Metabolic Flexibility to Predict Lifestyle Interventions Outcomes (MEPHISTO): Protocol for Predictive Validation Study and Randomized Controlled Trial
Bibliographic record
Abstract
Background Weight loss is a cornerstone of obesity treatment and diabetes mellitus type 2 (T2D) prevention, but its implementation in clinical practice is limited by its perceived burden and variability in response. Personalizing interventions to increase their success rate is an unmet clinical need. Objective Identification of predictive factors associated with successful weight loss after sequential exercise in women with obesity. Methods The study will consist of a 2-stage analytical approach, including a predictive validation study and a 2:1 randomized cross-over controlled trial. Women aged 25-45 years with obesity (BMI>30) will be included in the study. The intervention will consist of a progressive protocol of aerobic exercise on a treadmill and a bicycle ergometer. We will measure weight loss in terms of fat mass (FM) and fat-free mass (FFM), metabolic flexibility (MetFlex) as ΔRQ (change in respiratory quotient (VCO2/VO2) between basal and insulin-stimulated state during glucose clamp), insulin sensitivity, glucose tolerance, hemoglobin A1c, microbiome composition, and metabolomic signatures. Results Recruitment for the trial began in January 2024. A total of 12 participants were enrolled and randomized. Among them 6 participants have completed the first phase of the A-arm and 6 participants have completed the control period of the B-arm and their intervention is ongoing. Recruitment is ongoing. We expect the preliminary data from this study to be completed in 2026. Conclusions This intervention will investigate whether whole body and gut MetFlex can be further explored and used as ex ante predictors of successful weight loss following exercise intervention, providing proof of concept and paving the way for personalized lifestyle interventions. Trial Registration ClinicalTrials.gov NCT06329349; https://clinicaltrials.gov/study/NCT06329349 International Registered Report Identifier (IRRID) DERR1-10.2196/67570
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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 | 0.041 | 0.033 |
| Meta-epidemiology (narrow) | 0.008 | 0.003 |
| Meta-epidemiology (broad) | 0.012 | 0.006 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.057 | 0.012 |
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".