Derivation of a clinical prediction rule to determine fall risk in community-dwelling individuals with knee osteoarthritis: a cross-sectional study.

Summary: We derived a clinical prediction rule (CPR) to determine fall risk. The probability of falls increased, with positive likelihood ratio being 17.8 and post-test probability (positive predictive value) being 88.2%, in cases where the CPR score was 2 points. Our CPR could be a useful screening test to detect fall risk probability. Purpose: We aimed to examine the risk factors for falls in individuals with knee osteoarthritis (OA) and derive a clinical prediction rule (CPR) to determine fall risk. Methods: Eighty-one individuals with medial compartment knee OA were included. The outcome was whether the participants had a self-reported fall within the past 1 year of this study being conducted. The collected data included sex, age, body mass index, Kellgren-Lawrence grade, lesion type (bilateral or unilateral knee OA), pain (rated using the visual analog scale), muscle strength test of the quadriceps femoris, one-leg standing test (OLST), five times sit-to-stand test (FTSST), and 5-m walk test, which were used in binomial logistic regression analysis. The outcome measure of the analysis was whether the study participants belonged to a fall or non-fall group. Receiver operating characteristic (ROC) analysis was performed for the outcome measurements, and the factors were selected by binomial logistic regression analysis. Then, a CPR to determine fall risk was extracted, and its diagnostic characteristics were calculated. Results: Binomial logistic regression analysis showed that the OLST and FTSST were significant. ROC analysis showed that the cut-off values of the OLST and FTSST were 5.3 s and 7.9 s, respectively. The post-test probability (positive predictive value) increased to 88.2% (positive likelihood ratio = 17.8) when the OLST and FTSST were both positive (the CPR score was 2 points). Conclusion: The CPR obtained from this study would be useful as a screening test to detect the fall risk probability in individuals with knee OA. [ABSTRACT FROM AUTHOR]