Terry P Breisinger1, Elizabeth R Skidmore2, Christian Niyonkuru3, Lauren Terhorst4, Grace B Campbell5. 1. UPMC Rehabilitation Institute, Pittsburgh, PA, USA Centers for Rehab Services, Pittsburgh, PA, USA breisingertp@upmc.edu. 2. Department of Occupational Therapy, University of Pittsburgh School of Health and Rehabilitation Sciences, Pittsburgh, PA, USA Department of Physical Medicine and Rehabilitation, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA. 3. Department of Physical Medicine and Rehabilitation, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA. 4. Department of Occupational Therapy, University of Pittsburgh School of Health and Rehabilitation Sciences, Pittsburgh, PA, USA. 5. UPMC Rehabilitation Institute, Pittsburgh, PA, USA University of Pittsburgh School of Nursing, Pittsburgh, PA, USA.
Abstract
OBJECTIVE: To evaluate relative accuracy of a newly developed Stroke Assessment of Fall Risk (SAFR) for classifying fallers and non-fallers, compared with a health system fall risk screening tool, the Fall Harm Risk Screen. DESIGN AND SETTING: Prospective quality improvement study conducted at an inpatient stroke rehabilitation unit at a large urban university hospital. PARTICIPANTS: Patients admitted for inpatient stroke rehabilitation (N = 419) with imaging or clinical evidence of ischemic or hemorrhagic stroke, between 1 August 2009 and 31 July 2010. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Sensitivity, specificity, and area under the curve for Receiver Operating Characteristic Curves of both scales' classifications, based on fall risk score completed upon admission to inpatient stroke rehabilitation. RESULTS: A total of 68 (16%) participants fell at least once. The SAFR was significantly more accurate than the Fall Harm Risk Screen (p < 0.001), with area under the curve of 0.73, positive predictive value of 0.29, and negative predictive value of 0.94. For the Fall Harm Risk Screen, area under the curve was 0.56, positive predictive value was 0.19, and negative predictive value was 0.86. Sensitivity and specificity of the SAFR (0.78 and 0.63, respectively) was higher than the Fall Harm Risk Screen (0.57 and 0.48, respectively). CONCLUSIONS: An evidence-derived, population-specific fall risk assessment may more accurately predict fallers than a general fall risk screen for stroke rehabilitation patients. While the SAFR improves upon the accuracy of a general assessment tool, additional refinement may be warranted.
OBJECTIVE: To evaluate relative accuracy of a newly developed Stroke Assessment of Fall Risk (SAFR) for classifying fallers and non-fallers, compared with a health system fall risk screening tool, the Fall Harm Risk Screen. DESIGN AND SETTING: Prospective quality improvement study conducted at an inpatient stroke rehabilitation unit at a large urban university hospital. PARTICIPANTS: Patients admitted for inpatient stroke rehabilitation (N = 419) with imaging or clinical evidence of ischemic or hemorrhagic stroke, between 1 August 2009 and 31 July 2010. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Sensitivity, specificity, and area under the curve for Receiver Operating Characteristic Curves of both scales' classifications, based on fall risk score completed upon admission to inpatient stroke rehabilitation. RESULTS: A total of 68 (16%) participants fell at least once. The SAFR was significantly more accurate than the Fall Harm Risk Screen (p < 0.001), with area under the curve of 0.73, positive predictive value of 0.29, and negative predictive value of 0.94. For the Fall Harm Risk Screen, area under the curve was 0.56, positive predictive value was 0.19, and negative predictive value was 0.86. Sensitivity and specificity of the SAFR (0.78 and 0.63, respectively) was higher than the Fall Harm Risk Screen (0.57 and 0.48, respectively). CONCLUSIONS: An evidence-derived, population-specific fall risk assessment may more accurately predict fallers than a general fall risk screen for stroke rehabilitation patients. While the SAFR improves upon the accuracy of a general assessment tool, additional refinement may be warranted.
Authors: Lesley D Gillespie; M Clare Robertson; William J Gillespie; Catherine Sherrington; Simon Gates; Lindy M Clemson; Sarah E Lamb Journal: Cochrane Database Syst Rev Date: 2012-09-12
Authors: Isabella Campanini; Annalisa Bargellini; Stefano Mastrangelo; Francesco Lombardi; Stefano Tolomelli; Mirco Lusuardi; Andrea Merlo Journal: Int J Environ Res Public Health Date: 2021-02-04 Impact factor: 3.390