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Drummen SJJ, Aitken D, Balogun S, Bennell KL, Hinman RS, Callisaya ML, Otahal P, Blizzard L, Antony B, Munugoda IP, Winzenberg T, Jones G, Scheepers LEJM. Pre-exercise and acute movement-evoked pain trajectories during a 24-week outdoor walking program for knee osteoarthritis (WALK). OSTEOARTHRITIS AND CARTILAGE OPEN 2024; 6:100481. [PMID: 38883805 PMCID: PMC11176753 DOI: 10.1016/j.ocarto.2024.100481] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Accepted: 05/05/2024] [Indexed: 06/18/2024] Open
Abstract
Objectives Exploring (1) pre-exercise and acute movement-evoked pain (AMEP) during an outdoor walking program in individuals with knee osteoarthritis (OA); and (2) comparing baseline physical performance and AMEP flares initiated by walking between participants with either a higher or lower attendance rate. Methods Individuals with knee OA were prescribed a 24-week walking program, including one unsupervised walk and two supervised walk classes per week. Participants self-reported knee pain on a numerical rating scale (NRS; 0-10) before and after each supervised class. Mixed-effects models were used to investigate trajectories over time for pre-exercise pain and AMEP change (post-minus pre-exercise pain; positive value indicates flare-up). Baseline physical performance (6 tests) and AMEP flares were compared between participants with higher (attending ≥70% of supervised classes) and lower attendance rates. Results Of 24 participants commencing the program, 7 (29%) withdrew. Over 24 weeks, pre-exercise pain improved by 1.20 NRS (95% CI -1.41 to -0.99), with estimated largest per class improvements during the first 8 weeks (-0.05 (-0.06 to -0.03) and plateauing around 20-weeks. The AMEP was estimated to improve by 0.19 NRS (95% CI -0.38 to -0.004) over 24-weeks, with improvements plateauing around 12-weeks. Participants with lower attendance (n = 11) scored poorer on all physical performance tests and experienced a slight increase in AMEP during the first two weeks of the program. Conclusions Participants improved in pre-exercise pain and AMEP in the first 20 and 12 weeks, respectively. Despite supervision, physical performance and AMEP flares may have contributed to lower attendance. Trial registration number 12618001097235.
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Jones G, Kaufmann M, St-Arnaud R. Infantile hypercalcemia type 1 (HCINF1): a rare disease resulting in nephrolithiasis and nephrocalcinosis caused by mutations in the vitamin D catabolic enzyme, CYP24A1. J Endocrinol Invest 2024:10.1007/s40618-024-02381-8. [PMID: 38780860 DOI: 10.1007/s40618-024-02381-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Accepted: 04/21/2024] [Indexed: 05/25/2024]
Abstract
Infantile hypercalcemia type 1 (HCINF1), formerly known as Lightwood syndrome, is a subtype of hypercalcemia caused by loss-of-function biallelic mutations in the vitamin D catabolic enzyme, CYP24A1, which 24-hydroxylates the hormone 1,25-(OH)2D3. This short review focuses on the main features of the HCINF1 disease; emerging knowledge of the structure and function of the cytochrome P450, CYP24A1 and the location of inactivating mutations; the development of a rapid LC-MS/MS-based laboratory test for defective 24-hydroxylation; and future implications for bioanalytical assay and treatment of all types of vitamin D-related hypercalcemic conditions.
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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. THE SCIENCE OF THE TOTAL ENVIRONMENT 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] [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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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] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/21/2024]
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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] [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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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. NATURE 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] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/08/2023]
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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. THE LANCET. RESPIRATORY MEDICINE 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] [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] [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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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. NATURE AGING 2023; 3:1144-1166. [PMID: 37563227 PMCID: PMC10501909 DOI: 10.1038/s43587-023-00462-6] [Citation(s) in RCA: 64] [Impact Index Per Article: 64.0] [Reference Citation Analysis] [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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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] [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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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: 41] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [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
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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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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Evans RA, Leavy OC, Richardson M, Elneima O, McAuley HJC, Shikotra A, Singapuri A, Sereno M, Saunders RM, Harris VC, Houchen-Wolloff L, Aul R, Beirne P, Bolton CE, Brown JS, Choudhury G, Diar-Bakerly N, Easom N, Echevarria C, Fuld J, Hart N, Hurst J, Jones MG, Parekh D, Pfeffer P, Rahman NM, Rowland-Jones SL, Shah AM, Wootton DG, Chalder T, Davies MJ, De Soyza A, Geddes JR, Greenhalf W, Greening NJ, Heaney LG, Heller S, Howard LS, Jacob J, Jenkins RG, Lord JM, Man WDC, McCann GP, Neubauer S, Openshaw PJM, Porter JC, Rowland MJ, Scott JT, Semple MG, Singh SJ, Thomas DC, Toshner M, Lewis KE, Thwaites RS, Briggs A, Docherty AB, Kerr S, Lone NI, Quint J, Sheikh A, Thorpe M, Zheng B, Chalmers JD, Ho LP, Horsley A, Marks M, Poinasamy K, Raman B, Harrison EM, Wain LV, Brightling CE, Abel K, Adamali H, Adeloye D, Adeyemi O, Adrego R, Aguilar Jimenez LA, Ahmad S, Ahmad Haider N, Ahmed R, Ahwireng N, Ainsworth M, Al-Sheklly B, Alamoudi A, Ali M, Aljaroof M, All AM, Allan L, Allen RJ, Allerton L, 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, Nanda U, Nassa H, Nasseri M, Neal A, Needham R, Neill P, Newell H, Newman T, Newton-Cox A, Nicholson T, Nicoll D, Nolan CM, Noonan MJ, Norman C, Novotny P, Nunag J, Nwafor L, Nwanguma U, Nyaboko J, O'Donnell K, O'Brien C, O'Brien L, O'Regan D, Odell N, Ogg G, Olaosebikan O, Oliver C, Omar Z, Orriss-Dib L, Osborne L, Osbourne R, Ostermann M, Overton C, Owen J, Oxton J, Pack J, Pacpaco E, Paddick S, Painter S, Pakzad A, Palmer S, Papineni P, Paques K, Paradowski K, Pareek M, Parfrey H, Pariante C, Parker S, Parkes M, Parmar J, Patale S, Patel B, Patel M, Patel S, Pattenadk D, Pavlides M, Payne S, Pearce L, Pearl JE, Peckham D, Pendlebury J, Peng Y, Pennington C, Peralta I, Perkins E, Peterkin Z, Peto T, Petousi N, Petrie J, Phipps J, Pimm J, Piper Hanley K, Pius R, Plant H, Plein S, Plekhanova T, Plowright M, Polgar O, Poll L, Porter J, Portukhay S, Powell N, Prabhu A, Pratt J, Price A, Price C, Price C, Price D, Price L, Price L, Prickett A, Propescu J, Pugmire S, Quaid S, Quigley J, 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. THE LANCET. RESPIRATORY MEDICINE 2022; 10:761-775. [PMID: 35472304 PMCID: PMC9034855 DOI: 10.1016/s2213-2600(22)00127-8] [Citation(s) in RCA: 177] [Impact Index Per Article: 88.5] [Reference Citation Analysis] [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] [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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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] [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] [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] [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] [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] [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] [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] [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] [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] [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: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [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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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] [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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