Refining current risk stratification guidelines for pregnant women with Fontan circulation: lessons from PROFAT registry
Bibliographic record
Abstract
BACKGROUND: Pregnancy in women with a Fontan circulation carries increased risk. Given the relative evidence void, pregnancy counseling requires considerable nuance and experience. OBJECTIVES: This study aimed to identify risk factors for maternal and fetal complications and to contrast risk estimates obtained from existing risk stratification tools, including the modified WHO, CARPREG II, and ZAHARA risk scores. METHODS: Pregnant women (>20 weeks of gestation) with a Fontan circulation were retrospectively included from 13 international centers. Univariate and multivariable analyses identified predictors of complications, and the performance of risk stratification tools was assessed. RESULTS: From 2006 to 2018, 84 women with Fontan physiology had 108 pregnancies, and form the basis of this investigation. Maternal cardiovascular complications occurred in 32 (30%) of all pregnancies including Fontan circulatory failure (17%), supraventricular tachycardia (7.4%), and thromboembolic events (3.7%). No maternal deaths occurred. Premature birth constituted 68% of neonatal complications, with a fetal and neonatal mortality of 13%. Multivariable analysis linked adverse maternal outcomes to pre-pregnancy oxygen saturation (adjusted OR 0.77; 95%CI 0.61-0.96; p=0.02). None of the risk models showed good discriminative ability. The modified WHO classification was the only risk model significantly associated with adverse fetal outcomes. CONCLUSIONS: Pregnancy in women with Fontan circulation poses a significant cardiovascular risk for the mother and a high burden of fetal and neonatal complications. The existing predictive risk stratification models do not discriminate hazard between well-functioning patients with Fontan from those with additional hemodynamic burden. This underscores the necessity for large-scale studies to refine risk stratification.
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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 | 0.070 | 0.108 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.006 |
| 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".