Time-Restricted Eating is a Feasible Dietary Strategy in the Treatment of Complicated Type 2 Diabetes: The RESET2 Pilot Study
Bibliographic record
Abstract
OBJECTIVE: To investigate the feasibility of a 12-week time-restricted eating (TRE) intervention targeting people with overweight/obesity and complicated type 2 diabetes to inform the design of a 1-year randomized controlled trial. METHODS: In this single-arm pilot study, 20 participants with overweight/obesity and complicated type 2 diabetes were recruited from the diabetes clinics at Hvidovre Hospital and Steno Diabetes Center Copenhagen in the Greater Copenhagen area, Denmark. Participants followed 8 weeks of strict 10-hour TRE, followed by a 4-week TRE period with individual adjustments and support options. RESULTS: Nineteen participants completed the intervention. Median (quartile 1-quartile 3) adherence to the eating window across all 12 weeks was 94% (86-98). Mean (95% confidence interval) reductions in body weight of -2.0 kg (-2.9 to -1.1) and hemoglobin A1c of -0.4% (-0.6 to -0.1) were observed. Participants expressed that the individualized options added flexibility to the eating concept, enabled the maintenance of social life, and eased challenging times with TRE. CONCLUSIONS AND IMPLICATIONS: Twelve weeks of TRE was feasible. Individualized adjustments and support may have the potential to facilitate the maintenance of long-term TRE.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".