Atrial Fibrillation Patterns and Risks of Subsequent Stroke, Heart Failure, or Death in the Community

Author:

Lubitz Steven A.12,Moser Carlee3,Sullivan Lisa3,Rienstra Michiel14,Fontes João D.56,Villalon Mark L.7,Pai Manju8,McManus David D.910,Schnabel Renate B.611,Magnani Jared W.56,Yin Xiaoyan6,Levy Daniel612,Pencina Michael J.36,Larson Martin G.3136,Ellinor Patrick T.12,Benjamin Emelia J.145156

Affiliation:

1. Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA

2. Cardiac Arrhythmia Service, Massachusetts General Hospital, Boston, MA

3. Department of Biostatistics, Boston University School of Public Health, Boston, MA

4. Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands

5. Section of Cardiovascular Medicine, Boston University School of Medicine, Boston, MA

6. Boston University's and National Heart, Lung and Blood Institute's Framingham Heart Study, Framingham, MA

7. Department of Medicine, Boston University School of Medicine, Boston, MA

8. Department of Cardiovascular Medicine, Cleveland Clinic, Cleveland, OH

9. Department of Medicine, University of Massachusetts Medical School, Worcester, MA

10. Department of Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA

11. Department of General and Interventional Cardiology, University Medical Center Hamburg Eppendorf, Hamburg, Germany

12. Center for Population Studies, National Heart, Lung, and Blood Institute, Bethesda, MD

13. Department of Mathematics and Statistics, Boston University, Boston, MA

14. Department of Epidemiology, Boston University School of Public Health, Boston, MA

15. Preventive Medicine Section, Boston University School of Medicine, Boston, MA

Abstract

Background Atrial fibrillation ( AF ) patterns and their relations with long‐term prognosis are uncertain, partly because pattern definitions are challenging to implement in longitudinal data sets. We developed a novel AF classification algorithm and examined AF patterns and outcomes in the community. Methods and Results We characterized AF patterns between 1980 and 2005 among Framingham Heart Study participants who survived ≥1 year after diagnosis. We classified participants based on their pattern within the first 2 years after detection as having AF without recurrence, recurrent AF , or sustained AF . We examined associations between AF patterns and 10‐year survival using proportional hazards regression. Among 612 individuals with AF , mean age was 72.5±10.8 years, and 53% were men. Of these, 478 participants had ≥2 electrocardiograms (median, 3; limits 2 to 23) within 2 years after initial AF and were classified as having AF without 2‐year recurrence (n=63, 10%), recurrent AF (n=162, 26%) or sustained AF (n=207, 34%), although some (n=46, 8%) were indeterminate. Of 432 classified participants, 363 died, 75 had strokes, and 110 were diagnosed with heart failure during the next 10 years. Relative to individuals without AF recurrence, the multivariable‐adjusted mortality was higher among people with recurrent AF (hazard ratio [ HR ], 2.04; 95% confidence interval [ CI ], 1.26 to 3.29) and sustained AF ( HR , 2.36; 95% CI , 1.49 to 3.75). Conclusions In our community‐based AF sample, only 10% had AF without early‐term (2‐year) recurrence. Compared with individuals without 2‐year AF recurrences, the 10‐year prognosis was worse for individuals with either sustained or recurrent AF . Our proposed AF classification algorithm may be applicable in longitudinal datas ets.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Cardiology and Cardiovascular Medicine

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