with 807 lipid metabolites passed quality control. Mean age at baseline was 61.54±6.57 years and 50% were females. One hundred and twelve (21%) of the participants had persistent MSMP. Persistent MSMP was significantly associated with lower levels of monohexosylceramide (HexCer)(d18:1/22:0 and d18:1/24:0), acylcarnitine (AC)(26:0) and lysophosphatidylcholine (LPC)(18:1 [sn1], 18:2 [sn1], 18:2 [sn2], and 15-MHDA[sn1] [104_sn1]) after controlling for multiple testing. After adjustment for age, sex, body mass index, diabetes status, and physical activity, HexCer(d18:1/22:0 and d18:1/24:0) and LPC(18:1 [sn1] and 15-MHDA [sn1] [104_sn1]) were significantly associated with persistent MSMP [Odds Ratio (OR) ranging from 0.24 - 0.32]. Two lipid classes -- HexCer and LPC were negatively associated with persistent MSMP after adjustment for covariates (OR=0.19 and 0.21, respectively).ConclusionThis study identified four novel lipid signatures of persistent MSMP, suggesting that lipid metabolism is involved in the pathogenesis of persistent pain.Disclosure of InterestsNone declared
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Scheepers L, Jones G. AB0414 DRUG PERSISTENCE ON JANUS KINASE (JAK) INHIBITORS COMPARED TO BIOLOGIC DMARDs IN PATIENTS WITH RHEUMATOID ARTHRITIS: RETROSPECTIVE STUDY IN THE AUSTRALIAN POPULATION. Ann Rheum Dis 2022. [DOI: 10.1136/annrheumdis-2022-eular.4149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
BackgroundIn rheumatoid arthritis (RA) persistence on disease modifying anti-rheumatic drugs (DMARDs) can be interpreted as a composite measure of effectiveness, safety, and tolerability. There is limited data available on real-life use of the newest class of drugs, the Janus Kinase (JAK) inhibitors. JAK inhibitors are small-molecule treatments which are administered orally on a daily basis and offer a long-term option in RA treatment.ObjectivesTo compare drug persistence on JAK inhibitors tofacitinib, baricitinib and upadacitinib to tumor necrosis factor-α (TNF) inhibitors and other DMARDs in RA patients in Australia.MethodsA retrospective observational study was conducted among RA patients in the Australian Medicare Database (from January 2006 till October 2021), aged ≥18 and for whom a JAK inhibitor or biologic DMARDs were dispensed. Data were provided by the Australian Department of Health and Aging through PROSPECTION, an Australian healthcare consulting company. A deidentified 10% sample of the database was taken as a random representation of RA patients in Australia.Kaplan-Meier analysis was used to calculate drug persistence rates, defined as the time from treatment initiation until the date of the last dose when there had not been a script dispensed for 6 months; except for rituximab, where a 12-month gap was applied.ResultsData from 5,455 patients were analysed. For all patients the 12-month persistence rates were 61% for JAK inhibitors (baricitinib, tofacitinib, upadacitinib), 62% for tocilizumab, 52% for TNF inhibitors (adalimumab, certolizumab, etanercept, golimumab, infliximab), and 51% for abatacept. The JAK inhibitors baricitinib (64%) and upadacitinib (78%) were superior to tofacitinib (54%). Median treatment persistence for upadacitinib was not reached (n = 430); was 27.1 months for baricitinib and 15.2 months for tofacitinib. For TNF inhibitors, treatment persistence was 15.1 months for adalimumab, 14.1 months for certolizumab, 14.0 months for etanercept, 11.1 months for golimumab and 4.5 months for infliximab.Persistence rates on first-line JAK inhibitors were 70% for baricitinib and 57% for tofacitinib; persistence rates dropped to 63% for baricitinib and 47% for tofacitinib in the second-line setting. First-line persistence rates were 54% for TNF inhibitors and 65% for tocilizumab, rates were sustained for tocilizumab, but dropped to 48% for TNF inhibitors in the second-line setting.ConclusionThis real-world data highlights that in an Australian clinical practice setting treatment persistence rates on 12 months on JAK inhibitors, in particular baricitinib and upadacitinib, were superior to TNF inhibitors, but not to tocilizumab. Suggesting that persistence rates might differ according to biologics mode of action and line of treatment.Table 1.Persistence rates at 12 months post treatment initiationAll patientsFirst lineSecond lineJAK inhibitorsOverall61% (2155)60% (616)60% (554)Baricitinib64% (537)70% (158)63% (124)Tofacitinib54% (1188)57% (441)47% (294)Upadacitinib78% (430)28% (17)84% (136)TNF inhibitorsOverall52% (6339)54% (4227)48% (1561)Adalimumab55% (2710)56% (2030)48% (590)Certolizumab51% (593)54% (251)47% (147)Etanercept52% (2079)55% (1354)47% (623)Golimumab49% (814)49% (506)47% (174)Infliximab35% (143)23% (86)53% (27)Other DMARDsAbatacept51% (952)56% (263)46% (310)Rituximab49% (284)41% (70)65% (79)Tocilizumab62% (1156)65% (279)65% (351)In brackets are number of patients.References[1]Hetland, M.L., et al., Direct comparison of treatment responses, remission rates, and drug adherence in patients with rheumatoid arthritis treated with adalimumab, etanercept, or infliximab: results from eight years of surveillance of clinical practice in the nationwide Danish DANBIO registry. Arthritis Rheum, 2010[2]Jones, G., et al., A retrospective review of the persistence on bDMARDs prescribed for the treatment of rheumatoid arthritis in the Australian population. Int J Rheum Dis, 2018AcknowledgementsL. Scheepers receives funding from The Farrell Family Foundation.Disclosure of InterestsLieke Scheepers Grant/research support from: received the Competitive Grant Program InflammationASPIRE 2020 Rheumatology International Developed Markets from Pfizer, Employee of: worked as an Associate Director Epidemiology at the Medical Evidence Observational Research Department at AstraZeneca., Graeme Jones Speakers bureau: Received payment for a speakers bureau from Novartis
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Bonakdari H, Pelletier JP, Blanco FJ, Rego-Perez I, Durán-Sotuela A, Aitken D, Jones G, Cicuttini F, Jamshidi A, Abram F, Martel-Pelletier J. POS0231 GENETIC BIOMARKERS, SNP GENES AND mtDNA HAPLOGROUPS, PREDICT OSTEOARTHRITIS STRUCTURAL PROGRESSORS THROUGH THE USE OF SUPERVISED MACHINE LEARNING. Ann Rheum Dis 2022. [DOI: 10.1136/annrheumdis-2022-eular.4778] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
BackgroundKnee osteoarthritis is the most prevalent chronic musculoskeletal debilitating disease. Current treatments are only symptomatic and to improve this, we need a robust prediction model to stratify patients at an early stage according to the risk of joint structure disease progression. Some genetic factors, including single nucleotide polymorphism (SNP) genes and mitochondrial (mt)DNA haplogroups/clusters, have been linked to this disease.ObjectivesFor the first time, we aim to determine, by using machine learning, whether some SNP genes and mtDNA haplogroups/clusters alone or combined could predict early knee osteoarthritis structural progressors.MethodsParticipants (901) were first classified for the probability of being structural progressors. Genotyping included SNP genes TP63, FTO, GNL3, DUS4L, GDF5, SUPT3H, MCF2L, TGFA, mtDNA haplogroups H, J, T, Uk, others, and clusters HV, TJ, KU, C-others. They were considered for prediction with major risk factors of osteoarthritis, namely, age and body mass index (BMI). Seven supervised machine learning methodologies were evaluated. The support vector machine was used to generate gender-based models. The best input combination was assessed using sensitivity and synergy analyses. Validation was performed using 10-fold cross-validation as well as an external cohort (TASOAC).ResultsFrom 277 models, two were defined. Both used age and BMI in addition for the first one of the SNP genes TP63, DUS4L, GDF5, FTO with an accuracy of 85.0%; the second profits from the association of mtDNA haplogroups and SNP genes FTO and SUPT3H with 82.5% accuracy. The highest impact was associated with the haplogroup H, the presence of CT alleles for rs8044769 at FTO, and the absence of AA for rs10948172 at SUPT3H. Validation accuracy with the cross-validation (about 95%) and the external cohort (90.5%, 85.7%, respectively) was excellent for both models.ConclusionThis study introduces a novel source of decision support in precision medicine in which, for the first time, two models were developed consisting of i) age, BMI, TP63, DUS4L, GDF5, FTO and ii) the optimum one as it has one less variable: age, BMI, mtDNA haplogroup, FTO, SUPT3H. Such a framework is translational and would be of benefit to patients at risk of structural progressive knee osteoarthritis.AcknowledgementsThe authors would like to thank the Osteoarthritis Initiative (OAI) participants and Coordinating Center for their work in generating the clinical and radiological data of the OAI cohort and for making them publicly available. The OAI is a public-private partnership comprised of five contracts (N01-AR-2-2258; N01-AR-2-2259; N01-AR-2-2260; N01-AR-2-2261; N01-AR-2-2262) funded by the National Institutes of Health, a branch of the Department of Health and Human Services, and conducted by the OAI Study Investigators. Private funding partners include Merck Research Laboratories; Novartis Pharmaceuticals Corporation, GlaxoSmithKline; and Pfizer, Inc. Private sector funding for the OAI is managed by the Foundation for the National Institutes of Health. This manuscript was prepared using an OAI public use data set and does not necessarily reflect the opinions or views of the OAI investigators, the NIH, or the private funding partners. None of the authors are part of the OAI investigator team. Moreover, the authors are also grateful to the TASOAC participants.A special thanks to ArthroLab Inc. for having provided the MRI data used for classifying structural progressors for each individual.Disclosure of InterestsHossein Bonakdari: None declared, Jean-Pierre Pelletier Shareholder of: ArthroLab Inc., Grant/research support from: Work supported in part by the Osteoarthritis Research Unit of the University of Montreal Hospital Research Centre and the Chair in Osteoarthritis from the University of Montreal., Francisco J. Blanco: None declared, Ignacio Rego-Perez: None declared, Alejandro Durán-Sotuela: None declared, Dawn Aitken: None declared, Graeme Jones: None declared, Flavia Cicuttini: None declared, Afshin Jamshidi Grant/research support from: Received a bursary from the Canada First Research Excellence Fund through the TransMedTech Institute in Canada., François Abram Employee of: was an employee of ArthroLab Inc., Johanne Martel-Pelletier Shareholder of: ArthroLab Inc., Grant/research support from: Work supported in part by the Osteoarthritis Research Unit of the University of Montreal Hospital Research Centre and the Chair in Osteoarthritis from the University of Montreal.
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Antony B, Venn A, Blizzard L, March L, Cicuttini F, Eckstein F, Jones G, Ding C, Singh A. POS0178 ASSOCIATION BETWEEN KNEE MR IMAGING MARKERS AND KNEE SYMPTOMS OVER 7 YEARS IN YOUNG ADULTS. Ann Rheum Dis 2022. [DOI: 10.1136/annrheumdis-2022-eular.2543] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
BackgroundKnee magnetic resonance imaging (MRI)-based morphological markers (quantitative biomarkers) and structural abnormalities (semi-quantitative biomarkers) are known to be associated with the progression of knee osteoarthritis (OA). However, there is conflicting evidence on the association between knee MRI-based morphological markers and knee symptoms. Besides, there is a lack of evidence on the clinical significance of MR imaging markers in the general population-based young adults. Hence, our aim was to investigate the associations between MR imaging biomarkers and knee symptoms in middle-aged adults followed over seven years.ObjectivesTo describe the associations of cartilage volume, cartilage thickness, subchondral bone area, cartilage defects, and bone marrow lesions (BML) with knee symptoms in young adults followed up over 6-9 years.MethodsKnee symptoms (pain, stiffness, and dysfunction) were assessed using the Western Ontario and McMaster University Osteoarthritis Index (WOMAC) scale during Childhood Determinants of Adult Health (CDAH)-knee study at baseline (year: 2008-10, age: 30–40 years) and 6-9 year follow-up (CDAH-3; year: 2014–2019, age: 36–49 years). Knee MRI scans were obtained at baseline and were assessed quantitatively for morphological markers such as cartilage volume, cartilage thickness, subchondral bone area using semi-automated segmentation (Chondrometrics, Germany). Cartilage defects and BMLs were assessed using semi-quantitative scoring systems. Univariable and multivariable (adjusted for age, sex, and body mass index (BMI)) zero-inflated Poisson (ZIP) regression model with random effects were used to describe the cross-sectional and longitudinal associations.ResultsThe prevalence of knee pain at baseline (mean age (SD): 34 (2.7); female 49%) was 34% that increased to 50% over 6-9 year follow-up (mean age (SD): 43 (3.2)). Cross sectionally, there was a weak but statistically significant negative association between medial femorotibial compartment (MFTC) [Ratio of Mean (RoM)= 0.99971084; 95% CI: (0.9995525, 0.99986921; p<0.001], lateral femorotibial compartment (LFTC) [RoM=0.99982602; 95% CI: 0.99969915, 0.9999529; p=0.007], and patellar cartilage volume [RoM=0.99981722; 95% CI: 0.99965326, 0.9999811; p=0.029] with knee symptoms.Similarly, there was a negative association between patellar cartilage volume (RoM=0.99975523; 95% CI: 0.99961427, 0.99989621; p=0.014), MFTC cartilage thickness (RoM= 0.72090775; 95% CI: 0.59481806, 0.87372596; p=0.001) and knee symptoms assessed after seven years.The total bone area was consistently and negatively associated with knee symptoms at baseline [RoM= 0.9210485; 95%CI: 0.8939677, 0.9489496; p<0.001] and over seven years (RoM=0.9588811; 95% CI: 0.9313379, 0.9872388; p=0.005). Presence of any cartilage defect or BML was associated with higher knee symptoms at baseline and after seven years.ConclusionIn the middle-aged adult population, BML and cartilage defects were positively associated with knee symptoms, whereas cartilage volume and thickness at MFTC and total bone area were weakly and negatively associated with knee symptoms. These results suggest that the quantitative and semi-quantitative MR imaging biomarkers can be explored as a marker of the clinical progression of OA in a young adult population.Disclosure of InterestsBenny Antony: None declared, Alison Venn: None declared, Leigh Blizzard: None declared, Lyn March: None declared, Flavia Cicuttini: None declared, Felix Eckstein Shareholder of: Shareholder of Chondrometrics, image processing company, Graeme Jones: None declared, Changhai Ding: None declared, Ambrish Singh: None declared
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Sutton L, Lahham A, Jose K, Moore M, Antony B, Grunseit A, Cleland V, Balogun S, Winzenberg T, Jones G, Aitken D. Feasibility of ‘parkrun’ for people with knee osteoarthritis: A mixed methods pilot study. Osteoarthritis and Cartilage Open 2022; 4:100269. [DOI: 10.1016/j.ocarto.2022.100269] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2022] [Revised: 04/18/2022] [Accepted: 05/02/2022] [Indexed: 10/18/2022] Open
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Singh A, Venn A, Blizzard L, Jones G, Burgess J, Parameswaran V, Cicuttini F, March L, Eckstein F, Wirth W, Ding C, Antony B. Association between osteoarthritis-related serum biochemical markers over 11 years and knee MRI-based imaging biomarkers in middle-aged adults. Osteoarthritis Cartilage 2022; 30:756-764. [PMID: 35240332 DOI: 10.1016/j.joca.2022.02.616] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Revised: 12/20/2021] [Accepted: 02/17/2022] [Indexed: 02/02/2023]
Abstract
OBJECTIVE To describe the associations between osteoarthritis (OA)-related biochemical markers (COMP, MMP-3, HA) and MRI-based imaging biomarkers in middle-aged adults over 10-13 years. METHODS Blood serum samples collected during the Childhood Determinants of Adult Health (CDAH)-1 study (year:2004-06; n = 156) and 10-13 year follow-up at CDAH-3 (n = 167) were analysed for COMP, MMP-3, and HA using non-isotopic ELISA. Knee MRI scans obtained during the CDAH-knee study (year:2008-10; n = 313) were assessed for cartilage volume and thickness, subchondral bone area, cartilage defects, and BML. RESULTS In a multivariable linear regression model describing the association of baseline biochemical markers with MRI-markers (assessed after 4-years), we found a significant negative association of standardised COMP with medial femorotibial compartment cartilage thickness (β:-0.070; 95%CI:-0.138,-0.001), and standardised MMP-3 with patellar cartilage volume (β:-141.548; 95%CI:-254.917,-28.179) and total bone area (β:-0.729; 95%CI:-1.340,-0.118). In multivariable Tobit regression model, there was a significant association of MRI-markers with biochemical markers (assessed after 6-9 years); a significant negative association of patellar cartilage volume (β:-0.001; 95%CI:-0.002,-0.00004), and total bone area (β:-0.158; 95%CI-0.307,-0.010) with MMP-3, and total cartilage volume (β:-0.001; 95%CI:-0.001,-0.0001) and total bone area (β:-0.373; 95%CI:-0.636,-0.111) with COMP. No significant associations were observed between MRI-based imaging biomarkers and HA. CONCLUSION COMP and MMP-3 levels were negatively associated with knee cartilage thickness and volume assessed 4-years later, respectively. Knee cartilage volume and bone area were negatively associated with COMP and MMP-3 levels assessed 6-9 years later. These results suggest that OA-related biochemical markers and MRI-markers are interrelated in early OA.
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Affiliation(s)
- A Singh
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Australia
| | - A Venn
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Australia
| | - L Blizzard
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Australia
| | - G Jones
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Australia
| | - J Burgess
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Australia; Department of Endocrinology, Royal Hobart Hospital, Hobart, Australia
| | - V Parameswaran
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Australia; Department of Endocrinology, Royal Hobart Hospital, Hobart, Australia
| | - F Cicuttini
- Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia
| | - L March
- Institute of Bone and Joint Research, Kolling Institute of Medical Research, University of Sydney, Sydney, Australia; Florance and Cope Professorial Rheumatology Department, University of Sydney Royal North Shore Hospital, St Leonards, Sydney, Australia
| | - F Eckstein
- Chondrometrics GmbH, Ainring, Germany; Department of Imaging and Functional Musculoskeletal Research, Institute of Anatomy & Cell Biology, Paracelsus Medical University Salzburg & Nuremberg, Salzburg, Austria; Ludwig Boltzmann Institute for Arthritis and Rehabilitation, Paracelsus Medical University, Salzburg, Austria
| | - W Wirth
- Chondrometrics GmbH, Ainring, Germany; Department of Imaging and Functional Musculoskeletal Research, Institute of Anatomy & Cell Biology, Paracelsus Medical University Salzburg & Nuremberg, Salzburg, Austria; Ludwig Boltzmann Institute for Arthritis and Rehabilitation, Paracelsus Medical University, Salzburg, Austria
| | - C Ding
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Australia; Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia; Clinical Research Centre, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - B Antony
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Australia.
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Russell L, Janisse N, Jones G, Karachi T, Serrano PE, ApSimon M, Armstrong D, Pinto-Sanchez MI. A251 USE OF INDIRECT CALORIMETRY TESTING TO DIRECT NUTRITION SUPPORT IN CRITICALLY ILL PATIENTS WITH GASTROINTESTINAL CONDITIONS. J Can Assoc Gastroenterol 2022. [PMCID: PMC8859362 DOI: 10.1093/jcag/gwab049.250] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Background Indirect calorimetry (IC), which measures oxygen uptake and carbon dioxide output, determines energy expenditure (EE) more precisely than predictive equations in critically ill patients. It is unknown whether the use of IC affects energy provision in critically ill patients with gastrointestinal (GI) conditions that affect absorption and digestion Aims To (1) compare IC and predictive equations for determining energy needs and (2) evaluate whether IC results affect changes in nutrition support in critically ill patients with GI conditions. Methods In a prospective, observational study, IC was performed for 25 to 55 mins in critically ill patients admitted to intensive care or clinical wards at 2 tertiary-care hospitals in Hamilton, Ontario between Feb 2018 to Sept 2021. EE measured by IC was compared to EE determined by a predictive equation (25 kcal/kg) or the Harris-Benedict (HB) formula. A change in energy provision was defined as a change of >10% directed by IC. Continuous data are expressed as means and standard deviation (SD), and categorical data as a proportion of patients. The Mann Whitney U Test (SPSSv26) was used to compare GI and non-GI populations. Results Of 296 IC tests in 229 patients, 39 of them were in 30 GI patients (11 female; mean age 62 yrs; SD 19). Admission GI diagnoses were pancreatitis (33%), liver disease (20%), Crohn’s disease/ autoimmune enteropathy (20%), post-bowel resection (10%), chronic abdominal pain (10%), and cholangitis (7%). The predictive formula underestimated EE in 67% of GI patients (mean deficit 503 kcal/day) compared to IC, corresponding to a mean deficit of 25% of patients’ energy needs. The HB formula underestimated EE in 73% of patients (mean deficit 652 kcal/day), a mean deficit of 28% of patients’ energy needs compared to IC. Pancreatitis was the majority diagnosis (75% of the predictive equation; 50% HB) among patients with the highest deficit (>30%) in energy needs when compared to IC. There were no significant differences in the rates of underestimation of energy needs based on predictive and HB formulas between the GI and non-GI patients or between luminal GI and non-luminal GI conditions. After IC, 63% of tests led to changes in energy provisions in GI patients; most requiring an increase in energy provisions (53%). Conclusions The use of IC to accurately measure EE led to changes in energy provisions in critically ill GI patients. Preventing over- and underfeeding with the implementation of IC to guide nutrition has the potential to improve outcomes in critically ill patients with gastrointestinal conditions. Funding Agencies None
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Affiliation(s)
- L Russell
- McMaster University, Hamilton, ON, Canada
| | - N Janisse
- Hamilton Health Sciences, Hamilton, ON, Canada
| | - G Jones
- McMaster University, Hamilton, ON, Canada
| | - T Karachi
- McMaster University, Hamilton, ON, Canada
| | | | - M ApSimon
- Hamilton Health Sciences, Hamilton, ON, Canada
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Gao S, Porumb M, Mumith A, Parker A, Walker S, Jones G, Chartsias A, Oliveira J, Hawkes W, Sarwar R, Leeson P, Woodward G, Beqiri A. Fully automated quantification of LV regional wall motion from echocardiograms to detect myocardial infarction. Eur Heart J Cardiovasc Imaging 2022. [DOI: 10.1093/ehjci/jeab289.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Abstract
Funding Acknowledgements
Type of funding sources: Private company. Main funding source(s): Ultromics Ltd
Background
Myocardial wall motion analysis from echocardiography allows precise assessment of cardiac contractile function. Strain, which assesses myocardial deformation, has been shown to enable earlier detection of myocardial disease [1]. Current analysis software packages [2] use semi-automated methods to compute strain, which frequently require manual endocardial delineation and iterative contour adjustment based on tracking results, respectively, causing significant variability.
Purpose
We present a fully automated pipeline for tracking left ventricular (LV) wall motion to quantify global and segmental longitudinal strain from 2D echocardiograms, and go on to validate the pipeline with an openly available myocardial infarction (MI) dataset.
Methods
We applied our existing deep learning-based automated contouring method [3] to delineate the endocardial border in the A4C, A2C and A3C views and combined this with spline-based elastic image registration to track LV motion through time. We sampled points from a region of interest initiated from the endocardial border at the end-diastolic (ED) frame, and tracked subsequent motion by recomputing updated positions of all sample points based on each frame‘s displacement field, enabling us to both track the myocardium throughout the cardiac cycle and calculate longitudinal strain relative to the ED frame. The automated endocardial contour was used to regularise the process. The pipeline was independently tested on the HMC-QU dataset [4] which was downloaded from Kaggle and consists of a single cardiac cycle from the A4C view from 160 patients who were diagnosed with an acute MI and underwent echocardiography either prior to percutaneous coronary intervention or within 24 hours of undergoing the procedure; the dataset includes the labels of ED and end-systolic (ES) frames, as well as the presence of an MI in 6 segments excluding the apical cap (Fig 1a), as determined by the consensus of cardiologists from HMC Hospital in Qatar. The Wilcoxon signed-rank test was used to compare peak strain between the MI and non-MI segments; ROC curves were computed to compare the performance of the automatically derived peak longitudinal strain against the MI labels.
Results
Fig 1b shows ROC curves of peak segmental longitudinal strain for detecting MI, with the best performance in the mid-anterolateral segment (AUC 0.84), and a lower performance for basal segments than mid and apical segments, consistent with known variation in clinical practice [5]. Fig 2 shows that peak longitudinal strain computed from our pipeline was statistically significantly more positive in segments with an MI.
Conclusions
We present a fully automated pipeline for calculating segmental strain across a cardiac cycle to identify infarcted segments without any observer variability. Clinical application of this method has the potential to identify and monitor regional myocardial function and benefit patient management. Abstract Figure. Fig1. ROC of peak longitudinal strains Abstract Figure. Fig2.Boxplot of peak longitudinal strain
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Affiliation(s)
- S Gao
- Ultromics Ltd, Oxford, United Kingdom of Great Britain & Northern Ireland
| | - M Porumb
- Ultromics Ltd, Oxford, United Kingdom of Great Britain & Northern Ireland
| | - A Mumith
- Ultromics Ltd, Oxford, United Kingdom of Great Britain & Northern Ireland
| | - A Parker
- Ultromics Ltd, Oxford, United Kingdom of Great Britain & Northern Ireland
| | - S Walker
- Ultromics Ltd, Oxford, United Kingdom of Great Britain & Northern Ireland
| | - G Jones
- Ultromics Ltd, Oxford, United Kingdom of Great Britain & Northern Ireland
| | - A Chartsias
- Ultromics Ltd, Oxford, United Kingdom of Great Britain & Northern Ireland
| | - J Oliveira
- Ultromics Ltd, Oxford, United Kingdom of Great Britain & Northern Ireland
| | - W Hawkes
- Ultromics Ltd, Oxford, United Kingdom of Great Britain & Northern Ireland
| | - R Sarwar
- Ultromics Ltd, Oxford, United Kingdom of Great Britain & Northern Ireland
| | - P Leeson
- John Radcliffe Hospital, Cardiovascular Clinical Research Facility, Oxford, United Kingdom of Great Britain & Northern Ireland
| | - G Woodward
- Ultromics Ltd, Oxford, United Kingdom of Great Britain & Northern Ireland
| | - A Beqiri
- Ultromics Ltd, Oxford, United Kingdom of Great Britain & Northern Ireland
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Ramsay I, Patel N, Peat N, Jones G. The South-East London community head and neck cancer team audit of the altered airway service. Physiotherapy 2022. [DOI: 10.1016/j.physio.2021.12.185] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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Jones G, Cooper C, Petersson K. FLASH Mechanisms Track (Oral Presentations) COMET ASSAY MEASURES INDICATE LOWER DNA DAMAGE LEVELS IN WHOLE BLOOD PBLS FOLLOWING EX VIVO ELECTRON FLASH EXPOSURES OVER 0.25–1% OXYGEN. Phys Med 2022. [DOI: 10.1016/s1120-1797(22)01556-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/19/2022] Open
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Edwards R, Jones G, Pickford R, Mungin-Jenkins E, Lucas J. The Impact of a Pre-Operative Spinal Education (POSE) program on post-operative length of stay following spinal fusion surgery. Physiotherapy 2021. [DOI: 10.1016/j.physio.2021.10.268] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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Shah A, Wu F, Jones G, Cicuttini F, Toh LS, Laslett LL. The association between incident vertebral deformities, health-related quality of life and functional impairment: a 10.7-year cohort study. Osteoporos Int 2021; 32:2247-2255. [PMID: 34009448 DOI: 10.1007/s00198-021-06004-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/09/2020] [Accepted: 05/10/2021] [Indexed: 11/24/2022]
Abstract
UNLABELLED We aimed to describe longitudinal changes in health-related quality of life (HRQoL) measures associated with incident vertebral deformities (VDs) over 10.7 years. Incident VDs are associated with clinically significant functional impairment in men, and reduction in overall HRQoL in older women. Increasing severity and number of incident VDs are associated with clinically meaningful functional impairment in men, but not women. INTRODUCTION To describe associations between incident VD and changes in HRQoL and functional ability in older adults over 10.7 years. METHODS Participants (n = 780) underwent whole-body dual-energy X-ray absorptiometry (DXA) scans at baseline, 2.5, 5.1 and 10.7 years later. VD was defined as ≥ 25% reduction in anterior height relative to posterior height of vertebrae from T4 to L4. An incident VD was defined as a new VD at any follow-up visit. Assessment of Quality of Life (AQoL-4D) questionnaire and Health Assessment Questionnaire-Disability Index (HAQ-DI) were used to assess HRQoL and functional impairment. Changes in AQoL and HAQ-DI associated with incident VD were analysed using multilevel mixed-effects linear regression. Log binomial regression was used to examine clinically relevant changes and effects of severity and number of VD. RESULTS The incidence of VD was 37% over 10.7 years. In women, incident VDs were associated with annual reduction in AQoL utility score (β = -0.005, 95% CI -0.008 to -0.002). Men had increased risk of clinically significant reduction in HAQ-DI (IRR = 1.76, 95% CI 1.07-2.89). Men had increased risk of clinically important functional impairment with increasing severity (IRR 1.76, 95% CI 1.04-2.95 for mild vs IRR 1.98, 95% CI 1.13-3.47 for moderate to severe VD) as well as number of incident VD (IRR 1.85, 95% CI 1.17-2.93 for one vs IRR 1.88, 95% CI 0.94-3.78 for ≥ 2 VDs). Such associations were not observed in women. CONCLUSIONS Incident VDs are associated with clinically significant functional impairment in men, and reduction in overall HRQoL in older women. Increasing severity and number of incident VDs are associated with clinically meaningful functional impairment in men, but not women.
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Affiliation(s)
- A Shah
- Menzies Institute for Medical Research, University of Tasmania, 17 Liverpool Street, Hobart, TAS, 7000, Australia.
| | - F Wu
- Menzies Institute for Medical Research, University of Tasmania, 17 Liverpool Street, Hobart, TAS, 7000, Australia
| | - G Jones
- Menzies Institute for Medical Research, University of Tasmania, 17 Liverpool Street, Hobart, TAS, 7000, Australia
| | | | - L S Toh
- School of Pharmacy, University of Nottingham, Nottingham, UK
| | - L L Laslett
- Menzies Institute for Medical Research, University of Tasmania, 17 Liverpool Street, Hobart, TAS, 7000, Australia
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Bradley C, Aggarwal A, Goatman K, Jones G, Berry C, Good R. Patients presenting with acute coronary syndromes have unreported coronary artery calcium on historical CT imaging. Eur Heart J 2021. [DOI: 10.1093/eurheartj/ehab724.2528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Abstract
Introduction
Ischaemic heart disease (IHD) remains the leading cause of mortality globally1. The presence and extent of coronary artery calcification (CAC) is a strong predictor of cardiovascular events, and CAC scoring has been shown to be more predictive of cardiovascular events than other traditional risk assessment scores2.
Incidental coronary calcification can be detected and quantified on non-gated CT chest scans covering the heart in the field of view3. This finding is typically not reported4 and hence an opportunity to optimise cardiovascular risk assessment and treatment is missed.
Purpose
We sought to investigate whether patients presenting to our centre with an acute coronary syndrome (ACS) event had historical CT imaging demonstrating coronary artery calcification.
Methods
We retrospectively reviewed case records for all patients referred to our centre for an invasive coronary angiogram following their first known admission with an ACS event. ACS were defined according to contemporary guidelines from the European Society of Cardiology. We reviewed a 3 month period prior to the COVID-19 pandemic (01/01/2019–31/03/2019). The national imaging database was interrogated to identify previous CT imaging that includes the heart in the field of view. The presence of coronary calcification was confirmed and quantified using an ordinal scoring method previously described3. The clinical radiology reports for the scans were reviewed to determine the frequency of CAC being reported.
Demographic information was collected from our electronic patient record including the presence of risk factors for IHD. Prescribed medication prior to admission was also recorded using the on-admission medicines reconciliation documented in the electronic patient record.
Results
385 patients with first presentation of ACS were identified. 75 (19%) had a prior non-gated CT chest imaging. The most common indication for CT was for investigation of possible malignancy. The mean interval from CT imaging to ACS admission was 36 months.
CAC was present on 67 (89%) scans. The mean ordinal score was 4.04, corresponding to moderate CAC. The distribution of CAC by coronary artery revealed the majority of disease to involve the left anterior descending artery (Table 1). Only 12/67 (18%) of clinical radiology reports mentioned coronary calcification (Figure 1).
Patients with CAC frequently had additional risk factors for IHD. Despite this only 42% were prescribed antiplatelet therapy, and only 45% prescribed a statin.
Conclusions
A significant proportion of ACS admissions have evidence of CAC on historical CT scans. This finding is often not reported and the majority of patients with demonstrated coronary artery disease are not prescribed appropriate preventative therapies. Systematic reporting of this finding may have a significant impact on the prevention of acute cardiovascular events.
Funding Acknowledgement
Type of funding sources: None. Table 1
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Affiliation(s)
- C Bradley
- Golden Jubilee National Hospital, Glasgow, United Kingdom
| | - A Aggarwal
- University of Glasgow, Glasgow, United Kingdom
| | - K Goatman
- Canon Medical Europe, Edinburgh, United Kingdom
| | - G Jones
- Swansea University, Swansea, United Kingdom
| | - C Berry
- University of Glasgow, Glasgow, United Kingdom
| | - R Good
- Golden Jubilee National Hospital, Glasgow, United Kingdom
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Franzen-Castle L, Schwarz C, Brison C, Larvick C, Aufdenkamp B, Frecks N, Jones G, Urbanec N, Wells C. Home Food Preservation Virtual Learning Series Increases Knowledge, Understanding, and Confidence for Preserving Food. J Acad Nutr Diet 2021. [DOI: 10.1016/j.jand.2021.06.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Jones G, Parr J, Nithiarasu P, Pant S. Machine learning for detection of stenoses and aneurysms: application in a physiologically realistic virtual patient database. Biomech Model Mechanobiol 2021; 20:2097-2146. [PMID: 34333696 PMCID: PMC8595223 DOI: 10.1007/s10237-021-01497-7] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2021] [Accepted: 07/12/2021] [Indexed: 11/27/2022]
Abstract
This study presents an application of machine learning (ML) methods for detecting the presence of stenoses and aneurysms in the human arterial system. Four major forms of arterial disease-carotid artery stenosis (CAS), subclavian artery stenosis (SAS), peripheral arterial disease (PAD), and abdominal aortic aneurysms (AAA)-are considered. The ML methods are trained and tested on a physiologically realistic virtual patient database (VPD) containing 28,868 healthy subjects, adapted from the authors previous work and augmented to include disease. It is found that the tree-based methods of Random Forest and Gradient Boosting outperform other approaches. The performance of ML methods is quantified through the [Formula: see text] score and computation of sensitivities and specificities. When using six haemodynamic measurements (pressure in the common carotid, brachial, and radial arteries; and flow-rate in the common carotid, brachial, and femoral arteries), it is found that maximum [Formula: see text] scores larger than 0.9 are achieved for CAS and PAD, larger than 0.85 for SAS, and larger than 0.98 for both low- and high-severity AAAs. Corresponding sensitivities and specificities are larger than 90% for CAS and PAD, larger than 85% for SAS, and larger than 98% for both low- and high-severity AAAs. When reducing the number of measurements, performance is degraded by less than 5% when three measurements are used, and less than 10% when only two measurements are used for classification. For AAA, it is shown that [Formula: see text] scores larger than 0.85 and corresponding sensitivities and specificities larger than 85% are achievable when using only a single measurement. The results are encouraging to pursue AAA monitoring and screening through wearable devices which can reliably measure pressure or flow-rates.
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Affiliation(s)
- G Jones
- Faculty of Science and Engineering, Swansea University, Swansea, UK
| | - J Parr
- McLaren Technology Centre, Woking, UK
| | - P Nithiarasu
- Faculty of Science and Engineering, Swansea University, Swansea, UK
| | - S Pant
- Faculty of Science and Engineering, Swansea University, Swansea, UK.
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Gardner IA, Colling A, Caraguel C, Crowther JR, Jones G, Firestone SM, Heuer C. Introduction - Validation of tests for OIE-listed diseases as fit-for-purpose in a world of evolving diagnostic technologies. REV SCI TECH OIE 2021; 40:19-28. [PMID: 34140741 DOI: 10.20506/rst.40.1.3207] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
The World Organisation for Animal Health (OIE) has made leading contributions to the discipline of test validation science by providing standards and guidelines that inform the test validation process in terrestrial and aquatic animals. The OIE Manual of Diagnostic Tests and Vaccines for Terrestrial Animals, and the Manual of Diagnostic Tests for Aquatic Animals describe the test validation pathway in the context of fitness for purpose, elaborate on the importance of diagnostic sensitivity (DSe) and specificity (DSp) as measures of test accuracy, and designate additional factors (e.g. test cost, laboratory throughput capacity and rapidity of test results) that influence choices of a single test over others or the inclusion of a new test in a diagnostic process that includes multiple tests. This paper provides examples of each of the six main testing purposes listed in the Terrestrial Manual and describes additional metrics such as ruggedness and robustness that should be included in the validation of point-of-care tests. Challenges associated with new diagnostic technologies and platforms are described. Validated tests with estimates of DSe and DSp are needed to measure confidence in test results for OIE-listed diseases, to facilitate risk assessments related to animal movement, to estimate true prevalence, and for certification of disease freedom and use in epidemiological (risk factor) studies.
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Cheung A, Dufour S, Jones G, Kostoulas P, Stevenson MA, Singanallur NB, Firestone SM. Bayesian latent class analysis when the reference test is imperfect. REV SCI TECH OIE 2021; 40:271-286. [PMID: 34140724 DOI: 10.20506/rst.40.1.3224] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Latent class analysis (LCA) has allowed epidemiologists to overcome the practical constraints faced by traditional diagnostic test evaluation methods, which require both a gold standard diagnostic test and ample numbers of appropriate reference samples. Over the past four decades, LCA methods have expanded to allow epidemiologists to evaluate diagnostic tests and estimate true prevalence using imperfect tests over a variety of complex data structures and scenarios, including during the emergence of novel infectious diseases. The objective of this review is to provide an overview of recent developments in LCA methods, as well as a practical guide to applying Bayesian LCA (BLCA) to the evaluation of diagnostic tests. Before conducting a BLCA, the suitability of BLCA for the pathogen of interest, the availability of appropriate samples, the number of diagnostic tests, and the structure of the data should be carefully considered. While formulating the model, the model's structure and specification of informative priors will affect the likelihood that useful inferences can be drawn. With the growing need for advanced analytical methods to evaluate diagnostic tests for newly emerging diseases, LCA is a promising field of research for both the veterinary and medical disciplines.
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Nguyen HH, Wu F, Makin JK, Oddy WH, Wills K, Jones G, Winzenberg T. Associations of dietary patterns with bone density and fractures in adults: A systematic review and meta-analysis. Aust J Gen Pract 2021; 50:394-401. [PMID: 34059846 DOI: 10.31128/ajgp-02-20-5245] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
BACKGROUND AND OBJECTIVES Although nutrition is important to bone health, the impact of different dietary patterns on bone density and fracture is unclear. The aim of this study was to synthesise conflicting evidence from observational studies to determine associations of empirically derived dietary patterns with bone density and fracture in healthy adults. METHOD A systematic review (PROSPERO CRD42017071676) with meta-analysis where possible (for hip fracture) and otherwise with best-evidence synthesis. RESULTS Twenty-one studies were included in the best-evidence synthesis and four in the meta-analysis. Meta-analysis demonstrated a protective association between 'healthy' pattern score and hip fracture (risk ratio 0.73; 95% confidence interval: 0.56, 0.96; I2 = 95%) for highest compared to lowest 'healthy' pattern score category. In best-evidence synthesis, there was conflicting evidence for associations of both pattern scores with bone density at all sites and total fractures and for 'Western' score and hip fracture. No study reported detrimental effects of 'healthy' patterns, or beneficial effects of 'Western' patterns. DISCUSSION The results suggest that general practitioners promoting a 'healthy' dietary pattern is, at worst, unlikely to be detrimental for bone health and, at best, may reduce hip fracture.
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Affiliation(s)
- H H Nguyen
- BPH, MPH, Menzies Institute for Medical Research, University of Tasmania, Tas; Ho Chi Minh City University of Medicine and Pharmacy, Ho Chi Minh City, Vietnam
| | - F Wu
- PhD, Research Fellow, Menzies Institute for Medical Research, University of Tasmania, Tas
| | - J K Makin
- MSc, Senior Consultant: Research and Evaluation, Menzies Institute for Medical Research, University of Tasmania, Tas
| | - W H Oddy
- MPH, PhD, Professorial Research Fellow, Menzies Institute for Medical Research, University of@Tasmania, Tas
| | - K Wills
- PhD, Research Fellow Biostatistics, Menzies Institute for Medical Research, University of Tasmania, Tas
| | - G Jones
- FRACP, MD, Professorial Research Fellow, Menzies Institute for Medical Research, University of@Tasmania, Tas
| | - T Winzenberg
- FRACGP, PhD, Professor of Chronic Disease Management, Menzies Institute for Medical Research, University of Tasmania, Tas
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Wang Z, Jones G, Aitken D, Balogun S, Zhou Z, Blizzard L, Cicuttini F, Antony B. POS0280 ASSOCIATION OF COMPLEMENTARY AND ALTERNATIVE MEDICINE USE WITH KNEE SYMPTOMS AND KNEE STRUCTURAL CHANGES OVER 2.6 YEARS: A POPULATION-BASED COHORT STUDY OF TASMANIAN OLDER ADULTS. Ann Rheum Dis 2021. [DOI: 10.1136/annrheumdis-2021-eular.2762] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
Background:There is increasing use of complementary and alternative medicines (CAMs) alone or as an adjuvant therapy to conventional palliative medicines.1 However, there remains clinical uncertainty about the benefit of CAMs in the management of osteoarthritis in older population.Objectives:To describe the association between CAM use (alone or in combination with conventional analgesics) with knee symptoms and structural changes amongst a representative sample of Tasmanian older adults.Methods:A total of 1,099 participants were selected from the Tasmania Older Adult Cohort Study (TASOAC), an ongoing prospective population-based study. Exposure to CAM and conventional medications was classified into four categories according to the national drug code directory: 2 CAM only, conventional analgesics only, both CAM and conventional analgesics, and neither CAMs nor conventional analgesics. Knee pain was assessed using the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), and a 1.5-T MRI of the right knee was performed at baseline and follow-up (around 2.6 years). Longitudinal associations were assessed using mixed effect linear models.Results:At baseline, participants‘ mean age was 63, 86.5% (n=951) reported any medication use. The prevalence of CAM use was 35.0% and of conventional analgesics was 58.6%. Over follow-up, the analgesic only group had a significant increase in WOMAC pain, function, and stiffness scores compared to those who took neither CAMs nor conventional analgesics. There was a statistically significant femoral cartilage volume loss across all four groups, and no statistical difference was found between participants who takes both CAMs and analgesics group and the reference group, but participant in the CAM only or the analgesics only groups loss statistically significant more femoral cartilage volume than the reference group (Table 1).Table 1.Association of change in clinical knee symptoms and knee structural changes over 2.6 years with different medications groups.Mean change for reference group*Change for each category, coefficient (95% confident intervals)CAMsBothAnalgesicsReference group*No. of participants327128257387327WOMAC pain (5-50)-0.95 (-1.42, -0.48)0.04 (-0.85, 0.93)0.32 (-0.4, 1.04)0.78 (0.13, 1.43)RefWOMAC function (17-170)-3.09 (-4.52, -1.67)1.02 (-1.7, 3.73)1.39 (-0.81, 3.59)2.32 (0.33, 4.31)RefWOMAC stiffness (2-20)-0.39 (-0.62, -0.17)0.15 (-0.28, 0.58)0.35 (0, 0.7)0.40 (0.09, 0.72)RefFemoral cartilage volume (mL)-187.98 (-228.79, -147.18)-113.81 (-192.60, -35.03)-1.92 (-65.00, 61.17)-127.19 (-186.31, -68.06)Ref*Reference group=participants taken neither CAMs nor conventional analgesicsConclusion:CAM use alone or in combination with conventional analgesics may associate with slower progression of knee pain. Conclusive evidence on the longitudinal benefits of CAM in the management of osteoarthritis among older adults warrants more studies.References:[1]Steel A, McIntyre E, Harnett J, et al. Complementary medicine use in the Australian population: Results of a nationally-representative cross-sectional survey. Sci Rep 2018;8:17325.[2]National Center for Health Statistics. Long-term Care Drug Database System: Drugs by NDC Class Code, Drug Code and Name 2007 Available from: https://www.cdc.gov/nchs/data/nnhsd/DrugsbyNDCClass3.pdf [accessed date: 2020 23 December].The data were fitted using mixed effect linear models, which were constructed by entering baseline medication group, phase, the interaction between medication group and phase, covariates (baseline age, sex, body mass index [BMI], baseline value of outcome), the interaction between the covariates and phase, random intercept, and random slope on phase (time).Disclosure of Interests:None declared
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Pan F, Tian J, Cicuttini F, Jones G. OP0196 CIRCULATING LEVEL OF IL-6 IS ASSOCIATED WITH 10.7-YEAR KNEE CARTILAGE VOLUME LOSS AND WORSE PAIN TRAJECTORY. Ann Rheum Dis 2021. [DOI: 10.1136/annrheumdis-2021-eular.375] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
Background:There is growing evidence that inflammation plays a critical role in osteoarthritis (OA) progression and its symptoms evolution. OA pain is heterogeneous and there are distinct subgroups within OA pain patients. Recently, we identified three homogeneous subgroups following distinct pain trajectories in which metabolic mechanism may be involved. Whether circulating inflammatory markers are associated with long-term knee structural changes on MRI, and whether the association between inflammatory markers and the trajectories we identified differs remain to be clarified.Objectives:To examine whether inflammatory markers are associated with 10.7-year knee structural changes including knee cartilage volume (CV) and bone marrow lesions (BMLs), and to assess the associations between inflammatory markers and different pain trajectories.Methods:This study was conducted as part of a population-based older adult (mean age 63 years, 51% of females) cohort study with 1,099, 875, 768 and 563 participants attending at baseline, and 2.6-, 5.1- and 10.7-year follow-ups. Circulating levels of interleukin (IL)-6, tumour necrosis factor alpha (TNF-α) and high sensitivity C-reactive protein (CRP) were measured at baseline in 193 randomly selected participants. T1-weighted or T2-weighted MRI of the right knee was performed to measure CV and BMLs at baseline and 10.7-year. X-ray was performed to assess radiographic knee osteoarthritis (ROA). The Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain questionnaire was used to measure knee pain at all four visits. Data on demographic, psychological, lifestyle and comorbidities were also collected. Pain trajectories was previously identified using the group-based trajectory modelling. Linear, log-binomial and multi-nominal logistic regression modellings were used for the analyses.Results:IL-6 was associated with both medial and lateral tibial CV loss (Medial: β=-0.51% per log pg/ml, 95%CI -0.88 to -0.15; Lateral: β=-0.34% per log pg/ml, 95%CI -0.64 to -0.04) after adjusting for age, sex, body mass index, physical activity, comorbidities, and ROA. TNF-α was not associated with either medial or lateral CV loss, but CRP was positively associated with medial tibial CV loss (Medial: β=0.27% per log mg/L, 95%CI 0.04 to 0.49), not lateral CV loss. No inflammatory markers were found to associate with medial and lateral BML size increase. Of 169 participants who had complete data at baseline, 54%, 35% and 11% of participants fell into ‘Minimal pain’, ‘Mild pain’ and ‘Moderate pain’ trajectory group, respectively. In multivariable analysis, IL-6 was associated with an increased risk of being a ‘Moderate pain’ trajectory (relative risk ratio [RRR]: 4.03, 95%CI 1.34 to 12.13) in comparison with ‘Minimal pain’ trajectory group. There was no significant association of TNF-α and CRP with trajectory groups.Conclusion:IL-6 was associated with both medial and lateral tibial CV loss (Medial: β=-0.51% per log ml/pg, 95%CI -0.88 to -0.15; Lateral: β=-0.34% per log ml/pg, 95%CI -0.64 to -0.04) after adjusting for age, sex, body mass index, physical activity, comorbidities, and ROA. TNF-α was not associated with either medial or lateral CV loss, but CRP was positively associated with medial tibial CV loss (Medial: β=0.27% per log ml/pg, 95%CI 0.04 to 0.49), not lateral CV loss. No inflammatory markers were found to associate with medial and lateral BML size increase. Of 169 participants who had complete data at baseline, 54%, 35% and 11% of participants fell into ‘Minimal pain’, ‘Mild pain’ and ‘Moderate pain’ trajectory group, respectively. In multivariable analysis, IL-6 was associated with an increased risk of being a ‘Moderate pain’ trajectory (relative risk ratio [RRR]: 4.03, 95%CI 1.34 to 12.13) in comparison with ‘Minimal pain’ trajectory group. There was no significant association of TNF-α and CRP with trajectory groups.Disclosure of Interests:None declared
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Pan F, Tian J, Cicuttini F, Jones G. POS1103 SLEEP DISTURBANCE AND BONE MINERAL DENSITY, RISK OF FALLS AND FRACTURE: RESULTS FROM A 10.7-YEAR PROSPECTIVE COHORT STUDY. Ann Rheum Dis 2021. [DOI: 10.1136/annrheumdis-2021-eular.376] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
Background:Sleep problems are common in the general population and have been reported to adversely affect bone health and increase risk of falls and fracture. However, no study has investigated whether an increased risk of fracture is attributable to sleep-related low bone mineral density (BMD) and/or an increased risk of falls.Objectives:This study, therefore, sought to describe the associations of sleep disturbance with BMD, risk of falls and fractures.Methods:The analyses were performed in a population-based prospective cohort study with 1,099 participants (aged 50–80 years) enrolled at baseline, and 875, 768 and 563 participants traced at a mean follow-up of 2.6, 5.1 and 10.7 years, respectively. At each visit, self-reported sleep disturbance was recorded. BMD (by DXA), falls risk and fracture were measured at each visit. The short-form Physiological Profile Assessment was used to measure falls risk expressed as Z-score. Fractures were self-reported. Mixed-effects model and generalised estimating equations were used for the analyses.Results:In multivariable analysis, there was a dose-response relationship between extent of sleep disturbance and falls risk score with the strongest association in those reporting the worst sleep disturbance (β=0.15/unit; 95%CI 0.02-0.28). The worst sleep disturbance was associated with an increased risk of any (relative risk [RR] 1.30/unit; 95%CI 1.01-1.67) and vertebral fracture (RR 2.41/unit; 95%CI 1.00-5.80) compared with those reporting no interrupted sleep. This was independent of covariates, hip BMD and falls risk. There was no statistically significant association between sleep disturbance and BMD at hip, spine or total body.Conclusion:Sleep disturbance was independently associated with a greater falls risk score and an increased risk of fractures, suggesting that correcting sleep disturbance has the potential to reduce both falls risk and fractures.Disclosure of Interests:None declared.
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Laslett L, Scheepers L, Antony B, Wluka A, Hill C, March L, Keen H, Otahal P, Cicuttini F, Jones G. POS0276 EFFICACY OF KRILL OIL IN THE TREATMENT OF KNEE OSTEOARTHRITIS: A 24-WEEK MULTICENTRE RANDOMISED DOUBLE-BLIND CONTROLLED TRIAL. Ann Rheum Dis 2021. [DOI: 10.1136/annrheumdis-2021-eular.4242] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
Background:Elevated levels of systemic inflammation are common in people with osteoarthritis and predict both pain and structural outcomes. Krill oil has anti-inflammatory properties and reduces severity of inflammatory arthritis in mice by 50% compared to controls.1 In humans, krill oil reduced knee pain and function in two short, moderate quality randomised controlled trials (RCTs) in people with osteoarthritis. However, evidence from longer trials with imaging data is lacking.Objectives:The aim of this study was to compare the efficacy of krill oil (2g / day) vs. placebo for treating knee pain in patient with clinical knee osteoarthritis who have significant knee pain and effusion-synovitis.Methods:KARAOKE was a 24-week multicentre, randomised, double-blind, placebo-controlled trial conducted at five Australian sites. Participants aged ≥40 years with symptomatic knee OA (according to ACR criteria), significant knee pain (pain score ≥40mm on a 100mm visual analogue scale [VAS]), and effusion-synovitis present on MRI (grade ≥1 according to modified Whole-Organ Magnetic Resonance Imaging Score (WORMS) scoring) were eligible. The study protocol has been published previously.2Participants were randomised to receive 2g/day of krill oil, (350 mg/g omega-3 content, 12 mg/g total omega-6 content) or inert placebo (vegetable oil, no EPA or DHA, <5 mg/g (0.05%) other omega-3s).The primary outcome was absolute change in knee pain assessed using a VAS [0-100mm] after 24 weeks. Secondary outcomes were: change in knee pain and function assessed using Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) score [0-500mm]), change in back and hand pain assessed using a VAS [0-100mm], change in lower limb leg strength assessed using a dynamometer, and change in blood parameters (including CRP, triglycerides, fasting glucose and total, HDL, LDL cholesterol), after 24 weeks.Linear mixed-models were used, using patient identification as random intercepts and trial centre and treatment month as random effect to adjust for correlated data within trial centres and repeated measures and to allow different treatment effects among patients over time, respectively.Results:262 participants were randomised (mean age 61.5 years, 53% females) to receive krill oil (n=130) or placebo (n=132). A total of 85% completed the trial.Knee pain improved in both groups over 24 weeks, but with no between-group difference (krill oil, -20.1mm; placebo, -19.3mm, p=0.81). Secondary outcomes: knee pain and function score improved in both groups, but with no between-group difference (WOMAC pain: krill oil, -86.7; placebo, -82.5mm, p=0.81; WOMAC function: krill oil, -245.3; placebo, -184.3, p=0.14 at 24 weeks). The same applies for hand pain and back pain. No significant changes were seen in leg strength or any of the blood parameters at 24 weeks). Incidence of one or more adverse events was 50% in the krill oil group (n=66) and 55% in the placebo group (n=71). There were 8 serious adverse events in the krill oil group 6 in the placebo group, all considered unrelated to treatment.Conclusion:Krill oil was safe and well tolerated, but did not significantly reduce knee pain in patients with clinical knee osteoarthritis, significant knee pain and effusion-synovitis after 24 weeks compared to placebo. These findings do not support use of krill oil for alleviating knee pain in clinical knee osteoarthritis.References:[1]Ierna M, et al. BMC Musculoskelet Disord 2010;11:136.[2]Laslett L, et al. Trials 2020;21:79OutcomesAbsolute between group difference at 24 weeksP valuePrimaryKnee pain0.8 (-5.6 to 7.2)0.81SecondaryKnee pain (WOMAC)4.2 (-29.1 to 37.5)0.81Knee function (WOMAC)61 (-19.2 to 141.3)0.14Hand pain2.8 (-2.6 to 8.3)0.31Back pain1.9 (-3.9 to 7.8)0.46Leg strength-2.59 (-9.41 to 4.23)0.52Metabolic factorsTotal Cholesterol0.09 (-0.1 to 0.29)0.34HDL Cholesterol-0.03 (-0.1 to 0.03)0.35LDL Cholesterol0.05 (-0.12 to 0.22)0.57Triglycerides0.12 (-0.09 to 0.33)0.27Fasting glucose0.01 (-0.26 to 0.29)0.93hsCRP0.64 (-0.56 to 1.84)0.30Disclosure of Interests:Laura Laslett Speakers bureau: once, several years ago, and unrelated to this topic, Grant/research support from: Yes, received funding from Aker Biomarine to conduct this trial, Lieke Scheepers Shareholder of: AstraZeneca, Grant/research support from: Pfizer, unrelated to this topic, Employee of: Previously employed by AstraZeneca, Benny Antony Speakers bureau: Zydus, Grant/research support from: Grant support for investigator-initiated trial from NR Ltd for unrelated research, Anita Wluka: None declared, Catherine Hill: None declared, Lyn March Speakers bureau: Speaker fees from Pfizer Australia Ltd, Bristol Myer Squibb Australia, Abbvie Australia, Grant/research support from: Grant support for my institution from Janssen for unrelated research, Helen Keen: None declared, Petr Otahal: None declared, Flavia Cicuttini: None declared, Graeme Jones: None declared
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Singh A, Blizzard L, Venn A, Jones G, Burgess J, Parameswaran V, Ding C, Antony B. POS0190 ASSOCIATION BETWEEN OSTEOARTHRITIS-RELATED SERUM BIOCHEMICAL MARKERS OVER 11 YEARS AND KNEE SYMPTOMS IN MIDDLE-AGED ADULTS. Ann Rheum Dis 2021. [DOI: 10.1136/annrheumdis-2021-eular.98] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
Background:Serum levels of cartilage and joint-specific biochemical markers such as cartilage oligomeric matrix protein (COMP), matrix metalloproteinase (MMP)-3, and hyaluronan (HA) are associated with cartilage degradation, joint tissue degradation, and synovitis in patients with OA. Change in these biomarkers may precede the morphological and clinical manifestations of OA and therefore have been explored as predictive markers in OA. However, few studies have evaluated the association of OA-related biomarkers with knee symptoms in general population-based middle-aged adultsObjectives:To describe the associations between OA-related biomarkers and knee symptoms in middle-aged adults followed up over 10-13 yearsMethods:Blood samples were collected during the Childhood Determinants of Adult Health (CDAH)-1 study at baseline (year: 2004-06, age: 26–36 years) and 10-13 year follow-up (CDAH-3; year: 2014–2019, age: 36–49 years). Serum samples from baseline (n=156) and follow-up (n= 167) were analyzed for three OA-related biomarkers – namely COMP, MMP-3, and HA– using ELISA. Knee symptoms (pain, stiffness, and dysfunction) were assessed using the WOMAC scale during the CDAH-3 phase. Univariable and multivariable (adjusted for age, sex, and body mass index (BMI)) zero-inflated Poisson regression models with random effects were used to describe the above associationsResults:The prevalence of knee pain was 46%. In the multivariable model, adjusted for age, sex, and BMI, there was a significant positive association between COMP (ɞ=1.156, 95%CI: 0.989,1.324; p=0.04), MMP-3 (ɞ=1.013, 95%CI: 1.001,1.025; p=0.02), and HA (ɞ=1.008, 95%CI: 1.002,1.015, p=0.01) with knee pain and WOMAC-total score (Table 1) in middle-aged adults. The increase in knee pain per ng/ml increase in COMP, MMP-3, and HA was 15.7%, 1.3%, and 0.8%, respectively. The overall mean biomarker levels decreased over 10-13 years; however, the mean WOMAC-total scores were higher in participants whose COMP and HA levels increased (COMP: 24 (27.31), HA: 14.20 (22.60)) compared to those in whom it decreased or remained stable (COMP: 9.84 (16.83), and HA: 8.28 (13.22)) during this period. There was a significant positive association between COMP (ɞ=1.026, 95%CI: 1.002,1.050, p=0.03) and MMP-3 (ɞ=1.020, 95%CI: 1.009,1.030, p<0.01) measured at baseline and knee pain assessed after 10-13 year in the middle-aged adults (Table 1)Table 1.Cross-sectional and longitudinal association between WOMAC symptoms and OA-related biomarkersVariablesLongitudinal Biomarker at CDAH-1, knee symptom at CDAH-3Cross-sectional Biomarker at CDAH-3, knee symptom at CDAH-3Adjusted. Coef. (95%CI) p-valueAdjusted. Coef. (95%CI) p-valueCOMP (Predictor)WOMAC-total1.047 (1.035, 1.060)1.088 (1.017, 1.159)p<0.01p=0.01Stiffness1.019 (0.988, 1.051)0.877 (0.708, 1.057)p=0.23p=0.12Dysfunction1.045 (1.030, 1.061)1.040 (0.949, 1.130)p<0.01p=0.38MMP3 (Predictor)WOMAC-total1.026 (1.020, 1.031)1.017 (1.010, 1.023)p<0.01p<0.01Pain1.020 (1.009, 1.030)1.013 (1.001, 1.025)p<0.01p=0.03Stiffness1.020 (1.004, 1.035)1.004 (.987, 1.021)p=0.01p=0.66Dysfunction1.029 (1.022, 1.037)1.019 (1.010, 1.026)p<0.01p<0.01HA (Predictor)WOMAC-total0.995 (0.991, 0.999)1.007 (1.003, 1.010)p=0.01p<0.01Pain0.999 (0.991, 1.006)1.008 (1.002, 1.015)p=0.75p=0.01Stiffness0.989 (0.980, 0.998)0.997 (0.989, 1.007)p=0.03p=0.65Dysfunction1.003 (0.998, 1.009)1.015 (1.010, 1.020)p= 0.22p<0.01Bold denotes statistically significant. Model adjusted for age, sex, and BMIConclusion:OA-related biochemical markers such as COMP and MMP-3 were positively associated with knee pain in population-based middle-aged adults. These results suggest biochemical markers measured in middle-aged adults may be used as a marker of joint painAcknowledgements:AS is supported by International Graduate Research Scholarship, University of Tasmania.Disclosure of Interests:Ambrish Singh Employee of: Has worked in the past for Abbott and Eli Lilly and Company, Leigh Blizzard: None declared, Alison Venn: None declared, Graeme Jones: None declared, John Burgess: None declared, Venkat Parameswaran: None declared, Changhai Ding: None declared, Benny Antony: None declared
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Xie Z, Aitken D, Liu M, Lei G, Jones G, Zhai G. POS0186 METABOLOMIC SIGNATURES FOR KNEE CARTILAGE VOLUME LOSS OVER 10 YEARS. Ann Rheum Dis 2021. [DOI: 10.1136/annrheumdis-2021-eular.2735] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
Background:Osteoarthritis (OA) is the most common form of arthritis, and its impact is increasing year by year due to an aging population and lack of effective treatments. One of the main structural pathological changes of OA is the loss of articular cartilage. Tools that can predict cartilage loss would help identify people at high risk, thus preventing OA development.Objectives:Using a metabolomics approach, the current study aimed to identify serum metabolomic signatures for predicting the loss of knee cartilage volume over 10 years in a well-established community-based cohort - the Tasmania Older Adult Cohort (TASOAC).Methods:TASOAC is an on-going, prospective, population-based study of older adults who were randomly selected from the roll of electors in Southern Tasmania, Australia. Participants had a right knee magnetic resonance imaging (MRI) scan at baseline and a 10-year follow-up. Cartilage volume was measured in the medial, lateral, and patellar compartments and change in cartilage volume over 10 years was calculated as percentage change per year. Fasting serum samples collected at 2.6-year follow-up were metabolomically profiled using the TMIC Prime Metabolomics Profiling Assay which measures a total of 143 metabolites. 129 metabolite concentrations passed the quality control and the pairwise ratios of them as the proxies of enzymatic reaction were calculated. Linear regression models were used to test the association between each of the metabolite ratios and change in cartilage volume in each of the knee compartments with adjustment for age, sex, and body mass index (BMI). The significance was defined at a=3.0×10-6 to control multiple testing of 16,512 ratios with Bonferroni method.Results:A total of 344 participants (51% females) were included. The mean baseline age was 62.83±6.13 years and the mean BMI was 27.48±4.41 kg/m2. The average follow-up time was 10.84±0.66 years. Cartilage volume reduced by 1.34±0.72%, 1.06±0.58%, and 0.98±0.46% per year in the medial, lateral, and patellar compartments, respectively. Our data showed that an increased ratio of hexadecenoylcarnitine (C16:1) to tetradecanoylcarnitine (C14) was associated with a 0.12±0.02% per year reduction in patellar cartilage volume (p = 8.80×10-7). An increased ratio of hexadecenoylcarnitine (C16:1) to dodecanoylcarnitine (C12) was also associated with a 0.12±0.02% per year reduction in patellar cartilage volume (p = 2.66×10-6). While there were several metabolite ratios associated with cartilage volume loss in the medial and lateral compartments, none of them reached the predefined significance level.Conclusion:Our data suggested that alteration of fatty acid β-oxidation is involved in knee cartilage loss, especially in the patellar compartment, and the serum ratio of C16:1 to C14 and to C12 could be used to predict long-term patellar cartilage loss.Acknowledgements:We thank all the study participants who made the study possible. The original TASOAC study was supported by the National Health and Medical Research Council (NHMRC) and the current study was supported by the Canadian Institutes of Health Research (CIHR).Disclosure of Interests:None declared
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van Buuren MMA, Arden NK, Bierma-Zeinstra SMA, Bramer WM, Casartelli NC, Felson DT, Jones G, Lane NE, Lindner C, Maffiuletti NA, van Meurs JBJ, Nelson AE, Nevitt MC, Valenzuela PL, Verhaar JAN, Weinans H, Agricola R. Statistical shape modeling of the hip and the association with hip osteoarthritis: a systematic review. Osteoarthritis Cartilage 2021; 29:607-618. [PMID: 33338641 DOI: 10.1016/j.joca.2020.12.003] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/15/2020] [Revised: 10/30/2020] [Accepted: 12/08/2020] [Indexed: 02/02/2023]
Abstract
OBJECTIVE To summarize available evidence on the association between hip shape as quantified by statistical shape modeling (SSM) and the incidence or progression of hip osteoarthritis. DESIGN We conducted a systematic search of five electronic databases, based on a registered protocol (available: PROSPERO CRD42020145411). Articles presenting original data on the longitudinal relationship between radiographic hip shape (quantified by SSM) and hip OA were eligible. Quantitative meta-analysis was precluded because of the use of different SSM models across studies. We used the Newcastle-Ottawa Scale (NOS) for risk of bias assessment. RESULTS Nine studies (6,483 hips analyzed with SSM) were included in this review. The SSM models used to describe hip shape ranged from 16 points on the femoral head to 85 points on the proximal femur and hemipelvis. Multiple hip shape features and combinations thereof were associated with incident or progressive hip OA. Shape variants that seemed to be consistently associated with hip OA across studies were acetabular dysplasia, cam morphology, and deviations in acetabular version (either excessive anteversion or retroversion). CONCLUSIONS Various radiographic, SSM-defined hip shape features are associated with hip OA. Some hip shape features only seem to increase the risk for hip OA when combined together. The heterogeneity of the used SSM models across studies precludes the estimation of pooled effect sizes. Further studies using the same SSM model and definition of hip OA are needed to allow for the comparison of outcomes across studies, and to validate the found associations.
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Affiliation(s)
- M M A van Buuren
- Department of Orthopedics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands.
| | - N K Arden
- Nuffield Department of Orthopedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK; NIHR Musculoskeletal Biomedical Research Unit, Arthritis Research UK Centre for Sport, Exercise, and Osteoarthritis, University of Oxford, Oxford, UK
| | - S M A Bierma-Zeinstra
- Department of Orthopedics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands; Department of General Practice and Department of Orthopedics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - W M Bramer
- Medical Library, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - N C Casartelli
- Human Performance Lab, Schulthess Clinic, Zürich, Switzerland; Laboratory of Exercise and Health, ETH Zürich, Schwerzenbach, Switzerland
| | - D T Felson
- Centre for Epidemiology Versus Arthritis, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK; NIHR Manchester Biomedical Research Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK; Department of Rheumatology, Boston University School of Medicine, Boston, MA, USA
| | - G Jones
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia
| | - N E Lane
- Department of Medicine, University of California, Davis, CA, USA
| | - C Lindner
- Division of Informatics, Imaging & Data Sciences, University of Manchester, Manchester, UK
| | - N A Maffiuletti
- Human Performance Lab, Schulthess Clinic, Zürich, Switzerland
| | - J B J van Meurs
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - A E Nelson
- Thurston Arthritis Research Center and Department of Medicine, University of North Carolina, Chapel Hill, NC, USA
| | - M C Nevitt
- Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, USA
| | - P L Valenzuela
- Department of Systems Biology, University of Alcalá, Madrid, Spain
| | - J A N Verhaar
- Department of Orthopedics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - H Weinans
- Department of Orthopedics, University Medical Center Utrecht, Utrecht, the Netherlands; Department of Biomechanical Engineering, Delft University of Technology, Delft, the Netherlands
| | - R Agricola
- Department of Orthopedics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
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Riley J, Zeale M, Razgour O, Turpin J, Jones G. Predicting the past, present and future distributions of an endangered marsupial in a semi‐arid environment. Anim Conserv 2021. [DOI: 10.1111/acv.12696] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- J. Riley
- School of Biological Sciences University of Bristol Bristol UK
| | - M.R.K. Zeale
- School of Biological Sciences University of Bristol Bristol UK
| | | | - J. Turpin
- School of Environmental and Rural Science University of New England Armidale NSW Australia
| | - G. Jones
- School of Biological Sciences University of Bristol Bristol UK
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Gillam TB, Cole J, Gharbi K, Angiolini E, Barker T, Bickerton P, Brabbs T, Chin J, Coen E, Cossey S, Davey R, Davidson R, Durrant A, Edwards D, Hall N, Henderson S, Hitchcock M, Irish N, Lipscombe J, Jones G, Parr G, Rushworth S, Shearer N, Smith R, Steel N. Norwich COVID-19 testing initiative pilot: evaluating the feasibility of asymptomatic testing on a university campus. J Public Health (Oxf) 2021; 43:82-88. [PMID: 33124664 PMCID: PMC7665602 DOI: 10.1093/pubmed/fdaa194] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2020] [Revised: 10/01/2020] [Accepted: 10/07/2020] [Indexed: 11/13/2022] Open
Abstract
Background There is a high prevalence of COVID-19 in university-age students, who are returning to campuses. There is little evidence regarding the feasibility of universal, asymptomatic testing to help control outbreaks in this population. This study aimed to pilot mass COVID-19 testing on a university research park, to assess the feasibility and acceptability of scaling up testing to all staff and students. Methods This was a cross-sectional feasibility study on a university research park in the East of England. All staff and students (5625) were eligible to participate. All participants were offered four PCR swabs, which they self-administered over two weeks. Outcome measures included uptake, drop-out rate, positivity rates, participant acceptability measures, laboratory processing measures, data collection and management measures. Results 798 (76%) of 1053 who registered provided at least one swab; 687 (86%) provided all four; 792 (99%) of 798 who submitted at least one swab had all negative results and 6 participants had one inconclusive result. There were no positive results. 458 (57%) of 798 participants responded to a post-testing survey, demonstrating a mean acceptability score of 4.51/5, with five being the most positive. Conclusions Repeated self-testing for COVID-19 using PCR is feasible and acceptable to a university population.
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Affiliation(s)
- T Berger Gillam
- Faculty of Medicine and Health Sciences, University of East Anglia, Norwich NR4 7TJ, UK
| | - J Cole
- Faculty of Medicine and Health Sciences, University of East Anglia, Norwich NR4 7TJ, UK
| | - K Gharbi
- Genomics Pipelines, Earlham Institute, Norwich, NR4 7UZ, UK
| | - E Angiolini
- Scientific Training and Education, Earlham Institute, Norwich NR4 7UZ, UK
| | - T Barker
- Genomics Pipelines, Earlham Institute, Norwich, NR4 7UZ, UK
| | - P Bickerton
- Communications, Earlham Institute, Norwich NR4 7UZ, UK
| | - T Brabbs
- Genomics Pipelines, Earlham Institute, Norwich, NR4 7UZ, UK
| | - J Chin
- School of Computing Sciences, University of East Anglia, Norwich NR4 7TJ, UK
| | - E Coen
- John Innes Centre, Norwich NR4 7UH, UK
| | - S Cossey
- Earlham Institute, Norwich NR4 7UZ, UK
| | - R Davey
- Earlham Institute, Norwich NR4 7UZ, UK
| | - R Davidson
- Faculty of Medicine and Health Sciences, University of East Anglia, Norwich NR4 7TJ, UK
| | - A Durrant
- Genomics Pipelines, Earlham Institute, Norwich, NR4 7UZ, UK
| | - D Edwards
- Faculty of Medicine and Health Sciences, University of East Anglia, Norwich NR4 7TJ, UK
| | - N Hall
- Earlham Institute, Norwich NR4 7UZ, UK.,UEA Biosciences, University of East Anglia, Norwich NR4 7TJ, UK
| | - S Henderson
- Genomics Pipelines, Earlham Institute, Norwich, NR4 7UZ, UK
| | - M Hitchcock
- UEA Health and Social Care Partners, University of East Anglia, Norwich Research Park, Norwich NR4 7TJ, UK
| | - N Irish
- Genomics Pipelines, Earlham Institute, Norwich, NR4 7UZ, UK
| | - J Lipscombe
- Genomics Pipelines, Earlham Institute, Norwich, NR4 7UZ, UK
| | - G Jones
- Communications, Earlham Institute, Norwich NR4 7UZ, UK
| | - G Parr
- School of Computing Sciences, University of East Anglia, Norwich NR4 7TJ, UK
| | - S Rushworth
- Faculty of Medicine and Health Sciences, University of East Anglia, Norwich NR4 7TJ, UK
| | - N Shearer
- Genomics Pipelines, Earlham Institute, Norwich, NR4 7UZ, UK
| | - R Smith
- Faculty of Medicine and Health Sciences, University of East Anglia, Norwich NR4 7TJ, UK
| | - N Steel
- Faculty of Medicine and Health Sciences, University of East Anglia, Norwich NR4 7TJ, UK
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Wang M, Wu F, Callisaya ML, Jones G, Winzenberg T. Incidence and circumstances of falls among middle-aged women: a cohort study. Osteoporos Int 2021; 32:505-513. [PMID: 32918563 DOI: 10.1007/s00198-020-05617-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/11/2020] [Accepted: 09/01/2020] [Indexed: 11/26/2022]
Abstract
UNLABELLED This was the first study assessing falls prospectively in middle-aged women. The 1-year incidence was 42% for any fall, which suggest falls are a major issue in middle-aged women. Middle-aged women, particularly those sustaining a fall, could be a target group for fall-prevention strategies. PURPOSE Incidence and circumstances of falls in middle-aged people are poorly understood. This cohort study aimed to elucidate the incidence and circumstances of falls over 1 year in middle-aged women. METHODS Falls were recorded monthly for 1 year by questionnaire in 2017-2019 in a population-based sample of women aged 41-62 years. The incidence of falls and injurious falls and related circumstances were descriptively analysed. RESULTS Of 273 women, 115 sustained 209 falls. The 1-year incidence was 42% for any fall, 17% for multiple (two or more) falls, and 24% for injurious falls. The incidence was greater in older age groups for any fall (33, 45, and 44% for people aged < 50, 50-55, and > 55 years, respectively), multiple falls (7, 14, and 22%) and injurious falls (15, 20, and 28%), although only the incidence of multiple falls was significantly increased across the three age groups (P = 0.01). Most falls occurred outdoors (71%) and were attributed to tripping and slipping (60%) CONCLUSIONS: Falls are a major issue in middle-aged women, a group that has been largely ignored in the prevention of falls. Middle-aged women, in particular those sustaining a fall, could be a target group for fall-prevention strategies. Future studies are needed to identify risk factors for falling in this population so as inform the development of strategies for preventing falls in middle-aged women.
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Affiliation(s)
- M Wang
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia
| | - F Wu
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia.
| | - M L Callisaya
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia
- Peninsula Clinical School, Central Clinical School, Monash University, Melbourne, Victoria, Australia
| | - G Jones
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia
| | - T Winzenberg
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia
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Scott D, Hirani V, Waite LM, Blyth F, Le Couteur DG, Cumming R, Jones G. Letter to the Editor: 'Giant' Claims Require Strong Evidence: A Comment on 'Osteosarcopenia: A Geriatric Giant of the XXI Century'. J Nutr Health Aging 2021; 25:946-947. [PMID: 34409977 DOI: 10.1007/s12603-021-1659-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Affiliation(s)
- D Scott
- Associate Professor David Scott, Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Burwood, Victoria, Australia 3125, , Telephone: +61 3 9246 8438
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Froidevaux JSP, Boughey KL, Hawkins CL, Jones G, Collins J. Evaluating survey methods for bat roost detection in ecological impact assessment. Anim Conserv 2020; 23:597-606. [PMID: 33288979 PMCID: PMC7687239 DOI: 10.1111/acv.12574] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2019] [Accepted: 02/05/2020] [Indexed: 11/27/2022]
Abstract
The disturbance, damage and destruction of roosts are key drivers of bat population declines worldwide. In countries where bats are protected by law, bat roost surveys are often required to inform ecological impact assessments. Yet, evidence‐based information on survey methodology to detect bat roosts is crucially lacking, and failing to detect a roost can lead to serious errors during decision‐making processes. Here, we assess the efficacy of bat roost surveys in buildings as implemented in the UK. These consist of a daytime inspection of buildings, followed by a series of acoustic surveys at dusk/dawn if during the daytime inspection evidence of bats is found, or if the absence of bats cannot be verified. We reviewed 155 ecological consultants’ reports to (1) compare survey outcome between daytime inspection and acoustic surveys and (2) determine the minimum sampling effort required during acoustic surveys to be confident that no bats are roosting within a building. We focused on two genera of bats most frequently found in buildings in Europe – Pipistrellus (crevice roosting species with high‐intensity echolocation calls that can be easily detected by ultrasound detectors) and Plecotus (species that roost in open spaces and which emit faint echolocation calls that are difficult to detect). Daytime inspections were efficient in detecting open‐roosting species such as Plecotus species but were likely to miss the presence of crevice‐dwelling ones (here Pipistrellus species) which may lead to erroneous conclusions if no acoustic surveys are subsequently prescribed to confirm their absence. A minimum of three and four acoustic surveys are required to be 95% confident that a building does not host a roost of Pipistrellus species and Plecotus species, respectively, thus exceeding current recommendations. Overall, we demonstrated that reports submitted as part of an ecological impact assessment provide suitable data to test and improve survey methods.
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Affiliation(s)
- J S P Froidevaux
- School of Biological Sciences University of Bristol Bristol UK.,Université de Toulouse, INRAE, UMR DYNAFOR Castanet-Tolosan France
| | | | | | - G Jones
- School of Biological Sciences University of Bristol Bristol UK
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Thompson MJW, Jones G, Balogun SA, Aitken DA. Skin Photosensitivity is Associated with 25-Hydroxyvitamin D and BMD but not Fractures Independent of Melanin Density in Older Caucasian Adults. Calcif Tissue Int 2020; 107:335-344. [PMID: 32696106 DOI: 10.1007/s00223-020-00728-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/26/2020] [Accepted: 07/10/2020] [Indexed: 11/24/2022]
Abstract
Whether skin photosensitivity modulates sun exposure behaviours, consequent vitamin D status and skeletal health outcomes independently of constitutive pigmentation have not been systematically investigated. 1072 community-dwelling adults aged 50-80 years had skin photosensitivity quantified by questionnaire and melanin density by spectrophotometry. Bone mineral density (BMD), falls risk and 25-hydroxyvitamin D (25OHD) were measured using DXA, short form physiological profile assessment and radioimmunoassay, respectively. Sun exposure and symptomatic fractures were assessed by questionnaire. Participants were followed up at 2.5 (n = 879), 5 (n = 767) and 10 (n = 571) years. Higher resistance to sunburn and greater ability to tan were associated with reduced sun protection behaviours (RR 0.87, p < 0.001 & RR 0.88, p < 0.001), higher lifetime discretionary sun exposure in summer (RR 1.05, p = 0.001 & RR 1.07, p = 0.001) and winter (RR 1.07, p = 0.001 & RR 1.08, p = 0.02) and fewer lifetime sunburns (RR 0.86, p < 0.001 & RR 0.91, p = 0.001). Higher resistance to sunburn was associated with lower total body (β = - 0.006, p = 0.047) and femoral neck (β = - 0.006, p = 0.038) BMD, but paradoxically, fewer prevalent fractures (RR 0.94, p = 0.042). Greater ability to tan was associated with higher 25OHD (β = 1.43, p = 0.04), lumbar spine (β = 0.014, p = 0.046) and total body (β = 0.013, p = 0.006) BMD, but not fracture or falls risk. These associations were independent of constitutive melanin density. Cutaneous photosensitivity was associated with sun exposure behaviours, cutaneous sequelae and, consequently, 25OHD and BMD in older Caucasian adults independent of constitutive melanin density. There was no consistent association with fracture outcomes, suggesting environmental factors are at least as important.
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Affiliation(s)
- M J W Thompson
- Menzies Institute for Medical Research, University of Tasmania, 17 Liverpool St, Hobart, TAS, 7000, Australia.
| | - G Jones
- Menzies Institute for Medical Research, University of Tasmania, 17 Liverpool St, Hobart, TAS, 7000, Australia
| | - S A Balogun
- Menzies Institute for Medical Research, University of Tasmania, 17 Liverpool St, Hobart, TAS, 7000, Australia
| | - D A Aitken
- Menzies Institute for Medical Research, University of Tasmania, 17 Liverpool St, Hobart, TAS, 7000, Australia
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Cai G, Keen HI, Host LV, Aitken D, Laslett LL, Winzenberg T, Wluka AE, Black D, Jones G. Once-yearly zoledronic acid and change in abdominal aortic calcification over 3 years in postmenopausal women with osteoporosis: results from the HORIZON Pivotal Fracture Trial. Osteoporos Int 2020; 31:1741-1747. [PMID: 32361951 DOI: 10.1007/s00198-020-05430-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/22/2019] [Accepted: 04/22/2020] [Indexed: 12/19/2022]
Abstract
UNLABELLED This study evaluated whether zoledronic acid (ZA) inhibited the progression of abdominal aortic calcification (AAC) over 3 years in 502 postmenopausal women with osteoporosis. AAC progressed in a similar proportion of participants in the ZA (29%) and placebo (31%) groups, suggesting no effect of ZA on AAC progression. INTRODUCTION Bisphosphonate use is associated with reduced risk of all-cause mortality and cardiovascular events. The underlying mechanisms are uncertain but may include effects on vascular calcification. This study aimed to evaluate the effect of zoledronic acid (ZA) on abdominal aortic calcification (AAC) in postmenopausal women with osteoporosis. METHODS This was a post hoc analysis of the HORIZON Pivotal Fracture Trial that included 502 postmenopausal women (mean age 72.5 years) with osteoporosis (234 received ZA and 268 placebo). AAC scores (range, 0-8) were assessed from paired spine X-rays at baseline and after 3 years. Progression of AAC was defined as any increase in AAC score. The association between change in hip and femoral neck bone mineral density and change in AAC score was also assessed. RESULTS At baseline, 292 (58.2%) participants had AAC (i.e., AAC score > 0), with AAC scores similar in the two intervention groups (median [interquartile range], 1 [0 to 2] for both; p = 0.98). Over 3 years, AAC progressed in a similar proportion of participants in both groups (ZA 29% and placebo 31%; p = 0.64). Change in bone mineral density and change in AAC score were not correlated. CONCLUSION Once-yearly zoledronic acid did not affect progression of AAC over 3 years in postmenopausal women with osteoporosis. TRIAL REGISTRATION ClinicalTrials.gov identifier: NCT00049829.
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Affiliation(s)
- G Cai
- Menzies Institute for Medical Research, University of Tasmania, Private Bag 23, Hobart, Tasmania, 7000, Australia
| | - H I Keen
- Department of Rheumatology, Fiona Stanley Hospital, Murdoch, Australia
- School of Medicine and Pharmacology, The University of Western Australia, Perth, Australia
| | - L V Host
- Department of Rheumatology, Fiona Stanley Hospital, Murdoch, Australia
| | - D Aitken
- Menzies Institute for Medical Research, University of Tasmania, Private Bag 23, Hobart, Tasmania, 7000, Australia
| | - L L Laslett
- Menzies Institute for Medical Research, University of Tasmania, Private Bag 23, Hobart, Tasmania, 7000, Australia
| | - T Winzenberg
- Menzies Institute for Medical Research, University of Tasmania, Private Bag 23, Hobart, Tasmania, 7000, Australia
| | - A E Wluka
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Alfred Hospital, Monash University, Melbourne, Australia
| | - D Black
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA
| | - G Jones
- Menzies Institute for Medical Research, University of Tasmania, Private Bag 23, Hobart, Tasmania, 7000, Australia.
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Thompson MJW, Jones G, Balogun S, Aitken DA. Constitutive melanin density is associated with prevalent and short-term, but not long-term, incident fracture risk in older Caucasian adults. Osteoporos Int 2020; 31:1517-1524. [PMID: 32239236 DOI: 10.1007/s00198-020-05304-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/25/2019] [Accepted: 01/15/2020] [Indexed: 12/19/2022]
Abstract
UNLABELLED Higher cutaneous melanin reduces vitamin D3 production. This may increase fracture risk. We found that cutaneous melanin density was associated with prevalent and short-term, but not long-term, incident fracture risk in older Caucasian adults. Melanin density either acts as a surrogate marker or its relationship with fracture changes with time. INTRODUCTION Higher cutaneous melanin reduces vitamin D3 production. This may impact lifetime vitamin D status and increase fracture risk. This study aimed to describe the relationship between spectrophotometrically determined constitutive melanin density, prevalent and incident fractures in a cohort of exclusively older Caucasian adults. METHODS 1072 community-dwelling adults aged 50-80 years had constitutive melanin density quantified using spectrophotometry. Participants were followed up at 2.5 (n = 879), 5 (n = 767), and 10 (n = 571) years after the baseline assessment. Prevalence and number of symptomatic fractures were assessed by questionnaire. RESULTS Higher melanin density was independently associated with greater prevalence of any fracture (RR 1.08, p = 0.03), vertebral fracture (RR 1.41, p = 0.04) and major fracture (RR 1.12, p = 0.04) and the number of fractures (RR 1.09, p = 0.04) and vertebral fractures (RR 1.47, p = 0.04) in cross-sectional analysis. At the 2.5-year follow-up, higher melanin density was associated with incident fractures (RR 1.42, p = 0.01) and major fractures (RR 1.81, p = 0.01) and the number of incident fractures (RR 1.39, p = 0.02) and major fractures (RR 2.14, p = 0.01). The relationship between melanin density and incident fracture attenuated as the duration of follow-up increased and was not significant at the 5- or 10-year follow-up. CONCLUSIONS Constitutive melanin density was associated with prevalent and short-term, but not long-term, incident fracture risk in older Caucasian adults. This suggests melanin density either acts as a surrogate marker for an unmeasured fracture risk factor or the relationship between melanin density and fracture changes with time.
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Affiliation(s)
- M J W Thompson
- Menzies Institute for Medical Research, University of Tasmania, 17 Liverpool St, Hobart, Tasmania, 7000, Australia.
| | - G Jones
- Menzies Institute for Medical Research, University of Tasmania, 17 Liverpool St, Hobart, Tasmania, 7000, Australia
| | - S Balogun
- Menzies Institute for Medical Research, University of Tasmania, 17 Liverpool St, Hobart, Tasmania, 7000, Australia
| | - D A Aitken
- Menzies Institute for Medical Research, University of Tasmania, 17 Liverpool St, Hobart, Tasmania, 7000, Australia
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Cai G, Cicuttini F, Aitken D, Laslett LL, Zhu Z, Winzenberg T, Jones G. Comparison of radiographic and MRI osteoarthritis definitions and their combination for prediction of tibial cartilage loss, knee symptoms and total knee replacement: a longitudinal study. Osteoarthritis Cartilage 2020; 28:1062-1070. [PMID: 32413465 DOI: 10.1016/j.joca.2020.04.017] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/26/2019] [Revised: 04/02/2020] [Accepted: 04/28/2020] [Indexed: 02/02/2023]
Abstract
OBJECTIVE To describe the value of radiographic- and magnetic resonance imaging (MRI)-defined tibiofemoral osteoarthritis (ROA and MRI-OA, respectively) and in combination for predicting tibial cartilage loss, knee pain and disability and total knee replacement (TKR) in a population-based cohort. DESIGN A radiograph and 1.5T MRI of the right knee was performed. ROA and MRI-OA at baseline were defined according to the Osteoarthritis Research Society International atlas and a published Delphi exercise, respectively. Tibial cartilage volume was measured over 2.6 and 10.7 years. Knee pain and disability were assessed at baseline, 2.6, 5.1 and 10.7 years. Right-sided TKRs were assessed over 13.5 years. RESULTS Of 574 participants (mean 62 years, 49% female), 8% had ROA alone, 15% had MRI-OA alone, 13% had both ROA and MRI-OA. Having ROA (vs. no ROA) and MRI-OA (vs. no MRI-OA) predicted greater tibial cartilage loss over 2.6 years (-75.9 and -86.4 mm3/year) and higher risk of TKR over 13.5 years (Risk Ratio [RR]: 15.0 and 10.9). Only MRI-OA predicted tibial cartilage loss over 10.7 years (-7.1 mm3/year) and only ROA predicted onset and progression of knee symptoms (RR: 1.32-1.88). In participants with both MRI-OA and ROA, tibial cartilage loss was the greatest (over 2.6 years: -116.1 mm3/year; over 10.7 years: -11.2 mm3/year), and the onset and progression of knee symptoms (RR: 1.75-2.89) and risk of TKR (RR: 50.9) were the highest. CONCLUSIONS The Delphi definition of MRI-OA is not superior to ROA for predicting structural or symptomatic OA progression but, combining MRI-OA and ROA has much stronger predictive validity.
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Affiliation(s)
- G Cai
- Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, Australia.
| | - F Cicuttini
- Department of Epidemiology and Preventive Medicine, Monash University Medical School, Melbourne, Australia.
| | - D Aitken
- Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, Australia.
| | - L L Laslett
- Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, Australia.
| | - Z Zhu
- Clinical Research Centre, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong, China.
| | - T Winzenberg
- Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, Australia.
| | - G Jones
- Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, Australia.
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