Pre-Coronary Artery Bypass Graft Measures and Enrollment in Cardiac Rehabilitation
Bibliographic record
Abstract
PURPOSE: The aim of this study was to examine the relationship between exercise tolerance, functional status, exercise behavior, and enrollment in cardiac rehabilitation (CR), preoperatively in individuals undergoing coronary artery bypass graft (CABG) surgery. METHODS: Seventy-eight individuals undergoing CABG were evaluated 1 to 7 days preoperatively using the following measures: 2-minute walk test (2MWT), Duke Activity Status Index (DASI), Cardiac Exercise Self-Efficacy Instrument (CESEI), Stages of Change Questionnaire (SCQ), Short-Form 12 (SF-12), Hospital Anxiety Depression scale, location of residence, and education level. Participants were contacted via telephone 10 to 12 weeks postoperatively to determine if they were referred and enrolled in CR. Participants completed mailed questionnaires for follow-up. In subsequent telephone interviews, individuals who were not enrolled in CR were asked to provide reasons for nonenrollment. RESULTS: Overall enrollment in CR was 46%. No significant differences were found in 2MWT, CESEI, and DASI scores between enrolled and nonenrolled participants. Fifty-seven percent of urban-dwelling participants enrolled in CR compared to 29% of rural-dwelling participants (P < .01). Similarly, 65% of individuals with post-secondary education enrolled in CR compared to 38% of individuals without a post-secondary education (P = .05). The primary reasons for nonenrollment were behavioral intentions toward exercise and CR, accessibility, and healthcare team recommendation. Individuals who enrolled in CR demonstrated a larger postoperative improvement in CESEI score. CONCLUSIONS: Location of residence and education level predicted CR enrollment, whereas preoperative exercise tolerance, functional status, and exercise attitudes did not predict enrollment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".