Neonatal outcomes with caesarean delivery at term
Bibliographic record
Abstract
OBJECTIVE: To estimate the impact of caesarean delivery on the incidence of selected neonatal outcomes. PATIENTS AND METHODS: A 15-year, population-based, cohort study (1988-2002) using the Nova Scotia Atlee Perinatal Database compared neonatal outcomes in term newborns born by spontaneous and assisted vaginal delivery, with newborns born by caesarean delivery, with and without labour, using multiple logistic regression. RESULTS: From a total of 142 929 deliveries, there were 27 263 caesarean deliveries, 61% of which were performed in labour. Relative risks were adjusted for year of birth, maternal age, parity, smoking, maternal weight at delivery, hypertensive diseases, diabetes, previous caesarean delivery, use of regional anaesthesia, induction of labour, gestational age at delivery and large and small for gestational age, where significant. Caesarean delivery in labour, but not caesarean delivery without labour, had increased risks for depression at birth and neonatal respiratory conditions compared with spontaneous or assisted vaginal delivery. Compared with spontaneous vaginal delivery and assisted vaginal delivery, the risk of major neonatal birth trauma was decreased for infants after caesarean delivery with labour (odds ratio (OR) = 0.34, 95% CI 0.21 to 0.56 and OR = 0.07, 95% CI 0.04 to 0.11, respectively) and caesarean delivery without labour (OR = 0.20, 95% CI 0.08 to 0.52 and OR = 0.04, 95% CI 0.02 to 0.10, respectively). CONCLUSION: Caesarean delivery in labour, compared with vaginal delivery, is more likely to be associated with an increased risk for respiratory conditions and depression at birth than caesarean delivery without labour. Caesarean delivery appears protective against neonatal birth trauma, especially when performed without labour.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".