Management of Hypertrophic Cardiomyopathy
Bibliographic record
Abstract
Hypertrophic cardiomyopathy (HCM), a relatively common, globally distributed, and often inherited primary cardiac disease, has now transformed into a contemporary highly treatable condition with effective options that alter natural history along specific personalized adverse pathways at all ages. HCM patients with disease-related complications benefit from: matured risk stratification in which major markers reliably select patients for prophylactic defibrillators and prevention of arrhythmic sudden death; low risk to high benefit surgical myectomy (with percutaneous alcohol ablation a selective alternative) that reverses progressive heart failure caused by outflow obstruction; anticoagulation prophylaxis that prevents atrial fibrillation-related embolic stroke and ablation techniques that decrease the frequency of paroxysmal episodes; and occasionally, heart transplant for end-stage nonobstructive patients. Those innovations have substantially improved outcomes by significantly reducing morbidity and HCM-related mortality to 0.5%/y. Palliative pharmacological strategies with currently available negative inotropic drugs can control symptoms over the short-term in some patients, but generally do not alter long-term clinical course. Notably, a substantial proportion of HCM patients (largely those identified without outflow obstruction) experience a stable/benign course without major interventions. The expert panel has critically appraised all available data and presented management insights and recommendations with concise principles for clinical decision-making.
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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 | 0.001 |
| 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 | 0.000 |
| 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".