Comparative effectiveness of high-intensity interval training and moderate-intensity continuous training on cardiometabolic health in patients with diabesity: a systematic review and meta-analysis of randomized controlled trials
Bibliographic record
Abstract
OBJECTIVE: To evaluate the effects of high-intensity interval training (HIIT) on cardiometabolic health-related outcomes in patients with type 2 diabetes mellitus and concurrent overweight/obesity (diabesity). DESIGN: Systematic review and meta-analysis of randomized controlled trials (RCTs). DATA SOURCES: PubMed, Web of Science, Scopus, Science Direct, Cochrane Library, and Google Scholar databases were searched from inception up to January 31, 2025. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: RCTs comparing HIIT alone ≥ 2 weeks in duration with moderate-intensity continuous training (MICT). Participants were adults with diabesity. RESULTS: ). HIIT revealed a significant reduction in fasting insulin [standardized mean differences (SMD) - 0.43, 95% CI - 0.82 to - 0.05] and homeostatic model assessment for insulin resistance (HOMA-IR; SMD - 0.52, 95% CI - 0.97 to - 0.07) compared to MICT. Additionally, HIIT significantly increased cardiorespiratory fitness (VO₂max; SMD 0.53, 95% CI 0.14 to 0.91) compared to MICT. Other clinically relevant cardiometabolic outcomes, including body composition, lipid profile, fasting blood glucose, glycated hemoglobin, and blood pressure, showed comparable changes between HIIT and MICT. Subgroup analyses of studies reporting comorbidities indicated a significant increase in high-density lipoprotein cholesterol (SMD 0.49, 95% CI 0.04 to 0.95) and a decrease in HOMA-IR (SMD - 0.83, 95% CI - 1.62 to - 0.04) for HIIT compared to MICT. However, these findings are limited by very low certainty evidence and non-robust sensitivity analyses. CONCLUSIONS: The present findings suggest that HIIT may serve as an adjunctive non-pharmaceutical management solution for patients with diabesity. Open Science Framework registry: https://osf.io/9by24.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Meta-analysis | low |
| gpt | Meta-epidemiology (broad) Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Meta-analysis | low |
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 | 0.013 | 0.029 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.022 | 0.030 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".