Preeclampsia Brings the Risk of Premature Cardiovascular Disease in Women Closer to That of Men
Bibliographic record
Abstract
BACKGROUND: It is not known if sex differences in the risk of premature cardiovascular disease (CVD) vary by whether a woman had preeclampsia or not. The current study determined whether prior preeclampsia brings a woman's risk of CVD closer to that of a male counterpart. METHODS: A population-based cohort study was completed in Ontario, Canada, from 1993 to 2017. Participants were 55,186 women with prior preeclampsia, 110,372 randomly selected age- and region-matched men, and 110,372 similarly selected women who gave birth without prior preeclampsia. The primary outcome was a CVD composite outcome of any hospitalization or revascularization for coronary artery disease, cerebrovascular disease, peripheral artery disease, heart failure, and dysrhythmia. RESULTS: Median follow-up was approximately 16 years. Relative to women without prior preeclampsia (1193 events; 7.5 per 10,000 person-years), men had the highest risk of CVD (3706 events; 24.3 per 10,000 person-years) (adjusted hazard ratio [aHR], 2.52; 95% confidence interval [CI], 2.35-2.69). Women with a history of preeclampsia were also at higher risk (1252 events; 16.0 per 10,000 person-years) (aHR, 1.17; 95% CI, 1.08-1.28). Women with preeclampsia requiring preterm delivery were even more likely to experience CVD (21.5 per 10,000 person-years) (aHR, 1.44; 95% CI, 1.18-1.76). The absolute risk of CVD in men (22.5 per 10,000 person-years) was similar to the risk in women with preeclampsia and preterm delivery, but men had the highest aHR (2.48; 95% CI, 2.11-2.93). CONCLUSIONS: Although men remain at significantly higher risk of CVD, a history of preeclampsia, especially with preterm birth, elevates a woman's risk closer to that of a man.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".