Abstract 12530: Impact of Multiple Lifestyle Intervention on Body Weight, Insulin Sensitivity and Remission of Type 2 Diabetes: A Single-Center Experience
Bibliographic record
Abstract
Introduction: Type 2 diabetes (T2D) and pre-diabetes are mostly lifestyle diseases associated with high rates of morbidity, mortality, and health care expenditures. Hypothesis: The Montreal Heart Institute Cardiovascular Prevention EPIC Center started a comprehensive lifestyle clinic for patients with T2D in 2019. We sought to study the impacts of a 12-month non-pharmacological intervention on body weight, insulin sensitivity and remission of T2D. Methods: Between January and December 2019, 105 with T2D (HbA1c ≥ 6.5%) were recruited. Anthropometric measures and fasting blood analysis were measured at 0,3,6 and 12 months. All patients received regular nutritional counselling and personalized physical exercise prescription. Glucose-lowering therapies were not modified, unless necessary. Partial and complete remission of diabetes were defined by HbA1c <6.5% and HbA1c <5.7% respectively, for at least 3 months. Differences in means across variables with repeated observations were assessed with ANOVA. Factors associated with obtaining partial remission at 3 months were analyzed using a multivariate logistic model. Results: 96 patients completed the intervention (91%), mean age was 67.5±10.5 years, 72% male, 37% with coronary heart disease, 23% without glucose-lowering therapies. Mean baseline HbA1c was 7.3±0.8 %. At program end, all anthropometric and insulin resistance measures were significantly improved (Table 1); HbA1c -0.78 (95CI: -0.57 à -0.98, p<0.001). Gains were achieved at 3 months and were maintained during the program without significant change. Partial remission was achieved in 56.1% (95CI: 45.1 to 66.5%) and complete remission of diabetes was attained in 11% (95CI: 5.7 to 19.9%) of participants. Adjusted by age, sex, treatment, baselineHbA1c and weight loss at 3 months; individuals with low HbA1c (p=0.01) and those that lost >3.5Kg at 3 months (OR 4.1, 95%CI: 1.5 to 11.1, p=0.005) were significantly more likely to attain partial remission. Conclusions: Prioritizing lifestyle changes were shown to improve anthropometric and insulin resistance measures even to the point of normalizing some metabolic values among subjects with T2D. These changes were mostly achieved after 3 months and were maintained throughout the intervention.
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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 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".