Long‐Term Cardiovascular Outcomes After Pregnancy in Women With Heart Disease
Bibliographic record
Abstract
Background Women with heart disease are at risk for pregnancy complications, but their long‐term cardiovascular outcomes after pregnancy are not known. Methods and Results We examined long‐term cardiovascular outcomes after pregnancy in 1014 consecutive women with heart disease and a matched group of 2028 women without heart disease. The primary outcome was a composite of mortality, heart failure, atrial fibrillation, stroke, myocardial infarction, or arrhythmia. Secondary outcomes included cardiac procedures and new hypertension or diabetes mellitus. We compared the rates of these outcomes between women with and without heart disease and adjusted for maternal and pregnancy characteristics. We also determined if pregnancy risk prediction tools (CARPREG [Canadian Cardiac Disease in Pregnancy] and World Health Organization) could stratify long‐term risks. At 20‐year follow‐up, a primary outcome occurred in 33.1% of women with heart disease, compared with 2.1% of women without heart disease. Thirty‐one percent of women with heart disease required a cardiac procedure. The primary outcome (adjusted hazard ratio, 19.6; 95% CI, 13.8–29.0; P <0.0001) and new hypertension or diabetes mellitus (adjusted hazard ratio, 1.6; 95% CI, 1.4–2.0; P <0.0001) were more frequent in women with heart disease compared with those without. Pregnancy risk prediction tools further stratified the late cardiovascular risks in women with heart disease, a primary outcome occurring in up to 54% of women in the highest pregnancy risk category. Conclusions Following pregnancy, women with heart disease are at high risk for adverse long‐term cardiovascular outcomes. Current pregnancy risk prediction tools can identify women at highest risk for long‐term cardiovascular events.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".