Clinical CMR Genetic Biomarkers Family history of HCM-related SCD LV ejection fraction MYH7 NT-pro BNP Unexplained recent syncope LV mass/mass index MYBPC3 Singulex cardiac troponin Massive LVH (wall thickness >30mm) Maximum diastolic wall thickness Thin filament mutations PICP Multiiple burst of nonsustained VT LGE extent (% of LV mass) Compound/double heterozygotes ST2 Hypotensive BP response to exercise Global extracellular volume fraction Sarcomere mutation negative The initial tree is reduced in size (pruned) by comparing misclassification error rates of smaller trees to larger trees to assess the reduction of the predictive ability of trees resulting from the pruning process. The goal is to identify the strongest predictors of HCM, any interactions of the predictors, and eliminate any factors that have little predictive power. While tree models give rapid identification of the strongest predictors and combinations of predictors, they do not usually result in clinically useful prediction models that generalize well to patients in other settings. Regression methods, using test-validation re-sampling procedures, will be used to develop the most valid model possible.