Weight management using meal replacements and cardiometabolic risk reduction in individuals with pre‐diabetes and features of metabolic syndrome: A systematic review and meta‐analysis of randomized controlled trials
Bibliographic record
Abstract
Summary This review synthesized the evidence from randomized controlled trials comparing the effect of meal replacements (MRs) as part of a weight loss intervention with conventional food‐based weight loss diets on cardiometabolic risk in individuals with pre‐diabetes and features of metabolic syndrome. MEDLINE, EMBASE, and Cochrane Library were searched through January 16, 2024. Data were pooled using the generic inverse variance method and expressed as mean difference [95% confidence intervals]. The overall certainty of the evidence was assessed using GRADE. Ten trials ( n = 1254) met the eligibility criteria. MRs led to greater reductions in body weight (−1.38 kg [−1.81, −0.95]), body mass index (BMI, −0.56 kg/m 2 [−0.78, −0.34]), waist circumference (−1.17 cm [−1.93, −0.41]), HbA 1c (−0.11% [−0.22, 0.00]), LDL‐c (−0.18 mmol/L [−0.28, −0.08]), non‐HDL‐c (−0.17 mmol/L [−0.33, −0.01]), and systolic blood pressure (−2.22 mmHg [−4.20, −0.23]). The overall certainty of the evidence was low to moderate owing to imprecision and/or inconsistency. The available evidence suggests that incorporating MRs into a weight loss intervention leads to small important reductions in body weight, BMI, LDL‐c, non‐HDL‐c, and systolic blood pressure, and trivial reductions in waist circumference and HbA 1c , beyond that seen with conventional food‐based weight loss diets.
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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 | 0.016 | 0.037 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.021 | 0.024 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".