All-Cause and Cause-Specific Mortality After Hypertensive Disease of Pregnancy
Bibliographic record
Abstract
OBJECTIVE: To assess whether women with a history of hypertensive disease of pregnancy have increased risk for early adult mortality. METHODS: In this retrospective cohort study, women with one or more singleton pregnancies (1939-2012) with birth certificate information in the Utah Population Database were included. Diagnoses were categorized into gestational hypertension; preeclampsia; hemolysis, elevated liver enzymes, and low platelet count syndrome; and eclampsia. Women with more than one pregnancy with hypertensive disease (exposed) were included only once, assigned to the most severe category. Exposed women were matched one to two to unexposed women by age, year of childbirth, and parity at the time of the index pregnancy. The causes of death were ascertained using Utah death certificates and the fact of death was supplemented with the Social Security Death Index. Hazard ratios for cause-specific mortality among exposed women compared with unexposed women were estimated using Cox regressions adjusting for neonatal sex, parental education, preterm delivery, race-ethnicity, and maternal marital status. RESULTS: A total of 60,580 exposed women were matched to 123,140 unexposed women; 4,520 (7.46%) exposed and 6,776 (5.50%) unexposed women had died by 2012. All-cause mortality was significantly higher among women with hypertensive disease of pregnancy (adjusted hazard ratio [HR] 1.65, 95% confidence interval [CI] 1.57-1.73). Exposed women's greatest excess mortality risks were from Alzheimer disease (adjusted HR 3.44, 95% CI 1.00-11.82), diabetes (adjusted HR 2.80, 95% CI 2.20-3.55), ischemic heart disease (adjusted HR 2.23, 95% CI 1.90-2.63), and stroke (adjusted HR 1.88, 95% CI 1.53-2.32). CONCLUSION: Women with hypertensive disease of pregnancy have increased mortality risk, particularly for Alzheimer disease, diabetes, ischemic heart disease, and stroke.
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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 | 0.000 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".