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Abstract
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INTRODUCTION: Falls in the inpatient stroke population are common, resulting in increased morbidity and slow rehabilitation progress. Falls may result from stroke-specific neurologic deficits, however assessment of these deficits is lacking in many fall screening tools.
OBJECTIVE: To compare the ability of the Stroke Assessment of Fall Risk (SAFR) tool, which includes items related to stroke-specific neurologic deficits, to predict falls to the commonly used Morse Fall Scale, which does not include these items.
DESIGN: Prospective cohort study.
SETTING: Inpatient tertiary stroke rehabilitation unit.
PARTICIPANTS: Patients (N = 220) with acute stroke.
MAIN OUTCOME MEASURES: Falls were captured by the medical records from January 2017 to September 2018. Logistic regression analysis evaluated both screening tools for predicting falls by calculating sensitivity, specificity, area under the receiver operating characteristic (AUC-ROC) curve and odds ratio (OR). We compared SAFR and Morse mean scores between fallers and non-fallers using t-tests.
RESULTS: Forty-eight (21.8%) patients experienced ≥1 fall. SAFR, but not Morse, scores showed a statistically significant difference between fallers and non-fallers (P = 0.001 vs P = 0.24, respectively). Higher SAFR score was associated with higher odds of falls (OR 1.36, 95% CI [1.12, 1.64]), while Morse was not (OR 1.04, 95% CI [0.97, 1.12]). SAFR showed a statistically significant difference in hemi-neglect between fallers and non-fallers (P = 0.03). Sensitivity and specificity of SAFR were 47.9% and 76.7%, vs 45.8% and 68.0% for Morse, respectively. SAFR PPV and NPV were 36.5% and 84.1%, respectively, similar to Morse (28.6% and 81.8%). The AUC-ROC was 0.65 for SAFR, and 0.56 for Morse.
CONCLUSION: SAFR was significantly associated with fall risk and had better discrimination between fallers and non-fallers than Morse. The neurologic-specific hemi-neglect component of SAFR, a component not present on the Morse, was a fall risk factor. Further research evaluating the predictive value of fall scales that include neurologic deficits is needed. This article is protected by copyright. All rights reserved.
Language: en |