Background Chronic kidney disease (CKD) is known to increase the risk of atrial fibrillation (AF) development, but the relationship between AF and subsequent renal function decline in patients with CKD is not well understood. In this study, we explored the role of AF on renal outcomes among patients with CKD.
Methods In a retrospective hospital-based cohort study, we identified patients with CKD aged ≥20 years from 1 January 2008 to 31 December 2018. The patients were divided into AF and non-AF groups. We matched each patient with CKD and AF to two non-AF CKD controls according to propensity scores. The outcomes of interest included estimated glomerular filtration rate (eGFR) decline of ≥20%, ≥30%, ≥40% and ≥50%, and end-stage renal disease (ESRD).
Results After propensity score matching, 6731 patients with AF and 13 462 matched controls were included in the analyses. Compared with the non-AF group, the AF group exhibited greater risks of eGFR decline ≥20% (HR 1.43; 95% CI 1.33 to 1.53), ≥30% (HR 1.50; 95% CI 1.36 to 1.66), ≥40% (HR 1.62; 95% CI 1.41 to 1.85) and ≥50% (HR 1.82; 95% CI 1.50 to 2.20), and ESRD (HR 1.22; 95% CI 1.12 to 1.34). Higher CHA2DS2-VASc scores were associated with greater risks of eGFR decline and ESRD.
Conclusions In patients with CKD, AF was associated with greater risks of subsequent renal function decline. CHA2DS2-VASc scores may be a useful risk stratification scheme for predicting the risk of renal function decline.
- atrial fibrillation
Data availability statement
All data relevant to the study are included in the article or uploaded as supplemental information.
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Contributors Conception and study design—S-MO and T-HC. Data acquisition—S-MO and D-CT. Data analysis/interpretation—S-MO, Y-CC and T-HC. Statistical analysis—S-MO and T-HC. Drafting of the manuscript—T-HC, Y-CC and S-MO. Critical revision of the manuscript for important intellectual content—S-MO and D-CT. Final approval of the version to be published—S-MO and D-CT.
Funding This work was supported in part by the Ministry of Science and Technology, Taiwan (MOST 106-2314-B-010-039-MY3, MOST 107-2314-B-075-052, MOST 108-2314-B-075-008, MOST 109-2314-B-075 -067 -MY3, MOST 109-2320-B-075-006); Taipei, Taichung, Kaohsiung Veterans General Hospital, Tri-Service General Hospital, Academia Sinica Joint Research Program (VTA110-V1-3-1); Taipei Veterans General Hospital (V107B-027, V108B-023, V108C-103, V108D42-004-MY3-2, V109B-022, V109C-114, V109D50-001-MY3-1, V109D50-001-MY3-2, V110C-152, V110E-003-2); Taipei Veterans General Hospital-National Yang-Ming University Excellent Physician Scientists Cultivation Program (No.104-V-B-044). This work was also financially supported by the 'Center for Intelligent Drug Systems and Smart Bio-devices (IDS2B)' from The Featured Areas Research Center Program within the framework of the Higher Education Sprout Project by the Ministry of Education (MOE) in Taiwan, and Foundation for Poison Control (FPC-109-002). This study is based in part on data from the Big Data Center, Taipei Veterans General Hospital (BDC, TPEVGH).
Disclaimer The funders did not play any roles in the study design, data collection or analysis, decision to publish, or preparation of the manuscript. The interpretations and conclusions contained herein do not represent the position of Taipei Veterans General Hospital.
Competing interests None declared.
Provenance and peer review Not commissioned; externally peer reviewed.
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