The Association of Specific Dietary Patterns with Cardiometabolic Outcomes in Women with a History of Gestational Diabetes Mellitus: A Scoping Review
Bibliographic record
Abstract
Gestational diabetes mellitus is associated with a significantly increased risk of later type 2 diabetes (T2DM) and cardiovascular disease (CVD). Post-natal interventions aim to reduce this risk by addressing diet and lifestyle factors and frequently focus on restricting energy or macronutrient intake. With increased interest in the role of complete dietary patterns in the prevention of cardiometabolic disease, we sought to evaluate what is known about the role of dietary patterns in reducing cardiometabolic risk in women with previous GDM. A systematic search was conducted to identify studies relating to dietary pattern and cardiometabolic parameters in women with a history of GDM. The search criteria returned 6014 individual studies. In total, 71 full texts were reviewed, with 24 studies included in the final review. Eleven individual dietary patterns were identified, with the Alternative Health Eating Index (AHEI), Mediterranean diet (MD), and low glycaemic index (GI) as the most commonly featured dietary patterns. Relevant reported outcomes included incident T2DM and glucose tolerance parameters, as well as several cardiovascular risk factors. Dietary patterns which have previously been extensively demonstrated to reduce the risk of cardiovascular and metabolic disorders in the general population, including AHEI, MD, and DASH, were found to be associated with a reduction in the incidence of T2DM, hypertension, and additional risk factors for cardiometabolic disease in women with a history of GDM. Notable gaps in the literature were identified, including the relationship between dietary patterns and incident CVD, as well as the relationship between a low GI diet and the development of T2DM in this population.
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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 | 0.005 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.013 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".