A Comprehensive Appraisal of Meta-Analyses of Exercise-Based Stroke Rehabilitation with Trial Sequential Analysis

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Abstract

Meta-analysis is a common technique used to synthesise the results of multiple studies through the combination of effect size estimates and testing statistics. Numerous meta-analyses have investigated the efficacy of exercise programmes for stroke rehabilitation. However, meta-analyses may also report false-positive results because of insufficient information or random errors. Trial sequential analysis (TSA) is an advanced technique for calculating the required information size (RIS) and more restrictive statistical significance levels for the precise assessment of any specific treatment. This study used TSA to examine whether published meta-analyses in the field of stroke rehabilitation reached the RIS and whether their overall effect sizes were sufficient. A comprehensive search of six electronic databases for articles published before May 2022 was conducted. The intervention methods were divided into four primary groups, namely aerobic or resistance exercise, machine-assisted exercise, task-oriented exercise, and theory-based exercise. The primary outcome measure was gait speed and the secondary outcome measure was balance function. The data were obtained either from the meta-analyses or as raw data from the original cited texts. All data analysis was performed in TSA software. In total, 38 articles with 46 analysable results were included in the TSA. Only 17 results (37.0%) reached the RIS. In conclusion, meta-analysis interpretation is challenging. Clinicians must consider the RIS of meta-analyses before applying the results in real-world situations. TSA can provide accurate evaluations of treatment effects, which is crucial to the development of evidence-based medicine.

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Li, J. Q., Sun, Y. W., So, W. S., Sidarta, A., & Kwong, P. W. H. (2022, October 1). A Comprehensive Appraisal of Meta-Analyses of Exercise-Based Stroke Rehabilitation with Trial Sequential Analysis. Healthcare (Switzerland). MDPI. https://doi.org/10.3390/healthcare10101984

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