Familial Recurrence Patterns in Congenitally Corrected Transposition of the Great Arteries: An International Study
Bibliographic record
Abstract
BACKGROUND: Congenitally corrected transposition of the great arteries (ccTGA) is a rare disease of unknown cause. We aimed to better understand familial recurrence patterns. METHODS: An international, multicentre, retrospective cohort study was conducted in 29 tertiary hospitals in 6 countries between 1990 and 2018, entailing investigation of 1043 unrelated ccTGA probands. RESULTS: Laterality defects and atrioventricular block at diagnosis were observed in 29.9% and 9.3%, respectively. ccTGA was associated with primary ciliary dyskinesia in 11 patients. Parental consanguinity was noted in 3.4% cases. A congenital heart defect was diagnosed in 81 relatives from 69 families, 58% of them being first-degree relatives, including 28 siblings. The most prevalent defects in relatives were dextro-transposition of the great arteries (28.4%), laterality defects (13.6%), and ccTGA (11.1%); 36 new familial clusters were described, including 8 pedigrees with concordant familial aggregation of ccTGA, 19 pedigrees with familial co-segregation of ccTGA and dextro-transposition of the great arteries, and 9 familial co-segregation of ccTGA and laterality defects. In one family co-segregation of ccTGA, dextro-transposition of the great arteries and heterotaxy syndrome in 3 distinct relatives was found. In another family, twins both displayed ccTGA and primary ciliary dyskinesia. CONCLUSIONS: ccTGA is not always a sporadic congenital heart defect. Familial clusters as well as evidence of an association between ccTGA, dextro-transposition of the great arteries, laterality defects and in some cases primary ciliary dyskinesia, strongly suggest a common pathogenetic pathway involving laterality genes in the pathophysiology of ccTGA.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".