{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,13]],"date-time":"2026-06-13T06:55:55Z","timestamp":1781333755514,"version":"3.54.1"},"reference-count":53,"publisher":"Cambridge University Press (CUP)","issue":"02","content-domain":{"domain":["www.cambridge.org"],"crossmark-restriction":true},"short-container-title":["Prim Health Care Res Dev"],"published-print":{"date-parts":[[2018,3]]},"abstract":"<jats:sec id=\"S146342361700055X_abs1\" sec-type=\"general\">\n               <jats:title>Aim<\/jats:title>\n               <jats:p>To evaluate the possibility of determining predictors of falls in the active community-dwelling elderly from the routine medical records of the general practitioners (GPs).<\/jats:p>\n            <\/jats:sec>\n            <jats:sec id=\"S146342361700055X_abs2\" sec-type=\"general\">\n               <jats:title>Background<\/jats:title>\n               <jats:p>Time constraints and competing demands in the clinical encounters frequently undermine fall-risk evaluation. In the context of proactive primary healthcare, quick, and efficient tools for a preliminary fall-risk assessment are needed in order to overcome these barriers.<\/jats:p>\n            <\/jats:sec>\n            <jats:sec id=\"S146342361700055X_abs3\" sec-type=\"methods\">\n               <jats:title>Methods<\/jats:title>\n               <jats:p>The study included 1220 subjects of 65 years of age or older. Data were extracted from the GPs\u2019 patient records. For each subject, the following variables were considered: age, gender, diseases, and pharmacotherapy. Univariate and multivariable analyses have been conducted to identify the independent predictors of falls.<\/jats:p>\n            <\/jats:sec>\n            <jats:sec id=\"S146342361700055X_abs4\" sec-type=\"general\">\n               <jats:title>Findings<\/jats:title>\n               <jats:p>The mean age of the study population was 77.8\u00b18.7 years for women and 74.9\u00b17.3 years for men. Of the sample, 11.6% had experienced one or more falls in the previous year. The risk of falling was found to increase significantly (<jats:italic>P<\/jats:italic>&amp;lt;0.05) with age (OR=1.03; 95% CI=1.01\u20131.05), generalized osteoarthritis (OR=2.01; 95% CI=1.23\u20133.30), tinnitus (OR=4.14; 95% CI=1.25\u201313.74), cognitive impairment (OR=4.12; 95% CI=2.18\u20137.80), and two or more co-existing diseases (OR=5.4; 95% CI=1.68\u201317.39). Results suggest that it is possible to identify patients at higher risk of falling by going through the current medical records, without adding extra workload on the health personnel. In the context of proactive primary healthcare, the analysis of fall predictors from routine medical records may allow the identification of which of the several known and hypothesized risk factors may be more relevant for developing quick and efficient tools for a preliminary fall-risk assessment.<\/jats:p>\n            <\/jats:sec>","DOI":"10.1017\/s146342361700055x","type":"journal-article","created":{"date-parts":[[2017,9,5]],"date-time":"2017-09-05T06:18:29Z","timestamp":1504592309000},"page":"131-139","update-policy":"https:\/\/doi.org\/10.1017\/policypage","source":"Crossref","is-referenced-by-count":16,"title":["Identification of fall predictors in the active elderly population from the routine medical records of general 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