Observational studyAge and ageing2024
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.
Observational study in Age and ageing, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Validation of the World Falls Guidelines risk stratification algorithm. A systematic review.Age and ageing · 2026Pooled it
- Fall risk assessment using the World Guidelines for Falls Prevention Algorithm: Evidence from the ELSI-Brazil study.European geriatric medicine · 2026Article
- Falls prevention in community-dwelling older adults and implementation of world falls guidelines: a call for action across Europe by the European Geriatric Medicine Society Special Interest Group on Falls and Fractures.European geriatric medicine · 2025Article
- Associations Between Adherence to the Mediterranean Diet and Incident Sarcopenia in Prospective Cohort Studies.Nutrients · 2025Review
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionRecurrent 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).
methodsParticipants 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.
resultsTotally, 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%.
conclusionIn 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.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.