{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,10]],"date-time":"2025-11-10T05:10:47Z","timestamp":1762751447958,"version":"build-2065373602"},"reference-count":47,"publisher":"Oxford University Press (OUP)","issue":"12","license":[{"start":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T00:00:00Z","timestamp":1760054400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,11,6]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Hip fractures significantly increase health risks in older adults, yet the evolution of frailty before and after fracture and its impact on mortality remain unclear. This study investigated the relationship between frailty trajectories surrounding hip fractures and subsequent mortality risk.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This population-based cohort study used UK Biobank data with linked hospital and mortality records through 2023, including 4963 participants with hip fractures. Frailty was assessed via the Hospital Frailty Risk Score based on ICD-10 codes. Latent class trajectory analysis modeled frailty trends 12 months before and after fracture. Multinomial logistic regression identified frailty trajectory groups, and Cox models assessed their association with all-cause mortality.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Among 4963 participants (mean age: 70.1 years, 64.6% females), we identified three pre-fracture frailty trajectories: persistently robust (44.2%), moderately frail (37.1%), and progressively frail (18.7%). Frailty remained stable except in the progressively frail group, where scores increased by 28.6% in the year before fracture. Post-fracture, three trajectories emerged: moderate frailty with stability (63.0%), high frailty with stability (30.8%), and rapidly progressive frailty (6.2%). Higher pre-fracture frailty was strongly associated with greater post-fracture frailty. Mortality risk varied significantly across combined pre- and post-fracture frailty trajectories, with the highest risk in those with rapidly progressive frailty post-fracture.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Distinct frailty trajectories before and after hip fracture are associated with differential mortality risk, highlighting the need for routine frailty assessments. Identifying high-risk individuals may facilitate targeted interventions to improve recovery and survival in patients with hip fractures.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/gerona\/glaf226","type":"journal-article","created":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T12:10:40Z","timestamp":1760011840000},"source":"Crossref","is-referenced-by-count":0,"title":["Understanding frailty changes surrounding hip fracture"],"prefix":"10.1093","volume":"80","author":[{"given":"Jianhong","family":"Xu","sequence":"first","affiliation":[{"name":"Global Health Research Center, Duke Kunshan University , Kunshan, Jiangsu,","place":["China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanxin","family":"Wang","sequence":"additional","affiliation":[{"name":"Global Health Research Center, Duke Kunshan University , Kunshan, 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