Preeclampsia and Respiratory Distress Syndrome in Preterm Infants: a meta-analysis
Bibliographic record
Abstract
Objective To systematically assess the association between maternal pre-eclampsia (PE) and the risk of respiratory distress syndrome (RDS) in preterm offspring.Methods A meta-analysis was performed on selected case-control studies regarding maternal pre-eclampsia and RDS in offspring involving RDS patients regardless of age or ethnicity, after searching PubMed, Web of Science, Embase, Cochrane Library, CNKI, WanFang Data, and CBM up to November 2025. The main outcome was RDS confirmed by imaging, duration of ventilation support, or related diagnostic criteria. Pre-eclampsia was defined as sBP ≥ 140 mmHg and/or dBP ≥ 90 mmHg accompanied by proteinuria, elevated creatinine, reduced platelet count, elevated liver enzymes, cerebral or visual symptoms, or persistent epigastric pain. The quality of included studies was assessed using the Newcastle-Ottawa Scale (≥6 scores). Statistical analysis was carried out using Stata 17.0 software, and heterogeneity was determined by Q test combined with I² test. In accordance with the heterogeneity test results, the appropriate model (random or fixed) was selected. Subgroup analysis was performed. Potential publication bias was assessed by funnel plots.Results A total of 12 high-quality studies involving 216,833 subjects were included. The pooled results showed that the risk of RDS in preterm offspring born to mothers with pre-eclampsia was 1.24 times that of mothers without PE (OR=1.24, 95% CI: 1.14–1.35, P<0.05). Subgroup analysis indicated that study design was an important source of heterogeneity.Conclusion Maternal pre-eclampsia may increase the risk of RDS in preterm offspring. Neonatal care providers should maintain heightened vigilance for the offspring of women with pre-eclampsia and consider implementing early interventions to reduce the incidence of RDS.
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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 | 0.025 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.022 | 0.052 |
| Bibliometrics | 0.007 | 0.006 |
| 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".