Physical Performance Predictor Measures in Older Adults With Falls-Related Emergency Department Visits.

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2019-06

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Abstract

OBJECTIVES:Identifying strong predictors for falls and mobility limitations in older adults with a falls-related emergency department visit is crucial. This study aimed to compare, in this clinical population, the incremental predictive value of the Short Physical Performance Battery (SPPB) component tests for incident falls, injurious falls, and mobility limitations. DESIGN AND MEASURES:Prospective cohort study. SETTING AND PARTICIPANTS:A total of 323 community-dwelling older adults with a falls-related emergency department visit participated. Baseline physical performance was measured by the SPPB standing balance test, sit-to-stand test, and habitual gait speed test. Six-month prospective fall rate and self-reported mobility limitations at 6 months post baseline assessment were also measured. An injurious fall was defined as a fall for which the participant sought medical attention or that restricted his or her daily activities for at least 48 hours. RESULTS:In multivariable proportional odds analyses adjusted for demographics and clinical covariates, higher levels of full-tandem balance and sit-to-stand performance were significantly associated with fewer incident falls (P = .04 and .02, respectively) and lower odds of mobility limitations (P = .05 and .03, respectively) and marginally associated with lower odds of injurious falls (P = .06 and .07, respectively). Habitual gait speed was the weakest predictor of falls but the strongest predictor (odds ratio 0.24, 95% confidence interval 0.08-0.70; P < .001) of mobility limitations. CONCLUSIONS/IMPLICATIONS:In high-fall-risk older adults, the SPPB balance and sit-to-stand tests predicted falls whereas the SPPB gait speed test was adept at predicting mobility limitations. No one test is best across all situations, so the choice of test will depend on the goal of the assessment.

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10.1016/j.jamda.2018.12.005

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Pua, Yong-Hao, and David B Matchar (2019). Physical Performance Predictor Measures in Older Adults With Falls-Related Emergency Department Visits. Journal of the American Medical Directors Association, 20(6). pp. 780–784. 10.1016/j.jamda.2018.12.005 Retrieved from https://hdl.handle.net/10161/22782.

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Scholars@Duke

Matchar

David Bruce Matchar

Professor of Medicine

My research relates to clinical practice improvement - from the development of clinical policies to their implementation in real world clinical settings. Most recently my major content focus has been cerebrovascular disease. Other major clinical areas in which I work include the range of disabling neurological conditions, cardiovascular disease, and cancer prevention.
Notable features of my work are: (1) reliance on analytic strategies such as meta-analysis, simulation, decision analysis and cost-effectiveness analysis; (2) a balancing of methodological rigor the needs of medical professionals; and (3) dependence on interdisciplinary groups of experts.
This approach is best illustrated by the Stroke Prevention Patient Outcome Research Team (PORT), for which I served as principal investigator. Funded by the AHCPR, the PORT involved 35 investigators at 13 institutions. The Stroke PORT has been highly productive and has led to a stroke prevention project funded as a public/private partnership by the AHCPR and DuPont Pharma, the Managing Anticoagulation Services Trial (MAST). MAST is a practice improvement trial in 6 managed care organizations, focussing on optimizing anticoagulation for individuals with atrial fibrillation.
I serve as consultant in the general area of analytic strategies for clinical policy development, as well as for specific projects related to stroke (e.g., acute stroke treatment, management of atrial fibrillation, and use of carotid endarterectomy.) I have worked with AHCPR (now AHRQ), ACP, AHA, AAN, Robert Wood Johnson Foundation, NSA, WHO, and several pharmaceutical companies.
Key Words: clinical policy, disease management, stroke, decision analysis, clinical guidelines


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