Systematic Review and Meta-Analysis of Cognitive-Motor Interventions on BDNF Post-Stroke
by Edgar Vásquez-Carrasco·Updated 29d ago
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Description
A systematic review and meta-analysis synthesizes evidence from nine randomized controlled trials involving 457 participants. The analysis, conducted by Edgar Vásquez-Carrasco and registered in PROSPERO, quantifies the effect of cognitive-motor rehabilitation on serum brain-derived neurotrophic factor levels in adults and older adults after stroke. The findings, published on figshare in May 2026, indicate a statistically significant, large overall effect.
Use Cases
Conducting secondary meta-analyses on neuroplasticity biomarkers based on the aggregated effect size data.
Designing new clinical trials for stroke rehabilitation based on the synthesized evidence from nine included studies.
Evaluating the heterogeneity of treatment effects in neurorehabilitation based on the reported high I² statistic of 92%.
Assessing methodological quality of stroke rehabilitation studies using the referenced PRISMA, RoB 2, and GRADE frameworks.
Strengths
The meta-analysis is based on nine randomized controlled trials, a standard for high-quality evidence synthesis.
The protocol was pre-registered in PROSPERO (CRD420251140852), enhancing transparency and reducing bias.
The analysis reports a specific, large effect size (Hedges’ g = 2.51) with confidence intervals and p-value.
Limitations
Column-level documentation is absent; field semantics must be inferred after download.
The dataset is a 681.8 KB document file; the underlying extracted data tables are not provided as a separate, machine-readable format.
The description notes very high heterogeneity (I² = 92%) across the included studies, which complicates interpretation of the pooled effect.
Provenance
Source
figshare
Collection Method
Systematic literature review and meta-analysis of randomized controlled trials from multiple databases.
Freshness
Last updated 2026-05-07 05:42:50; freshness should be verified.
The primary data file is a DOCX document; users may need to extract tables or numerical results manually for computational analysis.