Associations between polycystic ovary syndrome and adverse obstetric and neonatal outcomes: a population study of 9.1 million births
Bibliographic record
Abstract
STUDY QUESTION: Does polycystic ovary syndrome (PCOS) confer an independent risk for adverse delivery and neonatal outcomes, based on analysis of the Healthcare Cost and Utilization Project-Nationwide Inpatient Sample (HCUP-NIS) database? SUMMARY ANSWER: After controlling for all potential confounding effects, women with PCOS are at an increased risk of experiencing preterm pre-labour rupture of membranes (PPROM), pre-term delivery (PTD), placental abruption, caesarean section (C/S) delivery, chorioamnionitis and post-partum maternal infections. WHAT IS KNOWN ALREADY: PCOS may be associated with an increased risk of adverse perinatal outcomes. However, there remain significant gaps in understanding the correlation between PCOS and important delivery and neonatal complications. STUDY DESIGN, SIZE, DURATION: This is a retrospective population-based cohort study utilising data from the HCUP-NIS over 11 years from 2004 to 2014. A cohort of all deliveries between 2004 and 2014 inclusively was created. Within this group, all deliveries to women with PCOS were identified as part of the study group (n = 14 882), and the remaining deliveries were categorised as non-PCOS births and comprised the reference group (n = 9 081 906). PARTICIPANTS/MATERIALS, SETTING, METHODS: The HCUP-NIS is the largest inpatient sample database in the USA and it is comprised of hospital inpatient stays throughout the entire country. It provides information relating to 7 million inpatient stays per year, includes ∼20% of admissions, and represents over 96% of the American population. MAIN RESULTS AND THE ROLE OF CHANCE: After adjustment for all potential confounders, women with PCOS were more likely to experience PPROM (aOR 1.48, 95% CI 1.20-1.83), PTD (aOR 1.37 95% CI 1.24-1.53) and placental abruption (aOR 1.63, 95% CI 1.30-2.05) and were more likely to deliver by C/S (aOR 1.50, 95% CI 1.40-1.61 (all P < 0.001). Women with PCOS more often developed chorioamnionitis (aOR 1.58, 95% CI 1.34-1.86, P < 0.001) and maternal infections (aOR 1.58, 95% CI 1.36-1.84 (both P < 0.001)). With the exception of multiple gestations (aOR 1.27, 95% CI 1.01-1.62, P = 0.04), there was no difference in the number of women who gave birth to small for gestational age (SGA) infants (aOR 0.97, 95% CI 0.82-1.15, P = 0.72) between the women with PCOS and the reference group. Intrauterine foetal deaths (IUFDs) were also comparable between the two groups (aOR 1.03, 95% CI 0.68-1.59, P = 0.88). However, congenital anomalies were more likely to occur in the offspring of women with PCOS (aOR 1.89, 95% CI 1.51-2.38, P < 0.001). LIMITATIONS, REASONS FOR CAUTION: This is a retrospective analysis utilising an administrative database which relies on the accuracy and consistency of the individuals coding the data. There are known limitations in how accurately hospital coding is able to capture perinatal conditions and complications, making it difficult to know with certainty that such events are accurate. WIDER IMPLICATIONS OF THE FINDINGS: Women with PCOS are more likely to experience adverse delivery and neonatal outcomes. It is important to additionally consider the risk of all other co-existing conditions frequently encountered in PCOS women, as these risks are additive and place women with PCOS at significantly increased risk of adverse pregnancy outcomes. STUDY FUNDING/COMPETING INTEREST(S): No specific funding was obtained for this study. The authors have no conflicts of interest to disclose.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| 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 | 0.001 |
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".