Hypertensive Disorders and Cardiovascular Severe Maternal Morbidity in the US, 2015-2019
Bibliographic record
Abstract
Importance: The incidence of severe maternal morbidity (SMM)-and particularly cardiovascular SMM (cvSMM), the first cause of pregnancy-related mortality-has been rising in North America. Although hypertensive disorders of pregnancy (HDP) are common, their association with cvSMM specifically remains unclear. Objective: To assess the association between individual subtypes of HDP and cvSMM, in addition to overall SMM, in a large, nationally representative sample. Design, Setting, and Participants: A population-based cohort study using the United States National Inpatient Sample was conducted. Individuals with obstetric deliveries between 2015 and 2019 were included. Data analysis was performed from October 2023 to February 2024. Exposure: HDP subtypes included gestational hypertension, chronic hypertension, preeclampsia without severe features, severe preeclampsia, and HELLP (hemolysis, elevated liver enzymes, and low platelet) syndrome. Main Outcomes and Measures: The primary outcome was a composite of cvSMM (including conditions such as pulmonary edema, stroke, and acute myocardial infarction) and the secondary outcome was a composite of overall SMM (including cvSMM and other conditions such as respiratory failure, severe postpartum hemorrhage, and sepsis). Adjusted risk ratios (aRRs) for the association between HDP subtypes and the outcomes were estimated using modified Poisson regression models adjusted for demographic and clinical characteristics. Results: Among 15 714 940 obstetric deliveries, 2 045 089 (13.02%) had HDP, 23 445 (0.15%) were affected by cvSMM, and 282 160 (1.80%) were affected by SMM. The mean (SD) age of the cohort was of 29 (6) years. The incidence of cvSMM was higher in participants with HDP than those without HDP (0.48% [9770 of 2 045 089] vs 0.10% [13 680 of 13 669 851]; P < .001). Participants with HELLP syndrome had the highest risk for cvSMM (aRR, 17.55 [95% CI, 14.67-21.01]), followed by severe preeclampsia (aRR, 9.11 [95% CI, 8.26-10.04]), and chronic hypertension (aRR, 3.57 [95% CI, 3.15-4.05]). Although HDP subtypes were also associated with overall SMM, the association with HELLP syndrome (aRR, 9.94 [95% CI, 9.44-10.45]), severe preeclampsia (aRR, 3.66 [95% CI, 3.55-3.78]), and chronic hypertension (aRR, 1.96 [95% CI, 1.88-2.03]) was attenuated compared with cvSMM. Conclusions and Relevance: In this cohort study, a graded relationship by severity characterized the association between HDP and cvSMM. Although all HDP subtypes were associated with an increased risk of overall SMM, the risk was more pronounced for cvSMM.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".