Abstract 14021: Brief Composite Mobility Index Predicts Post-Stroke Fallers After Hospital Discharge

Abstract

Introduction: Community-dwelling, ambulatory stroke survivors fall at very high rates in the first 3-6 months. Current inpatient clinical assessments for fall risk have inadequate predictive accuracy. We found that a pre-discharge obstacle-crossing test has excellent specificity (87%) but lacks acceptable sensitivity (67%) for identifying would-be fallers and non-fallers post discharge. Hypothesis: We assessed the hypothesis that combining the obstacle-crossing test with other highly discriminatory mobility factors would compensate for the obstacle-test’s fair sensitivity and yield an instrument with superior prediction accuracy. Methods: 45 ambulatory stroke survivors (60±11 years old, 15±11 days post stroke) being discharged home completed a battery of mobility and dynamic balance performance-based and self-reported measures 1-3 days prior to discharge. After discharge, participants were prospectively followed for 3 months and classified as fallers (≥1 fall) or non-fallers at 3 months. Four pre-discharge measures with the largest effect sizes for differentiating fallers and non-fallers (obstacle-crossing test, Walk-12, 5-meter gait speed, and paretic-limb Step Test score) were combined into a composite index. Results: The composite index significantly differentiated those who subsequently fell (11.1±4.5 points) from non-fallers (4.8±4.1 points, d =1.46, p<0.001). A person with an index discharge score of 11 was 6 times more likely to fall in the first 3-months post discharge than a person with a score of 5. The goodness of fit of the regression model with the composite index was significantly better than the model with only the obstacle-crossing test, χ 2 (1) = 6.036, p=0.014. Furthermore, whereas the obstacle-crossing test had acceptable discrimination (AUC 0.75, 95% CI 0.60-0.90), the composite index had excellent discrimination ability (AUC 0.85, 95% CI 0.74-0.96). Conclusion: Strategic aggregation of performance-based and self-reported mobility measures, including a novel and demanding obstacle-crossing test, can predict post-discharge fallers with excellent accuracy. This brief tool is highly pragmatic for inpatient use and may facilitate identification of high-risk stroke survivors before the first fall.