Neurodevelopmental impairment in necrotising enterocolitis survivors: systematic review and meta-analysis
Bibliographic record
Abstract
AIM: To determine (1) the incidence of neurodevelopmental impairment (NDI) in necrotising enterocolitis (NEC), (2) the impact of NEC severity on NDI in these babies and (3) the cerebral lesions found in babies with NEC. METHODS: Systematic review: three independent investigators searched for studies reporting infants with NDI and a history of NEC (PubMed, Medline, Cochrane Collaboration, Scopus). Meta-analysis: using RevMan V.5.3, we compared NDI incidence and type of cerebral lesions between NEC infants versus preterm infants and infants with medical vs surgical NEC. RESULTS: Of 10 674 abstracts screened, 203 full-text articles were examined. In 31 studies (n=2403 infants with NEC), NDI incidence was 40% (IQR 28%-64%) and was higher in infants with surgically treated NEC (43%) compared with medically managed NEC (27%, p<0.00001). The most common NDI in NEC was cerebral palsy (18%). Cerebral lesions: intraventricular haemorrhage (IVH) was more common in NEC babies (26%) compared with preterm infants (18%; p<0.0001). There was no difference in IVH incidence between infants with surgical NEC (25%) and those treated medically (20%; p=0.4). The incidence of periventricular leukomalacia (PVL) was significantly increased in infants with NEC (11%) compared with preterm infants (5%; p<0.00001). CONCLUSIONS: This study shows that a large proportion of NEC survivors has NDI. NEC babies are at higher risk of developing IVH and/or PVL than babies with prematurity alone. The degree of NDI seems to correlate to the severity of gut damage, with a worse status in infants with surgical NEC compared with those with medical NEC. TRIAL REGISTRATION NUMBER: CRD42019120522.
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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 | 0.009 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.033 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| 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".