Association between Pregnancy-Associated Diabetes and Macrosomia: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
Background: Diabetes mellitus (DM) is a major challenge for public health worldwide. Pre-existing diabetes and gestational diabetes (GDM) are linked to poor outcomes in pregnancy, perinatal and maternal. Research indicates that GDM has become significantly more prevalent in several countries, increasing by over 30%. Glycemic control in women during pregnancy plays a major role in the health status of the mother and fetus. Macrosomia is one of the most critical adverse outcomes of DM, which results in negative consequences for the health of infants. This systematic review and meta-analysis study aimed to investigate the association between pregnancy diabetes and macrosomia in infants. Methods: A comprehensive systematic search was conducted in electronic databases, from inception up to August 2024 to obtain related studies. Two independent researchers evaluated the studies based on the objectives of the study. The pooled effect size was computed using pooled odds risks (ORs) with 95% confidence intervals (CIs). Additionally, we conducted publication bias assessments, sensitivity analyses, and subgroup analyses. The statistical analysis incorporated twelve studies. Quality assessment of included studies was conducted using the Newcastle-Ottawa Scale (NOS). Results: Statistical analysis in the present study on the pregnant diabetic mother and infants with macrosomia demonstrated a direct significant association between DM and macrosomia (OR: 2.94, 95% CI: 2.06-4.20, P <0.0001) and (OR: 8.17, 95% CI: 4.85-13.75, P<0.0001), respectively. Sub-group analysis revealed subjects with pre-gestational diabetes against GDM, had a greater risk of delivering an infant with macrosomia. Conclusion: The results revealed a significant association between all three types of GDM. All three types of diabetes can lead to macrosomia, but pre-gestational diabetes has a more significant positive relationship with macrosomia. However, improving lifestyle can be considered as key strategy against macrosomia and associated diabetic complications.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".