Impact of a Center of Excellence in Confirming or Excluding a Diagnosis of Hypertrophic Cardiomyopathy.

Hypertrophic cardiomyopathy (HCM) is challenging to reliably diagnose. Comprehensive evaluation requires advanced imaging, genetic testing, and detailed clinical history. We hypothesized that clinical and imaging parameters from referring centers can predict the likelihood of confirming a diagnosis of HCM at a tertiary care center. A chart review of patients presenting to establish care at the University of Virginia HCM Center of Excellence between September 2020 and October 2022 was conducted. Referral diagnosis was either confirmed or rejected following comprehensive evaluation of outside and new imaging studies with the clinician and cardiac imager. Clinical and imaging characteristics from pre-referral studies were then used to construct a model for predictors of ruling out or confirming the diagnosis of HCM using machine learning methods (least absolute shrinkage and selection operator [LASSO] logistic regression). Alternative diagnoses were found in 38 (18.1%) of the 210 patients (median age 60 years; 50% female). Increased LVEDVi, greater septal thickness measurements, greater left atrial size, asymmetric hypertrophy on echocardiography, and the presence of an ICD were associated with higher odds ratios for confirming a diagnosis of HCM, whereas increasing age and the presence of diabetes were more predictive of rejecting the diagnosis (AUC = 0.902, p < 0.0001) (Figure 1 and Figure 2). Clinical and imaging parameters may predict diagnostic accuracy in patients presenting to a tertiary care center for presumed HCM. Further validation of this model in larger cohorts may enhance its clinical utility in referring centers. [ABSTRACT FROM AUTHOR]