Maternal and newborn outcomes among women with schizophrenia: a retrospective population‐based cohort study
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: More women with schizophrenia are becoming pregnant, such that contemporary data are needed about maternal and newborn outcomes in this potentially vulnerable group. We aimed to quantify maternal and newborn health outcomes among women with schizophrenia. DESIGN: Retrospective cohort study. SETTING: Population based in Ontario, Canada, from 2002 to 2011. POPULATION: Ontario women aged 15-49 years who gave birth to a liveborn or stillborn singleton infant. METHODS: Women with schizophrenia (n = 1391) were identified based on either an inpatient diagnosis or two or more outpatient physician service claims for schizophrenia within 5 years prior to conception. The reference group comprised 432 358 women without diagnosed mental illness within the 5 years preceding conception in the index pregnancy. MAIN OUTCOME MEASURES: The primary maternal outcomes were gestational diabetes mellitus, gestational hypertension, pre-eclampsia/eclampsia, and venous thromboembolism. The primary neonatal outcomes were preterm birth, and small and large birthweight for gestational age (SGA and LGA). Secondary outcomes included additional key perinatal health indicators. RESULTS: Schizophrenia was associated with a higher risk of pre-eclampsia (adjusted odds ratio, aOR 1.84; 95% confidence interval, 95% CI 1.28-2.66), venous thromboembolism (aOR 1.72, 95% CI 1.04-2.85), preterm birth (aOR 1.75, 95% CI 1.46-2.08), SGA (aOR 1.49, 95% CI 1.19-1.86), and LGA (aOR 1.53, 95% CI 1.17-1.99). Women with schizophrenia also required more intensive hospital resources, including operative delivery and admission to a maternal intensive care unit, paralleled by higher neonatal morbidity. CONCLUSIONS: Women with schizophrenia are at higher risk of multiple adverse pregnancy outcomes, paralleled by higher neonatal morbidity. Attention should focus on interventions to reduce the identified health disparities.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 it