Abstract 9969: Genotype-phenotype Correlations According to Clinical and Echocardiographic Characteristics in Hypertrophic Cardiomyopathy
Bibliographic record
Abstract
Background: Many mutations among genes encoding sarcomeric proteins have been identified in hypertrophic cardiomyopathy (HCM). Data on specific genotype-phenotype correlations are limited and highly variable. Methods: Identified mutations in genes TNNI3 (troponin I), TNNT2 (troponin T), MYBPC3 (myosin-binding protein C) and MYH7 (myosin heavy chain) were screened in 284 patients at the Cardiovascular Genetic Clinic of the Montreal Heart Institute. Mutations were identified in 113 patients (40%) and 84 patients (74%) were included for analysis. Five cardiac transplant recipients without previous echocardiographic images available were analysed according to clinical characteristics only. We excluded 16 patients without HCM phenotype and 13 patients with follow-up outside of our center. Results: MYH7 (40%) and MYBPC3 (40%) mutations were the most common. Only one patient was identified with a TNNI3 (1%) mutation and was excluded. Patients with MYH7 mutations were younger at diagnosis and presented more often with a familial history of sudden cardiac death (76%) and defibrillator implantation (59%). Patients with MYH7 mutations were also more likely to progress to “burn-out” HCM (27%) and cardiac transplantation (18%). Significant mitral insufficiency was more prevalent in patients with MYBPC3 mutations (33%). Patients with TNNT2 (18%) mutations showed an increased probability of having a significant resting and provocable left outflow tract obstruction (47%) with systolic anterior movement of the mitral valve (53%) leading to septal myomectomy (27%). Genotype did not affect septal morphology with an overall predominance of the midseptal form (73% overall). Conclusion: This retrospective study suggests that TNNT2 mutations are associated with obstructive HCM while MYH7 mutations are related with arrhythmic complications. Moreover, septal morphologies do not appear to be influenced by any specific gene mutation.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".