Clinical phenotypes in relation to outcomes in heart failure patients with cardiac resynchronization therapy and defibrillators (CRT-D): an unsupervised cluster analysis
Authors: Gerra L , Bucci T , Bisson A , Bodin A , Pierre B , Boriani G , Lip G Y H , Fauchier L 
Published: October 2024

Abstract

Background
Patients with heart failure undergoing CRT are an heterogenous and complex population. Selecting patients before implantation is essential to obtain a favorable response to CRT-D. Data-driven cluster analysis may be an approach to identify different patients’ phenotypic categories.

Purpose
To identify different clusters of patients with CRT-D who share similar clinical phenotypes, and to evaluate the associations between clusters and clinical outcomes, using cluster analysis.

Methods
Three agglomerative hierarchical cluster analysis were performed in CRT-D patients seen between 2010 and 2019 in French hospitals. Associations between clusters and death at one year and death during whole follow-up (FU) were evaluated using Cox regression analyses.

Results
The study included 23,029 CRT-D patients with no prior history of VT/VF/cardiac arrest (mean age 67.7 ± 9.9 years; 78.8 % male), who were analyzed in relation to 3 ways, as follows: the first group was a 50% random sample of all patients (n = 11,514), the second group included patients dead at 1 year (n = 1,604) and the third group included those alive at 3 years FU (n = 14,228).
A cluster analysis was performed on each group. Four clusters were identified in the first group: Cluster 1 identified young patients with dilated cardiomyopathy and low prevalence of coronary artery disease (CAD), cardiovascular (CV) risk factors and comorbidities (chronic kidney disease, lung and liver disease) (low-risk phenotype); Cluster 2 was composed of male patients with CAD but low burden of CV risk factors and comorbidities (CAD phenotype); Cluster 3 included CRT recipients with several CV risk factors but low prevalence of comorbidities (CV risk factors phenotype); Cluster 4 identified old patients with high prevalence of CAD, atrial fibrillation, CV risk factors and comorbidities (clinical complex phenotype). These phenotypes were maintained in the other two groups (dead at 1 year and alive at 3 years FU), with the highest consistency for low-risk and high-risk phenotypes(Cluster 1 and 4 respectively).
Compared with Cluster 1, Clusters 2, 3 and 4 were independently associated with an increased risk of all-cause death at 1-year FU and during the whole FU (Cluster 2: HR 1.21, 95% CI 1.08 - 1.36; Cluster 3: HR 1.15, 95%CI 1.04 - 1.26; and Cluster 4: HR 1.79, 95%CI 1.65 - 1.96). There were high prevalences of CAD, atrial fibrillation, mitral regurgitation, and comorbidities (which are all predictors of CRT-nonresponse) not only in Cluster 4 at baseline, but also among patients who died at 1-year FU in all 4 clusters.

Conclusion
Cluster analysis identified four statistically driven groups of CRT recipients, with specific clinical phenotypes and associated with different risks for all-cause death. Identifying those patients at higher risk of adverse events might help in the selection of patients with heart failure undergoing CRT-D implantation, especially in relation to CRT-nonresponse.Risk of all-cause death in 4 clusters