Genotype-negative hypertrophic cardiomyopathy: Exploring the role of cardiovascular risk factors in disease expression
Bibliographic record
Abstract
BACKGROUND: Hypertrophic cardiomyopathy (HCM) is the most common inherited myocardial disease. An inheritable cause is identified in approximately half of patients. Earlier research has identified clinical differences between genotype-positive (G+) and genotype-negative (G-) HCM patients, which this study aimed to further explore. METHODS AND RESULTS: Differences in baseline characteristics, including cardiovascular risk factors (CVRF), and phenotypical factors between G+ and G- patients were explored. Subanalyses among distinct age groups and sexes were performed. A total of 422 HCM (46 % G-, 54 % G+) patients were included. G- patients were older (62 vs 54 years, p < 0.001), experienced more limiting cardiac symptoms (47 % vs 28 %, p = 0.008), and more frequent left ventricular outflow tract obstruction (57 % vs 38 %, p < 0.001). CVRF were more prevalent in G- than in G+ HCM patients (70 % vs 41 %, p < 0.001), with hypertension being the most prevalent factor (51 % vs 22 %, p < 0.001). Despite adjusting for patient age, CVRF presence significantly predicted G- classification (OR 2.3, 95 %CI 1.5-3.6, p < 0.001). Female G- patients were less prevalent in younger age groups, and only in the older age group (>60 years) were female G- patients diagnosed later than their G+ counterparts. CONCLUSION: CVRF, particularly hypertension, are more prevalent in G- patients independent of age, suggesting that cardiovascular health may contribute to HCM disease development. Male-female differences suggest female-specific factors affecting the development of HCM in women. Recognizing G- HCM as a distinct clinical entity may have important implications for patient management, and a more comprehensive understanding of its aetiology may aid in tailoring future therapies.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".