Predicting Falls Using the Stroke Assessment of Fall Risk Tool

Area of Science:

• Neurology
• Rehabilitation Medicine
• Gerontology

Background:

• Falls are a significant issue in inpatient stroke populations, leading to increased morbidity and delayed rehabilitation.
• Existing fall screening tools often lack assessment of stroke-specific neurologic deficits, which contribute to fall risk.

Purpose of the Study:

• To compare the predictive accuracy of the Stroke Assessment of Fall Risk (SAFR) tool against the Morse Fall Scale for inpatient falls.
• To determine if SAFR's inclusion of stroke-specific neurologic deficits enhances fall prediction compared to the non-neurologic Morse Scale.

Main Methods:

• A prospective cohort study was conducted with 220 acute stroke patients in a tertiary stroke rehabilitation unit.
• Falls were tracked, and logistic regression analysis was used to compare the predictive abilities (sensitivity, specificity, AUC-ROC, OR) of SAFR and the Morse Fall Scale.
• T-tests compared mean scores of both tools between patients who fell and those who did not.

Main Results:

• Of 220 patients, 48 (21.8%) experienced at least one fall.
• SAFR scores significantly differed between fallers and non-fallers (P=.001), unlike Morse scores (P=.24).
• Higher SAFR scores correlated with increased fall odds (OR 1.36), and SAFR showed better discrimination (AUC-ROC 0.65 vs. 0.56 for Morse).

Conclusions:

• The SAFR tool demonstrates a significant association with fall risk and superior discrimination between fallers and non-fallers compared to the Morse Fall Scale.
• The neurologic-specific hemi-neglect component within SAFR was identified as a fall risk factor, underscoring the value of assessing such deficits.
• Further investigation into fall prediction scales incorporating neurologic deficits is warranted to improve fall prevention strategies in stroke patients.