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The optimal lookback period for estimating incidence and temporal trends in atrial fibrillation

Authors
 Kim, Seonji  ;  Kim, Daehoon  ;  Kim, Seung Il  ;  Jang, Eunsun  ;  Yu, Hee Tae  ;  Kim, Tae-Hoon  ;  Uhm, Jae-Sun  ;  Sung, Jung-Hoon  ;  Pak, Hui-Nam  ;  Lee, Moon-Hyoung  ;  You, Seng Chan  ;  Yang, Pil-Sung  ;  Joung, Boyoung 
Citation
 HEART RHYTHM, Vol.22(12) : e1115-e1124, 2025-12 
Journal Title
HEART RHYTHM
ISSN
 1547-5271 
Issue Date
2025-12
MeSH
Adult ; Aged ; Atrial Fibrillation* / epidemiology ; Atrial Fibrillation* / physiopathology ; Female ; Humans ; Incidence ; Male ; Middle Aged ; Prevalence ; Republic of Korea / epidemiology ; Retrospective Studies ; Time Factors
Keywords
Atrial fibrillation ; Lookback period ; Incidence ; Prevalence ; Mortality ; Epidemiology
Abstract
BACKGROUND Accurate measurement of atrial fibrillation (AF) incidence using secondary data is challenging because ofvari-ation in lookback period definitions used to distinguish incident from prevalent cases. As the choice of lookback period critically influences incidence estimates, establishing an appropriate duration is essential for sustained surveillance of AF trends. OBJECTIVE This study aimed to identify a reproducible definition of the lookback period and analyze trends in the incidence rate and prevalence of AF in Korea. METHODS This nationwide observational cohort study used Korean claims data from 2011 to 2021. Patients aged >= 20 years diagnosed with AF were identified. Annual age-and sex-standardized incidence rates were analyzed and compared across various lookback periods, and annual AF prevalence was calculated. RESULTS Among 1,185,366 patients with AF, the standardized incidence rate of AF was 2.14 per 1000 person-years in 2021 using a 10-year lookback period. A lookback period of at least 4 years yielded incidence rates within a 10% margin of those from a 10-year lookback period. Incidence rates varied depending on the duration of data availability and lookback periods, but using a fixed 4-year lookback produced consistent and stable estimates, ranging from 2.24 per 1000 person-years in 2015 to 2.32 in 2021. AF prevalence increased from 1.17% to 1.92% during the same period. CONCLUSION This study emphasizes the importance of defining and justifying lookback periods when estimating AF incidence. Using a fixed 4-year lookback period, we ensured a consistent and reproducible estimation of AF incidence and observed a steady increase in prevalence.
Full Text
https://www.sciencedirect.com/science/article/pii/S1547527125027341
DOI
10.1016/j.hrthm.2025.07.053
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Biomedical Systems Informatics (의생명시스템정보학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Internal Medicine (내과학교실) > 1. Journal Papers
Yonsei Authors
Kim, Dae Hoon(김대훈) ORCID logo https://orcid.org/0000-0002-9736-450X
Kim, Seonji(김선지)
Kim, Tae-Hoon(김태훈) ORCID logo https://orcid.org/0000-0003-4200-3456
Pak, Hui Nam(박희남) ORCID logo https://orcid.org/0000-0002-3256-3620
Yang, Pil Sung(양필성)
Uhm, Jae Sun(엄재선) ORCID logo https://orcid.org/0000-0002-1611-8172
You, Seng Chan(유승찬) ORCID logo https://orcid.org/0000-0002-5052-6399
Yu, Hee Tae(유희태) ORCID logo https://orcid.org/0000-0002-6835-4759
Lee, Moon-Hyoung(이문형) ORCID logo https://orcid.org/0000-0002-7268-0741
Joung, Bo Young(정보영) ORCID logo https://orcid.org/0000-0001-9036-7225
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/209978
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