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Record W4416906654 · doi:10.1007/s11886-025-02313-9

Exercise Rehabilitation for Heart Failure and Associated Cardiomyopathies

2025· article· en· W4416906654 on OpenAlexaff
Macy E. Stahl, Nathan R. Weeldreyer, James P. MacNamara, Patricia F. Rodriguez Lozano, Jason D. Allen

Bibliographic record

VenueCurrent Cardiology Reports · 2025
Typearticle
Languageen
FieldMedicine
TopicCardiomyopathy and Myosin Studies
Canadian institutionsUniversity of Alberta
FundersNational Heart, Lung, and Blood InstituteNational Institute on AgingNational Institutes of Health
KeywordsHeart failureRehabilitationAnginaEjection fractionQuality of life (healthcare)CardiomyopathyClinical trialHypertrophic cardiomyopathy

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: To summarize and provide insight into the role of exercise rehabilitation for heart failure, cardiomyopathies and associated conditions. We provide an overview of the evolution of exercise training from “bed rest” to current guidelines and highlight emerging approaches. RECENT FINDINGS: Exercise training appears to be safe and provide benefits for patients with heart failure. Emerging evidence also suggests potential benefit in hypertrophic cardiomyopathy as well as angina with non-obstructive coronary arteries, though more data are needed for widespread implementation. Given appropriate precautions and clinical assessments, exercise is a unifying therapy across most heart failure conditions regardless of ejection fraction. Exercise training appears to be safe, and beneficial in terms of improvements in functional capacity and health-related quality of life. Larger controlled trials are needed to better examine the impact of exercise on hard clinical endpoints such as HF hospitalizations (likely beneficial) and cardiovascular mortality.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.202
Threshold uncertainty score0.707

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.011
GPT teacher head0.303
Teacher spread0.292 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2025
Admission routes1
Has abstractyes

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