Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Multicenter Study
. 2013 Dec 3;159(11):721-8.
doi: 10.7326/0003-4819-159-11-201312030-00004.

Atrial ectopy as a predictor of incident atrial fibrillation: a cohort study

Multicenter Study

Atrial ectopy as a predictor of incident atrial fibrillation: a cohort study

Thomas A Dewland et al. Ann Intern Med. .

Abstract

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.

PubMed Disclaimer

Conflict of interest statement

Potential Conflicts of Interest: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M13-1229.

Figures

Figure 1
Figure 1. Observed versus predicted 10-year AF risk
Participants are grouped into deciles of predicted risk. In the setting of perfect model calibration, observed and predicted risk would be equal (dashed line). AF = atrial fibrillation; PAC = premature atrial contraction. Top. The Framingham model. Middle. PAC. Bottom. Framingham and PAC risk models.
Figure 2
Figure 2. Predicted AF risk and PAC count
The predicted 15-y risk for AF (using the log-transformed PAC model) is plotted against the hourly PAC count. The sensitivity and specificity for the diagnosis of AF at 15 y for an individual patient are listed for various PAC cutoff values. AF = atrial fibrillation; PAC = premature atrial contraction.

Comment in

References

    1. Naccarelli GV, Varker H, Lin J, Schulman KL. Increasing prevalence of atrial fibrillation and flutter in the United States. Am J Cardiol. 2009;104:1534–1539. [PMID: 19932788] - PubMed
    1. Lin HJ, Wolf PA, Kelly-Hayes M, Beiser AS, Kase CS, Benjamin EJ, et al. Stroke severity in atrial fibrillation. The Framingham Study. Stroke. 1996;27:1760–1764. [PMID: 8841325] - PubMed
    1. Benjamin EJ, Wolf PA, D’Agostino RB, Silbershatz H, Kannel WB, Levy D. Impact of atrial fibrillation on the risk of death: the Framingham Heart Study. Circulation. 1998;98:946–952. [PMID: 9737513] - PubMed
    1. Wolowacz SE, Samuel M, Brennan VK, Jasso-Mosqueda JG, Van Gelder IC. The cost of illness of atrial fibrillation: a systematic review of the recent literature. Europace. 2011;13:1375–1385. [PMID: 21757483] - PubMed
    1. Schnabel RB, Aspelund T, Li G, Sullivan LM, Suchy-Dicey A, Harris TB, et al. Validation of an atrial fibrillation risk algorithm in whites and African Americans. Arch Intern Med. 2010;170:1909–1917. [PMID: 21098350] - PMC - PubMed

Publication types