Abstract

Abstract Background Recent studies showed moderate aortic stenosis (AS) was associated with adverse cardiovascular outcomes. Ongoing studies are addressing whether moderate AS may benefit from early transcatheter aortic valvular replacement (TAVR). However, a high comorbidity burden is common, and may be the main driver of poor outcomes. Purpose We aimed to identify clusters of patients with moderate AS based on comorbidity and echocardiographic profiles. Methods Unsupervised clustering algorithms (including K means, partition around medoids (PAM), hierarchical clustering, Density-Based Spatial Clustering of Applications with Noise (DBSCAN), and Hierarchical Density-Based SCAN (HDBSCAN)) of comorbidities, demographics and echocardiographic parameters were conducted in patients diagnosed with moderate AS [aortic valvular area (AVA) 1-1.5 cm2 or peak velocity (Vmax) 3-4 m/s or dimensionless severity index (DSI) 0.25-0.5]. Cumulative hazard plots and Cox proportional hazards regression models were used to assess the difference in time to cardiac death, heart failure hospitalization or aortic valvular intervention between the clusters. Results Four distinct clusters were identified AS patients (n=2,409) using PAM algorithm. The highest risk of cardiovascular outcomes was found among patients in Cluster 4 (Comorbid cluster), followed by Cluster 3 (Risk factors cluster), and Cluster 2 (Valve morphology cluster) (Table 1, Figure 1). Comparing cardiac death outcomes between patients treated with TAVR vs. no TAVR in each cluster revealed that TAVR was of most benefit in Cluster 2 (HR = 0.05, 95% CI: 0.01-0.34, p=0.002). Conclusions Multiple comorbidities are the key driver of worse outcomes in patients with moderate AS, which can affect treatment outcomes from TAVR. Thus, careful attention to the comorbidities is imperative in the management of patients with moderate AS.Table 1.Characteristics of 4 clustersFig 1.Cumulative Hazard Plot

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