A randomised trial comparing weight loss with aerobic exercise in overweight individuals with coronary artery disease: The CUT-IT trial
Bibliographic record
Abstract
BACKGROUND: We aimed to compare the effect of aerobic interval training (AIT) versus a low energy diet (LED) on physical fitness, body composition, cardiovascular risk factors and symptoms in overweight individuals with coronary artery disease (CAD). METHODS AND DESIGN: Seventy non-diabetic participants with CAD, a BMI>28 kg/m(2) and aged 45 to 75 years were randomised to 12 weeks' AIT at 90% peak heart rate three times a week or LED (800-1000 kcal/day) for 8-10 weeks followed by 2-4 weeks' weight maintenance diet. RESULTS: Twenty-six (74%) AIT and 29 (83%) LED participants completed intervention per protocol. VO2peak (mL/kg fat free mass(0.67)/min) increased by 10.4% (p = 0.002) following AIT, whereas no change was observed after LED (-3.0%, p = 0.095). The LED group lost 10.6% body weight and 26.6% body fat mass (p < 0.001) compared to 1.6% (p = 0.002) and 5.5% (p < 0.001) following AIT. Waist circumference and visceral abdominal fat were reduced by both interventions but were most pronounced following LED (between-group, p < 0.001). Total cholesterol, non-HDL-C and triglycerides decreased significantly in both groups whereas HDL-C and blood pressure were unchanged. Six participants had their antihypertensive treatment reduced following LED (between-group, p = 0.032). Canadian Cardiovascular Society (CCS), New York Heart Association (NYHA) and anxiety scores were improved, while depressive symptoms remained unchanged. Intention-to-treat analyses including 65 participants (93%) were similar to per protocol analysis. CONCLUSION: Both interventions were feasible and effective in achieving the desired effects. LED was superior in improving body composition and blood pressure, whereas effects on lipids and symptoms were similar in the two groups. Thus, both AIT and LED improve the cardiovascular risk profile in overweight individuals with contemporarily treated CAD.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".