{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T05:01:04Z","timestamp":1790830864182,"version":"4.1.0"},"reference-count":41,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Med."],"abstract":"<jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>To develop and internally validate a frailty screening model for older adults with cataract that relies only on information already collected during routine ophthalmology outpatient assessment.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      In this cross-sectional study, 516 patients aged \u2265 60 years were enrolled and randomly divided into training (n\u2009=\u2009361) and internal validation (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u2009155) sets. Frailty was defined by the FRAIL scale, with non-frail and pre-frail categories combined for the primary binary analysis. Univariate screening was followed by multivariable binary logistic regression, with LASSO and a 5,000-resample bootstrap of the full development procedure as stability checks.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The frailty detection rate was 29.07%. Five factors were independently associated with frailty: advanced age, IADL impairment, poor self-rated health, depression, and history of falls. Discrimination was good (training AUC 0.841, 95% CI 0.796\u20130.887; validation AUC 0.816, 95% CI 0.745\u20130.888), the optimism-corrected C-statistic was 0.810 (95% CI 0.780\u20130.841), and calibration was acceptable (validation Brier score 0.1553). Decision curve analysis showed positive net benefit across a broad threshold range. Lowering the operating point from the Youden cutoff (0.463; sensitivity 57.8%, specificity 86.4%) to 0.181 raised validation sensitivity to 86.7% with a negative predictive value of 92.1%.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Because all five predictors are already recorded during routine cataract assessment, the model offers an opportunistic, zero-burden triage step for identifying concurrent frailty and prompting comprehensive geriatric assessment. External validation and comparison with the FRAIL scale are required.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fmed.2026.1934999","type":"journal-article","created":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T04:41:02Z","timestamp":1790829662000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Construction and validation of a frailty screening model for older adults with cataract: a cross-sectional study"],"prefix":"10.3389","volume":"13","author":[{"given":"Xingdong","family":"Cheng","sequence":"first","affiliation":[{"name":"Department of Nursing, Affiliated Hospital of Zunyi Medical University","place":["Zunyi, Guizhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Heting","family":"Liang","sequence":"additional","affiliation":[{"name":"Department of Nursing, Affiliated Hospital of Zunyi Medical University","place":["Zunyi, Guizhou, 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