Abstract
Patients with atrial fibrillation (AF) still experience a high mortality rate despite optimal antithrombotic treatment. We aimed to identify clinical phenotypes of patients to stratify mortality risk in AF. Cluster analysis was performed on 5171 AF patients from the nationwide START registry. The risk of all-cause mortality in each cluster was analyzed. We identified four clusters. Cluster 1 was composed of the youngest patients, with low comorbidities; Cluster 2 of patients with low cardiovascular risk factors and high prevalence of cancer; Cluster 3 of men with diabetes and coronary disease and peripheral artery disease; Cluster 4 included the oldest patients, mainly women, with previous cerebrovascular events. During 9857 person-years of observation, 386 deaths (3.92%/year) occurred. Mortality rates increased across clusters: 0.42%/year (cluster 1, reference group), 2.12%/year (cluster 2, adjusted hazard ratio (aHR) 3.306, 95% confidence interval (CI) 1.204–9.077, p = 0.020), 4.41%/year (cluster 3, aHR 6.702, 95%CI 2.433–18.461, p < 0.001), and 8.71%/year (cluster 4, aHR 8.927, 95%CI 3.238–24.605, p < 0.001). We identified four clusters of AF patients with progressive mortality risk. The use of clinical phenotypes may help identify patients at a higher risk of mortality.
Funder
Sapienza University of Rome, Progetto di Ateneo 2022
Cited by
5 articles.
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