Clinical prediction rules for multi surfaces walking independence using the Berg Balance Scale or Mini-Balance Evaluation Systems Test in persons with stroke

Abstract

ABSTRACT Background A Clinical prediction rule (CPR) for determining multi surfaces walking independence in persons with stroke has not been established. Objectives To develop a CPR for determining multi surfaces walking independence in persons with stroke. Methods This was a multicenter retrospective analysis of 419 persons with stroke. We developed a Berg Balance Scale (BBS)-model CPR combining the BBS, comfortable walking speed (CWS) and cognitive impairment, and a Mini-Balance Evaluation Systems Test (Mini-BESTest)-model CPR combining the Mini-BESTest, CWS, and cognitive impairment. A logistic regression analysis was conducted with multi surfaces walking independence as the dependent variable and each factor as an independent variable. The identified factors were scored (0, 1) based on reported cutoff values. The CPR’s accuracy was verified by the area under the curve (AUC). We used a bootstrap method internal validation and calculated the CPR’s posttest probability. Results The logistic regression analysis showed that the BBS, CWS, and cognitive impairment were factors in the BBS model, and the Mini-BESTest was a factor in the Mini-BESTest model. The CPRs were 0–3 points for the BBS model and 0–1 points for the Mini-BESTest model. The AUCs (bootstrap mean AUC) of the CPR score were 0.89 (0.90) for the BBS model and 0.72 (0.72) for the Mini-BESTest model. The negative predictive value (negative likelihood ratio) was 97% (0.054) for CPR scores < 2 for the BBS model and 94% (0.060) for CPR scores < 1 for the Mini-BESTest model. Conclusions The CPR developed herein is useful for determining multi surfaces walking independence.