Factors influencing necrotizing enterocolitis in premature infants in China: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Necrotizing enterocolitis (NEC) is a multifactorial gastrointestinal disease with high morbidity and mortality among premature infants. However, studies with large samples on the factors of NEC in China have not been reported. This meta-analysis aims to systematically review the literature to explore the influencing factors of necrotizing enterocolitis in premature infants in China and provide a reference for the prevention of NEC. METHODS: PubMed, Embase, Web of Science, Cochrane Library, China National Knowledge Infrastructure (CNKI), China Biomedical Literature Database (CBM), Wanfang and VIP databases were systematically searched from inception to February 2023. We used Stata14.0 software to perform the systematic review and meta-analysis. We used fixed or random effects models with combined odds ratios (ORs) and 95% confidence intervals (CIs), and quality was evaluated using the Newcastle‒Ottawa Scale (NOS). RESULTS: The total sample was 8616 cases, including 2456 cases in the intervention group and 6160 cases in the control group. It was found that 16 risk factors and 3 protective factors were related to necrotizing enterocolitis in premature infants. Septicemia (OR = 3.91), blood transfusion (OR = 2.41), neonatal asphyxia (OR = 2.46), pneumonia (OR = 6.17), infection (OR = 5.99), congenital heart disease (OR = 4.80), intrahepatic cholestasis of pregnancy (ICP) (OR = 2.71), mechanical ventilation (OR = 1.44), gestational diabetes mellitus (GDM) (OR = 3.08), respiratory distress syndrome (RDS) (OR = 3.28), hypoalbuminemia (OR = 2.80), patent ductus arteriosus (PDA) (OR = 3.10), respiratory failure (OR = 7.51), severe anemia (OR = 2.86), history of antibiotic use (OR = 2.12), and meconium-stained amniotic fluid (MSAF) (OR = 3.14) were risk factors for NEC in preterm infants in China. Breastfeeding (OR = 0.31), oral probiotics (OR = 0.36), and prenatal use of glucocorticoids (OR = 0.38) were protective factors for NEC in preterm infants. CONCLUSIONS: Septicemia, blood transfusion, neonatal asphyxia, pneumonia, infection, congenital heart disease, ICP, GDM, RDS, hypoproteinemia, PDA, respiratory failure, severe anemia, history of antibiotic use and MSAF will increase the risk of NEC in premature infants, whereas breastfeeding, oral probiotics and prenatal use of glucocorticoids reduce the risk. Due to the quantity and quality of the included literature, the above findings need to be further validated by more high-quality studies.
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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 | 0.010 | 0.019 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.034 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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 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".