Objectives: This study aimed to cross-validate a previously developed knee osteoarthritis falls (KOAF) screening tool to distinguish between fallers and nonfallers among community-dwelling older adults with knee osteoarthritis (OA).
Design: Cross-sectional survey study.
Setting: Three independent orthopedic clinics.
Participants: Older outpatients with knee OA (N=86; 71 women, 15 men; mean age, 75.2±6.2y).
Interventions: Not applicable.
Main Outcome Measures: The primary outcome was to identify fallers and nonfallers among outpatients with OA based on their history of falls within the past year. We investigated factors including sex, age, body mass index, Kellgren-Lawrence grade, affected side (bilateral or unilateral knee OA), number of comorbidities, pharmacotherapy, physical therapy, pain, and activity as individual predictors of falls. Participants performed the one-leg standing test and the 5 times sit-to-stand test to determine motor function. Sensitivity, specificity, likelihood ratio, and post-test probability of the KOAF screening tool were calculated using receiver operating characteristic (ROC) curve analysis.
Results: The results of the one-leg standing test and 5 times sit-to-stand test differed significantly between the 2 groups (P<.05). ROC curve analysis showed that the area under the curve was 0.88 (95% confidence interval, 0.80-0.96; P<.001). The post-test probability of falls was 83.3% (positive likelihood ratio, 11.54) when the total score of KOAF screening tool was 2 points and 2.6% (negative likelihood ratio, 0.06) when the total score of KOAF screening tool was less than 1 point.
Conclusions: Cross-validation results for the KOAF screening tool were better, confirming that the screening tool could distinguish between fallers and nonfallers with high accuracy. Our findings suggest that this simple screening tool could be readily used in clinical practice and could aid in clinical decision-making through providing choices for physical therapy evaluation and recommendations for physical therapy programs.
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http://dx.doi.org/10.1016/j.apmr.2020.12.001 | DOI Listing |
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