Clinical phenotyping of implantable cardioverter defibrillator patients to identify the association of remote device monitoring on survival benefit: a cluster analysis. (3rd October 2022) - Kolk, M Z H; Deb, B; Ruiperez-Campillo, S; Narayan, S M; Knops, R E; Tjong, F V Y
Abstract: Background/Introduction: Over the past decade, various studies have demonstrated an association between remote device monitoring (RM) in implantable cardioverter-defibrillator (ICD) patients and all-cause mortality. However, it is unclear which clinical phenotypes account for this survival benefit. Purpose: We aimed to identify clinical phenotypes within an ICD population on RM and conventional follow-up (NRM), and evaluate differences in long-term survival per clinical phenotype. Methods: This is a single-center, retrospective, observational study of de novo ICD implantations (single- and dual chamber, biventricular and subcutaneous) between 2010 and 2021 in patients ≥18 years old. Data was extracted from electronic health records. Unsupervised two-step cluster analysis (TSC) was performed to identify distinct clinical phenotypes in the RM and NRM cohorts. Multinomial logistic regression analysis was performed to identify cluster characteristics, differences among the different clusters were analysed by Chi-squared test. Variable importance was evaluated for each of the 18 included clinical variables. Survival analysis was performed using the Kaplan-Meier method, log-rank was used to compare survival between groups. Results: A total of 1872 ICD patients were analysed using TCS, comprising 1265 RM and 607 NRM patients, respectively. TCS for a mean follow-up duration of 5.4±3.1 years partitioned the RM and NRM groups into six clusters (Table 1). Clusters RM1 (n=444) and NRM3 (n=220) represented a predominantly primary prevention and DCM phenotype. Clusters RM2 (n=300) and NRM2 (n=173) indicated young and secondary prevention phenotypes. Clusters RM3 (n=220) and NRM1 (n=214) comprised an older, male and ischaemic cardiomyopathy (ICM) phenotype. In survival analysis 5-year cumulative incidence of mortality for the subsequent clusters was 7.4%, 4.5%, 11.6%, 41.4%, 29.8%, and 25.1%, respectively (log rank p-value <0.001, Figure 1). Thus, younger and DCM phenotypes (often with genetic aetiologies) experienced superior survival and high rates on RM, whereas older, male and ICM phenotypes with low rates on RM were associated with worse survival. In addition, between-group cluster-comparison of patients on RM only demonstrated important differences in long-term survival, where RM3 (comprising older, male with predominantly ICM) had poorer survival compared to young patients with a high prevalence of DCM, primary arrhythmia syndrome and low proportions of comorbidities (i.e. atrial arrhythmias, cerebral vascular accidents, diabetes mellitus). Conclusion: We identify novel clinical phenotypes (clusters) of ICD patients on RM and having conventional follow-up with large differences in long-term survival. Future studies should further explore if these differences reflect benefit from RM, or the underlying natural history of each phenotype. These results may accordingly guide monitoring strategies tailored to specific ICD patient profiles. Funding Acknowledgement: Type of funding sources: Public hospital(s). Main funding source(s): Public funding