Incidence and Timing of Presentation of Necrotizing Enterocolitis in Preterm Infants
Bibliographic record
Abstract
OBJECTIVES: To examine the variation in the incidence and to identify the timing of the presentation of necrotizing enterocolitis (NEC) in a cohort of preterm infants within the Canadian Neonatal Network (CNN). METHODS: This was a population-based cohort of 16 669 infants with gestational age (GA) <33 weeks, admitted to 25 NICUs participating in the CNN between January 1, 2003, and December 31(,) 2008. Variations in NEC incidence among the participating NICUs for the study period were examined. We categorized early-onset NEC as occurring at <14 days of age and late-onset NEC occurring at ≥14 days. Multivariate logistic regression analysis was performed to identify risk factors for early-onset NEC. RESULTS: The overall incidence of NEC was 5.1%, with significant variation in the risk adjusted incidence among the participating NICUs in the CNN. Early-onset NEC occurred at a mean of 7 days compared with 32 days for late-onset NEC. Early-onset NEC infants had lower incidence of respiratory distress syndrome, patent ductus treated with indomethacin, less use of postnatal steroids, and shorter duration of ventilation days. Multivariate logistic regression analysis identified that greater GA and vaginal delivery were associated with increased risk of early-onset NEC. CONCLUSIONS: Among infants <33 weeks' gestation, NEC appears to present at mean age of 7 days in more mature infants, whereas onset of NEC is delayed to 32 days of age in smaller, lower GA infants. Further studies are required to understand the etiology of this disease process.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".