{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,2]],"date-time":"2026-02-02T16:25:14Z","timestamp":1770049514881,"version":"3.49.0"},"reference-count":44,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2025,12,4]],"date-time":"2025-12-04T00:00:00Z","timestamp":1764806400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"funder":[{"DOI":"10.13039\/100000049","name":"NIA","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000049","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,1,12]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>The Veterans Affairs Frailty Index (VA-FI) has been implemented in subgroups of U.S. Veterans. The objectives were to operationalize the VA-FI in long-term care residents and examine its associations with mortality, falls, and fractures.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This retrospective cohort study included Veterans \u226565\u2009years who stayed \u226590\u2009days in Community Living Centers (CLCs). We calculated the VA-FI by dividing the count of health deficits by 31. We categorized the residents in 4 groups: non\/pre-frail, mildly, moderately and severely frail. Mortality, the first events of falls and fractures were examined with a 1-year follow-up. Cox regression and Fine-Gray competing-risk models were fit to assess associations between frailty and outcomes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Among 45 183 CLC residents, 12.2% were non\/pre-frail, 24.2%, 28.8%, and 34.8% were mildly, moderately and severely frail. With increasing frailty severity, rates of mortality, falls and fractures ranged respectively from 65.3 to 59.0, 13.1 to 18.8, and 1.9 to 2.2 per 100 person-years. Relative to the non\/pre-frail, residents with mild, moderate and severe frailty had lower rates of death (HRs [95% CIs]: 0.88 [0.84-0.92], 0.87 [0.83-0.91], 0.90 [0.85-0.94]), higher rates of falls (SHRs [95% CI]: 1.26 [1.10-1.43], 1.32 [1.17-1.50], 1.29 [1.14-1.46]) and fractures (1.29 [0.92-1.81], 1.47 [1.06-2.04], 1.45 [1.04-2.02]).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Frailty was highly prevalent in Veterans receiving long-term care in CLCs and was associated with higher rates of falls and fractures. Frail residents had a lower rate of mortality compared with their non\/pre-frail counterparts. Length of stay, confounded by unobserved factors, and collider bias could potentially serve as explanations for this counterintuitive finding.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/gerona\/glaf263","type":"journal-article","created":{"date-parts":[[2025,12,3]],"date-time":"2025-12-03T13:19:02Z","timestamp":1764767942000},"source":"Crossref","is-referenced-by-count":0,"title":["Frailty and outcomes in VA long-term care residents"],"prefix":"10.1093","volume":"81","author":[{"given":"Yongmei","family":"Li","sequence":"first","affiliation":[{"name":"Department of Epidemiology and Population Health, Stanford University , Stanford, California,","place":["United States"]},{"name":"Geriatric Research Education and Clinical Center, VA Palo Alto Health Care System , Palo Alto, California,","place":["United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9564-9480","authenticated-orcid":false,"given":"Michael 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A","family":"Graham","sequence":"additional","affiliation":[{"name":"Health Economics Resource Center, VA Palo Alto Health Care System , Palo Alto, California,","place":["United States"]},{"name":"Stanford-Surgery Policy Improvement Research and Education (S-SPIRE) Center, Department of Surgery, Stanford University , Stanford, California,","place":["United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bocheng","family":"Jing","sequence":"additional","affiliation":[{"name":"Department of Epidemiology and Population Health, Stanford University , Stanford, California,","place":["United States"]},{"name":"Division of Geriatrics, Department of Medicine, University of California San Francisco , San Francisco, California,","place":["United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chintan","family":"Dave","sequence":"additional","affiliation":[{"name":"Center for Pharmacoepidemiology and Treatment Science, Institute for Health, Health Care Policy and Aging Research, Rutgers University , New Brunswick, New Jersey,","place":["United States"]},{"name":"Center for Health Outcomes, Policy, and Economics, Ernest Mario College of Pharmacy, Rutgers University , Piscataway, New Jersey,","place":["United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaojuan","family":"Liu","sequence":"additional","affiliation":[{"name":"Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women\u2019s Hospital, Harvard Medical School , Boston, Massachusetts,","place":["United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6592-7550","authenticated-orcid":false,"given":"Christine K","family":"Liu","sequence":"additional","affiliation":[{"name":"Geriatric Research Education and Clinical Center, VA Palo Alto Health Care System , Palo Alto, California,","place":["United States"]},{"name":"Section of Geriatrics, Division of 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