Advances in the diagnosis and treatment of catecholaminergic polymorphic ventricular tachycardia
Bibliographic record
Abstract
Since the sentinel description of exercise-triggered ventricular arrhythmias in 21 children, our recognition and understanding of catecholaminergic polymorphic ventricular tachycardia has improved substantially. A variety of treatments are now available, but reaching a diagnosis before cardiac arrest remains a challenge. Most cases are related to variants in the gene encoding for ryanodine receptor-2 (RyR2), which mediates calcium-induced calcium release. Up to half of cases remain genetically elusive. The condition is presently incurable, but one basic intervention, the universal administration of β-blockers, has improved survival. In the past, implantable cardioverter-defibrillators (ICDs) were frequently implanted, especially in those with a history of cardiac arrest. Treatment limitations include under-dosing and poor compliance with β-blockers, and potentially lethal ICD-related electrical storm. Newer therapies include flecainide and sympathetic ganglionectomy. Limited data have suggested that genotype may predict phenotype in catecholaminergic polymorphic ventricular tachycardia, including a higher risk of life-threatening cardiac events in subjects with variants in the C-terminus of ryanodine receptor-2 (RyR2). At present, international efforts are underway to better understand this condition through large prospective registries. The recent publication of gene therapy in an animal model of the recessive form of the disease highlights the importance of improving our understanding of the genetic underpinnings of the disease.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.003 | 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".