Characteristics and clinical outcomes in atrial fibrillation patients classified using cluster analysis: the Fushimi AF Registry

Hisashi Ogawa, Yoshimori An, Hidehisa Nishi, Shunichi Fukuda, Kenjiro Ishigami, Syuhei Ikeda, Kosuke Doi, Yuya Ide, Yasuhiro Hamatani, Akiko Fujino, Mitsuru Ishii, Moritake Iguchi, Nobutoyo Masunaga, Masahiro Esato, Hikari Tsuji, Hiromichi Wada, Koji Hasegawa, Mitsuru Abe, Tetsuya Tsukahara, Gregory Y H LipMasaharu Akao*, Fushimi AF Registry Investigators

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

11 Citations (Scopus)

Abstract

AIMS: The risk of adverse events in atrial fibrillation (AF) patients was commonly stratified by risk factors or clinical risk scores. Risk factors often do not occur in isolation and are often found in multimorbidity 'clusters' which may have prognostic implications. We aimed to perform cluster analysis in a cohort of AF patients and to assess the outcomes and prognostic implications of the identified comorbidity cluster phenotypes.

METHODS AND RESULTS: The Fushimi AF Registry is a community-based prospective survey of the AF patients in Fushimi-ku, Kyoto, Japan. Hierarchical cluster analysis was performed on 4304 patients (mean age: 73.6 years, female; 40.3%, mean CHA2DS2-VASc score 3.37 ± 1.69), using 42 baseline clinical characteristics. On hierarchical cluster analysis, AF patients could be categorized into six statistically driven comorbidity clusters: (i) younger ages (mean age: 48.3 years) with low prevalence of risk factors and comorbidities (n = 209); (ii) elderly (mean age: 74.0 years) with low prevalence of risk factors and comorbidities (n = 1301); (iii) those with high prevalence of atherosclerotic risk factors, but without atherosclerotic disease (n = 1411); (iv) those with atherosclerotic comorbidities (n = 440); (v) those with history of any-cause stroke (n = 681); and (vi) the very elderly (mean age: 83.4 years) (n = 262). Rates of all-cause mortality and major adverse cardiovascular or neurological events can be stratified by these six identified clusters (log-rank test; P < 0.001 and P < 0.001, respectively).

CONCLUSIONS: We identified six clinically relevant phenotypes of AF patients on cluster analysis. These phenotypes can be associated with various types of comorbidities and associated with the incidence of clinical outcomes.

CLINICAL TRIAL REGISTRATION INFORMATION: https://www.umin.ac.jp/ctr/index.htm. Unique identifier: UMIN000005834.

Original languageEnglish
JournalEuropace
Volume23
Issue number9
Pages (from-to)1369-1379
Number of pages11
ISSN1099-5129
DOIs
Publication statusPublished - 8 Sept 2021

Bibliographical note

Published on behalf of the European Society of Cardiology. All rights reserved. © The Author(s) 2021. For permissions, please email: journals.permissions@oup.com.

Keywords

  • Atrial fibrillation
  • Cluster analysis
  • Comorbidity
  • Outcome
  • Registry

Fingerprint

Dive into the research topics of 'Characteristics and clinical outcomes in atrial fibrillation patients classified using cluster analysis: the Fushimi AF Registry'. Together they form a unique fingerprint.

Cite this