Development and internal validation of two prediction models of walking dependence and restricted walking speed in individuals with subacute stroke

Abstract

Abstract Background The prognosis of the walking ability of individuals with stroke affects the choice of rehabilitation program. Identifying patients who will need assistance with ambulation at discharge allows clinicians to deliver rehabilitation programs focused on educating caregivers and adjusting the patient’s environment to allow safe transfer within the home. The primary objective of this study was to develop and internally validate a prediction model of walking dependence for patients with stroke admitted to a rehabilitation facility. The secondary objective was to establish a prediction model of restricted walking speed. Methods This retrospective cohort study included 476 individuals with subacute stroke who were admitted to a rehabilitation facility. Model 1 was developed to predict the probability of walking dependence. Model 2 was developed to predict restricted walking speed. Walking dependence was defined as a functional independence measure walk score of 5 or less. Restricted walking speed was defined as the ability to walk at 0.93 m/s or less. Potential predictors, including age, leg strength of the affected side, sitting balance, cognitive function, and urinary function, were selected based on the literature and analyzed using logistic regression analysis. Models were internally validated using the bootstrap method. Model performance was assessed by discrimination (area under the receiver operating characteristic curve (AUC)) and calibration (Hosmer–Lemeshow (H–L) goodness-of-fit test and calibration plots). Results A total of 236 patients (49.6%) walked dependently at discharge. Of the 240 individuals who achieved walking independence, 121 (50.4%) had restricted walking speed. In model 1, older age, poor leg strength, sitting balance, cognitive function, and urinary incontinence were significantly associated with walking dependence at discharge. The AUCs of models 1 and 2 were 0.93 (95% confidence interval (CI) = .90–.95) and 0.69 (95%CI = .62–.76), respectively. Both models had good calibration confirmed by the H-L test. Conclusions The internally validated prediction model of walking dependence had good discrimination and calibration, while the prediction model of restricted walking speed had poor discrimination. The prediction model for walking dependence developed in this study may be useful for planning rehabilitation strategies and setting realistic goals for patients.