Reproductive and neonatal outcomes in women with unicornuate uterus: a population-based study
Bibliographic record
Abstract
Objective: To investigate reproductive and neonatal outcomes in women with unicornuate uterus. Study design: Data from the Health Care Cost and Utilization Project-Nationwide Inpatient Sample database were extracted from 2010 through 2014 to create a delivery cohort using ICD-9 codes. Code 752.33 was used to identify cases with unicornuate uterus and reproductive outcomes were compared to pregnancies without unicornuate uterus. A multivariate logistic regression model was used to adjust for statistically significant variables (P-value<0.05). Results: Among 3,850,226 deliveries during the study period, 802 women had unicornuate uterus. Patient with unicornuate uterus were more likely to be older (P<0.001), have thyroid disease (P<0.001), previous Caesarean section (P<0.001), and to have had in-vitro fertilization (IVF) (P<0.001). The risk of gestational diabetes, pregnancy induced hypertension, gestational hypertension and preeclampsia were significantly greater in the unicornuate uterus group relative to controls, after controlling for baseline risk factors; aOR 1.32 [95% CI 1.03–1.71], aOR 1.46 [95% CI 1.16–1.85], aOR 1.16 [95% CI 1.22-2.28] and aOR 1.70 [95% CI 1.24-2.32], respectively. Also, the rates of preterm delivery, preterm premature rupture of membranes and caesarean section were higher in the unicornuate uterus group compared to controls after controlling for confounding factors, aOR 3.83 (95% CI 3.19–4.6), aOR 5.11 (95% CI 3.73–7.14) and aOR 11.38 (95% CI 9.16–14.14) respectively. At birth, 11.1% and 2.6% of neonates were small for gestational age in the unicornuate uterus and the control groups, respectively, aOR 4.90, (95% CI 3.87-6.21). Conclusion: Women with unicornuate uterus are at higher risk for pregnancy complications, preterm delivery and having small for gestation age neonates. Women with known unicornuate uterus may benefit from increased surveillance to prevent and/or decrease maternal and neonate morbidity and mortality.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".