1
|
Putra IGB, Kuo PF, Lord D. Estimating the effectiveness of marked sidewalks: An application of the spatial causality approach. ACCIDENT; ANALYSIS AND PREVENTION 2024; 206:107699. [PMID: 39018626 DOI: 10.1016/j.aap.2024.107699] [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: 02/17/2024] [Revised: 07/01/2024] [Accepted: 07/02/2024] [Indexed: 07/19/2024]
Abstract
Various safety enhancements and policies have been proposed to enhance pedestrian safety and minimize vehicle-pedestrian accidents. A relatively recent approach involves marked sidewalks delineated by painted pathways, particularly in Asia's crowded urban centers, offering a cost-effective and space-efficient alternative to traditional paved sidewalks. While this measure has garnered interest, few studies have rigorously evaluated its effectiveness. Current before-after studies often use correlation-based approaches like regression, lacking effective consideration of causal relationships and confounding variables. Moreover, spatial heterogeneity in crash data is frequently overlooked during causal inference analyses, potentially leading to inaccurate estimations. This study introduces a geographically weighted difference-in-difference (GWDID) method to address these gaps and estimate the safety impact of marked sidewalks. This approach considers spatial heterogeneity within the dataset in the spatial causal inference framework, providing a more nuanced understanding of the intervention's effects. The simplicity of the modeling process makes it applicable to various study designs relying solely on pre- and post-exposure outcome measurements. Conventional DIDs and Spatial Lag-DID models were used for comparison. The dataset we utilized included a total of 13,641 pedestrian crashes across Taipei City, Taiwan. Then the crash point data was transformed into continuous probability values to determine the crash risk on each road segment using network kernel density estimation (NKDE). The treatment group comprised 1,407 road segments with marked sidewalks, while the control group comprised 3,097 segments with similar road widths. The pre-development program period was in 2017, and the post-development period was in 2020. Results showed that the GWDID model outperformed the spatial lag DID and traditional DID models. As a local causality model, it illustrated spatial heterogeneity in installing marked sidewalks. The program significantly reduced pedestrian crash risk in 43% of the total road segments in the treatment group. The coefficient distribution map revealed a range from -22.327 to 2.600, with over 95% of the area yielding negative values, indicating reduced crash risk after installing marked sidewalks. Notably, the impact of crash risk reduction increased from rural to urban areas, emphasizing the importance of considering spatial heterogeneity in transportation safety policy assessments.
Collapse
Affiliation(s)
| | - Pei-Fen Kuo
- Department of Geomatics, National Cheng Kung University, Taiwan.
| | - Dominique Lord
- Zachry Department of Civil and Environmental Engineering, Texas A&M University, USA
| |
Collapse
|
2
|
Layton GR, Sinha S, Caputo M, Angelini GD, Fudulu DP, Zakkar M. Two Decades of CABG in the UK: A Propensity Matched Analysis of Outcomes by Conduit Choice. J Clin Med 2024; 13:4717. [PMID: 39200859 PMCID: PMC11355931 DOI: 10.3390/jcm13164717] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2024] [Revised: 07/31/2024] [Accepted: 08/04/2024] [Indexed: 09/02/2024] Open
Abstract
Background/Objectives: Grafting of LIMA to LAD has long been considered the gold-standard conduit choice for patients undergoing CABG. Despite this, the LSV remains the most used conduit by volume and some patients may not receive even a single arterial conduit. However, the outcomes in this group are not frequently explored. This study, therefore, compares in-hospital outcomes of patients who underwent CABG without any arterial conduits to those who received at least one arterial conduit. Methods: Retrospective propensity-matched database analysis of consecutive patients undergoing CABG in the UK between 1996 and 2019 using data from the National Adult Cardiac Surgery Audit. Results: 335,144 patients underwent CABG, with 6% receiving venous conduits only; matched outcomes are reported for 39,812 patients. In both unmatched and matched groups, we found a significant increase in mortality with the use of veins only (matched mortality 5.3% vs. 3.8%, p < 0.001) with estimated treatment effect for mortality OR 1.43, p < 0.001 (95% CI: 1.31-1.57). We also identified greater rates of post-operative dialysis, IABP insertion, and length of hospital stay in this group. Conclusions: We identified a significant increase in in-hospital mortality with the use of veins only compared to using at least one arterial graft to the LAD. While a single arterial graft should be prioritised wherever possible, venous revascularisation retains a critical role for specific patients. We must, therefore, continue to conduct research addressing the mechanisms underlying and propagating vein graft disease in order better to optimise outcomes for this niche patient group after CABG.
Collapse
Affiliation(s)
- Georgia R. Layton
- Department of Cardiovascular Sciences, University of Leicester, Leicester LE1 7RH, UK
- Department of Cardiac Surgery, University Hospitals of Leicester NHS Trust, Leicester LE1 5WW, UK
| | - Shubhra Sinha
- Bristol Heart Institute, University of Bristol, Bristol BS8 1QU, UK
| | - Massimo Caputo
- Bristol Heart Institute, University of Bristol, Bristol BS8 1QU, UK
| | | | - Daniel P. Fudulu
- Bristol Heart Institute, University of Bristol, Bristol BS8 1QU, UK
| | - Mustafa Zakkar
- Department of Cardiovascular Sciences, University of Leicester, Leicester LE1 7RH, UK
- Department of Cardiac Surgery, University Hospitals of Leicester NHS Trust, Leicester LE1 5WW, UK
| |
Collapse
|
3
|
Wang T, Zhao H, Yang S, Tang S, Cui Z, Li L, Faries DE. Propensity score matching for estimating a marginal hazard ratio. Stat Med 2024; 43:2783-2810. [PMID: 38705726 PMCID: PMC11178458 DOI: 10.1002/sim.10103] [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: 06/29/2022] [Revised: 01/31/2024] [Accepted: 04/24/2024] [Indexed: 05/07/2024]
Abstract
Propensity score matching is commonly used to draw causal inference from observational survival data. However, its asymptotic properties have yet to be established, and variance estimation is still open to debate. We derive the statistical properties of the propensity score matching estimator of the marginal causal hazard ratio based on matching with replacement and a fixed number of matches. We also propose a double-resampling technique for variance estimation that takes into account the uncertainty due to propensity score estimation prior to matching.
Collapse
Affiliation(s)
| | - Honghe Zhao
- Department of Statistics, North Carolina State University, Raleigh, North Carolina, USA
| | - Shu Yang
- Department of Statistics, North Carolina State University, Raleigh, North Carolina, USA
| | - Shuhan Tang
- Eli Lilly and Company, Indianapolis, Indiana, USA
| | - Zhanglin Cui
- Eli Lilly and Company, Indianapolis, Indiana, USA
| | - Li Li
- Eli Lilly and Company, Indianapolis, Indiana, USA
| | | |
Collapse
|
4
|
Kennedy E, Liebel SW, Lindsey HM, Vadlamani S, Lei PW, Adamson MM, Alda M, Alonso-Lana S, Anderson TJ, Arango C, Asarnow RF, Avram M, Ayesa-Arriola R, Babikian T, Banaj N, Bird LJ, Borgwardt S, Brodtmann A, Brosch K, Caeyenberghs K, Calhoun VD, Chiaravalloti ND, Cifu DX, Crespo-Facorro B, Dalrymple-Alford JC, Dams-O’Connor K, Dannlowski U, Darby D, Davenport N, DeLuca J, Diaz-Caneja CM, Disner SG, Dobryakova E, Ehrlich S, Esopenko C, Ferrarelli F, Frank LE, Franz CE, Fuentes-Claramonte P, Genova H, Giza CC, Goltermann J, Grotegerd D, Gruber M, Gutierrez-Zotes A, Ha M, Haavik J, Hinkin C, Hoskinson KR, Hubl D, Irimia A, Jansen A, Kaess M, Kang X, Kenney K, Keřková B, Khlif MS, Kim M, Kindler J, Kircher T, Knížková K, Kolskår KK, Krch D, Kremen WS, Kuhn T, Kumari V, Kwon J, Langella R, Laskowitz S, Lee J, Lengenfelder J, Liou-Johnson V, Lippa SM, Løvstad M, Lundervold AJ, Marotta C, Marquardt CA, Mattos P, Mayeli A, McDonald CR, Meinert S, Melzer TR, Merchán-Naranjo J, Michel C, Morey RA, Mwangi B, Myall DJ, Nenadić I, Newsome MR, Nunes A, O’Brien T, Oertel V, Ollinger J, Olsen A, Ortiz García de la Foz V, Ozmen M, Pardoe H, Parent M, Piras F, Piras F, Pomarol-Clotet E, Repple J, Richard G, Rodriguez J, Rodriguez M, Rootes-Murdy K, Rowland J, Ryan NP, Salvador R, Sanders AM, Schmidt A, Soares JC, Spalleta G, Španiel F, Sponheim SR, Stasenko A, Stein F, Straube B, Thames A, Thomas-Odenthal F, Thomopoulos SI, Tone EB, Torres I, Troyanskaya M, Turner JA, Ulrichsen KM, Umpierrez G, Vecchio D, Vilella E, Vivash L, Walker WC, Werden E, Westlye LT, Wild K, Wroblewski A, Wu MJ, Wylie GR, Yatham LN, Zunta-Soares GB, Thompson PM, Pugh MJ, Tate DF, Hillary FG, Wilde EA, Dennis EL. Verbal Learning and Memory Deficits across Neurological and Neuropsychiatric Disorders: Insights from an ENIGMA Mega Analysis. Brain Sci 2024; 14:669. [PMID: 39061410 PMCID: PMC11274572 DOI: 10.3390/brainsci14070669] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2024] [Revised: 06/20/2024] [Accepted: 06/26/2024] [Indexed: 07/28/2024] Open
Abstract
Deficits in memory performance have been linked to a wide range of neurological and neuropsychiatric conditions. While many studies have assessed the memory impacts of individual conditions, this study considers a broader perspective by evaluating how memory recall is differentially associated with nine common neuropsychiatric conditions using data drawn from 55 international studies, aggregating 15,883 unique participants aged 15-90. The effects of dementia, mild cognitive impairment, Parkinson's disease, traumatic brain injury, stroke, depression, attention-deficit/hyperactivity disorder (ADHD), schizophrenia, and bipolar disorder on immediate, short-, and long-delay verbal learning and memory (VLM) scores were estimated relative to matched healthy individuals. Random forest models identified age, years of education, and site as important VLM covariates. A Bayesian harmonization approach was used to isolate and remove site effects. Regression estimated the adjusted association of each clinical group with VLM scores. Memory deficits were strongly associated with dementia and schizophrenia (p < 0.001), while neither depression nor ADHD showed consistent associations with VLM scores (p > 0.05). Differences associated with clinical conditions were larger for longer delayed recall duration items. By comparing VLM across clinical conditions, this study provides a foundation for enhanced diagnostic precision and offers new insights into disease management of comorbid disorders.
Collapse
Affiliation(s)
- Eamonn Kennedy
- Department of Neurology, University of Utah School of Medicine, Salt Lake City, UT 84132, USA; (E.K.); (S.W.L.); (H.M.L.); (S.V.); (M.R.N.); (M.J.P.); (D.F.T.); (E.A.W.)
- Division of Epidemiology, University of Utah, Salt Lake City, UT 84108, USA;
- George E Wahlen Veterans Affairs Medical Center, Salt Lake City, UT 84148, USA
| | - Spencer W. Liebel
- Department of Neurology, University of Utah School of Medicine, Salt Lake City, UT 84132, USA; (E.K.); (S.W.L.); (H.M.L.); (S.V.); (M.R.N.); (M.J.P.); (D.F.T.); (E.A.W.)
- George E Wahlen Veterans Affairs Medical Center, Salt Lake City, UT 84148, USA
| | - Hannah M. Lindsey
- Department of Neurology, University of Utah School of Medicine, Salt Lake City, UT 84132, USA; (E.K.); (S.W.L.); (H.M.L.); (S.V.); (M.R.N.); (M.J.P.); (D.F.T.); (E.A.W.)
- George E Wahlen Veterans Affairs Medical Center, Salt Lake City, UT 84148, USA
| | - Shashank Vadlamani
- Department of Neurology, University of Utah School of Medicine, Salt Lake City, UT 84132, USA; (E.K.); (S.W.L.); (H.M.L.); (S.V.); (M.R.N.); (M.J.P.); (D.F.T.); (E.A.W.)
| | - Pui-Wa Lei
- Department of Educational Psychology, Counseling, and Special Education, Pennsylvania State University, University Park, PA 16802, USA;
| | - Maheen M. Adamson
- WRIISC-WOMEN & Rehabilitation Department, VA Palo Alto, Palo Alto, CA 94304, USA (X.K.); (V.L.-J.)
- Neurosurgery, Stanford School of Medicine, Stanford, CA 94305, USA
| | - Martin Alda
- Department of Psychiatry, Dalhousie University, Halifax, NS B3H 4R2, Canada; (M.A.); (A.N.)
| | - Silvia Alonso-Lana
- FIDMAG Research Foundation, 08025 Barcelona, Spain; (S.A.-L.); (P.F.-C.); (E.P.-C.); (R.S.)
- Centro Investigación Biomédica en Red Salud Mental (CIBERSAM), 28029 Madrid, Spain; (C.A.); (R.A.-A.); (B.C.-F.); (A.G.-Z.); (E.V.)
- Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya, 08022 Barcelona, Spain
| | - Tim J. Anderson
- Department of Medicine, University of Otago, Christchurch 8011, New Zealand; (T.J.A.); (J.C.D.-A.); (T.R.M.)
- New Zealand Brain Research Institute, Christchurch 8011, New Zealand;
- Department of Neurology, Te Whatu Ora–Health New Zealand Waitaha Canterbury, Christchurch 8011, New Zealand
| | - Celso Arango
- Centro Investigación Biomédica en Red Salud Mental (CIBERSAM), 28029 Madrid, Spain; (C.A.); (R.A.-A.); (B.C.-F.); (A.G.-Z.); (E.V.)
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), School of Medicine, Universidad Complutense, 28040 Madrid, Spain; (C.M.D.-C.); (J.M.-N.)
| | - Robert F. Asarnow
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA 90095, USA; (R.F.A.); (T.B.); (C.H.); (T.K.); (A.T.)
- Brain Research Institute, University of California Los Angeles, Los Angeles, CA 90095, USA
- Department of Psychology, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Mihai Avram
- Translational Psychiatry, Department of Psychiatry and Psychotherapy, University of Lübeck, 23562 Lübeck, Germany; (M.A.); (S.B.)
| | - Rosa Ayesa-Arriola
- Centro Investigación Biomédica en Red Salud Mental (CIBERSAM), 28029 Madrid, Spain; (C.A.); (R.A.-A.); (B.C.-F.); (A.G.-Z.); (E.V.)
- Department of Psychiatry, Marqués de Valdecilla University Hospital, Instituto de Investigación Sanitaria Valdecilla (IDIVAL), School of Medicine, University of Cantabria, 39008 Santander, Spain;
| | - Talin Babikian
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA 90095, USA; (R.F.A.); (T.B.); (C.H.); (T.K.); (A.T.)
- UCLA Steve Tisch BrainSPORT Program, University of California Los Angeles, Los Angeles, CA 90095, USA;
| | - Nerisa Banaj
- Laboratory of Neuropsychiatry, Santa Lucia Foundation IRCCS, 00179 Rome, Italy; (N.B.); (R.L.); (F.P.); (F.P.); (G.S.); (D.V.)
| | - Laura J. Bird
- School of Clinical Sciences, Monash University, Clayton, VIC 3800, Australia;
| | - Stefan Borgwardt
- Translational Psychiatry, Department of Psychiatry and Psychotherapy, University of Lübeck, 23562 Lübeck, Germany; (M.A.); (S.B.)
- Center of Brain, Behaviour and Metabolism (CBBM), University of Lübeck, 23562 Lübeck, Germany
| | - Amy Brodtmann
- Cognitive Health Initiative, School of Translational Medicine, Monash University, Melbourne, VIC 3800, Australia;
- Department of Medicine, Royal Melbourne Hospital, Melbourne, VIC 3050, Australia;
| | - Katharina Brosch
- Department of Psychiatry and Psychotherapy, University of Marburg, 35032 Marburg, Germany; (K.B.); (A.J.); (T.K.); (I.N.); (F.S.); (B.S.); (F.T.-O.); (A.W.)
- Institute of Behavioral Science, Feinstein Institutes for Medical Research, Manhasset, NY 11030, USA
| | - Karen Caeyenberghs
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Burwood, VIC 3125, Australia;
| | - Vince D. Calhoun
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, Emory University, Atlanta, GA 30322, USA; (V.D.C.); (K.R.-M.)
| | - Nancy D. Chiaravalloti
- Centers for Neuropsychology, Neuroscience & Traumatic Brain Injury Research, Kessler Foundation, East Hanover, NJ 07936, USA;
- Department of Physical Medicine & Rehabilitation, Rutgers, New Jersey Medical School, Newark, NJ 07103, USA; (J.D.); (E.D.); (H.G.); (D.K.); (J.L.); (G.R.W.)
| | - David X. Cifu
- Rehabilitation Medicine Department, National Institutes of Health Clinical Center, Bethesda, MD 20892, USA;
| | - Benedicto Crespo-Facorro
- Centro Investigación Biomédica en Red Salud Mental (CIBERSAM), 28029 Madrid, Spain; (C.A.); (R.A.-A.); (B.C.-F.); (A.G.-Z.); (E.V.)
- Department of Psychiatry, Virgen del Rocio University Hospital, School of Medicine, University of Seville, IBIS, 41013 Seville, Spain
| | - John C. Dalrymple-Alford
- Department of Medicine, University of Otago, Christchurch 8011, New Zealand; (T.J.A.); (J.C.D.-A.); (T.R.M.)
- New Zealand Brain Research Institute, Christchurch 8011, New Zealand;
- School of Psychology, Speech and Hearing, University of Canterbury, Christchurch 8041, New Zealand
| | - Kristen Dams-O’Connor
- Department of Rehabilitation and Human Performance, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA (C.E.)
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, 48149 Münster, Germany; (U.D.); (J.G.); (D.G.); (M.G.); (S.M.); (J.R.)
| | - David Darby
- Department of Neuroscience, Monash University, Melbourne, VIC 3800, Australia; (D.D.); (C.M.); (L.V.)
- Department of Neurology, Alfred Health, Melbourne, VIC 3004, Australia
- The Florey Institute of Neuroscience and Mental Health, Melbourne, VIC 3052, Australia; (H.P.); (E.W.)
| | - Nicholas Davenport
- Department of Psychiatry and Behavioral Sciences, University of Minnesota Medical School, Minneapolis, MN 55455, USA; (N.D.); (S.G.D.); (C.A.M.); (S.R.S.)
- Minneapolis VA Health Care System, Minneapolis, MN 55417, USA
| | - John DeLuca
- Department of Physical Medicine & Rehabilitation, Rutgers, New Jersey Medical School, Newark, NJ 07103, USA; (J.D.); (E.D.); (H.G.); (D.K.); (J.L.); (G.R.W.)
- Kessler Foundation, East Hanover, NJ 07936, USA
| | - Covadonga M. Diaz-Caneja
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), School of Medicine, Universidad Complutense, 28040 Madrid, Spain; (C.M.D.-C.); (J.M.-N.)
| | - Seth G. Disner
- Department of Psychiatry and Behavioral Sciences, University of Minnesota Medical School, Minneapolis, MN 55455, USA; (N.D.); (S.G.D.); (C.A.M.); (S.R.S.)
- Minneapolis VA Health Care System, Minneapolis, MN 55417, USA
| | - Ekaterina Dobryakova
- Department of Physical Medicine & Rehabilitation, Rutgers, New Jersey Medical School, Newark, NJ 07103, USA; (J.D.); (E.D.); (H.G.); (D.K.); (J.L.); (G.R.W.)
- Center for Traumatic Brain Injury, Kessler Foundation, East Hanover, NJ 07936, USA
| | - Stefan Ehrlich
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, Technische Universität Dresden, 01307 Dresden, Germany;
- Eating Disorders Research and Treatment Center, Department of Child and Adolescent Psychiatry, Faculty of Medicine, Technische Universität Dresden, 01307 Dresden, Germany
| | - Carrie Esopenko
- Department of Rehabilitation and Human Performance, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA (C.E.)
| | - Fabio Ferrarelli
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA 15213, USA; (F.F.); (A.M.)
| | - Lea E. Frank
- Department of Psychology, University of Oregon, Eugene, OR 97403, USA
| | - Carol E. Franz
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA; (C.E.F.); (W.S.K.); (J.R.); (A.S.)
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA 92093, USA
| | - Paola Fuentes-Claramonte
- FIDMAG Research Foundation, 08025 Barcelona, Spain; (S.A.-L.); (P.F.-C.); (E.P.-C.); (R.S.)
- Centro Investigación Biomédica en Red Salud Mental (CIBERSAM), 28029 Madrid, Spain; (C.A.); (R.A.-A.); (B.C.-F.); (A.G.-Z.); (E.V.)
| | - Helen Genova
- Department of Physical Medicine & Rehabilitation, Rutgers, New Jersey Medical School, Newark, NJ 07103, USA; (J.D.); (E.D.); (H.G.); (D.K.); (J.L.); (G.R.W.)
- Center for Autism Research, Kessler Foundation, East Hanover, NJ 07936, USA
| | - Christopher C. Giza
- UCLA Steve Tisch BrainSPORT Program, University of California Los Angeles, Los Angeles, CA 90095, USA;
- Department of Pediatrics, Division of Neurology, UCLA Mattel Children’s Hospital, Los Angeles, CA 90095, USA
- Department of Neurosurgery, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095, USA
| | - Janik Goltermann
- Institute for Translational Psychiatry, University of Münster, 48149 Münster, Germany; (U.D.); (J.G.); (D.G.); (M.G.); (S.M.); (J.R.)
| | - Dominik Grotegerd
- Institute for Translational Psychiatry, University of Münster, 48149 Münster, Germany; (U.D.); (J.G.); (D.G.); (M.G.); (S.M.); (J.R.)
| | - Marius Gruber
- Institute for Translational Psychiatry, University of Münster, 48149 Münster, Germany; (U.D.); (J.G.); (D.G.); (M.G.); (S.M.); (J.R.)
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt, Goethe University, 60590 Frankfurt, Germany
| | - Alfonso Gutierrez-Zotes
- Centro Investigación Biomédica en Red Salud Mental (CIBERSAM), 28029 Madrid, Spain; (C.A.); (R.A.-A.); (B.C.-F.); (A.G.-Z.); (E.V.)
- Hospital Universitari Institut Pere Mata, 43007 Tarragona, Spain
- Institut d’Investiació Sanitària Pere Virgili-CERCA, Universitat Rovira i Virgili, 43007 Tarragona, Spain
| | - Minji Ha
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul 08826, Republic of Korea; (M.H.); (J.K.); (J.L.)
| | - Jan Haavik
- Department of Biomedicine, University of Bergen, 5007 Bergen, Norway;
- Division of Psychiatry, Haukeland University Hospital, 5021 Bergen, Norway
| | - Charles Hinkin
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA 90095, USA; (R.F.A.); (T.B.); (C.H.); (T.K.); (A.T.)
| | - Kristen R. Hoskinson
- Center for Biobehavioral Health, The Abigail Wexner Research Institute at Nationwide Children’s Hospital, Columbus, OH 43205, USA;
- Section of Pediatrics, The Ohio State University College of Medicine, Columbus, OH 43210, USA
| | - Daniela Hubl
- Translational Research Centre, University Hospital of Psychiatry and Psychotherapy, University of Bern, 3000 Bern, Switzerland;
| | - Andrei Irimia
- Ethel Percy Andrus Gerontology Center, Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA 90089, USA;
- Department of Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA 90089, USA
- Department of Quantitative & Computational Biology, Dornsife College of Arts & Sciences, University of Southern California, Los Angeles, CA 90089, USA
| | - Andreas Jansen
- Department of Psychiatry and Psychotherapy, University of Marburg, 35032 Marburg, Germany; (K.B.); (A.J.); (T.K.); (I.N.); (F.S.); (B.S.); (F.T.-O.); (A.W.)
| | - Michael Kaess
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, 3000 Bern, Switzerland; (M.K.); (J.K.); (C.M.)
- Clinic of Child and Adolescent Psychiatry, Centre of Psychosocial Medicine, University of Heidelberg, 69120 Heidelberg, Germany
| | - Xiaojian Kang
- WRIISC-WOMEN & Rehabilitation Department, VA Palo Alto, Palo Alto, CA 94304, USA (X.K.); (V.L.-J.)
| | - Kimbra Kenney
- Department of Neurology, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA;
| | - Barbora Keřková
- National Institute of Mental Health, 250 67 Klecany, Czech Republic; (B.K.); (K.K.); (M.R.); (F.Š.)
| | - Mohamed Salah Khlif
- Cognitive Health Initiative, Central Clinical School, Monash University, Melbourne, VIC 3800, Australia;
| | - Minah Kim
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul 03080, Republic of Korea;
- Department of Psychiatry, Seoul National University College of Medicine, Seoul 03080, Republic of Korea
| | - Jochen Kindler
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, 3000 Bern, Switzerland; (M.K.); (J.K.); (C.M.)
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, University of Marburg, 35032 Marburg, Germany; (K.B.); (A.J.); (T.K.); (I.N.); (F.S.); (B.S.); (F.T.-O.); (A.W.)
| | - Karolina Knížková
- National Institute of Mental Health, 250 67 Klecany, Czech Republic; (B.K.); (K.K.); (M.R.); (F.Š.)
- Department of Psychiatry, First Faculty of Medicine, Charles University and General University Hospital, 128 00 Prague, Czech Republic
| | - Knut K. Kolskår
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital, 0424 Oslo, Norway; (K.K.K.); (G.R.); (A.-M.S.); (K.M.U.); (L.T.W.)
- Department of Psychology, University of Oslo, 0373 Oslo, Norway;
- Department of Research, Sunnaas Rehabilitation Hospital, 1450 Nesodden, Norway
| | - Denise Krch
- Department of Physical Medicine & Rehabilitation, Rutgers, New Jersey Medical School, Newark, NJ 07103, USA; (J.D.); (E.D.); (H.G.); (D.K.); (J.L.); (G.R.W.)
- Center for Traumatic Brain Injury, Kessler Foundation, East Hanover, NJ 07936, USA
| | - William S. Kremen
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA; (C.E.F.); (W.S.K.); (J.R.); (A.S.)
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA 92093, USA
| | - Taylor Kuhn
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA 90095, USA; (R.F.A.); (T.B.); (C.H.); (T.K.); (A.T.)
| | - Veena Kumari
- Department of Life Sciences, College of Health, Medicine and Life Sciences, Brunel University London, Uxbridge UB8 3PH, UK;
| | - Junsoo Kwon
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul 08826, Republic of Korea; (M.H.); (J.K.); (J.L.)
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul 03080, Republic of Korea;
- Department of Psychiatry, Seoul National University College of Medicine, Seoul 03080, Republic of Korea
| | - Roberto Langella
- Laboratory of Neuropsychiatry, Santa Lucia Foundation IRCCS, 00179 Rome, Italy; (N.B.); (R.L.); (F.P.); (F.P.); (G.S.); (D.V.)
| | - Sarah Laskowitz
- Brain Imaging and Analysis Center, Duke University, Durham, NC 27710, USA; (S.L.); (R.A.M.)
| | - Jungha Lee
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul 08826, Republic of Korea; (M.H.); (J.K.); (J.L.)
| | - Jean Lengenfelder
- Department of Physical Medicine & Rehabilitation, Rutgers, New Jersey Medical School, Newark, NJ 07103, USA; (J.D.); (E.D.); (H.G.); (D.K.); (J.L.); (G.R.W.)
- Center for Traumatic Brain Injury, Kessler Foundation, East Hanover, NJ 07936, USA
| | - Victoria Liou-Johnson
- WRIISC-WOMEN & Rehabilitation Department, VA Palo Alto, Palo Alto, CA 94304, USA (X.K.); (V.L.-J.)
| | - Sara M. Lippa
- National Intrepid Center of Excellence, Walter Reed National Military Medical Center, Bethesda, MD 20814, USA; (S.M.L.); (J.O.)
- Department of Neuroscience, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA
| | - Marianne Løvstad
- Department of Psychology, University of Oslo, 0373 Oslo, Norway;
- Department of Research, Sunnaas Rehabilitation Hospital, 1450 Nesodden, Norway
| | - Astri J. Lundervold
- Department of Biological and Medical Psychology, University of Bergen, 5007 Bergen, Norway;
| | - Cassandra Marotta
- Department of Neuroscience, Monash University, Melbourne, VIC 3800, Australia; (D.D.); (C.M.); (L.V.)
- Department of Neurology, Alfred Health, Melbourne, VIC 3004, Australia
| | - Craig A. Marquardt
- Department of Psychiatry and Behavioral Sciences, University of Minnesota Medical School, Minneapolis, MN 55455, USA; (N.D.); (S.G.D.); (C.A.M.); (S.R.S.)
- Minneapolis VA Health Care System, Minneapolis, MN 55417, USA
| | - Paulo Mattos
- Institute D’Or for Research and Education (IDOR), São Paulo 04501-000, Brazil;
| | - Ahmad Mayeli
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA 15213, USA; (F.F.); (A.M.)
| | - Carrie R. McDonald
- Department of Radiation Medicine and Applied Sciences and Psychiatry, University of California San Diego, La Jolla, CA 92093, USA;
- Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA 92093, USA
| | - Susanne Meinert
- Institute for Translational Psychiatry, University of Münster, 48149 Münster, Germany; (U.D.); (J.G.); (D.G.); (M.G.); (S.M.); (J.R.)
- Institute for Translational Neuroscience, University of Münster, 48149 Münster, Germany
| | - Tracy R. Melzer
- Department of Medicine, University of Otago, Christchurch 8011, New Zealand; (T.J.A.); (J.C.D.-A.); (T.R.M.)
- New Zealand Brain Research Institute, Christchurch 8011, New Zealand;
- School of Psychology, Speech and Hearing, University of Canterbury, Christchurch 8041, New Zealand
| | - Jessica Merchán-Naranjo
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), School of Medicine, Universidad Complutense, 28040 Madrid, Spain; (C.M.D.-C.); (J.M.-N.)
| | - Chantal Michel
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, 3000 Bern, Switzerland; (M.K.); (J.K.); (C.M.)
| | - Rajendra A. Morey
- Brain Imaging and Analysis Center, Duke University, Durham, NC 27710, USA; (S.L.); (R.A.M.)
- VISN 6 MIRECC, Durham VA, Durham, NC 27705, USA
| | - Benson Mwangi
- Center of Excellence on Mood Disorders, Louis A Faillace, MD Department of Psychiatry and Behavioral Sciences, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA; (B.M.); (J.C.S.); (M.-J.W.); (G.B.Z.-S.)
| | - Daniel J. Myall
- New Zealand Brain Research Institute, Christchurch 8011, New Zealand;
| | - Igor Nenadić
- Department of Psychiatry and Psychotherapy, University of Marburg, 35032 Marburg, Germany; (K.B.); (A.J.); (T.K.); (I.N.); (F.S.); (B.S.); (F.T.-O.); (A.W.)
| | - Mary R. Newsome
- Department of Neurology, University of Utah School of Medicine, Salt Lake City, UT 84132, USA; (E.K.); (S.W.L.); (H.M.L.); (S.V.); (M.R.N.); (M.J.P.); (D.F.T.); (E.A.W.)
- George E Wahlen Veterans Affairs Medical Center, Salt Lake City, UT 84148, USA
| | - Abraham Nunes
- Department of Psychiatry, Dalhousie University, Halifax, NS B3H 4R2, Canada; (M.A.); (A.N.)
- Faculty of Computer Science, Dalhousie University, Halifax, NS B3H 4R2, Canada
| | - Terence O’Brien
- Department of Medicine, Royal Melbourne Hospital, Melbourne, VIC 3050, Australia;
- Department of Neuroscience, The School of Translational Medicine, Alfred Health, Monash University, Melbourne VIC 3004, Australia
| | - Viola Oertel
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, Frankfurt University, 60590 Frankfurt, Germany;
| | - John Ollinger
- National Intrepid Center of Excellence, Walter Reed National Military Medical Center, Bethesda, MD 20814, USA; (S.M.L.); (J.O.)
| | - Alexander Olsen
- Department of Psychology, Norwegian University of Science and Technology, 7491 Trondheim, Norway;
- Department of Physical Medicine and Rehabilitation, St Olavs Hospital, Trondheim University Hospital, 7006 Trondheim, Norway
- NorHEAD—Norwegian Centre for Headache Research, 7491 Trondheim, Norway
| | - Victor Ortiz García de la Foz
- Department of Psychiatry, Marqués de Valdecilla University Hospital, Instituto de Investigación Sanitaria Valdecilla (IDIVAL), School of Medicine, University of Cantabria, 39008 Santander, Spain;
| | - Mustafa Ozmen
- Division of Epidemiology, University of Utah, Salt Lake City, UT 84108, USA;
- Department of Electrical and Electronics Engineering, Antalya Bilim University, 07190 Antalya, Turkey
| | - Heath Pardoe
- The Florey Institute of Neuroscience and Mental Health, Melbourne, VIC 3052, Australia; (H.P.); (E.W.)
| | - Marise Parent
- Neuroscience Institute & Department of Psychology, Georgia State University, Atlanta, GA 30303, USA;
| | - Fabrizio Piras
- Laboratory of Neuropsychiatry, Santa Lucia Foundation IRCCS, 00179 Rome, Italy; (N.B.); (R.L.); (F.P.); (F.P.); (G.S.); (D.V.)
| | - Federica Piras
- Laboratory of Neuropsychiatry, Santa Lucia Foundation IRCCS, 00179 Rome, Italy; (N.B.); (R.L.); (F.P.); (F.P.); (G.S.); (D.V.)
| | - Edith Pomarol-Clotet
- FIDMAG Research Foundation, 08025 Barcelona, Spain; (S.A.-L.); (P.F.-C.); (E.P.-C.); (R.S.)
- Centro Investigación Biomédica en Red Salud Mental (CIBERSAM), 28029 Madrid, Spain; (C.A.); (R.A.-A.); (B.C.-F.); (A.G.-Z.); (E.V.)
| | - Jonathan Repple
- Institute for Translational Psychiatry, University of Münster, 48149 Münster, Germany; (U.D.); (J.G.); (D.G.); (M.G.); (S.M.); (J.R.)
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt, Goethe University, 60590 Frankfurt, Germany
| | - Geneviève Richard
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital, 0424 Oslo, Norway; (K.K.K.); (G.R.); (A.-M.S.); (K.M.U.); (L.T.W.)
| | - Jonathan Rodriguez
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA; (C.E.F.); (W.S.K.); (J.R.); (A.S.)
| | - Mabel Rodriguez
- National Institute of Mental Health, 250 67 Klecany, Czech Republic; (B.K.); (K.K.); (M.R.); (F.Š.)
| | - Kelly Rootes-Murdy
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, Emory University, Atlanta, GA 30322, USA; (V.D.C.); (K.R.-M.)
| | - Jared Rowland
- WG (Bill) Hefner VA Medical Center, Salisbury, NC 28144, USA;
- Department of Neurobiology & Anatomy, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA
- VA Mid-Atlantic Mental Illness Research Education and Clinical Center (MA-MIRECC), Durham, NC 27705, USA
| | - Nicholas P. Ryan
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, VIC 3220, Australia;
- Department of Paediatrics, The University of Melbourne, Parkville, VIC 3052, Australia
| | - Raymond Salvador
- FIDMAG Research Foundation, 08025 Barcelona, Spain; (S.A.-L.); (P.F.-C.); (E.P.-C.); (R.S.)
- Centro Investigación Biomédica en Red Salud Mental (CIBERSAM), 28029 Madrid, Spain; (C.A.); (R.A.-A.); (B.C.-F.); (A.G.-Z.); (E.V.)
| | - Anne-Marthe Sanders
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital, 0424 Oslo, Norway; (K.K.K.); (G.R.); (A.-M.S.); (K.M.U.); (L.T.W.)
- Department of Psychology, University of Oslo, 0373 Oslo, Norway;
- Department of Research, Sunnaas Rehabilitation Hospital, 1450 Nesodden, Norway
| | - Andre Schmidt
- Department of Psychiatry (UPK), University of Basel, 4002 Basel, Switzerland;
| | - Jair C. Soares
- Center of Excellence on Mood Disorders, Louis A Faillace, MD Department of Psychiatry and Behavioral Sciences, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA; (B.M.); (J.C.S.); (M.-J.W.); (G.B.Z.-S.)
| | - Gianfranco Spalleta
- Laboratory of Neuropsychiatry, Santa Lucia Foundation IRCCS, 00179 Rome, Italy; (N.B.); (R.L.); (F.P.); (F.P.); (G.S.); (D.V.)
| | - Filip Španiel
- National Institute of Mental Health, 250 67 Klecany, Czech Republic; (B.K.); (K.K.); (M.R.); (F.Š.)
- 3rd Faculty of Medicine, Charles University, 100 00 Prague, Czech Republic
| | - Scott R. Sponheim
- Department of Psychiatry and Behavioral Sciences, University of Minnesota Medical School, Minneapolis, MN 55455, USA; (N.D.); (S.G.D.); (C.A.M.); (S.R.S.)
- Minneapolis VA Health Care System, Minneapolis, MN 55417, USA
| | - Alena Stasenko
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA; (C.E.F.); (W.S.K.); (J.R.); (A.S.)
- Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA 92093, USA
| | - Frederike Stein
- Department of Psychiatry and Psychotherapy, University of Marburg, 35032 Marburg, Germany; (K.B.); (A.J.); (T.K.); (I.N.); (F.S.); (B.S.); (F.T.-O.); (A.W.)
| | - Benjamin Straube
- Department of Psychiatry and Psychotherapy, University of Marburg, 35032 Marburg, Germany; (K.B.); (A.J.); (T.K.); (I.N.); (F.S.); (B.S.); (F.T.-O.); (A.W.)
| | - April Thames
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA 90095, USA; (R.F.A.); (T.B.); (C.H.); (T.K.); (A.T.)
| | - Florian Thomas-Odenthal
- Department of Psychiatry and Psychotherapy, University of Marburg, 35032 Marburg, Germany; (K.B.); (A.J.); (T.K.); (I.N.); (F.S.); (B.S.); (F.T.-O.); (A.W.)
| | - Sophia I. Thomopoulos
- Imaging Genetics Center, Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of the University of Southern California, Marina del Rey, CA 90292, USA; (S.I.T.); (P.M.T.)
| | - Erin B. Tone
- Department of Psychology, Georgia State University, Atlanta, GA 30303, USA;
| | - Ivan Torres
- Department of Psychiatry, University of British Columbia, Vancouver, BC V6T 1Z4, Canada; (I.T.); (L.N.Y.)
- British Columbia Mental Health and Substance Use Services Research Institute, Vancouver, BC V5Z 1M9, Canada
| | - Maya Troyanskaya
- Michael E DeBakey Veterans Affairs Medical Center, Houston, TX 77030, USA;
- H Ben Taub Department of Physical Medicine and Rehabilitation, Baylor College of Medicine, Houston, TX 77030, USA
| | - Jessica A. Turner
- Psychiatry and Behavioral Health, Ohio State Wexner Medical Center, Columbus, OH 43210, USA;
| | - Kristine M. Ulrichsen
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital, 0424 Oslo, Norway; (K.K.K.); (G.R.); (A.-M.S.); (K.M.U.); (L.T.W.)
- Department of Psychology, University of Oslo, 0373 Oslo, Norway;
- Department of Research, Sunnaas Rehabilitation Hospital, 1450 Nesodden, Norway
| | - Guillermo Umpierrez
- Division of Endocrinology, Emory University School of Medicine, Atlanta, GA 30322, USA;
| | - Daniela Vecchio
- Laboratory of Neuropsychiatry, Santa Lucia Foundation IRCCS, 00179 Rome, Italy; (N.B.); (R.L.); (F.P.); (F.P.); (G.S.); (D.V.)
| | - Elisabet Vilella
- Centro Investigación Biomédica en Red Salud Mental (CIBERSAM), 28029 Madrid, Spain; (C.A.); (R.A.-A.); (B.C.-F.); (A.G.-Z.); (E.V.)
- Hospital Universitari Institut Pere Mata, 43007 Tarragona, Spain
- Institut d’Investiació Sanitària Pere Virgili-CERCA, Universitat Rovira i Virgili, 43007 Tarragona, Spain
| | - Lucy Vivash
- Department of Neuroscience, Monash University, Melbourne, VIC 3800, Australia; (D.D.); (C.M.); (L.V.)
- Department of Neurology, Alfred Health, Melbourne, VIC 3004, Australia
| | - William C. Walker
- Department of Physical Medicine and Rehabilitation, Virginia Commonwealth University, Richmond, VA 23298, USA;
- Richmond Veterans Affairs (VA) Medical Center, Central Virginia VA Health Care System, Richmond, VA 23249, USA
| | - Emilio Werden
- The Florey Institute of Neuroscience and Mental Health, Melbourne, VIC 3052, Australia; (H.P.); (E.W.)
| | - Lars T. Westlye
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital, 0424 Oslo, Norway; (K.K.K.); (G.R.); (A.-M.S.); (K.M.U.); (L.T.W.)
- Department of Psychology, University of Oslo, 0373 Oslo, Norway;
- KG Jebsen Center for Neurodevelopmental Disorders, University of Oslo, 0372 Oslo, Norway
| | - Krista Wild
- Department of Psychology, Phoenix VA Health Care System, Phoenix, AZ 85012, USA;
| | - Adrian Wroblewski
- Department of Psychiatry and Psychotherapy, University of Marburg, 35032 Marburg, Germany; (K.B.); (A.J.); (T.K.); (I.N.); (F.S.); (B.S.); (F.T.-O.); (A.W.)
| | - Mon-Ju Wu
- Center of Excellence on Mood Disorders, Louis A Faillace, MD Department of Psychiatry and Behavioral Sciences, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA; (B.M.); (J.C.S.); (M.-J.W.); (G.B.Z.-S.)
| | - Glenn R. Wylie
- Department of Physical Medicine & Rehabilitation, Rutgers, New Jersey Medical School, Newark, NJ 07103, USA; (J.D.); (E.D.); (H.G.); (D.K.); (J.L.); (G.R.W.)
- Rocco Ortenzio Neuroimaging Center, Kessler Foundation, East Hanover, NJ 07936, USA
| | - Lakshmi N. Yatham
- Department of Psychiatry, University of British Columbia, Vancouver, BC V6T 1Z4, Canada; (I.T.); (L.N.Y.)
| | - Giovana B. Zunta-Soares
- Center of Excellence on Mood Disorders, Louis A Faillace, MD Department of Psychiatry and Behavioral Sciences, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA; (B.M.); (J.C.S.); (M.-J.W.); (G.B.Z.-S.)
| | - Paul M. Thompson
- Imaging Genetics Center, Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of the University of Southern California, Marina del Rey, CA 90292, USA; (S.I.T.); (P.M.T.)
- Departments of Neurology, Pediatrics, Psychiatry, Radiology, Engineering, and Ophthalmology, University of Southern California, Los Angeles, CA 90089, USA
| | - Mary Jo Pugh
- Department of Neurology, University of Utah School of Medicine, Salt Lake City, UT 84132, USA; (E.K.); (S.W.L.); (H.M.L.); (S.V.); (M.R.N.); (M.J.P.); (D.F.T.); (E.A.W.)
- Division of Epidemiology, University of Utah, Salt Lake City, UT 84108, USA;
| | - David F. Tate
- Department of Neurology, University of Utah School of Medicine, Salt Lake City, UT 84132, USA; (E.K.); (S.W.L.); (H.M.L.); (S.V.); (M.R.N.); (M.J.P.); (D.F.T.); (E.A.W.)
- George E Wahlen Veterans Affairs Medical Center, Salt Lake City, UT 84148, USA
| | - Frank G. Hillary
- Department of Psychology, Penn State University, State College, PA 16801, USA;
- Department of Neurology, Hershey Medical Center, State College, PA 16801, USA
- Social Life and Engineering Science Imaging Center, Penn State University, State College, PA 16801, USA
| | - Elisabeth A. Wilde
- Department of Neurology, University of Utah School of Medicine, Salt Lake City, UT 84132, USA; (E.K.); (S.W.L.); (H.M.L.); (S.V.); (M.R.N.); (M.J.P.); (D.F.T.); (E.A.W.)
- George E Wahlen Veterans Affairs Medical Center, Salt Lake City, UT 84148, USA
| | - Emily L. Dennis
- Department of Neurology, University of Utah School of Medicine, Salt Lake City, UT 84132, USA; (E.K.); (S.W.L.); (H.M.L.); (S.V.); (M.R.N.); (M.J.P.); (D.F.T.); (E.A.W.)
- George E Wahlen Veterans Affairs Medical Center, Salt Lake City, UT 84148, USA
| |
Collapse
|
5
|
Cozzi A, Di Leo G, Houssami N, Gilbert FJ, Helbich TH, Álvarez Benito M, Balleyguier C, Bazzocchi M, Bult P, Calabrese M, Camps Herrero J, Cartia F, Cassano E, Clauser P, de Lima Docema MF, Depretto C, Dominelli V, Forrai G, Girometti R, Harms SE, Hilborne S, Ienzi R, Lobbes MBI, Losio C, Mann RM, Montemezzi S, Obdeijn IM, Aksoy Ozcan U, Pediconi F, Pinker K, Preibsch H, Raya Povedano JL, Rossi Saccarelli C, Sacchetto D, Scaperrotta GP, Schlooz M, Szabó BK, Taylor DB, Ulus SÖ, Van Goethem M, Veltman J, Weigel S, Wenkel E, Zuiani C, Sardanelli F. Preoperative breast MRI positively impacts surgical outcomes of needle biopsy-diagnosed pure DCIS: a patient-matched analysis from the MIPA study. Eur Radiol 2024; 34:3970-3980. [PMID: 37999727 PMCID: PMC11166778 DOI: 10.1007/s00330-023-10409-5] [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: 08/06/2023] [Revised: 09/16/2023] [Accepted: 10/11/2023] [Indexed: 11/25/2023]
Abstract
OBJECTIVES To investigate the influence of preoperative breast MRI on mastectomy and reoperation rates in patients with pure ductal carcinoma in situ (DCIS). METHODS The MIPA observational study database (7245 patients) was searched for patients aged 18-80 years with pure unilateral DCIS diagnosed at core needle or vacuum-assisted biopsy (CNB/VAB) and planned for primary surgery. Patients who underwent preoperative MRI (MRI group) were matched (1:1) to those who did not receive MRI (noMRI group) according to 8 confounding covariates that drive referral to MRI (age; hormonal status; familial risk; posterior-to-nipple diameter; BI-RADS category; lesion diameter; lesion presentation; surgical planning at conventional imaging). Surgical outcomes were compared between the matched groups with nonparametric statistics after calculating odds ratios (ORs). RESULTS Of 1005 women with pure unilateral DCIS at CNB/VAB (507 MRI group, 498 noMRI group), 309 remained in each group after matching. First-line mastectomy rate in the MRI group was 20.1% (62/309 patients, OR 2.03) compared to 11.0% in the noMRI group (34/309 patients, p = 0.003). The reoperation rate was 10.0% in the MRI group (31/309, OR for reoperation 0.40) and 22.0% in the noMRI group (68/309, p < 0.001), with a 2.53 OR of avoiding reoperation in the MRI group. The overall mastectomy rate was 23.3% in the MRI group (72/309, OR 1.40) and 17.8% in the noMRI group (55/309, p = 0.111). CONCLUSIONS Compared to those going directly to surgery, patients with pure DCIS at CNB/VAB who underwent preoperative MRI had a higher OR for first-line mastectomy but a substantially lower OR for reoperation. CLINICAL RELEVANCE STATEMENT When confounding factors behind MRI referral are accounted for in the comparison of patients with CNB/VAB-diagnosed pure unilateral DCIS, preoperative MRI yields a reduction of reoperations that is more than twice as high as the increase in overall mastectomies. KEY POINTS • Confounding factors cause imbalance when investigating the influence of preoperative MRI on surgical outcomes of pure DCIS. • When patient matching is applied to women with pure unilateral DCIS, reoperation rates are significantly reduced in women who underwent preoperative MRI. • The reduction of reoperations brought about by preoperative MRI is more than double the increase in overall mastectomies.
Collapse
Affiliation(s)
- Andrea Cozzi
- Unit of Radiology, IRCCS Policlinico San Donato, Via Rodolfo Morandi 30, 20097, San Donato Milanese, Italy
- Imaging Institute of Southern Switzerland, Ente Ospedaliero Cantonale, Lugano, Switzerland
| | - Giovanni Di Leo
- Unit of Radiology, IRCCS Policlinico San Donato, Via Rodolfo Morandi 30, 20097, San Donato Milanese, Italy
| | - Nehmat Houssami
- The Daffodil Centre, Faculty of Medicine and Health, The University of Sydney (Joint Venture with Cancer Council NSW), Sydney, Australia
| | - Fiona J Gilbert
- Department of Radiology, School of Clinical Medicine, Cambridge Biomedical Campus, University of Cambridge, Cambridge, UK
| | - Thomas H Helbich
- Division of General and Paediatric Radiology, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
- Division of Molecular and Structural Preclinical Imaging, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | | | - Corinne Balleyguier
- Department of Radiology, Institut Gustave Roussy, Villejuif, France
- Biomaps, UMR1281 INSERM, CEA, CNRS, Université Paris-Saclay, Villejuif, France
| | - Massimo Bazzocchi
- Institute of Radiology, Department of Medicine, Ospedale Universitario S. Maria della Misericordia, Università degli Studi di Udine, Udine, Italy
| | - Peter Bult
- Department of Pathology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Massimo Calabrese
- Unit of Oncological and Breast Radiology, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Julia Camps Herrero
- Department of Radiology, Hospital Universitario de La Ribera, Alzira, Spain
- Ribera Salud Hospitals, Valencia, Spain
| | - Francesco Cartia
- Unit of Breast Imaging, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Enrico Cassano
- Breast Imaging Division, IEO, European Institute of Oncology IRCCS, Milan, Italy
| | - Paola Clauser
- Division of General and Paediatric Radiology, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | | | - Catherine Depretto
- Unit of Breast Imaging, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Valeria Dominelli
- Breast Imaging Division, IEO, European Institute of Oncology IRCCS, Milan, Italy
| | - Gábor Forrai
- Department of Radiology, MHEK Teaching Hospital, Semmelweis University, Budapest, Hungary
- Department of Radiology, Duna Medical Center, GE-RAD Kft, Budapest, Hungary
| | - Rossano Girometti
- Institute of Radiology, Department of Medicine, Ospedale Universitario S. Maria della Misericordia, Università degli Studi di Udine, Udine, Italy
| | - Steven E Harms
- Breast Center of Northwest Arkansas, Fayetteville, AR, USA
| | - Sarah Hilborne
- Department of Radiology, School of Clinical Medicine, Cambridge Biomedical Campus, University of Cambridge, Cambridge, UK
| | - Raffaele Ienzi
- Department of Radiology, Di.Bi.MED, Policlinico Universitario Paolo Giaccone Università degli Studi di Palermo, Palermo, Italy
| | - Marc B I Lobbes
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, The Netherlands
- Department of Medical Imaging, Zuyderland Medical Center, Sittard-Geleen, The Netherlands
| | - Claudio Losio
- Department of Breast Radiology, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Ritse M Mann
- Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Radiology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Stefania Montemezzi
- Department of Radiology, Azienda Ospedaliera Universitaria Integrata Verona, Verona, Italy
| | - Inge-Marie Obdeijn
- Department of Radiology and Nuclear Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Umit Aksoy Ozcan
- Department of Radiology, Acıbadem Atasehir Hospital, Istanbul, Turkey
| | - Federica Pediconi
- Department of Radiological, Oncological and Pathological Sciences, Università degli Studi di Roma "La Sapienza", Rome, Italy
| | - Katja Pinker
- Division of General and Paediatric Radiology, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
- Department of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Heike Preibsch
- Department of Diagnostic and Interventional Radiology, University Hospital of Tübingen, Tübingen, Germany
| | | | | | - Daniela Sacchetto
- Kiwifarm S.R.L., La Morra, Italy
- Disaster Medicine Service 118, ASL CN1, Levaldigi, Italy
| | | | - Margrethe Schlooz
- Department of Surgery, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Botond K Szabó
- Department of Radiology, Barking Havering and Redbridge University Hospitals NHS Trust, London, UK
| | - Donna B Taylor
- Medical School, Faculty of Health and Medical Sciences, The University of Western Australia, Perth, Australia
- Department of Radiology, Royal Perth Hospital, Perth, Australia
| | - Sila Ö Ulus
- Department of Radiology, Acıbadem Atasehir Hospital, Istanbul, Turkey
| | - Mireille Van Goethem
- Gynecological Oncology Unit, Department of Obstetrics and Gynecology, Department of Radiology, Multidisciplinary Breast Clinic, Antwerp University Hospital, University of Antwerp, Antwerp, Belgium
| | - Jeroen Veltman
- Maatschap Radiologie Oost-Nederland, Oldenzaal, The Netherlands
| | - Stefanie Weigel
- Clinic for Radiology and Reference Center for Mammography, University of Münster, Münster, Germany
| | - Evelyn Wenkel
- Department of Radiology, University Hospital of Erlangen, Erlangen, Germany
| | - Chiara Zuiani
- Institute of Radiology, Department of Medicine, Ospedale Universitario S. Maria della Misericordia, Università degli Studi di Udine, Udine, Italy
| | - Francesco Sardanelli
- Unit of Radiology, IRCCS Policlinico San Donato, Via Rodolfo Morandi 30, 20097, San Donato Milanese, Italy.
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Milan, Italy.
| |
Collapse
|
6
|
Stein AN, Mills CW, McGovern I, McDermott KW, Dean A, Bogdanov AN, Sullivan SG, Haag MDM. Relative Vaccine Effectiveness of Cell- vs Egg-Based Quadrivalent Influenza Vaccine Against Test-Confirmed Influenza Over 3 Seasons Between 2017 and 2020 in the United States. Open Forum Infect Dis 2024; 11:ofae175. [PMID: 38698895 PMCID: PMC11064727 DOI: 10.1093/ofid/ofae175] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Accepted: 03/20/2024] [Indexed: 05/05/2024] Open
Abstract
Background Influenza vaccine viruses grown in eggs may acquire egg-adaptive mutations that may reduce antigenic similarity between vaccine and circulating influenza viruses and decrease vaccine effectiveness. We compared cell- and egg-based quadrivalent influenza vaccines (QIVc and QIVe, respectively) for preventing test-confirmed influenza over 3 US influenza seasons (2017-2020). Methods Using a retrospective test-negative design, we estimated the relative vaccine effectiveness (rVE) of QIVc vs QIVe among individuals aged 4 to 64 years who had an acute respiratory or febrile illness and were tested for influenza in routine outpatient care. Exposure, outcome, and covariate data were obtained from electronic health records linked to pharmacy and medical claims. Season-specific rVE was estimated by comparing the odds of testing positive for influenza among QIVc vs QIVe recipients. Models were adjusted for age, sex, geographic region, influenza test date, and additional unbalanced covariates. A doubly robust approach was used combining inverse probability of treatment weights with multivariable regression. Results The study included 31 824, 33 388, and 34 398 patients in the 2017-2018, 2018-2019, and 2019-2020 seasons, respectively; ∼10% received QIVc and ∼90% received QIVe. QIVc demonstrated superior effectiveness vs QIVe in prevention of test-confirmed influenza: rVEs were 14.8% (95% CI, 7.0%-22.0%) in 2017-2018, 12.5% (95% CI, 4.7%-19.6%) in 2018-2019, and 10.0% (95% CI, 2.7%-16.7%) in 2019-2020. Conclusions This study demonstrated consistently superior effectiveness of QIVc vs QIVe in preventing test-confirmed influenza over 3 seasons characterized by different circulating viruses and degrees of egg adaptation.
Collapse
Affiliation(s)
- Alicia N Stein
- Centre for Outcomes Research and Epidemiology, CSL Seqirus, Melbourne, Australia
| | | | - Ian McGovern
- Centre for Outcomes Research and Epidemiology, CSL Seqirus, Waltham, Massachusetts, USA
| | | | - Alex Dean
- Real World Evidence, Veradigm, Chicago, Illinois, USA
| | | | - Sheena G Sullivan
- WHO Collaborating Centre for Reference and Research on Influenza, Royal Melbourne Hospital, and Department of Infectious Diseases, University of Melbourne, at the Peter Doherty Institute of Infection and Immunity, Melbourne, Australia
- Department of Epidemiology, University of California, Los Angeles, California, USA
| | - Mendel D M Haag
- Centre for Outcomes Research and Epidemiology, CSL Seqirus, Amsterdam, Netherlands
| |
Collapse
|
7
|
Wang H, Deng W, Zhang Y, Yang J, Wang Z, Liu B, Han Y, Yu Y, Zhao R, Xiaohu Li. Changes in subclinical cardiac abnormalities 1 Year after recovering from COVID-19 in patients without clinical cardiac findings. Heliyon 2024; 10:e27380. [PMID: 38495174 PMCID: PMC10943378 DOI: 10.1016/j.heliyon.2024.e27380] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Revised: 02/26/2024] [Accepted: 02/28/2024] [Indexed: 03/19/2024] Open
Abstract
Aim To evaluate the subclinical cardiac involvement in COVID-19 patients without clinical cardiac evidence using cardiac MR imaging. Material and methods Participants recovered from COVID-19 without cardiac symptoms and no cardiovascular medical history were enrolled in a prospective cohort study. They underwent baseline cardiac MR and follow-up cardiac MR > 300 days after discharge (n = 20). The study also included healthy controls (n = 20). Extracellular volume fraction (ECV), native T1, and 2D strain data were assessed and compared. Results The ECV values of participants at baseline [30.0% (28.3%-32.5%)] and at follow-up [31.0% (28.0%-32.8%)] were increased compared to the healthy control group [27.0% (25.3%-28.0%)] (both p < 0.001). However, the ECV increase from baseline cardiac MR to follow-up cardiac MR was not significant (p = 0.378). There was a statistically significant difference in global native T1 between baseline [1140 (1108.3-1192.0) ms] and follow-up [1176.0 (1113.0-1206.3) ms] (p = 0.016). However, no native T1 difference was found between the healthy controls [1160.7 (1119.6-1195.4) ms] and the baseline (p = 0.394) or follow-up group (p = 0.168). The global T2 was 41(40-42) ms at follow-up which was within the normal range. In addition, We found a recovery in 2D GLS among COVID-19 participants between baseline and follow-up [-12.4(-11.7 to -14.3)% vs. -17.2(-16.2 to -18.3)%; p<0.001]. Conclusion Using cardiac MR myocardial tissue and strain imaging parameters, 35% of people without cardiac symptoms or clinical evidence of myocardial injury still had subclinical myocardial tissue characteristic abnormalities at 300 days, but 2D GLS had recovered.
Collapse
Affiliation(s)
- Haitao Wang
- Department of Radiology, No.2 People's Hospital of Fuyang City, Fuyang, Anhui, China
| | - Wei Deng
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Research Center of Clinical Medical Imaging, Anhui Province Clinical Image Quality Control Center, Hefei, Anhui Province, No. 218 Jixi Road, Hefei, 230022, China
| | - Yang Zhang
- Department of Radiology, Fuyang People's Hospital, Fuyang, 236015, Anhui Province, China
| | - Jinxiu Yang
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Research Center of Clinical Medical Imaging, Anhui Province Clinical Image Quality Control Center, Hefei, Anhui Province, No. 218 Jixi Road, Hefei, 230022, China
| | - Zhen Wang
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Research Center of Clinical Medical Imaging, Anhui Province Clinical Image Quality Control Center, Hefei, Anhui Province, No. 218 Jixi Road, Hefei, 230022, China
| | - Bin Liu
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Research Center of Clinical Medical Imaging, Anhui Province Clinical Image Quality Control Center, Hefei, Anhui Province, No. 218 Jixi Road, Hefei, 230022, China
| | - Yuchi Han
- Cardiovascular Division, Wexner Medical Center, College of Medicine, The Ohio State University Medical Center, Columbus, OH, USA
| | - Yongqiang Yu
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Research Center of Clinical Medical Imaging, Anhui Province Clinical Image Quality Control Center, Hefei, Anhui Province, No. 218 Jixi Road, Hefei, 230022, China
| | - Ren Zhao
- Department of Cardiology The First Affiliated Hospital of Anhui Medical University,Anhui, China
| | - Xiaohu Li
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Research Center of Clinical Medical Imaging, Anhui Province Clinical Image Quality Control Center, Hefei, Anhui Province, No. 218 Jixi Road, Hefei, 230022, China
| |
Collapse
|
8
|
Fudulu DP, Argyriou A, Kota R, Chan J, Vohra H, Caputo M, Zakkar M, Angelini GD. Effect of on-pump vs. off-pump coronary artery bypass grafting in patients with non-dialysis-dependent severe renal impairment: propensity-matched analysis from the UK registry dataset. Front Cardiovasc Med 2024; 11:1341123. [PMID: 38414924 PMCID: PMC10897021 DOI: 10.3389/fcvm.2024.1341123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2023] [Accepted: 01/09/2024] [Indexed: 02/29/2024] Open
Abstract
Introduction On-pump coronary artery bypass (ONCABG) grafting in patients with a pre-existing poor renal reserve is known to carry significant morbidity and mortality. There is limited controversial evidence on the benefit of off-pump coronary artery bypass (OPCABG) grafting in these high-risk groups of patients. We compared early clinical outcomes in propensity-matched cohorts of patients with non-dialysis-dependent pre-operative severe renal impairment undergoing OPCABG vs. ONCABG, captured in a large national registry dataset. Methods All data for patients with a pre-operative creatinine clearance of less than 50 mL/min who underwent elective or urgent isolated OPCABG or ONCABG from 1996 to 2019 were extracted from the UK National Adult Cardiac Surgery Audit (NACSA) database. Propensity score matching was performed using 1:1 nearest neighbor matching without replacement using several baseline characteristics. We investigated the effect of ONCABG vs. OPCABG in the matched cohort using cluster-robust standard error regression. Results We identified 8,628 patients with severe renal impairment undergoing isolated CABG, of whom 1,142 (13.23%) underwent OPCABG during the study period. We compared 1,141 propensity-matched pairs of patients undergoing OPCABG vs. ONCABG. The median age of the matched population was 78 years in both groups, with no significant imbalance post-matching in the rest of the variables. There was no difference between OPCABG and ONCABG in in-hospital mortality rates, post-operative dialysis, and stroke rates. However, the return to theatre for bleeding or tamponade was higher in ONCABG vs. OPCABG (P > 0.02); however, OPCABG reduced the total length of stay in the hospital by 1 day (P = 0.008). After double adjustment in the matched population using cluster-robust standard regression, ONCABG did not increase mortality compared to OPCABG (OR, 1.05, P = 0.78), postoperative stroke (OR, 1.7, P = 0.12), and dialysis (OR, 0.7, P = 0.09); however, ONCABG was associated with an increased risk of bleeding (OR, 1.53, P = 0.03). Discussion In this propensity analysis of a large national registry dataset, we found no difference in early mortality and stroke in patients with pre-operative severe renal impairment undergoing OPCABG or ONCABG surgery; however, ONCABG was associated with an increased risk of return to theatre for bleeding and an increased length of hospital stay.
Collapse
Affiliation(s)
- Daniel P. Fudulu
- Department of Cardiac Surgery, Bristol Heart Institute, University of Bristol, Bristol, United Kingdom
| | - Amerikos Argyriou
- Department of Cardiac Surgery, Bristol Heart Institute, University of Bristol, Bristol, United Kingdom
| | - Rahul Kota
- Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Jeremy Chan
- Department of Cardiac Surgery, Bristol Heart Institute, University of Bristol, Bristol, United Kingdom
| | - Hunaid Vohra
- Department of Cardiac Surgery, Bristol Heart Institute, University of Bristol, Bristol, United Kingdom
| | - Massimo Caputo
- Department of Cardiac Surgery, Bristol Heart Institute, University of Bristol, Bristol, United Kingdom
| | - Mustafa Zakkar
- Department of Cardiac Surgery, Bristol Heart Institute, University of Bristol, Bristol, United Kingdom
| | - Gianni D. Angelini
- Department of Cardiac Surgery, Bristol Heart Institute, University of Bristol, Bristol, United Kingdom
| |
Collapse
|
9
|
Dams GM, Ketchen BR, Burden JL, Smith NB. Effectiveness of residential treatment services for veterans with substance use disorders: A propensity score matching evaluation. Drug Alcohol Depend 2024; 255:111081. [PMID: 38211367 DOI: 10.1016/j.drugalcdep.2024.111081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Revised: 12/28/2023] [Accepted: 12/31/2023] [Indexed: 01/13/2024]
Abstract
BACKGROUND Prior reviews of substance use disorder (SUD) treatment have found mixed support for residential level of care but are limited by methodology problems and the ethical concerns of randomizing patients with severe SUD to lower levels of care. METHODS The present study is the first to use a large archival SUD residential sample with a matched comparison group and one-year follow-up period to examine the benefits of residential treatment provided to adults clinically assessed as warranting SUD residential care. We used propensity score matching in our sample (N = 6177) of veterans with a SUD who were screened and accepted for Veterans Affairs (VA) SUD residential treatment between January 1st, 2019 and June 30th, 2019. RESULTS We found evidence that VA SUD residential treatment saves veteran lives with an average 66% all-cause mortality risk reduction during the study period (b = -1.09, exp(b) = 0.34, p <0.001). Medium-to-large residential pre- to post-treatment self-reported mental health and SUD symptom improvements (|SMDrobust| = 0.54-0.93) were sustained by one-year post-screening. These residential treatment improvements were significantly larger than estimated counterfactual outcomes across self-reported SUD and stress disorder symptoms at one-year post-screening (ps <0.001). We found mixed behavioral, service utilization, and other self-reported mental health outcomes. CONCLUSIONS We conclude that VA SUD residential treatment is an effective level of care for veterans warranting residential care particularly for SUD symptom improvements and reductions in mortality risk.
Collapse
Affiliation(s)
- Gregory M Dams
- Salem Veterans Affairs Medical Center, Salem, VA, United States; VA Program Evaluation and Resource Center, Menlo Park, CA, United States.
| | | | - Jennifer L Burden
- Department of Veterans Affairs, Veterans Health Administration, Salem, VA, United States
| | - Noelle B Smith
- Department of Psychiatry, Yale School of Medicine, Yale University, United States; VA Northeast Program Evaluation Center, West Haven, CT, United States
| |
Collapse
|
10
|
Rivera AS, Pak K, Mefford MT, Hechter RC. Changes in Glomerular Filtration Rate After Switching From Tenofovir Disoproxil Fumarate to Tenofovir Alafenamide Fumarate for Human Immunodeficiency Virus Preexposure Prophylaxis. Open Forum Infect Dis 2024; 11:ofad695. [PMID: 38352151 PMCID: PMC10863550 DOI: 10.1093/ofid/ofad695] [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: 10/26/2023] [Accepted: 12/27/2023] [Indexed: 02/16/2024] Open
Abstract
Background Tenofovir alafenamide fumarate (TAF) was promoted as a safer alternative to tenofovir disoproxil fumarate (TDF) for human immunodeficiency virus oral preexposure prophylaxis (PrEP). It is unknown if switching from TDF to TAF translates to improved renal function. We used electronic health record (EHR) data to assess changes in creatinine-estimated glomerular filtration rate (eGFR) after switching from TDF to TAF. Methods We conducted a retrospective cohort study using EHR data from Kaiser Permanente Southern California. We identified individuals who switched from TDF to TAF between October 2019 and May 2022 and used time-varying propensity score matching to identify controls who were on TDF ("nonswitchers"). We then used Bayesian longitudinal modeling to compare differences in eGFR between switching and nonswitching scenarios. Results Among 5246 eligible individuals, we included 118 TDF to TAF switchers and 114 nonswitchers. Compared to nonswitchers, switchers had older age of starting TDF but similar body weights at index date. A higher proportion of switchers were White, on Medicare or Medicaid, and had dyslipidemia at index date. Switching to TAF was associated with a higher eGFR compared to staying on TDF in 3-15 months post-switch, but the differences were not statistically significant (eg, month 9 difference: 1.27 [95% credible interval, -1.35 to 3.89]). While most of the estimated changes showed eGFR increase associated with switching, most were <2 eGFR units. Sensitivity analyses to address missingness or nonadherence showed similar results. Conclusions Switching from TDF to TAF for PrEP was associated with a nonsignificant increase in eGFR. Findings need to be confirmed using larger cohorts.
Collapse
Affiliation(s)
- Adovich S Rivera
- Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, California, USA
| | - Katherine Pak
- Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, California, USA
| | - Matthew T Mefford
- Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, California, USA
| | - Rulin C Hechter
- Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, California, USA
- Department of Health Systems Science, Kaiser Permanente Bernard J. Tyson School of Medicine, Pasadena, California, USA
| |
Collapse
|
11
|
Eichhorn M, Bernauer E, Rotärmel A, Heurich M, Winter H. Clinical effectiveness of robotic-assisted compared to open or video-assisted lobectomy in Germany: a real-world data analysis. INTERDISCIPLINARY CARDIOVASCULAR AND THORACIC SURGERY 2024; 38:ivae001. [PMID: 38175785 PMCID: PMC10805345 DOI: 10.1093/icvts/ivae001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Accepted: 01/03/2024] [Indexed: 01/06/2024]
Abstract
OBJECTIVES Despite robotic-assisted thoracic surgery (RATS) lobectomy being on the rise in Europe, the majority of lobectomies in Germany are still performed with an open or thoracoscopic [video-assisted thoracic surgery (VATS)] approach. Empirical evidence in favour of RATS lobectomy is inconsistent. This retrospective cohort study investigates the impact of RATS lobectomy compared with open thoracic surgery (OPEN) and VATS lobectomy on short-term outcomes in Germany using multicentre real-world data. METHODS Anonymized routine data from Germany from 2018 to 2020 were retrospectively analysed. These data were provided by 61 German hospitals. Propensity score matching with subsequent generalized linear models was performed for statistical analysis. Additionally, in order to test the robustness of the results, multivariable regression analyses with cluster-robust standard errors were used. RESULTS A total of 2498 patients with lobectomy were identified: in 1345 patients OPEN, in 983 VATS and 170 a RATS lobectomy was performed. RATS-compared to OPEN and VATS-reduced length of stay (LOS) by 28% or 4.2 days [confidence interval: 2.9; 5.4] and by 13% or 1.6 days [confidence interval: 0.2; 3.0], respectively. The risk of pneumonia was reduced by 5.3 percentage points in the RATS group compared to both OPEN and VATS (P = 0.07/0.01). RATS-compared to an open approach-reduces the risk of blood transfusions by 8.8 percentage points (P < 0.001) and LOS on the intensive care unit (P < 0.001). CONCLUSIONS This study provides strong support that RATS lobectomy outperforms OPEN or VATS lobectomy in terms of hospital LOS, and short-term in-hospital postoperative complications in the real-world scenario in Germany.
Collapse
Affiliation(s)
- Martin Eichhorn
- Department of Thoracic Surgery, Thoraxklinik, University of Heidelberg, Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC-H), Member of the German Center for Lung Research (DZL), Heidelberg, Germany
| | | | - Andre Rotärmel
- Department of Thoracic Surgery, Thoraxklinik, University of Heidelberg, Heidelberg, Germany
- Department of Surgery, University of Heidelberg, Heidelberg, Germany
| | | | - Hauke Winter
- Department of Thoracic Surgery, Thoraxklinik, University of Heidelberg, Heidelberg, Germany
- Translational Lung Research Center Heidelberg (TLRC-H), Member of the German Center for Lung Research (DZL), Heidelberg, Germany
| |
Collapse
|
12
|
Yan Wang N, Liu X, Kong X, Sumi Y, Chhetri JK, Hu L, Zhu M, Kang L, Liang Z, Ellis JW, Shi L. Implementation and impact of the World Health Organization integrated care for older people (ICOPE) program in China: a randomised controlled trial. Age Ageing 2024; 53:afad249. [PMID: 38251736 DOI: 10.1093/ageing/afad249] [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: 10/04/2023] [Revised: 12/07/2023] [Indexed: 01/23/2024] Open
Abstract
BACKGROUND Fragmentation of services increases health and social care burden as people live longer with higher prevalence of diseases, frailty and dependency. Local evidence for implementing person-centred integrated care is urgently needed to advance practice and policies to achieve healthy ageing. OBJECTIVE To test the feasibility and impact of World Health Organization's (WHO) Integrated Care for Older People (ICOPE) approach in China. DESIGN A randomised controlled trial examining the feasibility of implementing ICOPE approach, evaluating its impact on health outcomes and health resource utilisation. SETTING Primary care setting in urban and suburban communities of Chaoyang District, Beijing, China. SUBJECTS Community-dwelling older adults screened as at-risk of functional declines and randomised into intervention (537) and control (1611) groups between September 2020 and February 2021. METHODS A 6-month intervention program following WHO's ICOPE care pathways implemented by integrated care managers compared to standard available care. RESULTS After 1 to 1 propensity score matching, participants in intervention and control groups (totally 938) had comparable baseline characteristics, demonstrated feasibility of implementing ICOPE with satisfaction by participants (97-99%) and providers (92-93%). All outcomes showed improvements after a 6-month intervention, while statistically significant least-squares mean differences (control-intervention) in vitality (Mini-Nutritional Assessment Short Form to measure vitality, -0.21, 95% CI, -0.40-0.02), mobility (Short Physical Performance Battery to measure mobility, -0.29, 95% CI, -0.44-0.14) and psychological health (Geriatric Depression Scale five items to measure psychological health, 0.09, 95% CI, 0.03-0.14) were observed (P < 0.05). CONCLUSIONS It is feasible to localise and implement WHO's ICOPE approach in regions with fragmented resources such as China. Preliminary evidence supports its acceptance among key stakeholders and impact on health outcomes.
Collapse
Affiliation(s)
- Ninie Yan Wang
- Department of Health Policy and Management, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA
| | - Xiaohong Liu
- Department of Geriatrics, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Xiangrong Kong
- Wilmer Eye Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Yuka Sumi
- Ageing and Health (AAH), Department of Maternal, Newborn, Child & Adolescent Health & Ageing (MCA), World Health Organization, Geneva, Switzerland
| | - Jagadish K Chhetri
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Linlin Hu
- School of Health Policy and Management, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Minglei Zhu
- Department of Geriatrics, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Lin Kang
- Department of Geriatrics, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Zhen Liang
- Shenzhen People's Hospital, Shenzhen, China
| | - John W Ellis
- Department of Health Policy and Management, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA
| | - Leiyu Shi
- Department of Health Policy and Management, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA
| |
Collapse
|
13
|
Serdarevic M, Cvitanovich M, MacDonald BR, d'Etienne J, DeMoss D, Ojha RP. Emergency Department Bridge Model and Health Services Use Among Patients With Opioid Use Disorder. Ann Emerg Med 2023; 82:694-704. [PMID: 37542490 DOI: 10.1016/j.annemergmed.2023.06.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2023] [Revised: 06/06/2023] [Accepted: 06/15/2023] [Indexed: 08/07/2023]
Abstract
STUDY OBJECTIVES Little is known about the effectiveness of bridge clinics as transitional care programs for people with opioid use disorder in emergency departments (EDs). We assessed the effect of bridge clinic referral on health services use among patients with opioid use disorder identified in the ED. METHODS We used data for individuals aged 18 years and over with active opioid use disorder and no history of medication for opioid use disorder who were administered medication for opioid use disorder while in the ED between January 2013 and August 2022. Bridge clinic referrals started in January 2021. Eligible patients after this date comprised the intervention group. The usual care group included eligible patients before bridge clinic implementation, who were a 1:1 propensity score matched to intervention patients. We estimated risk differences and 95% confidence limits for linkage to long-term care, ED use, and inpatient admission within 120 days of the index ED visit. RESULTS Our study population comprised 928 observations after matching. Patients referred to the bridge clinic had a higher risk of linkage to long-term care (risk differences=25%; 95% confidence limits: 20%, 30%), higher risk of ED use (risk differences=7.5%, 95% confidence limits: 1.6%, 13%), and lower risk of inpatient admission (risk differences= -1.9%, 95% confidence limits: -5.9%, 2.1%). Inpatient admission increased among patients with serious mental illness but decreased among patients without serious mental illness. CONCLUSION Our overall results suggest that bridge clinic referral increases linkage to long-term care. Nevertheless, qualitatively different effects on inpatient admission between patients with and without serious mental illness warrant consideration of unmet needs among patients with serious mental illness.
Collapse
Affiliation(s)
- Mirsada Serdarevic
- Center for Epidemiology and Healthcare Delivery Research, JPS Health Network, Fort Worth, TX.
| | - Matthew Cvitanovich
- Center for Epidemiology and Healthcare Delivery Research, JPS Health Network, Fort Worth, TX
| | - Brooke R MacDonald
- Center for Epidemiology and Healthcare Delivery Research, JPS Health Network, Fort Worth, TX
| | - James d'Etienne
- Department of Emergency Medicine, Integrative Emergency Services, JPS Health Network, Fort Worth, TX
| | - Dustin DeMoss
- Acclaim Behavioral Health (DeMoss), JPS Health Network, Fort Worth, TX
| | - Rohit P Ojha
- Center for Epidemiology and Healthcare Delivery Research, JPS Health Network, Fort Worth, TX
| |
Collapse
|
14
|
Barker MM, Davies MJ, Sargeant JA, Chan JCN, Gregg EW, Shabnam S, Khunti K, Zaccardi F. Age at Type 2 Diabetes Diagnosis and Cause-Specific Mortality: Observational Study of Primary Care Patients in England. Diabetes Care 2023; 46:1965-1972. [PMID: 37625035 DOI: 10.2337/dc23-0834] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Accepted: 08/07/2023] [Indexed: 08/27/2023]
Abstract
OBJECTIVE To examine the associations between age at type 2 diabetes diagnosis and the relative and absolute risk of all-cause and cause-specific mortality in England. RESEARCH DESIGN AND METHODS In this cohort study using primary care data from the Clinical Practice Research Datalink, we identified 108,061 individuals with newly diagnosed type 2 diabetes (16-50 years of age), matched to 829,946 individuals without type 2 diabetes. We estimated all-cause and cause-specific mortality (cancer, cardiorenal, other [noncancer or cardiorenal]) by age at diagnosis, using competing-risk survival analyses adjusted for key confounders. RESULTS Comparing individuals with versus without type 2 diabetes, the relative risk of death decreased with an older age at diagnosis: the hazard ratio for all-cause mortality was 4.32 (95% CI 3.35-5.58) in individuals diagnosed at ages 16-27 years compared with 1.53 (95% CI 1.46-1.60) at ages 48-50 years. Smaller relative risks by increasing age at diagnosis were also observed for cancer, cardiorenal, and noncancer or cardiorenal death. Irrespective of age at diagnosis, the 10-year absolute risk of all-cause and cause-specific mortality were higher in individuals with type 2 diabetes; yet, the absolute differences were small. CONCLUSIONS Although the relative risk of death in individuals with versus without type 2 was higher at younger ages, the 10-year absolute risk of all investigated causes of death was small and similar in the two groups. Further multidecade studies could help estimate the long-term risk of complications and death in individuals with early-onset type 2 diabetes.
Collapse
Affiliation(s)
- Mary M Barker
- Leicester Real World Evidence Unit, Leicester Diabetes Centre, University of Leicester, Leicester, U.K
- Unit of Integrative Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Solna, Sweden
| | - Melanie J Davies
- Diabetes Research Centre, University of Leicester, College of Life Sciences, Leicester General Hospital, Leicester, U.K
- Leicester Diabetes Centre, University Hospitals of Leicester NHS Trust, Leicester, U.K
- National Institute for Health Research Leicester Biomedical Research Centre, Leicester, U.K
| | - Jack A Sargeant
- Diabetes Research Centre, University of Leicester, College of Life Sciences, Leicester General Hospital, Leicester, U.K
- Leicester Diabetes Centre, University Hospitals of Leicester NHS Trust, Leicester, U.K
- National Institute for Health Research Leicester Biomedical Research Centre, Leicester, U.K
| | - Juliana C N Chan
- Department of Medicine and Therapeutics, Hong Kong Institute of Diabetes and Obesity, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong
| | - Edward W Gregg
- School of Population Health, Royal College of Surgeons of Ireland, University of Medicine and Health Sciences, Dublin, Ireland
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College, London, U.K
| | - Sharmin Shabnam
- Leicester Real World Evidence Unit, Leicester Diabetes Centre, University of Leicester, Leicester, U.K
| | - Kamlesh Khunti
- Leicester Real World Evidence Unit, Leicester Diabetes Centre, University of Leicester, Leicester, U.K
- Diabetes Research Centre, University of Leicester, College of Life Sciences, Leicester General Hospital, Leicester, U.K
- National Institute for Health Research Leicester Biomedical Research Centre, Leicester, U.K
- National Institute for Health Research Applied Research Collaboration East Midlands, Leicester Diabetes Centre, University of Leicester, Leicester, U.K
| | - Francesco Zaccardi
- Leicester Real World Evidence Unit, Leicester Diabetes Centre, University of Leicester, Leicester, U.K
- Diabetes Research Centre, University of Leicester, College of Life Sciences, Leicester General Hospital, Leicester, U.K
- National Institute for Health Research Leicester Biomedical Research Centre, Leicester, U.K
| |
Collapse
|
15
|
Mol KHJM, Liem VGB, van Lier F, Stolker RJ, Hoeks SE. Intraoperative hypotension in noncardiac surgery patients with chronic beta-blocker therapy: A matched cohort analysis. J Clin Anesth 2023; 89:111143. [PMID: 37216803 DOI: 10.1016/j.jclinane.2023.111143] [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: 09/06/2022] [Revised: 04/19/2023] [Accepted: 05/01/2023] [Indexed: 05/24/2023]
Abstract
STUDY OBJECTIVE To explore the incidence of intraoperative hypotension in patients with chronic beta-blocker therapy, expressed as time spent, area and time-weighted average under predefined mean arterial pressure thresholds. DESIGN Retrospective analysis of a prospective observational cohort registry. SETTING Patients ≥60 years undergoing intermediate- to high-risk noncardiac surgery with routine postoperative troponin measurements on the first three days after surgery. PATIENTS 1468 matched sets of patients (1:1 ratio with replacement) with and without chronic beta-blocker treatment. INTERVENTIONS None. MEASUREMENTS The primary outcome was the exposure to intraoperative hypotension in beta-blocker users vs. non-users. Time spent, area and time-weighted average under predefined mean arterial pressure thresholds (55-75 mmHg) were calculated to express the duration and severity of exposure. Secondary outcomes included incidence of postoperative myocardial injury and thirty-day mortality, myocardial infarction (MI) and stroke. Furthermore, analyses for patient subgroup and beta-blocker subtype were conducted. MAIN RESULTS In patients with chronic beta-blocker therapy, no increased exposure to intraoperative hypotension was observed for all characteristics and thresholds calculated (all P > .05). Beta-blocker users had lower heart rate before, during and after surgery (70 vs. 74, 61 vs. 65 and 68 vs. 74 bpm, all P < .001, respectively). Postoperative myocardial injury (13.6% vs. 11.6%, P = .269) and thirty-day mortality (2.5% vs. 1.4%, P = .055), MI (1.4% vs. 1.5%, P = .944) and stroke (1.0% vs 0.7%, P = .474) rates were comparable. The results were consistent in subtype and subgroup analyses. CONCLUSIONS In this matched cohort analysis, chronic beta-blocker therapy was not associated with increased exposure to intraoperative hypotension in patients undergoing intermediate- to high-risk noncardiac surgery. Furthermore, differences in patient subgroups and postoperative adverse cardiovascular events as a function of treatment regimen could not be demonstrated.
Collapse
Affiliation(s)
- Kristin H J M Mol
- Department of Anesthesia, Erasmus University Medical Center, Rotterdam, the Netherlands.
| | - Victor G B Liem
- Department of Anesthesia, Erasmus University Medical Center, Rotterdam, the Netherlands.
| | - Felix van Lier
- Department of Anesthesia, Erasmus University Medical Center, Rotterdam, the Netherlands.
| | - Robert Jan Stolker
- Department of Anesthesia, Erasmus University Medical Center, Rotterdam, the Netherlands.
| | - Sanne E Hoeks
- Department of Anesthesia, Erasmus University Medical Center, Rotterdam, the Netherlands.
| |
Collapse
|
16
|
Rivera AS, Pak KJ, Mefford MT, Hechter RC. Use of Tenofovir Alafenamide Fumarate for HIV Pre-Exposure Prophylaxis and Incidence of Hypertension and Initiation of Statins. JAMA Netw Open 2023; 6:e2332968. [PMID: 37695583 PMCID: PMC10495863 DOI: 10.1001/jamanetworkopen.2023.32968] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Accepted: 08/02/2023] [Indexed: 09/12/2023] Open
Abstract
Importance Pre-exposure prophylaxis (PrEP) is an important tool for preventing HIV infection. However, PrEP's impact on cardiometabolic health is understudied. Objective To examine the risk of incident hypertension and statin initiation among adult (age ≥18 years) health plan members starting PrEP with tenofovir alafenamide fumarate (TAF) compared with propensity score-matched adults taking tenofovir disoproxil fumarate (TDF). Design, Setting, and Participants This retrospective cohort study used electronic health records (EHRs) from Kaiser Permanente Southern California. Adult members starting PrEP in Kaiser Permanente Southern California between October 2019 and May 2022 were included. Propensity score matching with multiple imputation (50 matched data sets) was conducted to generate 1 TAF:4 TDF matched data sets with balanced baseline covariates. Exposures PrEP initiation with either TAF or TDF during the study period. Main Outcomes and Measures Incident hypertension and statin initiation within 2 years of PrEP initiation were ascertained through blood pressure and outpatient pharmacy records, respectively. Risk differences and odds ratios (ORs) were estimated using logistic regression and g-computation. Results A total of 6824 eligible individuals were identified (mean [SD] age, 33.9 [10.3] years; 6618 [97%] male). This pool was used to generate 2 cohorts without baseline hypertension or statin use for matching (hypertension: n = 5523; statin: n = 6149) In both cohorts, those starting PrEP with TAF were older and were more likely to be non-Hispanic White compared with those starting with TDF. In matched analysis adjusting for baseline covariates, TAF use was associated with elevated risk of incident hypertension (TAF: n = 371; risk difference, 0.81 [95% CI, 0.12-1.50]; OR, 1.64 [95% CI, 1.05-2.56]). TAF use was also associated with elevated risk of statin initiation (TAF: n = 382; risk difference, 0.85 [95% CI, 0.37-1.33]; OR, 2.33 [95% CI, 1.41-3.85]). Subgroup analyses restricted to individuals 40 years and older at PrEP initiation showed similar results with larger risk difference in statin initiation (risk difference, 4.24 [95% CI, 1.82-6.26]; OR, 3.05 [95% CI, 1.64-5.67]). Conclusions and Relevance In this study of people taking PrEP, TAF use was found to be associated with higher incident hypertension and statin initiation compared with TDF use, especially in those 40 years or older. Continued monitoring of blood pressure and lipids for TAF users is warranted.
Collapse
Affiliation(s)
- Adovich S. Rivera
- Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena
| | - Katherine J. Pak
- Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena
| | - Matthew T. Mefford
- Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena
| | - Rulin C. Hechter
- Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena
- Health Systems Science, Kaiser Permanente Bernard J. Tyson School of Medicine, Pasadena, California
| |
Collapse
|
17
|
de Tymowski C, Sahnoun T, Provenchere S, Para M, Derre N, Mutuon P, Duval X, Grall N, Iung B, Kernéis S, Lucet JC, Montravers P. Impact of Antibiotic Prophylaxis on Surgical Site Infections in Cardiac Surgery. Antibiotics (Basel) 2023; 12:85. [PMID: 36671286 PMCID: PMC9854463 DOI: 10.3390/antibiotics12010085] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2022] [Revised: 12/27/2022] [Accepted: 12/29/2022] [Indexed: 01/06/2023] Open
Abstract
(1) Background: Cephalosporins (CA) are the first-line antibiotic prophylaxis recommended to prevent surgical site infection (SSI) after cardiac surgery. The combination of vancomycin/gentamicin (VGA) might represent a good alternative, but few studies have evaluated its efficacy in SSI prevention. (2) Methods: A single-centre retrospective study was conducted over a 13-year period in all consecutive adult patients undergoing elective cardiac surgery. Patients were stratified according to the type of antibiotic prophylaxis. CA served as the first-line prophylaxis, and VGA was used as the second-line prophylaxis. The primary endpoint was SSI occurrence at 90 days, which was defined as the need for reoperation due to SSI. (3) Results: In total, 14,960 adult patients treated consecutively from 2006 to 2019 were included in this study, of whom 1774 (12%) received VGA and 540 (3.7%) developed SSI. VGA patients had higher severity with increased 90-day mortality. Nevertheless, the frequency of SSI was similar between CA and VGA patients. However, the microbiological aetiologies were different, with more Gram-negative bacteria noted in the VGA group. (4) Conclusions: VGA seems to be as effective as CA in preventing SSI.
Collapse
Affiliation(s)
- Christian de Tymowski
- Department of Anaesthesiology and Surgical Intensive Care, DMU PARABOL, AP-HP, Hôpital Bichat, 75018 Paris, France
- Université Paris Cité, Centre de Recherche sur l’Inflammation, INSERM UMR 1149, CNRS ERL8252, F-75018 Paris, France
- Laboratory of Excellence, Inflamex, Université Paris Cité, F-75018 Paris, France
- Department of Immunology, DHU Fire, AP-HP, Hôpital Bichat, 75018 Paris, France
| | - Tarek Sahnoun
- Department of Anaesthesiology and Surgical Intensive Care, DMU PARABOL, AP-HP, Hôpital Bichat, 75018 Paris, France
| | - Sophie Provenchere
- Department of Anaesthesiology and Surgical Intensive Care, DMU PARABOL, AP-HP, Hôpital Bichat, 75018 Paris, France
- INSERM Clinical Investigation Center 1425, 75018 Paris, France
| | - Marylou Para
- Department of Cardiac Surgery, AP-HP, Hôpital Bichat, 75018 Paris, France
- UFR Paris Nord, Université Paris Cité, 75006 Paris, France
| | - Nicolas Derre
- Department of Anaesthesiology and Surgical Intensive Care, DMU PARABOL, AP-HP, Hôpital Bichat, 75018 Paris, France
| | - Pierre Mutuon
- Service MSI, AP-HP, Hôpital Bichat, 75018 Paris, France
| | - Xavier Duval
- INSERM Clinical Investigation Center 1425, 75018 Paris, France
- UFR Paris Nord, Université Paris Cité, 75006 Paris, France
- Université Paris Cité, INSERM, IAME, F-75018 Paris, France
| | - Nathalie Grall
- Université Paris Cité, INSERM, IAME, F-75018 Paris, France
- Service de Bactériologie, AP-HP, Hôpital Bichat, 75018 Paris, France
| | - Bernard Iung
- UFR Paris Nord, Université Paris Cité, 75006 Paris, France
- Cardiology Department, AP-HP, Bichat Hospital, Université Paris Cite, INSERM 1148, 46 Rue Henri Huchard, 75018 Paris, France
| | - Solen Kernéis
- UFR Paris Nord, Université Paris Cité, 75006 Paris, France
- Université Paris Cité, INSERM, IAME, F-75018 Paris, France
- Equipe de Prévention du Risque Infectieux (EPRI), AP-HP, Hôpital Bichat, 75018 Paris, France
| | - Jean-Christophe Lucet
- UFR Paris Nord, Université Paris Cité, 75006 Paris, France
- Université Paris Cité, INSERM, IAME, F-75018 Paris, France
- Equipe de Prévention du Risque Infectieux (EPRI), AP-HP, Hôpital Bichat, 75018 Paris, France
| | - Philippe Montravers
- Department of Anaesthesiology and Surgical Intensive Care, DMU PARABOL, AP-HP, Hôpital Bichat, 75018 Paris, France
- UFR Paris Nord, Université Paris Cité, 75006 Paris, France
- Université Paris Cité, Physiopathologie et Epidémiologie des Maladies Respiratoires, INSERM UMR 1152, F-75018 Paris, France
| |
Collapse
|
18
|
Noninterventional studies in the COVID-19 era: methodological considerations for study design and analysis. J Clin Epidemiol 2023; 153:91-101. [PMID: 36400263 PMCID: PMC9671552 DOI: 10.1016/j.jclinepi.2022.11.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2022] [Revised: 10/27/2022] [Accepted: 11/09/2022] [Indexed: 11/19/2022]
Abstract
The global COVID-19 pandemic has generated enormous morbidity and mortality, as well as large health system disruptions including changes in use of prescription medications, outpatient encounters, emergency department admissions, and hospitalizations. These pandemic-related disruptions are reflected in real-world data derived from electronic medical records, administrative claims, disease or medication registries, and mobile devices. We discuss how pandemic-related disruptions in healthcare utilization may impact the conduct of noninterventional studies designed to characterize the utilization and estimate the effects of medical interventions on health-related outcomes. Using hypothetical studies, we highlight consequences that the pandemic may have on study design elements including participant selection and ascertainment of exposures, outcomes, and covariates. We discuss the implications of these pandemic-related disruptions on possible threats to external validity (participant selection) and internal validity (for example, confounding, selection bias, missing data bias). These concerns may be amplified in populations disproportionately impacted by COVID-19, such as racial/ethnic minorities, rural residents, or people experiencing poverty. We propose a general framework for researchers to carefully consider during the design and analysis of noninterventional studies that use real-world data from the COVID-19 era.
Collapse
|
19
|
Wu X, Mealli F, Kioumourtzoglou MA, Dominici F, Braun D. Matching on Generalized Propensity Scores with Continuous Exposures. J Am Stat Assoc 2022; 119:757-772. [PMID: 38524247 PMCID: PMC10958667 DOI: 10.1080/01621459.2022.2144737] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2020] [Accepted: 10/30/2022] [Indexed: 11/09/2022]
Abstract
In the context of a binary treatment, matching is a well-established approach in causal inference. However, in the context of a continuous treatment or exposure, matching is still underdeveloped. We propose an innovative matching approach to estimate an average causal exposure-response function under the setting of continuous exposures that relies on the generalized propensity score (GPS). Our approach maintains the following attractive features of matching: a) clear separation between the design and the analysis; b) robustness to model misspecification or to the presence of extreme values of the estimated GPS; c) straightforward assessments of covariate balance. We first introduce an assumption of identifiability, called local weak unconfoundedness. Under this assumption and mild smoothness conditions, we provide theoretical guarantees that our proposed matching estimator attains point-wise consistency and asymptotic normality. In simulations, our proposed matching approach outperforms existing methods under settings with model misspecification or in the presence of extreme values of the estimated GPS. We apply our proposed method to estimate the average causal exposure-response function between long-term PM2.5 exposure and all-cause mortality among 68.5 million Medicare enrollees, 2000-2016. We found strong evidence of a harmful effect of long-term PM2.5 exposure on mortality. Code for the proposed matching approach is provided in the CausalGPS R package, which is available on CRAN and provides a computationally efficient implementation.
Collapse
Affiliation(s)
- Xiao Wu
- Department of Biostatistics, Mailman School of Public Health, Columbia University
| | - Fabrizia Mealli
- Department of Statistics, Informatics, Applications and Florence Center for Data Science, University of Florence
- Department of Economics, European University Institute
| | | | | | - Danielle Braun
- Department of Biostatistics, Harvard T.H. Chan School of Public Health
| |
Collapse
|
20
|
Chang T, Stuart EA. Propensity score methods for observational studies with clustered data: A review. Stat Med 2022; 41:3612-3626. [PMID: 35603766 PMCID: PMC9540428 DOI: 10.1002/sim.9437] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Revised: 04/20/2022] [Accepted: 05/01/2022] [Indexed: 12/04/2022]
Abstract
Propensity score methods are a popular approach to mitigating confounding bias when estimating causal effects in observational studies. When study units are clustered (eg, patients nested within health systems), additional challenges arise such as accounting for unmeasured confounding at multiple levels and dependence between units within the same cluster. While clustered observational data are widely used to draw causal inferences in many fields, including medicine and healthcare, extensions of propensity score methods to clustered settings are still a relatively new area of research. This article presents a framework for estimating causal effects using propensity scores when study units are nested within clusters and are nonrandomly assigned to treatment conditions. We emphasize the need for investigators to examine the nature of the clustering, among other properties, of the observational data at hand in order to guide their choice of causal estimands and the corresponding propensity score approach.
Collapse
Affiliation(s)
- Ting‐Hsuan Chang
- Department of Epidemiology Johns Hopkins Bloomberg School of Public Health Baltimore Maryland USA
| | - Elizabeth A. Stuart
- Department of Mental Health Johns Hopkins Bloomberg School of Public Health Baltimore Maryland USA
- Department of Biostatistics Johns Hopkins Bloomberg School of Public Health Baltimore Maryland USA
- Department of Health Policy and Management Johns Hopkins Bloomberg School of Public Health Baltimore Maryland USA
| |
Collapse
|
21
|
Marsden AM, Dixon WG, Dunn G, Emsley R. The impact of moderator by confounder interactions in the assessment of treatment effect modification: a simulation study. BMC Med Res Methodol 2022; 22:88. [PMID: 35369866 PMCID: PMC8978434 DOI: 10.1186/s12874-022-01519-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Accepted: 01/11/2022] [Indexed: 12/22/2022] Open
Abstract
Background When performed in an observational setting, treatment effect modification analyses should account for all confounding, where possible. Often, such studies only consider confounding between the exposure and outcome. However, there is scope for misspecification of the confounding adjustment when estimating moderation as the effects of the confounders may themselves be influenced by the moderator. The aim of this study was to investigate bias in estimates of treatment effect modification resulting from failure to account for an interaction between a binary moderator and a confounder on either treatment receipt or the outcome, and to assess the performance of different approaches to account for such interactions. Methods The theory behind the reason for bias and factors that impact the magnitude of bias is explained. Monte Carlo simulations were used to assess the performance of different propensity scores adjustment methods and regression adjustment where the adjustment 1) did not account for any moderator-confounder interactions, 2) included moderator-confounder interactions, and 3) was estimated separately in each moderator subgroup. A real-world observational dataset was used to demonstrate this issue. Results Regression adjustment and propensity score covariate adjustment were sensitive to the presence of moderator-confounder interactions on outcome, whilst propensity score weighting and matching were more sensitive to the presence of moderator-confounder interactions on treatment receipt. Including the relevant moderator-confounder interactions in the propensity score (for methods using this) or the outcome model (for regression adjustment) rectified this for all methods except propensity score covariate adjustment. For the latter, subgroup-specific propensity scores were required. Analysis of the real-world dataset showed that accounting for a moderator-confounder interaction can change the estimate of effect modification. Conclusions When estimating treatment effect modification whilst adjusting for confounders, moderator-confounder interactions on outcome or treatment receipt should be accounted for. Supplementary Information The online version contains supplementary material available at 10.1186/s12874-022-01519-7.
Collapse
|
22
|
Wasilewski D, Radke J, Xu R, Raspe M, Trelinska-Finger A, Rosenstock T, Poeser P, Schumann E, Lindner J, Heppner F, Kaul D, Suttorp N, Vajkoczy P, Frost N, Onken J. Effectiveness of Immune Checkpoint Inhibition vs Chemotherapy in Combination With Radiation Therapy Among Patients With Non-Small Cell Lung Cancer and Brain Metastasis Undergoing Neurosurgical Resection. JAMA Netw Open 2022; 5:e229553. [PMID: 35486401 PMCID: PMC9055459 DOI: 10.1001/jamanetworkopen.2022.9553] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
IMPORTANCE Patients with brain metastases from non-small cell lung cancer (NSCLC) have regularly been excluded from prospective clinical trials that include therapy with immune checkpoint inhibitors (ICIs). Clinical data demonstrating benefit with ICIs, specifically following neurosurgical brain metastasis resection, are scarce. OBJECTIVE To evaluate and compare the association of radiation therapy with ICIs vs classic therapy involving radiation therapy and chemotherapy regarding overall survival in a cohort of patients who underwent NSCLC brain metastasis resection. DESIGN, SETTING AND PARTICIPANTS This single-center 1:1 propensity-matched comparative effectiveness study at the largest neurosurgical clinic in Germany included individuals who had undergone craniotomy with brain metastasis resection from January 2010 to December 2021 with histologically confirmed NSCLC. Of 1690 patients with lung cancer and brain metastasis, 480 were included in the study. Key exclusion criteria were small-cell lung cancer, lack of tumor cells by means of histopathological analysis on brain metastasis resection, and patients who underwent biopsy without tumor resection. The association of overall survival with treatment with radiation therapy and chemotherapy vs radiation therapy and ICI was evaluated. EXPOSURES Radiation therapy and chemotherapy vs radiation therapy and ICI following craniotomy and microsurgical brain metastasis resection. MAIN OUTCOMES AND MEASURES Median overall survival. RESULTS From the whole cohort of patients with NSCLC (N = 384), 215 (56%) were male and 169 (44%) were female. The median (IQR) age was 64 (57-72) years. The 2 cohorts of interest included 108 patients (31%) with radiation therapy and chemotherapy and 63 patients (16%) with radiation therapy and ICI following neurosurgical metastasis removal (before matching). Median (IQR) follow-up time for the total cohort was 47.9 (28.2-70.1) months with 89 patients (23%) being censored and 295 (77%) dead at the end of follow-up in December 2021. After covariate equalization using propensity score matching (62 patients per group), patients receiving radiation therapy and chemotherapy after neurosurgery had significantly lower overall survival (11.8 months; 95% CI; 9.1-15.2) compared with patients with radiation therapy and ICIs (23.0 months; 95% CI; 20.3-53.8) (P < .001). CONCLUSIONS AND RELEVANCE Patients with NSCLC brain metastases undergoing neurosurgical resection had longer overall survival when treated with radiation therapy and ICIs following neurosurgery compared with those receiving platinum-based chemotherapy and radiation. Radiation and systemic immunotherapy should be regularly evaluated as a treatment option for these patients.
Collapse
Affiliation(s)
- David Wasilewski
- Department of Neurosurgery, Charité – Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Josefine Radke
- Department of Neuropathology, Charité – Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
- German Cancer Consortium, Heidelberg, Berlin, Germany
- Berlin Institute of Health at Charité – Universitätsmedizin Berlin, Berlin, Germany
| | - Ran Xu
- Department of Neurosurgery, Charité – Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
- Berlin Institute of Health at Charité – Universitätsmedizin Berlin, Berlin, Germany
| | - Matthias Raspe
- Department of Infectious Diseases and Pulmonary Medicine, Charité – Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Anna Trelinska-Finger
- Berlin Institute of Health at Charité – Universitätsmedizin Berlin, Berlin, Germany
- Charité Comprehensive Cancer Center – Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Tizian Rosenstock
- Department of Neurosurgery, Charité – Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
- Berlin Institute of Health at Charité – Universitätsmedizin Berlin, Berlin, Germany
| | - Paul Poeser
- Department of Neurosurgery, Charité – Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Elisa Schumann
- Department of Neuropathology, Charité – Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Judith Lindner
- Department of Pathology, Charité – Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Frank Heppner
- Department of Neuropathology, Charité – Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - David Kaul
- Department of Radiation Oncology, Charité – Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Norbert Suttorp
- Department of Infectious Diseases and Pulmonary Medicine, Charité – Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Peter Vajkoczy
- Department of Neurosurgery, Charité – Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Nikolaj Frost
- German Cancer Consortium, Heidelberg, Berlin, Germany
| | - Julia Onken
- Department of Neurosurgery, Charité – Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
- Department of Infectious Diseases and Pulmonary Medicine, Charité – Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| |
Collapse
|
23
|
Considerations for Transgender Population Health Research Based on US National Surveys. Ann Epidemiol 2021; 65:65-71. [PMID: 34757013 DOI: 10.1016/j.annepidem.2021.10.009] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Revised: 09/24/2021] [Accepted: 10/22/2021] [Indexed: 11/23/2022]
Abstract
Transgender identities and health are highly politicized in the United States leading to restrictions on relevant data collection in national health surveillance systems. This has serious implications on transgender population health research; an urgent area of study given the systemic discrimination faced by transgender individuals and the resultant social and health inequities. In this precarious political climate, obtaining high-quality data for research is challenging and in recent years, two data sources have formed the foundation of transgender health research in the United States, namely the 2015 United States Transgender Study and the Behavioral Risk Factor Surveillance System (BRFSS) after the launch of the optional Sexual Orientation and Gender Identity Module in 2014. While useful, there are serious challenges to using these data to study transgender health, specifically related to survey weighting methodologies, ascertainment of gender identity, and study design. In this article, we detail these challenges and discuss the strengths and weaknesses of various methodological approaches that have been implemented as well as clarify several common errors that exist in the literature. We feel that this contribution is necessary to provide accurate interpretation of the evidence that currently informs policy and priority setting for transgender population health and will provide vital insights for future studies with these now ubiquitous sources of data in the field.
Collapse
|