Cardiometabolic responses to cardiac rehabilitation in people with and without diabetes
Bibliographic record
Abstract
BACKGROUND: Type 2 diabetes and cardiometabolic comorbidities manifesting as the metabolic syndrome (MetS) are highly prevalent in coronary heart disease (CHD) patients attending cardiac rehabilitation (CR). The study aimed to determine the prevalence of cardiometabolic derangements and MetS, and compare post-CR clinical responses in a large cohort of CHD patients with and without diabetes. METHODS: Analyses were conducted on 3953 CHD patients [age: 61.1 ± 10.5 years; 741 (18.7%) with diabetes] that completed a representative 12-week CR program. A propensity model was used to match patients with diabetes (n = 731) to those without diabetes (n = 731) on baseline and clinical characteristics. RESULTS: Diabetic patients experienced smaller improvements in metabolic parameters after completing CR, including abdominal obesity, and lipid profiles (all P ≤ .002), compared to non-diabetic patients. For both groups, there were similar improvement rates in peak metabolic equivalents ([METs]; P < .001); however, peak METs remained lower at 12-weeks in patients with diabetes than without diabetes. At baseline, the combined prevalence of insulin resistance (IR) and diabetes was 57.3%, whereas IR was present in 48.2% of non-diabetic patients, of which rates were reduced to 48.2% and 32.8% after CR, respectively. Accordingly, MetS prevalence decreased from 25.5% to 22.3% in diabetic versus 20.0% to 13.4% in non-diabetic patients (all P ≤ .004). CONCLUSIONS: Completing CR appears to provide comprehensive risk reduction in cardio-metabolic parameters associated with diabetes and MetS; however, CHD patients with diabetes may require additional and more aggressive attention towards all MetS criteria over the course of CR in order to prevent future cardiovascular events.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".