Department of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialties "G. D'Alessandro", Geriatric Unit, University Hospital Policlinic Paolo Giaccone, 90100 Palermo, Sicilia, Italy.
Faculty of Medicine and Surgery, "Kore" University of Enna, 94100 Enna, Italy.
Age Ageing. 2024 Aug 6;53(8). doi: 10.1093/ageing/afae187.
Recurrent falls are observed frequently among older people, and they are responsible for significant morbidity and mortality. The aim of the present study was to verify sensitivity, specificity and accuracy of World Guidelines for Falls Prevention and Management (WGFPM) falls risk stratification algorithm using data from the Osteoarthritis Initiative (OAI).
Participants aged between 40 and 80 years were stratified as 'low risk', 'intermediate risk' or 'high risk' as per WGFPM stratification. Data from the OAI cohort study were used, a multi-centre, longitudinal, observational study focusing primarily on knee osteoarthritis. The assessment of the outcome was carried out at baseline and during the follow-up visit at 24 months. Data about sensitivity, specificity and accuracy were reported.
Totally, 4796 participants were initially included. Participants were aged a mean of 61.4 years (SD = 9.1) and were predominantly women (58.0%). The population was divided into three groups: low risk (n = 3266; 82%), intermediate risk (n = 25; 0.6%) and high risk (n = 690; 17.3%). WGFPM algorithm applied to OAI, excluding the intermediate-risk group, produced a sensitivity score of 33.7% and specificity of 89.9% for predicting one or more falls, with an accuracy of 72.4%.
In our study, WGFPM risk assessment algorithm successfully distinguished older people at greater risk of falling using the opportunistic case finding method with a good specificity, but limited sensitivity, of WGFPM falls risk stratification algorithm.
老年人经常会出现反复跌倒的情况，这会导致严重的发病率和死亡率。本研究旨在通过骨关节炎倡议（OAI）的数据来验证世界跌倒预防和管理指南（WGFPM）跌倒风险分层算法的敏感性、特异性和准确性。
根据 WGFPM 分层标准，将年龄在 40 至 80 岁之间的参与者分为“低风险”、“中风险”或“高风险”。本研究使用了 OAI 队列研究的数据，该研究是一项多中心、纵向、观察性研究，主要关注膝骨关节炎。结局评估在基线和 24 个月的随访时进行。报告了敏感性、特异性和准确性的数据。
共纳入 4796 名参与者。参与者的平均年龄为 61.4 岁（标准差=9.1），且主要为女性（58.0%）。人群分为三组：低风险（n=3266；82%）、中风险（n=25；0.6%）和高风险（n=690；17.3%）。WGFPM 算法应用于 OAI，排除中风险组后，预测一次或多次跌倒的敏感性评分为 33.7%，特异性为 89.9%，准确性为 72.4%。
在我们的研究中，WGFPM 风险评估算法使用机会性病例发现方法成功区分了跌倒风险较高的老年人，特异性较好，但敏感性有限。WGFPM 跌倒风险分层算法。
