Perinatal Outcomes Associated With Preterm Birth at 33 to 36 Weeks’ Gestation: A Population-Based Cohort Study
Bibliographic record
Abstract
OBJECTIVE: The aim of our population-based study was to compare the mortality and morbidity of late-preterm infants to those born at term. Advancement in the care of extremely preterm infants has led to a shift of focus away from the more mature preterms, who are being managed as "near terms" and treated as "near normal." Some recent studies have suggested an increased risk of mortality and morbidity in this group compared with infants born at term. However, there are few population-based mortality and morbidity statistics for this cohort, particularly reflecting current practice. METHODS: Using data from the British Columbia Perinatal Database Registry we analyzed all singleton births between 33 and 40 weeks' gestation from April 1999 to March 2002 in the province of British Columbia, Canada. We divided this birth cohort into late preterm (33-36 weeks, n = 6381) and term (37-40 weeks, n = 88 867) groups. We compared mortality and morbidity data and associated maternal factors between the 2 groups. RESULTS: Stillbirth rate and perinatal, neonatal, and infant mortality rates were significantly higher in the late-preterm group. Infants in this group needed resuscitation at birth more frequently than those in the term group. Late-preterm infants had a significantly higher incidence of respiratory morbidity and infection and had a significantly longer duration of hospital stay. Maternal factors that were more common in the late-preterm group included chorioamnionitis, hypertension, diabetes, thrombophilia, prelabor rupture of membranes, primigravida, and teenage pregnancy. CONCLUSIONS: Our data support recent literature regarding neonatal mortality and morbidity in late-preterm infants and warrants a review of care for this group at the local, national, and global levels. Reorganization of services and increased resource allocation may be needed in most hospitals and community settings to achieve optimization of care for this group of infants.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".