Prevalence and risk factors of delivery of large‐for‐gestational age infants among pregnant women with gestational diabetes: A systematic review and meta‐analysis
Bibliographic record
Abstract
Abstract Background Delivery of large‐for‐gestational age (LGA) infants among women with gestational diabetes (GD) is a public problem that endangers mothers and children. Although numerous studies have reported various risk factors associated with LGA delivery among patients with GD, there is currently a lack in systematic summarization. Objectives The objective of the current study was to identify the risk factors of LGA delivery among women with GD and provide guidance for clinical personnel. Search Strategy Systematic searches of PubMed, Web of Science, Cochrane Library, Scopus, EMBASE, OVID, and CINAHL were conducted from inception to August 1, 2024. Selection Criteria Observational studies that focused on risk factors of LGA deliveries among women with GD were included in this review. Data Collection and Analysis This review followed Preferred Reporting Items for Systematic Review and Meta‐Analysis guidelines, and the Newcastle‐Ottawa Scale and Agency for Healthcare Research and Quality checklist were used to evaluate the quality of the included studies. The pooled odds ratios with 95% confidence intervals were calculated by a fixed/random‐effects model. To identify the sources of heterogeneity, subgroup, meta‐regression, and sensitivity analyses were also conducted. The I 2 statistic was used to measure heterogeneity between studies. Publication bias was assessed using funnel plots and Egger test. Main Results A total of 25 studies were included in this review, including 60 580 women with GD. The prevalence of LGA deliveries among women with GD was found to be associated with significant heterogeneity ( I 2 = 97.60%; P < 0.100), suggesting that caution is needed when generalizing these findings. The prevalence of LGA deliveries among women with GD was found to be more likely a result of several identified factors, including multiparity (≥2), prepregnancy overweight/obesity, excessive gestational weight gain, unstable blood glucose control during pregnancy, hypertriglyceridemia in pregnancy, and low levels of high‐density lipoprotein cholesterol in pregnancy. Conclusions The prevalence of LGA deliveries among women with GD was approximately 14.5%. Identifying the associated risk factors allowed for more precise screening for high‐risk populations, enabling timely interventions to reduce the incidence of LGA deliveries among women with GD. PROSPERO registration no. CRD42024559013.
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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 | 0.013 | 0.043 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.037 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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".