Cardiac magnetic resonance imaging characteristics and pregnancy outcomes in women with Mustard palliation for complete transposition of the great arteries
Bibliographic record
Abstract
Women with transposition of the great arteries (TGA) following atrial redirection surgery are at risk of pregnancy-associated arrhythmia and heart failure. The cardiovascular magnetic resonance imaging (CMR) characteristics of these women and the relationship of CMR findings to pregnancy outcomes have not been described. We included 17 women with atrial redirection surgery and CMR within 2 years of delivery. All women were asymptomatic at baseline (New York Heart Association Class 1). CMR studies were completed pre-pregnancy in 3, antepartum/peripartum in 2, and postpartum in 12 women. Three women (3/17, 18%) experienced major cardiovascular events related to pregnancy: cardiac arrest (n = 1) and symptomatic atrial arrhythmia (n = 2). Median gestational age at delivery was 38 weeks (24–39 weeks) and birth weight was 2770 g (2195–3720 g). Complications were seen in 3 offspring (3/17, 18%): death (n = 1) and prematurity (n = 2). CMR characteristics included median right ventricular end diastolic volume 119 mL/m2 (range 85–214 mL/m2) and median right ventricular ejection fraction (RVEF) 37% (range 30–51%). All women with cardiovascular complications had an RVEF < 35% (range 32–34%). The association between RVEF < 35% and cardiovascular complications trended towards statistical significance (p = 0.05). No statistically significant differences in CMR measurements were found between those with and without neonatal complications. While the majority of women in this cohort had successful outcomes following pregnancy, important cardiovascular complications were seen in a significant minority, all of whom had an RVEF < 35%. The preliminary findings of our study provide impetus for a larger prospective study to evaluate the prognostic role of CMR in pregnant women with atrial redirection surgery.
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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 | 0.005 |
| 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) | 0.001 | 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".