Change in Cardiometabolic Health Following Participation in Cardiac Rehabilitation for Coronary Heart Disease: Effect Modification by Metabolic Syndrome Status
Bibliographic record
Abstract
Objective: To investigate changes in cardiometabolic risk factors after completion of cardiac rehabilitation (CR) for coronary heart disease (CHD) and ascertain whether the magnitude of improvement in cardiometabolic health differs between those with and without metabolic syndrome (MetS). Methods: In this observational cohort study, data were analyzed from 1984 patients enrolled in CR at the University of Michigan between 2011-01-01 and 2020-02-29 for the indication of CHD. Patient characteristics were collected from standardized health questionnaires and during CR intake evaluations. Cardiometabolic biomarkers were recorded from baseline laboratory data and re-examined upon completion of CR. Differences in baseline patient characteristics by MetS status were compared using chi-square tests. Wilcoxon rank-sum tests were used to compare baseline differences, and signed-rank tests were used to evaluate the change in variables between baseline and completion of CR. The difference of change by MetS status was assessed using difference-in-differences regression models. Results: Of the 1984 patients, 1070 (53.9%) met the criteria for MetS at baseline, of which 770 were male (72.0%). Those with MetS lost 1.43 pounds more (95% CI: 0.56, 2.31, P = 0.001), experienced a 0.21 larger drop in body mass index (95% CI: 0.03, 0.37, P = 0.02), and had a 0.31 greater reduction in waist circumference (95% CI: 0.08, 0.54, P = 0.008). Difference-in-differences regression models revealed those with MetS experienced a greater reduction in triglycerides and fasting glucose, with a difference of change of − 8.70 for triglycerides (95% CI: − 15.04, − 2.37, P = 0.007) and − 5.48 for glucose (95% CI: − 10.44, − 0.53, P = 0.03). There was no significant difference in the change in HDL-C or LDL-C for MetS status. Conclusion: Compared to those without MetS, patients with MetS experienced a comparable or greater benefit from CR, particularly with respect to improvements in MetS components. Keywords: chronic disease management, coronary heart disease, cardiometabolic risk factors, cardiovascular disease
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".