The role of the World Guidelines for Falls Prevention and Management's risk stratification algorithm in predicting falls: a retrospective analysis of the Osteoarthritis Initiative

Abstract

Introduction: 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).

Methods: 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.

Results: 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%.

Conclusion: 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.

Keywords: algorithm; fall; older people; osteoarthritis; prediction.