Diabetes in pregnancy may differentially affect neonatal outcomes for twins and singletons
Bibliographic record
Abstract
AIM: We tested the hypothesis that diabetes in pregnancy may differentially affect neonatal outcomes in twin vs. singleton pregnancies. METHODS: In a retrospective cohort analysis of twins (n = 422 068) and singletons (n = 14 298 367) born in the USA from 1998 to 2001, we evaluated the adjusted odds ratios of adverse neonatal outcomes comparing diabetic vs. non-diabetic pregnancies, controlling for maternal characteristics. Primary outcomes include macrosomia (birthweight for gestational age > 90th percentile), congenital anomalies, low 5-min Apgar score (< 4) and neonatal death. RESULTS: Diabetes in pregnancy was associated with a similarly increased risk of congenital anomalies (adjusted odds ratios 1.52 vs. 1.59) and smaller increased risks of preterm birth (adjusted odds ratios 1.27 vs. 1.49) and macrosomia (adjusted odds ratios 1.38 vs. 2.03) in twins vs. singletons, but reduced risks of low 5-min Apgar score (adjusted odds ratio 0.74) and neonatal death (adjusted odds ratio 0.76) in twins but not singletons. CONCLUSIONS: Diabetes in pregnancy may differentially affect neonatal outcomes in twins and singletons, indicating a need for further studies to differentiate the effects by clinical subtypes of diabetes in pregnancy, and to consider/evaluate differential clinical management protocols of diabetes in multiple vs. singleton pregnancies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".