The Revolution of Cardiac Myosin Inhibitors in Patients With Hypertrophic Cardiomyopathy
Bibliographic record
Abstract
Hypertrophic cardiomyopathy (HCM) is the most common genetic cardiomyopathy worldwide and causes significant morbidity and mortality. For decades, medical treatment options have been limited and untargeted, with frequent need for invasive interventions not readily accessible to many HCM patients. More recently, our understanding of the genetic basis and pathophysiologic mechanism of HCM has grown significantly, leading to the discovery of a new class of medications, cardiac myosin inhibitors (CMIs), that shift myosin into the super-relaxed state to counteract the hypercontractility in HCM. Subsequent clinical trials have proven the mechanism and efficacy of CMIs in humans with obstructive HCM, and additional trials are under way in patients with nonobstructive HCM. With favourable results in the completed clinical trials and ongoing research on the horizon, CMIs represent a bright new era in the targeted management of HCM. This review is focused on the discovery of CMIs, provides a summary of the results of clinical trials to date, provides clinicians with a roadmap for implementing CMIs into practice, and identifies gaps in our current understanding as well as areas of ongoing investigation.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".