Abstract 13977: Low Operative Mortality Achieved With Surgical Septal Myectomy: Role of Dedicated Hypertrophic Cardiomyopathy Centers in the Management of Dynamic Subaortic Obstruction
Bibliographic record
Abstract
Background: Treatment of progressive heart failure, due to left ventricular (LV) outflow tract obstruction has been a major component of hypertrophic cardiomyopathy (HCM) disease management for 50 years. Septal myectomy has been the primary treatment option to abolish gradients and relieve heart failure symptoms. The role of myectomy in HCM management has depended on effectiveness in relieving heart failure symptoms, but also an acceptable operative risk. Methods: Over the most recent 15-year period, we reviewed 3,700 consecutive isolated myectomy operations performed at major North American HCM institutions. Composite operative mortality (first 30 days) was only 0.4%. Seventeen operative deaths were at ages 24 to 82 (≥70 years), and only 6 occurred after 2010. Notably, 2 of the 4 Mayo Clinic deaths were in patients with prior alcohol septal ablation. Septal myectomy, when performed in experienced HCM centers, was much safer when compared to operative mortality with coronary artery bypass grafting (2.3%); valve replacement (3.5%); mitral valve replacement specifically (5.7%) (STS Database), similar to atrial or ventricular septal defect closure and 15-fold less than myectomy in community hospital or low volume surgical settings. Conclusions: Surgical myectomy performed in dedicated HCM centers with experienced surgeons and staff is one of the safest open-heart procedures currently practiced, with a mortality rate as low as 0.4%. The large mortality discrepancy for myectomy between community hospitals and dedicated HCM centers underscores that this operation should be considered a specialized procedure best performed in high volume HCM institutions.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".