Background: Atrial fibrillation (AF) prediction models have unclear clinical utility given the absence of AF prevention therapies and the immutability of many risk factors. Premature atrial contractions (PACs) play a critical role in AF pathogenesis and may be modifiable.
Objective: To investigate whether PAC count improves model performance for AF risk.
Design: Prospective cohort study.
Setting: 4 U.S. communities.
Patients: A random subset of 1260 adults without prevalent AF enrolled in the Cardiovascular Health Study between 1989 and 1990.
Measurements: The PAC count was quantified by 24-hour electrocardiography. Participants were followed for the diagnosis of incident AF or death. The Framingham AF risk algorithm was used as the comparator prediction model.
Results: In adjusted analyses, doubling the hourly PAC count was associated with a significant increase in AF risk (hazard ratio, 1.17 [95% CI, 1.13 to 1.22]; P < 0.001) and overall mortality (hazard ratio, 1.06 [CI, 1.03 to 1.09]; P < 0.001). Compared with the Framingham model, PAC count alone resulted in similar AF risk discrimination at 5 and 10 years of follow-up and superior risk discrimination at 15 years. The addition of PAC count to the Framingham model resulted in significant 10-year AF risk discrimination improvement (c-statistic, 0.65 vs. 0.72; P < 0.001), net reclassification improvement (23.2% [CI, 12.8% to 33.6%]; P < 0.001), and integrated discrimination improvement (5.6% [CI, 4.2% to 7.0%]; P < 0.001). The specificity for predicting AF at 15 years exceeded 90% for PAC counts more than 32 beats/h.
Limitation: This study does not establish a causal link between PACs and AF.
Conclusion: The addition of PAC count to a validated AF risk algorithm provides superior AF risk discrimination and significantly improves risk reclassification. Further study is needed to determine whether PAC modification can prospectively reduce AF risk.
Primary Funding Source: American Heart Association, Joseph Drown Foundation, and National Institutes of Health.