Adverse Neonatal and Cardiac Outcomes Are More Common in Pregnant Women With Cardiac Disease
Bibliographic record
Abstract
BACKGROUND: Pregnant women with heart disease (HD) are at increased risk for cardiac (CV) complications. However, the frequency of neonatal (NE) complications in pregnant women with HD relative to pregnant women without HD has not been examined. METHODS AND RESULTS: Pregnant women with HD were prospectively monitored during 302 pregnancies. The frequency of NE and CV complications was compared with those in a control group without HD during 572 pregnancies. The frequency of NE complications was higher in the HD group (18% versus 7%; HD versus controls). The NE complication rate was lowest in pregnancies of women age 20 to 35 years who did not smoke during pregnancy, did not receive anticoagulants, and had no obstetric risk factors: 4% in control patients, 5% in HD patients with no cardiac risk factors for NE complications (left heart obstruction, poor functional class, or cyanosis), and 7% in HD patients with > or =1 such risk factor. In contrast, the event rate in pregnancies of controls age <20 or >35 years who had obstetric risk factors or multiple gestation or who smoked was 11%. In the HD group, women age <20 or >35 years who had obstetric risk factors or multiple gestation, who smoked, or who received anticoagulants experienced an even higher NE complication rate (27% with no cardiac risks for NE events and 33% in the presence of >or =1 cardiac risk factors). The frequency of CV complications was higher in the HD group (17% versus 0%; HD versus controls). CONCLUSION: Pregnant women with HD are at increased risk for both NE and CV complications. The risk for NE adverse events in pregnant women with HD is highest in those with both obstetric and cardiac risk factors for NE complications.
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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 | 0.008 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".