Elective Delivery versus Expectant Management for Gastroschisis: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Abstract Introduction The optimal timing of delivery for pregnancies complicated by prenatally diagnosed gastroschisis remains controversial. Therefore, the aim of this study was to find whether elective or expectant delivery is associated with improved neonatal outcome. Materials and Methods MEDLINE and Embase databases were searched for studies up to 2021 that reported timing of delivery for prenatally diagnosed gastroschisis. A systematic review and meta-analysis were then performed in group 1: moderately preterm (gestational age [GA]: 34–35 weeks) elective delivery versus expectant management after GA 34–35 weeks; and group 2: near-term (GA: 36–37 weeks) elective delivery versus expectant management after GA 36–37 weeks. The following clinical outcomes were evaluated: length of stay (LOS), total parenteral nutrition (TPN) days, bowel morbidity (atresia, perforation, and volvulus), sepsis, time of first feeding, short gut syndrome and respirator days, and mortality. Results Two randomized controlled trials (RCT)s and eight retrospective cohort studies were included, comprising 629 participants. Moderately preterm elective delivery failed to improve clinical outcomes. However, near-term elective delivery significantly reduced bowel morbidity (7.4 vs. 15.4%, relative risk = 0.37; 95% confidence interval [CI]: 0.18, 0.74; p = 0.005; I2 = 0%) and TPN days (mean difference =−13.44 days; 95% CI: −26.68, −0.20; p = 0.05; I2 = 45%) compared to expectant delivery. The mean LOS was 39.2 days after near-term delivery and 48.7 days in the expectant group (p = 0.06). Conclusion Based on the data analyzed, near-term elective delivery (GA 36–37 weeks) appears to be the optimal timing for delivery of pregnancies complicated by gastroschisis as it is associated with less bowel morbidity and shorter TPN days. However, more RCTs are necessary to better validate these findings.
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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 | 0.026 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.021 | 0.036 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| 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".