Myosin inhibitors for the treatment of obstructive hypertrophic cardiomyopathy: a Canadian perspective on a first-in-class therapy
Bibliographic record
Abstract
Hypertrophic cardiomyopathy (HCM) is a relatively common heritable cardiac condition (∼1 in 500), which poses significant morbidity and mortality. Severe symptoms are often from dynamic left ventricular outflow tract (LVOT) obstruction which may result in dyspnea, chest pain, fatigue, and (pre)syncope. This obstructive phenotype is present in more than half of cases. Traditional pharmacological therapies used to treat symptomatic LVOT obstruction are ineffective in many patients thereby necessitating septal reduction therapy in the form of alcohol septal ablation or surgical myectomy. In recent years, the demand for improved HCM treatment without surgical intervention has led to the development of a new class of drugs called cardiac myosin inhibitors. Mavacamten represents the first-in-class cardiac myosin inhibitor, which is now approved in Canada, available for special authorization cost coverage in most provinces, and is increasingly being prescribed in both specialized HCM programs and general cardiology clinics. As such, many general cardiologists, internists, and family physicians will need to be familiar with these agents. This review on the myosin inhibitors, particularly mavacamten, provides a perspective for more general cardiovascular providers by summarizing the key mechanisms, clinical trials, expected outcomes, and potential impacts on the Canadian healthcare system.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.014 | 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".