Maternal Cigarette Smoking and the Development of Necrotizing Enterocolitis
Bibliographic record
Abstract
BACKGROUND: The maternal variables that affect fetal development and correlate with necrotizing enterocolitis (NEC), the most common gastrointestinal emergency in premature infants, are not well defined. We hypothesized that maternal risk factors were the primary determinant of future development of NEC. METHODS: Patients with NEC were identified from an established NICU database and were control-matched with 2 neonates treated at the same institution. The medical records of each patient during the NICU admission as well as the prenatal and delivery record of the patient's mother were reviewed. Perinatal data, including maternal smoking, maternal hypertension, maternal BMI, maternal gestational diabetes, conduct of labor and type of delivery, Apgar scores, types of feedings, and placental pathology, were examined, with P < .05 deemed significant. RESULTS: A total of 73 neonates diagnosed with NEC and 146 matched controls were identified. Medical records for each subject and their mothers were reviewed (438 records total). Maternal cigarette smoking was significantly associated with the future development of NEC (P = .02). Maternal gestational diabetes, maternal hypertension, formula feeding, and pathologic chorioamnionitis or uteroplacental insufficiency did not correlate with NEC. CONCLUSIONS: These data identified maternal cigarette smoking as the only risk factor that is associated with the development of NEC in premature infants. Our data imply that smoking delivers toxins and nicotine to the uterine microenvironment that can affect microvascular development and may predispose the fetus to future NEC.
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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 | 0.000 | 0.003 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".