RESULTS
Patient population : We studied 831 patients with a
clinical diagnosis of HCM. Atrial fibrillation was diagnosed in
22% of the HCM cohort: 139 patients were diagnosed with AF prior
to/at the first clinic visit, and 52 patients were diagnosed with AF
during follow up (Supplementary Figure 1). Prevalence of AF varied from
9-30% and increased with age; AF prevalence was highest in the age
group of 61-80 years (Figure 1).
Demographic, clinical and imaging features of the HCM cohort at the time
of their first clinic visit are presented in Table 4 Patients from the
AF group were older, more likely to have obstructive HCM, higher NYHA
class, and lower exercise capacity than the No-AF group. The AF group
also had larger LA size (Figure 2), greater diastolic dysfunction, worse
global longitudinal strain and greater amount of LV replacement fibrosis
(reflected by LV-LGE), when compared to the No-AF group, suggesting
greater degree of LV myopathy. No difference was observed in LV mass,
maximum LV thickness or LVOT gradients between the AF and No-AF groups
of HCM patients (Table 4).
Mean follow up was 3.1 years (median = 2.1,
25th-75th percentile = 1.0 - 4.8
years). HCM patients from the AF group had a higher incidence of heart
failure and all-cause death, when compared to the No-AF group (Table 4).
Machine learning-based identification of atrial fibrillation
cases: Our feature selection process identified 18 clinical variables
whose values distinguish AF from No-AF cases within the HCM population.
Table 1 provides a list of these predictive variables, along with the
corresponding polychoric correlation and P values, indicating their
degree of association (or lack thereof) with AF. We identified 7
variables that are negatively correlated with AF, and 11 variables that
are positively associated with AF. Left atrial diameter is highly
correlated with AF. Several exercise-related parameters, including,
lower exercise capacity (reflected by lower METs, exercise time, peak
stress heart rate), abnormal BP response to exercise, lower diastolic BP
at peak exercise and lower heart rate recovery post-exercise are
associated with higher risk for AF. Other predictors of AF include
replacement fibrosis in the LV (reflected by LV-LGE), greater diastolic
dysfunction (reflected by higher E/A and E/e′, lower LV-SR_E) and worse
(more positive) global longitudinal systolic strain rate (LV-SR_S).
Notably, combining the ensemble classifier comprising logistic
regression and naïve Bayes with over- and under-sampling led to higher
sensitivity and area under the receiver operating curve (AUC), compared
to the four simple classifiers (naïve Bayes, logistic regression,
decision tree and random forest) alone (Table 2). Figure 3 illustrates
the C-index (0.80 ) for our method (HCM-AF-Risk Model ),
which assigns an individualized probability to each patient to present
with AF.
Comparison of HCM-AF-Risk Model performance with previous AF
models : We compared the performance of the HCM-AF-Risk Modelwith that obtained by the Framingham Heart Study,[8] ARIC[10]
and CHARGE-AF[9] risk models (Tables 3, 5). The HCM-AF-Risk
Model demonstrates significantly higher performance (p <
0.001) across all evaluation metrics including specificity, sensitivity
and area under ROC curve (C-index) for HCM patients, when compared with
published models [8-10] focused on AF prediction in the general
population. The datasets used in these studies are not publicly
available, which preclude their use for training/testing on our dataset
and comparing their performance according to all the measures we have
used. As such, we compared the performance level attained by our model
with that reported by the other studies in terms of the C-index.
We also repeated our experiments, using only LA diameter to represent
our dataset, based on results from several previous studies [2, 35,
36] that identified LA enlargement as most predictive of AF in HCM. We
observed reduction in our model’s performance when LA diameter alone is
included in the feature set: specifically, area under ROC curve
decreased by 20% (C-index: 0.66 from 0.80), sensitivity decreased by
37% (0.54 from 0.74) and specificity decreased by 14% (0.63 from
0.72).