Pregnant women with congenital heart disease: cardiac, anesthetic and obstetrical implications
Bibliographic record
Abstract
Remarkable advances in surgical and clinical management have resulted in survival to adulthood in the large majority of patients with congenital heart malformations, even with the most complex disease. Over 1 million adults with congenital heart disease currently live in the USA, approximately half of whom are women of childbearing age. Collectively, congenital malformations are the most common form of heart disease in pregnant women. Indeed, in North America, congenital defects are now the leading cause of maternal morbidity and mortality from heart disease. This article begins with a summary of cardiovascular changes during pregnancy and highlights key features in pre-pregnancy counseling, maternal cardiac and obstetric risk, and neonatal complications. Management issues regarding pregnancy and delivery are elaborated, including anesthesia considerations. While it is beyond the scope of this article to discuss particulars related to all forms of congenital heart disease, selected subtypes are detailed at greater length. In the absence of clinical trial evidence to inform the care of pregnant women with congenital heart disease, this article is inspired by the premise that knowledgeable multidisciplinary assessment and management provides the best opportunity to substantially improve outcomes for mother and baby.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.002 | 0.001 |
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".