Recent progress in the genetics of cardiomyopathy and its role in the clinical evaluation of patients with cardiomyopathy
Bibliographic record
Abstract
PURPOSE OF REVIEW: This review will provide an overview of the genetic basis of cardiomyopathy with an emphasis on the clinically relevant breakthroughs that have occurred recently and their role in the evaluation of patients with cardiomyopathy. RECENT FINDINGS: Recent developments that have occurred in genetic cardiomyopathy include the finding of a shared genetic basis of familial dilated cardiomyopathy in at least a subset of cases of peripartum cardiomyopathy; the increased yield for the diagnosis of arrhythmogenic right ventricular cardiomyopathy/dysplasia (ARVC/D) when genetic testing is incorporated into Task Force Criteria; and the value of testing a spectrum of implicated genes in hypertrophic cardiomyopathy and ARVC because of the severe phenotype associated with compound mutations. SUMMARY: Recent progress in genetic cardiomyopathy points to the potential value of genetic testing in shaping the clinician's ability to diagnose and understand the pathogenetic basis of the inherited cardiomyopathies. The rapid rate at which the field is progressing emphasizes the importance of referral of such patients to multidisciplinary teams equipped to address the complex biological, social and psychological issues that accompany the genetic diagnosis of inherited cardiomyopathy.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".