Comparison of Surgical Ventricular Septal Reduction to Alcohol Septal Ablation Therapy in Patients with Hypertrophic Cardiomyopathy
Bibliographic record
Abstract
Ventricular septal myectomy (SM) and alcohol septal ablation (ASA), 2 septal reduction therapies (SRTs), are recommended in symptomatic obstructive hypertrophic cardiomyopathy (HCM) despite maximum tolerated medical therapy. Contradictory results between the outcomes of these 2 types of therapies persist to this day. The objective of this study was to compare in-hospital and mid-term outcomes of SM versus ASA, at a nationwide level in France. We collected information on patients who underwent SRT for HCM using the French nationwide Programme de Médicalisation des Systèmes d'Information database between 2010 and 2019. A total of 1,574 patients were identified in the database, including 340 patients in the SM arm and 1,234 patients in the ASA arm. No difference during the median follow-up of 1.3 years between the 2 groups was noted in terms of mortality (adjusted incidence rate ratio 0.687, 95% confidence interval 0.361 to 1.309, p = 0.25). However, there was a significantly lower risk of all-cause stroke (adjusted incidence rate ratio 0.180, 95% confidence interval 0.058 to 0.554, p = 0.003) in the ASA group. In conclusion, in our "real-life" data from France, mortality after SRT in patients with HCM was similar after ASA or SM. Moreover, ASA was more widely used than SM despite European Society of Cardiology guidelines recommendations.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".