Impact of clinical phenotypes on management and outcomes in European atrial fibrillation patients: a report from the ESC-EHRA EURObservational Research Programme in AF (EORP-AF) General Long-Term Registry.

Creative Commons License

Proietti M., Vitolo M., Harrison S. L., Lane D. A., Fauchier L., Marin F., ...More

BMC medicine, vol.19, no.1, pp.256, 2021 (SCI-Expanded) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 19 Issue: 1
  • Publication Date: 2021
  • Doi Number: 10.1186/s12916-021-02120-3
  • Journal Name: BMC medicine
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, BIOSIS, CINAHL, EMBASE, MEDLINE, Directory of Open Access Journals
  • Page Numbers: pp.256
  • Keywords: Atrial fibrillation, Clinical phenotypes, Cluster analysis, Clinical management, Major adverse outcomes, CLUSTER-ANALYSIS, FOLLOW-UP, PROGNOSIS, RISK
  • Hacettepe University Affiliated: Yes


Background Epidemiological studies in atrial fibrillation (AF) illustrate that clinical complexity increase the risk of major adverse outcomes. We aimed to describe European AF patients' clinical phenotypes and analyse the differential clinical course. Methods We performed a hierarchical cluster analysis based on Ward's Method and Squared Euclidean Distance using 22 clinical binary variables, identifying the optimal number of clusters. We investigated differences in clinical management, use of healthcare resources and outcomes in a cohort of European AF patients from a Europe-wide observational registry. Results A total of 9363 were available for this analysis. We identified three clusters: Cluster 1 (n = 3634; 38.8%) characterized by older patients and prevalent non-cardiac comorbidities; Cluster 2 (n = 2774; 29.6%) characterized by younger patients with low prevalence of comorbidities; Cluster 3 (n = 2955;31.6%) characterized by patients' prevalent cardiovascular risk factors/comorbidities. Over a mean follow-up of 22.5 months, Cluster 3 had the highest rate of cardiovascular events, all-cause death, and the composite outcome (combining the previous two) compared to Cluster 1 and Cluster 2 (all P < .001). An adjusted Cox regression showed that compared to Cluster 2, Cluster 3 (hazard ratio (HR) 2.87, 95% confidence interval (CI) 2.27-3.62; HR 3.42, 95%CI 2.72-4.31; HR 2.79, 95%CI 2.32-3.35), and Cluster 1 (HR 1.88, 95%CI 1.48-2.38; HR 2.50, 95%CI 1.98-3.15; HR 2.09, 95%CI 1.74-2.51) reported a higher risk for the three outcomes respectively. Conclusions In European AF patients, three main clusters were identified, differentiated by differential presence of comorbidities. Both non-cardiac and cardiac comorbidities clusters were found to be associated with an increased risk of major adverse outcomes.