Gestational diabetes mellitus and vascular malperfusion lesions in the placenta: A systematic review and meta‐analysis
Bibliographic record
Abstract
BACKGROUND: Gestational diabetes mellitus (GDM) can result in increased placental lesions related to high maternal blood glucose, but these relationships are not well understood. OBJECTIVE: To examine the relationship between GDM and placental vascular malperfusion lesions: accelerated villous maturation, increased syncytial knots, delayed villous maturation, and increased fibrin deposition. SEARCH STRATEGY: PubMed, BIOSIS, and Web of Science databases were systematically searched for full-text articles in English from inception until August 21, 2024. SELECTION CRITERIA: Our inclusion criteria were randomized controlled trials, case-control, cohort, and cross-sectional studies that examined the relationship between GDM and selected placental vascular malperfusion lesions. The outcome must have been reported as a total proportion. DATA COLLECTION AND ANALYSIS: We included all eligible studies in narrative synthesis. If an outcome of interest was in at least three studies, we calculated the odds ratios (ORs) by GDM diagnosis, with 95% confidence intervals (CIs), using mixed-effects logistic regression with random study effects. We evaluated the risk of bias with the Newcastle-Ottawa Scale. MAIN RESULTS: We screened 151 studies, of which eight were included (n = 1291), and six met the criteria for meta-analysis (n = 561). Unadjusted odds (95% CI) of delayed villous maturation were six-fold higher (OR: 6.37 [3.28-12.37]) in pregnancies with GDM than in those without GDM. The narrative synthesis of the literature found higher proportions of increased syncytial knots, delayed villous maturation, and increased fibrin deposition, but not accelerated villous maturation, in pregnancies with versus without GDM. CONCLUSIONS: GDM was associated with a higher risk of three placental malperfusion lesions, although there is a small number of studies in this area. Future investigations should examine if these vascular malperfusions are associated with adverse pregnancy outcomes often linked with GDM.
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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 | 0.011 | 0.032 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.027 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".