Sudden cardiac death caused by ventricular arrhythmias is a common cause of death in patients with hypertrophic cardiomyopathy. However, current strategies to identify patients with hypertrophic cardiomyopathy at risk for sudden cardiac death are limited and may miss a significant proportion of high-risk patients. Conversely, many patients at low sudden cardiac death risk who may not require a primary prevention ICD may be classified as higher risk, leading to overtreatment with ICDs. In 2014, a novel sudden cardiac death prediction algorithm was endorsed by the ESC to differentiate between patients with low, intermediate and high risk for sudden cardiac death to guide recommendations for ICD therapy. Based on a retrospective, multicenter longitudinal cohort study, which included 3,675 consecutive patients from six European centers in Spain, Italy, Greece and the U.K., a Cox proportional hazards model to predict sudden cardiac death events was developed (O’Mahony C, et al. Eur Heart J. 2014;doi:10.1093/eurheartj/eht439). This model was generated based on a follow-up period of 24,313 patient-years (median 5.7 years) and projects the rate of sudden cardiac death over 5 years. In addition to incorporating four of the five major conventional hypertrophic cardiomyopathy sudden cardiac death risk factors, including left ventricular wall thickness, family history of sudden cardiac death, nonsustained ventricular tachycardia and unexplained syncope, the ESC sudden cardiac death risk model also included two new risk markers (dynamic LV outflow obstruction and left atrial size), which previously have not proved to be independent predictors of sudden cardiac death risk. Overall, this online calculator offered theoretical advantage over previous algorithms. For instance, while previous guidelines only considered extreme LV hypertrophy (> 3 cm) as a significant risk factor for sudden cardiac death, the new model considers LV hypertrophy as a continuous variable, which better reflects the relationship between LV hypertrophy and sudden cardiac death risk. An independent validation study with 706 patients with hypertrophic cardiomyopathy from the Netherlands confirmed that the ESC hypertrophic cardiomyopathy risk model outperformed risk stratification models proposed by earlier clinical guidelines and improved the risk stratification of patients with hypertrophic cardiomyopathy for primary prevention of sudden cardiac death (Vriesendorp PA, et al. Circ Arrhythm Electrophysiol. 2015;doi:10.1161/CIRCEP.114.002553). A similar result was found in a cohort of 502 patients with hypertrophic cardiomyopathy from South America (Fernández A, et al. Am J Cardiol. 2016;doi:10.1016/j.amjcard.2016.04.021). Additionally, the same group who developed the initial hypertrophic cardiomyopathy-sudden cardiac death risk model recently published a study validating the hypertrophic cardiomyopathy-sudden cardiac death risk calculator in a second independent cohort of more than 3,700 patients from North America, Europe, the Middle East and Asia (O’Mahony C, et al. Circulation. 2017;doi:10.1161/CIRCULATIONAHA.117.030437). Low-risk patients with a predicted 5-year risk of less than 4% (n = 1,524; 71%) had an observed 5-year sudden cardiac death incidence of 1.4% while patients with a predicted risk of greater than or equal to 6% (n = 297; 14%) had an observed sudden cardiac death incidence of 8.9%. Thus, the authors concluded that the ESC hypertrophic cardiomyopathy-sudden cardiac death model provides accurate prognostic information which can be used to target ICD therapy in patients at the highest risk for sudden cardiac death.Yet, while the ESC risk model has a consistently higher C-index score compared with models used in previous guideline recommendations, this may not always indicate a higher sensitivity and specificity. In this respect, the study of Leong and colleagues raises important questions. Leong and colleagues used a smaller cohort of 288 patients with hypertrophic cardiomyopathy followed at a tertiary university medical center in Europe to independently validate the hypertrophic cardiomyopathy-sudden cardiac death risk model. In contrast to the aforementioned studies, Leong and colleagues found that the hypertrophic cardiomyopathy sudden cardiac death risk model endorsed by the ESC underestimated risk in their cohort and may therefore leave more patients vulnerable to sudden cardiac death without an ICD. Thus, while the ESC model correctly identified low-risk patients with high specificity, it lacked sensitivity for detecting high-risk patients. Specifically, out of 14 patients who experienced aborted sudden cardiac death in their cohort of 288 patients, five (ie, 43% of patients with sudden cardiac death) would not have received an ICD recommendation based on the 2014 ESC hypertrophic cardiomyopathy risk score. While this could be attributed to the smaller sample size and possible type I error, these findings are nonetheless noteworthy, as they were consistent with the results of another validation study which questioned the accuracy of the hypertrophic cardiomyopathy-sudden cardiac death risk model. In a cohort of greater than 1,600 patients with hypertrophic cardiomyopathy, Barry J. Maron, MD, and colleagues (Maron BJ, et al. Am J Cardiol. 2015;doi:10.1016/j.amjcard.2015.05.047) showed that the ESC hypertrophic cardiomyopathy sudden cardiac death prognostic model did not reliably predict future sudden cardiac death events in individual patients. Of the patients with sudden cardiac death and appropriate ICD shocks, only 20% had prognostic risk scores that would justify a primary-prevention ICD, leaving the vast majority of high risk patients vulnerable to sudden cardiac death.How can we reconcile those discrepant and conflicting results? In addition to differences in mathematical and statistical modeling, the phenotypic diversity of hypertrophic cardiomyopathy, the low sudden cardiac death event rates, the long recruitment periods, evolving assessment methods and corresponding incomplete data have made interpretation of the aforementioned studies difficult (Grace A. Circ Arrhythm Electrophysiol. 2015;doi:10.1161/CIRCEP.115.003140). Refined risk markers are clearly needed, and one can only hope that improved imaging techniques, specifically myocardial substrate and scar-based imaging with cardiac MRI, will help to refine sudden cardiac death risk and ultimately be incorporated into risk models. Cardiac MRI is emerging as a powerful tool for diagnosis and risk stratification in hypertrophic cardiomyopathy, including assessment of LV mass and pattern of hypertrophy. Late gadolinium enhancement by cardiac MRI is a marker of focal myocardial fibrosis, which underlies the arrhythmogenic substrate. Whether cardiac MRI findings correlate with sudden cardiac death event rates is the focus of a NIH-sponsored study with more than 2,700 patients (Kramer CM, et al. Am Heart J. 2015;doi:10.1016/j.ahj.2015.05.013). Until more data become available, overreliance on one specific risk prediction model is to be avoided. Following a patient-centered approach and shared decision making, the discussion of pros and cons of primary prevention ICD in hypertrophic cardiomyopathy needs to address also the knowledge gaps in sudden cardiac death prediction, particularly when evidence for risk is ambiguous as is the case for intermediate-risk patients, defined as a 5-year sudden cardiac death risk of 4% to 6%. While the relatively small sample size limits definitive conclusions, the high misclassification rate of high-risk patients by the ESC model raises important concerns and highlights the fact that current risk prediction models are imperfect and that more accurate sudden cardiac death risk models are needed. The discussion of pros and cons of ICDs for primary prevention in hypertrophic cardiomyopathy also needs to stress that no strategy will ever be able to predict sudden cardiac deaths with 100% certainty, particularly when evidence for risk is ambiguous, as is the case for intermediate-risk patients. New risk markers are urgently needed to refine sudden cardiac death risk prediction. I’m hopeful that cardiac MRI will become the arbiter, particularly for intermediate-risk patients.