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Record W7133027917

The Effectiveness of Cardiac Rehabilitation on Cardiovascular Disease Risk Factors in Women with Breast Cancer

2024· dissertation· W7133027917 on OpenAlexaff
Elia Rishis

Bibliographic record

VenueTSpace · 2024
Typedissertation
Language
FieldMedicine
TopicChemotherapy-induced cardiotoxicity and mitigation
Canadian institutionsYork University
Fundersnot available
KeywordsCardiorespiratory fitnessPedometerBreast cancerRehabilitationDiseaseAnthropometryProspective cohort studyRisk factor
DOInot available

Abstract

fetched live from OpenAlex

In 2019, the American Heart Association recommended multimodal cardiac rehabilitation (CR) as an effective and viable strategy to mitigate cardiovascular disease (CVD) risk in early-stage cancer survivors, yet little prospective data was available to support the recommendation. This thesis prospectively assessed the effectiveness of a 16-week CR program on CVD risk factors among 50 women with breast cancer. Participants completed a cardiopulmonary exercise test, 12-hour fasted venipuncture, a series of questionnaires, and wore a pedometer for seven days before and after program completion. The CR program elicited significant improvements in cardiorespiratory fitness, peak oxygen pulse, anaerobic threshold, diet quality, moderate-to-vigorous physical activity, and cancer-related fatigue. However, anthropometric measures, blood lipids, stress, and depressive symptoms did not change. Breast cancer stage, diet quality, and cancer-related fatigue predicted the change in VO2peak following program completion. These findings suggest CR is effective at reducing select CVD risk factors in women with breast cancer.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.006
GPT teacher head0.279
Teacher spread0.273 · 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 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
Published2024
Admission routes1
Has abstractyes

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