CONCLUSION
The HCM-AF-Risk Model effectively identifies HCM patients with
AF, in addition to predictors of AF in HCM. Our approach attains good
performance (0.74 sensitivity, 0.72 specificity, C-index = 0.80)
improving upon current AF risk scores from community cohorts, while
addressing the imbalance between high-risk and low-risk cases that is
inherent in most clinical data. The set of clinical attributes
identified by our method as indicative of AF – and serving to justify
the severity level assigned by the classifier, includes several hitherto
un-identified markers of AF in HCM, and suggests that HCM patients with
AF have a more severe cardiac HCM phenotype.
Funding: This work was funded in part by NSF IIS EAGER
grant#1650851 (to HS), an award from the John Taylor Babbitt (JTB)
foundation (Chatham, New Jersey) and startup funds from the UCSF
Division of Cardiology (to MRA).