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Record W2274783911 · doi:10.1161/str.43.suppl_1.a86

Abstract 86: Does Exercise Post Stroke have a Beneficial Effect on Post-Stroke Depression: A Meta-Analysis

2012· article· en· W2274783911 on OpenAlexaff
Katherine Salter, Hannah Mahon, James A. McClure, Norine Foley, Robert Teasell

Bibliographic record

VenueStroke · 2012
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsParkwood Institute
Fundersnot available
KeywordsMedicineStroke (engine)Depression (economics)Physical therapyMeta-analysisPopulationRandomized controlled trialInternal medicine

Abstract

fetched live from OpenAlex

Given the high prevalence and negative personal and social consequences of post-stroke depression (PSD), identification and application of safe and effective treatments is imperative. While recent publications examining the evidence regarding the impact of physical activity on depression suggest that, in the general population, exercise is associated with significant benefit in terms of reduction of depressive symptomatology, it is not clear that physical activity has the same benefit for individuals who have experienced stroke. Objective: To examine the effectiveness of exercise or physical activity on depressive symptomatology following stroke. Methods: We undertook a literature review to identify stroke-specific clinical trials examining the effectiveness of exercise or exercise programs when compared to a control condition that included longitudinal assessment of depression as a primary or secondary study outcome. Identified studies were evaluated for methodological quality using the PEDro scale and, where possible, results entered into a pooled, random effect analysis based on reported means and standard deviations from repeated assessments. Pre-post test correlations were estimated using published test/re-test reliability coefficients. Results: Eight studies were identified for inclusion; total PEDro scores ranged from 4 to 8. Depression was assessed at baseline and post-intervention using 4 self-report and 1 interview-based assessment tool(s). Participants were community-dwelling individuals; mean age ranged from 56 to 87. Only two trials reported significant between group differences for the outcome of depression, although several noted significant improvement within the intervention group only. Of the 8 identified studies, 6 reported sufficient data for inclusion in pooled analysis. Based on data from 276 participants, there was a moderate reduction in self-reported symptoms of depression associated with post-stroke exercise (ES=0.576; 95% CI 0.22, 0.93). No significant publication bias was identified (Egger’s intercept = 1.21, p=0.64). Conclusions: Although previous trials have reported a positive trend toward improvement of the self-reported symptoms of depression associated with exercise, the impact of exercise on depression has not been clear. On pooled analysis, however, it is apparent that participation in exercise is associated with a moderate and significant reduction in self-reported depressive symptomatology in older, community-dwelling individuals with stroke. Since physical impairments may limit participation in exercise programs for many individuals following stroke, additional research is required to examine exercise frequency and/or intensity required to demonstrate benefit.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.017
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0200.046
Bibliometrics0.0030.004
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0070.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.021
GPT teacher head0.300
Teacher spread0.279 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2012
Admission routes1
Has abstractyes

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