Influence of Gender on the Improvement in Exercise Capacity following Cardiac Rehabilitation
Bibliographic record
Abstract
Participation in cardiac rehabilitation (CR) programs reduces morbidity and mortality after acute cardiac events. Despite this clinically important adaptation, referral rates to such programs following a cardiac event remain low. Further there exists an apparent gender disparity as women are less likely to be referred. PURPOSE: To assess differences in exercise capacity pre and post CR between male and female participants. METHODS: Four thousand two hundred and eighty-two subjects diagnosed with coronary artery disease (3474 male/808 female), who were consecutively enrolled in a multidisciplinary interventional CR program at the Cardiac Wellness Institute of Calgary were included in this analysis. Subjects underwent physician supervised treadmill exercise testing to determine peak metabolic equivalent (MET) level pre and post CR. Based on the initial treadmill test, participants were assigned a target heart rate (40–75% of maximal heart rate) and underwent 30–50 minutes of continuous aerobic activity, 3–5 times per week, over the course of 12 weeks. RESULTS: Data are reported male vs. female throughout. Males were significantly younger than the females (60.3 ± 10.1 vs. 62.1 ± 10.2 years, p<0.001). The number of CR sessions attended was not significantly different between groups (23.3 ± 9.4 vs. 23.4 ± 9.4 sessions, p=0.90). Peak MET level was significantly greater in the male subjects both prior to (7.9 ± 2.0 vs. 6.4 ± 1.9 METs, p<0.001) and following (8.9 ± 2.0 vs. 7.3 ± 1.8 METs, p<0.001) completion of the CR program. Both males and females, however, demonstrated a significant improvement in peak MET level following CR (p<0.001). Furthermore, while the absolute improvement in peak MET level was similar between groups (0.96 ± 0.90 vs. 0.92 ± 0.97 METs, p=0.27), the percent improvement in peak MET level was significantly greater in female subjects (14.3 ± 18.6% vs. 18.1 ± 25.5%, p<0.001). CONCLUSION: The significant difference in absolute peak MET level between male and female subjects is consistent with trends in the general population. However, these results indicate females completing CR may experience a greater percent improvement in exercise capacity compared to males. Efforts should be made to improve referral patterns and attendance to CR in females with cardiac disease.
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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 | 0.000 |
| 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".