Pregnancy risks in women with pre-existing coronary artery disease, or following acute coronary syndrome
Bibliographic record
Abstract
OBJECTIVE: The objective of this study was to determine outcomes in pregnant women with pre-existing coronary artery disease (CAD) or following an acute coronary syndrome (ACS) including myocardial infarction (MI). BACKGROUND: The physiological changes of pregnancy can contribute to myocardial ischaemia. The pregnancy risk for women with pre-established CAD or a history of ACS/MI is not well studied. METHODS: This was a retrospective multicentre study. Adverse maternal cardiac, obstetric and fetal/neonatal events were examined. The primary outcome was a composite endpoint of cardiac arrest, ACS/MI, ventricular arrhythmia or congestive heart failure. The prevalence of new or progressive angina during pregnancy was also examined. RESULTS: Fifty pregnancies in 43 women (mean age 35±5 years) were included. Coronary atherosclerosis (40%) and coronary thrombus (36%) were the most common underlying diagnoses. The primary outcome occurred in 10% (5/50) of pregnancies and included one maternal death secondary to cardiac arrest. Other events included ACS/MI (3/50) and heart failure (1/50). New or progressive angina occurred in 18% of pregnancies. Ischaemic complications of any type (new or progressive angina, ACS/MI, ventricular arrhythmia, cardiac arrest) occurred more commonly in women with coronary atherosclerosis compared with those without (50% vs 10%, p=0.003). A high rate of adverse obstetric (16%) and fetal/neonatal (30%) events was observed. CONCLUSIONS: Pregnant women with pre-existing CAD or ACS/MI before pregnancy are at increased risk of adverse events during pregnancy. Those with coronary atherosclerosis are at highest risk of adverse maternal cardiac events due to myocardial ischaemia during pregnancy.
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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 | 0.003 |
| 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) | 0.001 | 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".