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.
|Number of pages||8|
|Journal||Annals of internal medicine|
|State||Published - Dec 3 2013|