{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,30]],"date-time":"2026-10-30T22:00:05Z","timestamp":1793397605616,"version":"4.5.0"},"reference-count":60,"publisher":"American Medical Association (AMA)","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JAMA Netw Open"],"abstract":"\n Importance<\/jats:title>\n People with HIV experience higher rates of frailty and falls than age-matched people without HIV.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n To estimate the life-years lost, quality-adjusted life-years (QALYs) lost, and costs attributable to prefrailty, frailty, and falls among people with HIV and viral suppression in the United States.<\/jats:p>\n <\/jats:sec>\n \n Design, Setting, and Participants<\/jats:title>\n This decision analytic modeling study used the Frailty Policy Model, a microsimulation model, to project lifetime health and cost outcomes associated with frailty and falls among people with HIV in the United States. The model simulated individuals representing people with HIV and viral suppression in the United States aged 40 years and older in 2022, and results were scaled to the estimated population size of 521\u202f994 individuals. Simulation model parameters were drawn from the Advancing Clinical Therapeutics Globally (ACTG) A5322 Study, the Multicenter AIDS Cohort Study (MACS)\/Women\u2019s Interagency HIV Study (WIHS) Combined Cohort Study, and published literature. Data analysis was conducted from November 2023 to October 2025.<\/jats:p>\n <\/jats:sec>\n \n Exposures<\/jats:title>\n Prefrailty, frailty, and falls.<\/jats:p>\n <\/jats:sec>\n \n Main Outcomes and Measures<\/jats:title>\n Life-years lost, QALYs lost, and costs attributable to prefrailty, frailty, and falls.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n The simulated individuals representing people with HIV and viral suppression had a mean (SD) age of 56 (10) years; 25% were female; 41% had prefrailty, and 7% had frailty. The model projected that the simulated individuals would have a remaining life expectancy of 20.3 (95% uncertainty interval [UI], 19.7-20.8) years, with a mean of 12.0 (95% UI, 11.2-12.8) years with prefrailty or frailty and 10.1 (95% UI, 8.2-12.1) falls per person. Scaled to the population level, the model projected that there would be 31\u202f000 (95% UI, 16\u202f000-57\u202f000) life-years lost, 214\u202f000 (95% UI, 130\u202f000-292\u202f000) QALYs lost, and $5.0 (95% UI, $3.2-$7.2) billion in lifetime costs attributable to prefrailty. There would be 1\u202f352\u202f000 (95% UI, 84\u202f000-3\u202f336\u202f000) life-years lost, 1\u202f091\u202f000 (95% UI, 209\u202f000-2\u202f500\u202f000) QALYs lost, and $8.8 (95% UI, $4.7-$14.2) billion in lifetime costs attributable to frailty. There would be 183\u202f000 (95% UI, 120\u202f000-266\u202f000) life-years lost, 141\u202f000 (95% UI, 94\u202f000-198\u202f000) QALYs lost, and $3.4 (95% UI, $2.2-$4.8) billion attributable to falls.<\/jats:p>\n <\/jats:sec>\n \n Conclusions and Relevance<\/jats:title>\n In this decision analytic modeling study of frailty and falls among people with HIV and viral suppression, the lifetime QALYs lost and costs attributable to frailty and falls were substantial. These findings highlight the potential clinical and economic benefits that could result from interventions to identify, prevent, and treat frailty and falls among people with HIV.<\/jats:p>\n <\/jats:sec>","DOI":"10.1001\/jamanetworkopen.2025.54809","type":"journal-article","created":{"date-parts":[[2026,1,21]],"date-time":"2026-01-21T16:00:25Z","timestamp":1769011225000},"page":"e2554809","source":"Crossref","is-referenced-by-count":1,"title":["Modeled Health and Economic Burden of Frailty and Falls Among Adults With HIV"],"prefix":"10.1001","volume":"9","author":[{"given":"Karen C.","family":"Smith","sequence":"first","affiliation":[{"name":"Orthopedic and Arthritis Center for Outcomes Research (OrACORe), Department of Orthopedic Surgery, Brigham and Women\u2019s Hospital, Boston, Massachusetts"},{"name":"Harvard Medical School, Boston, 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