Low birthweight, gestational age, need for surgical intervention and gram‐negative bacteraemia predict intestinal failure following necrotising enterocolitis
Bibliographic record
Abstract
AIM: Necrotising enterocolitis (NEC) is associated with high morbidity and mortality. The aim of this study was to identify predictors of intestinal failure (IF), morbidity and mortality following NEC. METHODS: We performed a retrospective study of all neonates treated for NEC stage II or greater at a tertiary referral NICU between 2000 and 2009. Demographic data, need for surgery, residual bowel length and rates of bacteraemia, cholestasis, IF and mortality were analysed. RESULTS: During the 10-year period, 301 patients were referred with NEC and 152 had surgical intervention. Overall mortality was 32%. Of the 230 infants who survived >42 days, 97 (42%) had IF at 42 days, decreasing to 15% at >90 days. The rate of IF was significantly higher in the surgical group than the medical group (OR 2.04, 95% CI, 1.25-3.35, p < 0.004), but 23% of the medically treated infants with NEC also developed IF. There was a significant relationship between IF and gram-negative bacteraemia, the need for surgery, cholestasis, liver failure and mortality. CONCLUSION: Intestinal failure occurred in a significant proportion of infants with NEC. Predictors for IF among infants with NEC were low birthweight, low gestational age, need for surgical intervention and gram-negative bacteraemia.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".