Influence of Maternal Factors on Health Outcomes in Gastroschisis: A Canadian Population-Based Study
Bibliographic record
Abstract
BACKGROUND: Gastroschisis is increasing in incidence worldwide. There is a need for a disease-specific, population-based approach to determining factors linked with gastroschisis and its outcome. OBJECTIVES: To examine racial, socioeconomic, health and geographic predictors of gastroschisis and its outcome in Canada. METHODS: 535 cases of gastroschisis from the Canadian Pediatric Surgery Network national database were included from May 2005 to May 2010. Baseline characteristics of mothers were compared with those reported by Statistics Canada. Factors associated with adverse neonatal outcomes were examined using regression analyses. RESULTS: Mothers of infants with gastroschisis are young, often from small communities. Smoking (37%) and illicit drug use are common in this population. Single mothers receive less perinatal care (OR 0.06; 95% CI 0.02-0.28). Geographically isolated mothers are more likely to undergo caesarian section (OR 3.84; 95% CI 1.26-11.74). Cocaine use predicts a lower odds of delivering at a planned center (OR 0.25; 95% CI 0.08-0.79), and is also associated with an increased likelihood of intestinal injury at birth (OR 6.26; 95% CI 1.52-25.72). Infants of mothers from isolated communities will spend a mean of 31.9 days longer in hospital. Aboriginal status is not independently predictive of perinatal or neonatal outcome. CONCLUSION: Gastroschisis in Canada occurs frequently in young mothers, aboriginals and smokers. Features associated with worse outcomes include single parent status, cocaine use and maternal hometown geographic isolation.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".