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Record W4396590156 · doi:10.1111/obr.13751

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

2024· review· en· W4396590156 on OpenAlexafffund
Jarvis C. Noronha, Stephanie Nishi, Tauseef Khan, Sonia Blanco Mejía, Cyril W.C. Kendall, Hana Kahleová, Dario Rahelić, Jordi Salas‐Salvadó, Lawrence A. Leiter, Michael E. J. Lean, John L. Sievenpiper

Bibliographic record

VenueObesity Reviews · 2024
Typereview
Languageen
FieldMedicine
TopicDiet and metabolism studies
Canadian institutionsUniversity of TorontoUniversity of SaskatchewanSt. Michael's Hospital
FundersInstitute of Nutrition, Metabolism and DiabetesInternational Nut and Dried Fruit CouncilLoblaw Companies LimitedInstitute for the Advancement of Food and Nutrition SciencesAgriculture and Agri-Food CanadaCanadian Institutes of Health ResearchDanoneAlmond Board of CaliforniaNational Honey BoardGeneral MillsCanola Council of CanadaCanada Foundation for InnovationEuropean Association for the Study of DiabetesDiabetes CanadaPepsiCo
KeywordsMedicineMeta-analysisRandomized controlled trialMetabolic syndromeDiabetes mellitusWeight managementWeight lossMealReduction (mathematics)ObesityInternal medicineEndocrinologyMathematics

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.034
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.420
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0340.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.1080.006
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.049
GPT teacher head0.355
Teacher spread0.307 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations12
Published2024
Admission routes2
Has abstractyes

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