Optimizing cardiovascular health with a type 2 diabetes remission program: Ultraprocessed food‐intake reduction, Mediterranean diet, chrononutrition and physical training—The <scp>DIABEPIC</scp> ‐2 pilot study
Bibliographic record
Abstract
AIMS: The possibility of type 2 diabetes (T2D) remission following very-low caloric restriction has been demonstrated. However, the feasibility of T2D remission following other health behavioural interventions remains to be explored. MATERIALS AND METHODS: The DIABEPIC-2 pilot study assessed the feasibility of a 6-month programme based on ultra-processed food intake reduction, a Mediterranean diet, and physical training. Also, a randomised 2:1 proportion of participants added intermittent fasting (IF) in the last 3 months. The study explored the T2D remission rate and its impact on cardiometabolic and anthropometric parameters, cardiorespiratory fitness, and quality of food matrix. RESULTS: Feasibility was demonstrated with a recruitment rate of 6.4 participants/month, 34 participants (81%) who completed the programme, with an 87% attendance rate (63.6 ± 9.2 years old, initial mean HbA1c of 6.7 ± 0.7%, mean T2D duration of 7.4 ± 6.7 years). At 6 months, participants had a mean weight loss of -6.8 kg (-9.3 to -4.4, p < 0.001), and 13 participants out of 34 (38%) achieved T2D remission. Overall, participants significantly improved cardiometabolic health and anthropometric parameters, cardiorespiratory fitness, and food matrix quality. Participants randomised to the IF add-on intervention group did not show significant additional improvement. CONCLUSION: The DIABEPIC-2 program enabled a significant proportion of participants to achieve T2D remission and to improve their cardiovascular health; therefore, it would be relevant to confirm these results. The recruitment and visit completion rates observed in this pilot study further demonstrate its feasibility, supporting the rationale for conducting a larger randomized clinical trial.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".