Outcomes in pregnant patients with congenital heart disease by rurality
Bibliographic record
Abstract
OBJECTIVES: To examine the association between rurality, major adverse cardiac events (MACE), adverse pregnancy outcomes (APO) and neonatal outcomes in pregnant women with CHD (congenital heart disease). METHODS: A retrospective cohort study using the HCUP-NIS database (Healthcare Cost and Utilization Project-National Inpatient Sample) from 2016 to 2021 was conducted with pregnant CHD patients by location of residence (urban vs. rural). Primary outcomes were MACE, APO and neonatal outcomes. Multivariate logistic regression with survey procedures and weighted odds ratios was used to represent national estimates. RESULTS: The weighted sample represented 24,295 (n=4,859) patients, of which 20,840 (n=4168) were in urban setting and 3,455 (n=691) lived rurally. Only 27 % (n=185/691) of rural patients accessed care at a rural hospital. Rurality was associated with lower odds of APO (adjusted-OR 0.76; 95 %-CI 0.63-0.91; p=0.003). Rural patients with complex CHD had the lowest odds of APO. There was no statistically significant difference, by rurality, in odds of MACE (adjusted-OR 1.17; 95 %-CI 0.98-1.40; p=0.09) or neonatal outcomes (adjusted-OR 0.78; 95 %-CI 0.59-1.03; p=0.082). There was no effect modification of rurality by CHD complexity on the association between rurality and MACE (p-value=0.66), APO (p-value=0.60) or neonatal outcomes (p-value=0.75). CONCLUSIONS: In this national cohort, pregnant patients with CHD living in rural areas had decreased odds of APO and no significant difference in MACE or neonatal complications. Notably, the majority of rural CHD patients received care in urban hospitals, suggesting referral patterns may mitigate outcome disparities. These findings highlight the need for further research on access, delivery of care, and outcomes for rural patients with CHD, and underscore the importance of ensuring multidisciplinary cardio-obstetric care across geographic settings.
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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".