Pregnancy outcomes in type 2 versus type 1 diabetes: systematic review with meta-analyses
Bibliographic record
Abstract
Objective: Increasing numbers of pregnancies are complicated by pregestational diabetes mellitus, especially type 2 diabetes (T2DM). Some studies have reported similar or greater risks of adverse pregnancy outcomes among women with T2DM relative to type 1 diabetes (T1DM). We aimed to compare the risk of four pregnancy complications: pre-eclampsia, preterm delivery, macrosomia, and perinatal mortality, in pregnant women with T2DM vs T1DM in high-income countries. Design: Systematic review with meta-analyses. Methods: Systematic literature searches in Medline and Embase were performed. We included observational studies with original data of outcome occurrence in both women with pregestational T2DM and T1DM. Two researchers independently evaluated full-text studies for inclusion and assessed the risk of bias using the Newcastle-Ottawa scale. Finally, we performed four meta-analyses. Results: We included 35 publications in total. Meta-analyses demonstrated that, compared to T1DM, T2DM was associated with a lower risk of pre-eclampsia (risk ratio (RR): 0.76; 95% CI: 0.68-0.85), preterm delivery (RR: 0.69; 95% CI: 0.62-0.77), and macrosomia (RR: 0.75; 95% CI: 0.60-0.94). Perinatal mortality was more likely in pregnancies with T2DM (RR: 1.26; 95% CI: 1.06-1.50). Conclusion: A summation of the research literature demonstrated that, compared to T1DM, women with T2DM had a lower risk of pre-eclampsia, preterm delivery, and macrosomia, but a higher risk of perinatal mortality. Significance statement: Our review of pregnant women with diabetes suggests a higher risk of perinatal mortality for cases with maternal type 2 diabetes, even though the risks of pre-eclampsia, preterm delivery, and macrosomia were higher in cases with type 1 diabetes. Hence, the prevention of the development of type 2 diabetes and focus on improved gestational and diabetic care could be beneficial for fetal health.
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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 | 0.012 | 0.035 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.023 | 0.045 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".