Multidisciplinary management of heart disease in pregnancy: a single centre experience
Bibliographic record
Abstract
Background Heart disease in pregnancy is a leading cause for maternal morbidity and mortality as highlighted by CEMACH (2003–2005). Methods and results 60 women (59 singletons and one twin) with heart disease were seen jointly by maternal medicine team and cardiologist in 4 months. 22 patients had congenital heart disease, 21 had arrhythmias, 5 had cardiomyopathies, 3 had acquired valvular disease, 7 had persistent cardiac symptoms in pregnancy and 1 had collagen tissue disorder. Mean age of these women was 27.8 years and at each visit, symptoms were evaluated using NYHA classification. Three women were NYHA 2 pre pregnancy and remaining were NYHA 1. 27 women had Toronto risk score of 1 and 33 had a score of 0. Nine women were on medication such as flecanide, sotalol, bisoprolol and propranalol. 19 of the 59 (32%) had caesarean sections (CS) 17 for obstetric indications, 1 for cardiac reason and one for cardiac and obstetric indications. Two women had planned admission to intensive care postoperatively following planned CS. 40/59 patients (65%) had vaginal delivery and one had a spontaneous abortion at 18 weeks gestation. The average neonatal birth weight was 3.08 kg and there was no adverse neonatal outcome. 27 women had fetal echocardiography. Conclusion Cardiac diseases of varying severity were managed with good outcome for mother and baby. This has been possible because of a joint clinical approach between Obstetric and cardiology team, which enabled early risk stratification and effective planning for pregnancy and delivery.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| 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".