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Supraventricular premature beats and risk of new‐onset atrial fibrillation in coronary artery disease
Author(s) -
Nortamo Santeri,
Kenttä Tuomas V.,
Ukkola Olavi,
Huikuri Heikki V.,
Perkiömäki Juha S.
Publication year - 2017
Publication title -
journal of cardiovascular electrophysiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.193
H-Index - 138
eISSN - 1540-8167
pISSN - 1045-3873
DOI - 10.1111/jce.13304
Subject(s) - medicine , atrial fibrillation , cardiology , coronary artery disease , sinus rhythm , quartile , univariate analysis , cohort , multivariate analysis , confidence interval
The significance of premature atrial contraction (PAC) count and supraventricular runs (SVR) for the risk of development of new‐onset atrial fibrillation (AF) in patients with coronary artery disease (CAD) is not well established. Methods The Innovation to Reduce Cardiovascular Complications of Diabetes at the Intersection (ARTEMIS) study cohort consisted of 1,946 patients with CAD who underwent clinical and echocardiographic examinations, 24‐hour ambulatory ECG monitoring, and laboratory tests. After excluding patients who were not in sinus rhythm at baseline or were lost from the follow‐up, the present study included 1,710 patients. SVR was defined as at least four PACs in a row with a duration <30 seconds. Results During a follow‐up for an average 5.6 ± 1.5 years, new‐onset AF was identified in 143 (8.4%) patients. In the univariate analysis, both SVR and PAC count were associated with the development of new‐onset AF. When SVR and PAC count were adjusted with the established AF risk markers of the modified CHARGE‐AF model in the Cox multivariate regression analysis, both parameters remained significant predictors of the occurrence of new‐onset AF (HR = 2.529, 95 % CI = 1.763–3.628, P ˂ 0.001 and HR = 8.139 for ≥1,409 PACs [the fourth quartile] vs. ≤507 PACs [the first quartile], 95 % CI = 3.967–16.696, P ˂ 0.001, respectively). Together these parameters improved the C‐index of the established AF risk model from 0.649 to 0.718, P < 0.001. Conclusion Including SVR and PAC count to the established AF risk model improves the discrimination accuracy in predicting AF in patients with CAD.