Neonatal outcomes among multiple births ≤ 32 weeks gestational age: Does mode of conception have an impact? A Cohort Study
Bibliographic record
Abstract
BACKGROUND: Studies comparing perinatal outcomes in multiples conceived following the use of artificial reproductive technologies (ART) vs. spontaneous conception (SC) have reported conflicting results in terms of mortality and morbidity. Therefore, the objective of our study was to compare composite outcome of mortality and severe neonatal morbidities amongst preterm multiple births ≤ 32 weeks gestation infant born following ART vs. SC. METHODS: We conducted a single center cohort study at Mount Sinai Hospital, Toronto, Ontario, Canada. Data on all preterm multiple births (≤ 32 weeks GA) discharged between July 2005 and June 2008 were retrospectively collected from a prospective database at our centre. Details regarding mode of conception were collected retrospectively from maternal health records. Preterm multiple births were categorized into those born following ART vs. SC. Composite outcome was defined as combination of death or any of the three neonatal morbidities (grade 3/4 intraventricular hemorrhage or periventricular leukomalacia; retinopathy of prematurity > stage 2 or chronic lung disease). Univariate and multivariate regression analysis were preformed after adjustment of confounders (maternal age, parity, triplets, gestational age, sex, and small for gestational age). RESULTS: One hundred and thirty seven neonates were born following use of ART and 233 following SC. The unadjusted composite outcome rate was significantly higher in preterm multiples born following ART vs. SC [43.1% vs. 26.6%, p = 0.001; OR 1.98 (95% CI 1.13, 3.45)]; however, when adjusted for confounders the difference between groups was not statistically significant [OR 1.39, 95% CI 0.67, 2.89]. CONCLUSION: In our population of preterm multiple births, the mode of conception had no detectable effect on the adjusted composite neonatal outcome of mortality and/or three neonatal morbidities.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".