Real-World Candidacy to Mavacamten in a Contemporary Hypertrophic Obstructive Cardiomyopathy Population
Bibliographic record
Abstract
Abstract Aims In the EXPLORER-HCM trial, mavacamten reduced left ventricular outflow tract obstruction (LVOTO) and improved functional capacity of symptomatic hypertrophic obstructive cardiomyopathy (HOCM) patients. We sought to define the potential use of mavacamten by comparing real-world HOCM patients with those enrolled in EXPLORER-HCM and assessing their eligibility to treatment. Methods and results We collected information on HOCM patients followed up at 25 Italian HCM outpatient clinics and with significant LVOTO (i.e. gradient ≥30 mmHg at rest or ≥50 mmHg after Valsalva manoeuvre or exercise) despite pharmacological or non-pharmacological therapy. Pharmacological or non-pharmacological therapy resolved LVOTO in 1044 (61.2%) of the 1706 HOCM patients under active follow-up, whereas 662 patients (38.8%) had persistent LVOTO. Compared to the EXPLORER-HCM trial population, these real-world HOCM patients were older (62.1 ± 14.3 vs. 58.5 ± 12.2 years, p = 0.02), had a lower body mass index (26.8 ± 5.3 vs. 29.7 ± 4.9 kg/m2, p < 0.0001) and a more frequent history of atrial fibrillation (21.5% vs. 9.8%, p = 0.027). At echocardiography, they had lower left ventricular ejection fraction (LVEF, 66 ± 7% vs. 74 ± 6%, p < 0.0001), higher left ventricular outflow tract gradients at rest (60 ± 27 vs. 52 ± 29 mmHg, p = 0.003), and larger left atrial volume index (49 ± 16 vs. 40 ± 12 ml/m2, p < 0.0001). Overall, 324 (48.9%) would have been eligible for enrolment in the EXPLORER-HCM trial and 339 (51.2%) for treatment with mavacamten according to European guidelines. Conclusions Real-world HOCM patients differ from the EXPLORER-HCM population for their older age, lower LVEF and larger atrial volume, potentially reflecting a more advanced stage of the disease. About half of real-world HOCM patients were found eligible to mavacamten.
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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 | 0.002 | 0.004 |
| 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 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".