Left ventricular global longitudinal strain and diagnostic yield of genetic testing in hypertrophic cardiomyopathy in a multicenter registry analysis
Bibliographic record
Abstract
In this multicenter study we investigated whether echocardiography-derived left ventricular global longitudinal strain (LV GLS), an indicator of myocardial fibrosis, independently predicts a positive genotype in hypertrophic cardiomyopathy (HCM). We performed a cross-sectional analysis including HCM patients with genetic testing results and echocardiographic data from two Austrian HCM registries. Echocardiographic parameters were measured in post-processing analysis by a blinded investigator. Among 125 patients with HCM, a positive genotype was present in 39%. Worse LV GLS was associated with a positive genotype in univariate analysis (Odds Ratio [OR] 95% CI 1.141, 1.018-1.279, p = 0.023). In multivariate regression analysis adjusted for genotype predictors (age at diagnosis < 45 years, arterial hypertension, positive family history of HCM, maximal to posterior wall thickness [MWTH: PWTH], reverse curve septal phenotype), the reverse curve septal phenotype remained as a single independent predictor of genotype-positive HCM (OR 6.948, 2.342-20.614, p < 0.001). Adding LV GLS to established Toronto and Mayo genotype prediction scores did not improve their performance. To conclude, worse LV GLS was not independently associated with genotype-positive HCM and did not improve the diagnostic yield of genetic testing in HCM in a multivariate model. Our study highlights the reverse curve septal phenotype as the strongest genotype predictor in HCM.
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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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".