Abstract Background Hypertrophic cardiomyopathy (HCM) is a heterogeneous disorder with varying risks of clinical outcomes, including sudden cardiac death (SCD). Purpose We aimed to identify distinct phenotypes among patients with HCM in relation to SCD risk factors, interpret their clinical characteristics, and examine their outcomes. Methods This retrospective study analyzed 1,231 consecutive patients with HCM from two tertiary hospitals. We performed latent class analysis (LCA) to categorize patients into phenotypic groups, which is a probabilistic modeling technique that reveals hidden patterns and subgroups within a dataset. Results Three distinct phenotypic groups were identified using LCA. Group 1 (n=554) consisted of young patients with HCM with minimal SCD risk factors and favorable cardiac remodeling. Group 2 (n=114) comprised young patients with HCM and a high prevalence of SCD risk factors, whereas Group 3 (n=563) included older patients (median age, 68 years). Over a median 6.5-year follow-up, 34 SCD-related events, 131 cardiovascular (CV) events, 133 all-cause mortality, and 70 non-CV mortality were observed. Group 2 exhibited the highest rate of SCD-related events (5-year SCD rate: Group 1 vs. 2 vs. 3: 0.8% vs. 8.2% vs. 4.0%, respectively, p<0.001), and CV events were more frequent in Group 2 and 3 compared to Group 1 (Figure 1). All-cause and non-CV mortality were the most frequent in Group 3. A simplified decision tree was developed for the straightforward assignment of phenotypic group membership, demonstrating fair concordance. The phenotypic categorization and the decision tree is shown in Figure 2. Conclusions This study identified three distinct clinical phenotypes in patients with HCM, each associated with different SCD risks and outcomes. Data-driven phenotyping of patients with HCM offers effective risk stratification and may optimize patient management.
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