Toronto Hypertrophic Cardiomyopathy Genotype Score for Prediction of a Positive Genotype in Hypertrophic Cardiomyopathy
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Bibliographic record
Abstract
BACKGROUND: Genotyping in hypertrophic cardiomyopathy has gained increasing attention in the past decade. Its major role is for family screening and rarely influences decision-making processes in any individual patient. It is associated with substantial costs, and cost-effectiveness can only be achieved in the presence of high-detection rates for disease-causing sarcomere protein gene mutations. Therefore, our aim was to develop a score based on clinical and echocardiographic variables that allows prediction of the probability of a positive genotype. METHODS AND RESULTS: Clinical and echocardiographic variables were collected in 471 consecutive patients undergoing genetic testing at a tertiary referral center between July 2005 and November 2010. Logistic regression for a positive genotype was used to construct integer risk weights for each independent predictor variable. These were summed for each patient to create the Toronto hypertrophic cardiomyopathy genotype score. A positive genotype was found in 163 of 471 patients (35%). Independent predictors with associated-risk weights in parentheses were as follows: age at diagnosis 20 to 29 (-1), 30 to 39 (-2), 40 to 49 (-3), 50 to 59 (-4), 60 to 69 (-5), 70 to 79 (-6), ≥80 (-7); female sex (4); arterial hypertension (-4); positive family history for hypertrophic cardiomyopathy (6); morphology category (5); ratio of maximal wall thickness:posterior wall thickness <1.46 (0), 1.47 to 1.70 (1), 1.71 to 1.92 (2), 1.93 to 2.26 (3), ≥2.27 (4). The model had a receiver operator curve of 0.80 and Hosmer-Lemeshow goodness-of-fit P=0.22. CONCLUSIONS: The Toronto genotype score is an accurate tool to predict a positive genotype in a hypertrophic cardiomyopathy cohort at a tertiary referral center.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it