Maternal Diabetes Mellitus and Persistent Pulmonary Hypertension of the Newborn: Accumulated Evidence From Observational Studies
Bibliographic record
Abstract
OBJECTIVES: Maternal diabetes mellitus (including pre-existing and gestational diabetes mellitus) is linked with adverse infant outcomes. However, the question of whether maternal diabetes increases the risk of persistent pulmonary hypertension of the newborn (PPHN) is unclear. Herein, we conducted a systematic review and meta-analysis to summarize clinical evidence to determine the association between maternal diabetes mellitus and PPHN. METHODS: In this systematic review and meta-analysis, we systematically searched PubMed, Embase, Cochrane Library, Web of Science and Google Scholar to identify relevant studies according to predefined criteria. Data from selected studies were extracted, and meta-analysis was performed using fixed effects modelling. RESULTS: In all, we included 7 unique studies with aggregated data on 2 million individuals and >5,000 cases of PPHN. Maternal diabetes was significantly associated with a higher risk of PPHN (risk ratio [RR], 1.37; 95% confidence interval [CI], 1.23 to 1.51). Both case-control and cohort studies exhibited that the presence of maternal diabetes increased the risk of PPHN (case-control: RR, 1.91; 95% CI, 1.02 to 2.79; cohort: RR, 1.36; 95% CI, 1.22 to 1.50). By omitting 1 study at a time, sensitivity analysis made sure that no individual study was entirely responsible for the combined results. CONCLUSIONS: Maternal diabetes was associated with increased risk of PPHN. For babies with refractory hypoxemia, with mothers with diabetes, PPHN should be taken into consideration in clinical practice.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".