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Validation of the World Falls Guidelines risk stratification algorithm. A systematic review
Frederico Pieruccini-Faria1,2, Surim Son3,4, Kim Delbaere5,6
1Department of Medicine, Division of Geriatric Medicine, Schulich School of Medicine & Dentistry, Western University, 1151 Richmond Street, London, Ontario N6C 3K7, Canada.
Background:
Falls are a major cause of morbidity and mortality in older adults. The World Falls Guidelines (WFG) propose a risk stratification algorithm using fall history, three key questions (3KQ), mobility tests and clinical criteria, but it has yet to be systematically evaluated.
Objective:
To assess whether the WFG algorithm, in original or modified form, effectively stratifies community-dwelling older adults into low, intermediate or high risk of future falls; whether it has been prospectively validated; and whether it has been adequately operationalised.
Methods:
We conducted a systematic review (PROSPERO CRD420251151506) by searching MEDLINE, Embase and Google Scholar. Two reviewers independently screened studies and extracted data on cohort characteristics, algorithm adaptations, baseline risk distribution and prospective falls outcomes over ≥6 months. Given the heterogeneity of the studies included, quantitative meta-analysis was not conducted.
Results:
Eight cohort studies (n = 25 027; mean age range 61-82 years) met the inclusion criteria. No study implemented the WFG algorithm as published; two used minor modifications and six had major adaptations due to dataset limitations. Common modifications included rephrasing the 3KQ, replacing 'subjective unsteadiness' question with objective measures, applying mobility test universally, adjusting mobility tests thresholds and omitting fall severity definition components. Across studies, 7.9%-82.6% of participants were classified as low risk, 0.4%-18.3% as intermediate risk and 10.5%-88.7% as high risk. High-risk classification showed modest sensitivity (26.5%-52.3%) and moderate-to-high specificity (34.2%-88.9%) for future falls (1-2 years), with an overall accuracy of 61.2%-74.2%. High-risk groups consistently had a two- to three-fold higher incidence of falls than low-risk groups, while intermediate-risk groups only showed a slightly elevated risk. Use of 3KQ alongside fall history and universal mobility testing improved discrimination and increased the proportion in the intermediate-risk category.
Conclusion:
The operationalised versions of the WFG algorithm identify older adults at high falls risk with high specificity but limited sensitivity. Proposed pragmatic modifications improve stratification accuracy for intermediate risk group but require prospective validation.
