Time-restricted eating with or without low-carbohydrate diet reduces visceral fat and improves metabolic syndrome: A randomized trial
Bibliographic record
Abstract
Overconsumption of carbohydrate-rich food combined with adverse eating patterns contributes to the increasing incidence of metabolic syndrome (MetS) in China. Therefore, we conducted a randomized trial to determine the effects of a low-carbohydrate diet (LCD), an 8-h time-restricted eating (TRE) schedule, and their combination on body weight and abdominal fat area (i.e., primary outcomes) and cardiometabolic outcomes in participants with MetS. Compared with baseline, all 3-month treatments significantly reduce body weight and subcutaneous fat area, but only TRE and combination treatment reduce visceral fat area (VFA), fasting blood glucose, uric acid (UA), and dyslipidemia. Furthermore, compared with changes of LCD, TRE and combination treatment further decrease body weight and VFA, while only combination treatment yields more benefits on glycemic control, UA, and dyslipidemia. In conclusion, without change of physical activity, an 8-h TRE with or without LCD can serve as an effective treatment for MetS (ClinicalTrials.gov: NCT04475822).
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".