Risk Prediction of Atrial Fibrillation Based on Electrocardiographic Interatrial Block

Author:

Skov Morten W.12,Ghouse Jonas12,Kühl Jørgen T.2,Platonov Pyotr G.3,Graff Claus4,Fuchs Andreas2,Rasmussen Peter V.1,Pietersen Adrian5,Nordestgaard Børge G.67,Torp‐Pedersen Christian4,Hansen Steen M.48,Olesen Morten S.1,Haunsø Stig127,Køber Lars27,Gerds Thomas A.9,Kofoed Klaus F.210,Svendsen Jesper H.127,Holst Anders G.1,Nielsen Jonas B.111

Affiliation:

1. Laboratory for Molecular Cardiology, The Heart Center, Rigshospitalet University of Copenhagen, Denmark

2. Department of Cardiology, The Heart Center, Rigshospitalet University of Copenhagen, Denmark

3. Center for Integrative Electrocardiography at Lund University and Arrhythmia Clinic, Skåne University Hospital, Lund, Sweden

4. Department of Health Science and Technology, Aalborg University, Aalborg, Denmark

5. Copenhagen General Practitioners’ Laboratory, Copenhagen, Denmark

6. Department of Clinical Biochemistry and the Copenhagen General Population Study, Herlev and Gentofte Hospital University of Copenhagen, Denmark

7. Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark

8. Department of Cardiology/Epidemiology & Biostatistics, Aalborg University Hospital, Aalborg, Denmark

9. Department of Biostatistics, University of Copenhagen, Denmark

10. Department of Radiology, Rigshospitalet, University of Copenhagen, Denmark

11. Division of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, MI

Abstract

Background The electrocardiographic interatrial block ( IAB ) has been associated with atrial fibrillation ( AF ). We aimed to test whether IAB can improve risk prediction of AF for the individual person. Methods and Results Digital ECGs of 152 759 primary care patients aged 50 to 90 years were collected from 2001 to 2011. We identified individuals with P‐wave ≥120 ms and the presence of none, 1, 2, or 3 biphasic P‐waves in inferior leads. Data on comorbidity, medication, and outcomes were obtained from nationwide registries. We observed a dose‐response relationship between the number of biphasic P‐waves in inferior leads and the hazard of AF during follow‐up. Discrimination of the 10‐year outcome of AF , measured by time‐dependent area under the curve, was increased by 1.09% (95% confidence interval 0.43–1.74%) for individuals with cardiovascular disease at baseline ( CVD ) and 1.01% (95% confidence interval 0.40–1.62%) for individuals without CVD , when IAB was added to a conventional risk model for AF . The highest effect of IAB on the absolute risk of AF was observed in individuals aged 60 to 70 years with CVD . In this subgroup, the 10‐year risk of AF was 50% in those with advanced IAB compared with 10% in those with a normal P‐wave. In general, individuals with advanced IAB and no CVD had a higher risk of AF than patients with CVD and no IAB . Conclusions IAB improves risk prediction of AF when added to a conventional risk model. Clinicians may consider monitoring patients with IAB more closely for the occurrence of AF , especially for high‐risk subgroups.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Cardiology and Cardiovascular Medicine

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