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Record W2132363115 · doi:10.1186/1745-6215-12-92

A Meta-analysis of the effects of Exercise Training on Left Ventricular Remodeling Following Myocardial Infarction: Start early and go longer for greatest exercise benefits on remodeling

2011· review· en· W2132363115 on OpenAlexafffund
Mark J. Haykowsky, Jessica M. Scott, Ben T. Esch, Don Schopflocher, Jonathan Myers, D. Ian Paterson, Darren E. R. Warburton, Lee W. Jones, Alexander M. Clark

Bibliographic record

VenueTrials · 2011
Typereview
Languageen
FieldMedicine
TopicCardiovascular Effects of Exercise
Canadian institutionsUniversity of British ColumbiaUniversity of Alberta
FundersCanadian Institutes of Health ResearchU.S. Department of Veterans Affairs
KeywordsMedicineVentricular remodelingMyocardial infarctionCardiologyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: The effects of variations in exercise training on left ventricular (LV) remodeling in patients shortly after myocardial infarction (MI) are important but poorly understood. METHODS: Systematic review incorporating meta-analysis using meta-regression. Studies were identified via systematic searches of: OVID MEDLINE (1950 to 2009), Cochrane Central Register of Controlled Trials (1991 to 2009), AMED (1985 to 2009), EMBASE (1988 to 2009), PUBMED (1966 to 2009), SPORT DISCUS (1975 to 2009), SCOPUS (1950 to 2009) and WEB OF SCIENCE (1950 to 2009) using the medical subject headings: myocardial infarction, post myocardial infarction, post infarction, heart attack, ventricular remodeling, ventricular volumes, ejection fraction, left ventricular function, exercise, exercise therapy, kinesiotherapy, exercise training. Reference lists of all identified studies were also manually searched for further relevant studies. Studies selected were randomized controlled trials of exercise training interventions reporting ejection fraction (EF) and/or ventricular volumes in patients following recent MI (≤ 3 months) post-MI patients involving control groups. Studies were excluded if they were not randomized, did not have a 'usual-care' control (involving no exercise), evaluated a non-exercise intervention, or did not involve human subjects. Non-English studies were also excluded. RESULTS: After screening of 1029 trials, trials were identified that reported EF (12 trials, n = 647), End Systolic Volumes (ESV) (9 trials, n = 475) and End Diastolic Volumes (EDV) (10 trials, n = 512). Meta-regression identified that changes in EF effect size difference decreased as the time between MI and initiation of the exercise program lengthened, and increased as the duration of the program increased (Q = 25.48, df = 2, p < 0.01, R2 = 0.76). Greater reductions in ESV and EDV (as indicated by effect size decreases) occurred with earlier initiation of exercise training and with longer training durations (ESV: Q = 23.89, df = 2, p < 0.05, R2 = 0.79; EDV: Q = 27.42, df = 2, p < 0.01, R2 = 0.83). Differences remained following sensitivity analysis. Each week that exercise was delayed required an additional month of training to achieve the same level of benefit on LV remodeling. CONCLUSIONS: Exercise training has beneficial effects on LV remodeling in clinically stable post-MI patients with greatest benefits occurring when training starts earlier following MI (from one week) and lasts longer than 3 months.

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)0.020
metaresearch head score (Gemma)0.049
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: Review · Consensus signal: Review
Teacher disagreement score0.024
Threshold uncertainty score0.106

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.049
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0240.067
Bibliometrics0.0080.007
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.259
GPT teacher head0.373
Teacher spread0.114 · 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
GenreReview

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

Citations227
Published2011
Admission routes2
Has abstractyes

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