IMPACT OF MULTIPLE LIFESTYLE INTERVENTIONS ON METABOLIC HEALTH AND REMISSION OF PREDIABETES AND TYPE 2 DIABETES: A TWO-YEAR CLINICAL EXPERIENCE
Bibliographic record
Abstract
Diabetes, Lifestyle Interventions Different intensive lifestyle interventions have been shown to be useful for effective control and even reversal of prediabetes and type 2 diabetes (T2D). The Montreal Heart Institute Cardiovascular Prevention Center (EPIC) started a comprehensive lifestyle clinic to study the impact of 6 and 12-month non-pharmacological interventions on metabolic health and remission of these two conditions. Between January 2019 and December 2020, 81 prediabetic (HbA1c ≥ 5.7%) and 184 T2D (HbA1c ≥ 6.5%) were recruited. All participants received regular nutritional counselling (therapeutic moderate carbohydrate restriction Mediterranean diet) and personalized physical exercise prescription (≥30 minutes of moderate aerobic training, 5 times a week, and strength training). Anthropometric measures and fasting blood analysis were measured at 0, 3, 6 and 12 months. Glucose-lowering therapies were not modified, unless necessary. Complete remission of prediabetes and T2D was defined as HbA1c <5.7%, whereas partial remission of T2D was defined as HbA1c <6.5% for at least 3 months, and it was calculated for all the participants that completed the 12-month program. Remission was further evaluated according to pharmacological status (drug-naïve or on glucose-lowering therapy). 231 participants completed the short-term program (87%) and 117 were followed-up to 12 months. Mean age was 67.1 (9.1) years, 67% male, 48.3% with CHD, 53.5% with glucose-lowering therapies. All metabolic health measures were improved, particularly among T2D participants (Table 1). Gains were achieved at 3 months and were maintained during the remainder of the program without significant change. Complete remission of prediabetes was achieved in 24% (95CI: 10.7 to 45.4%) of participants. Complete and partial remission of T2D were achieved in 5.4% (95CI: 2.2 to 12.5%) and 41.3% (95CI: 31.6 to 51.7%) of participants respectively and was observed in both with or without glucose-lowering therapies subgroups (Table 2). Prioritizing lifestyle changes were shown to improve metabolic health measures even to the point of achieving remission among subjects with prediabetes or T2D. These metabolic changes were mostly achieved after 3 months and persisted throughout the intervention. Future research is required to better understand which non-pharmacological interventions work best among subjects with varying metabolic profiles and pharmacotherapy, how long should the interventions last and how partial or complete normalization of glucose impact long-term outcomes.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".