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Original Research |

Atrial Ectopy as a Predictor of Incident Atrial Fibrillation: A Cohort Study

Thomas A. Dewland, MD; Eric Vittinghoff, PhD, MPH; Mala C. Mandyam, MD; Susan R. Heckbert, MD, PhD; David S. Siscovick, MD, MPH; Phyllis K. Stein, PhD; Bruce M. Psaty, MD, PhD; Nona Sotoodehnia, MD; John S. Gottdiener, MD; and Gregory M. Marcus, MD, MAS
[+] Article and Author Information

From University of California, San Francisco, San Francisco, California; University of Washington and Group Health Research Institute, Seattle, Washington; Washington University School of Medicine, St. Louis, Missouri; and University of Maryland Medical Center, Baltimore, Maryland.

Disclaimer: Drs. Dewland and Marcus had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. A full list of principal Cardiovascular Health Study investigators and institutions can be found at www.chs-nhlbi.org. The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of the National Institutes of Health.

Grant Support: By grants 12POST11810036 (Dr. Dewland) and 12GRNT11780061 (Dr. Marcus) from the American Heart Association, the Joseph Drown Foundation (Dr. Marcus), and grant R01HL116747 (Dr. Sotoodehnia) from the National Heart, Lung, and Blood Institute; contracts HHSN268201200036C, N01HC85239, N01HC55222, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, and N01HC85086 and grant HL080295 from the National Heart, Lung, and Blood Institute, with additional contribution from the National Institute of Neurological Disorders and Stroke; and grant AG023629 from the National Institute on Aging.

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

Reproducible Research Statement:Study protocol and statistical code: Available from Dr. Marcus (e-mail, marcusg@medicine.ucsf.edu). Data set: Available through established CHS procedures for obtaining and analyzing data (see https://chs-nhlbi.org/).

Requests for Single Reprints: Gregory M. Marcus, MD, MAS, 505 Parnassus Avenue, M-1180B, San Francisco, CA 94143; e-mail, marcusg@medicine.ucsf.edu.

Current Author Addresses: Drs. Dewland, Mandyam, and Marcus: University of California, San Francisco, 505 Parnassus Avenue, M-1180B, San Francisco, CA 94143.

Dr. Vittinghoff: University of California, San Francisco, 185 Berry Street, Suite 5700, San Francisco, CA 94107.

Drs. Heckbert, Siscovick, Psaty, and Sotoodehnia: University of Washington Cardiovascular Health Research Unit, 1730 Minor Avenue, Suite 1360, Seattle, WA 98101.

Dr. Stein: Washington University School of Medicine, 660 South Euclid Avenue, Campus Box 8086, St. Louis, MO 63110.

Dr. Gottdiener: University of Maryland Medical Center, 22 South Greene Street, Baltimore, MD 21201.

Author Contributions: Conception and design: T.A. Dewland, M.C. Mandyam, G.M. Marcus.

Analysis and interpretation of the data: T.A. Dewland, E. Vittinghoff, M.C. Mandyam, S.R. Heckbert, D.S. Siscovick, P.K. Stein, B.M. Psaty, N. Sotoodehnia, J.S. Gottdeiner, G.M. Marcus.

Drafting of the article: T.A. Dewland, E. Vittinghoff, M.C. Mandyam, G.M. Marcus.

Critical revision of the article for important intellectual content: T.A. Dewland, E. Vittinghoff, M.C. Mandyam, S.R. Heckbert, D.S. Siscovick, P.K. Stein, B.M. Psaty, N. Sotoodehnia, J.S. Gottdeiner, G.M. Marcus.

Final approval of the article: T.A. Dewland, E. Vittinghoff, M.C. Mandyam, S.R. Heckbert, D.S. Siscovick, P.K. Stein, B.M. Psaty, N. Sotoodehnia, J.S. Gottdiener, G.M. Marcus.

Provision of study materials or patients: S.R. Heckbert, D.S. Siscovick, P.K. Stein, B.M. Psaty, N. Sotoodehnia, J.S. Gottdeiner.

Statistical expertise: T.A. Dewland, E. Vittinghoff, G.M. Marcus.

Obtaining of funding: T.A. Dewland, G.M. Marcus.

Administrative, technical, or logistic support: T.A. Dewland, S.R. Heckbert, D.S. Siscovick, P.K. Stein, B.M. Psaty, N. Sotoodehnia, J.S. Gottdeiner, G.M. Marcus.

Collection and assembly of data: T.A. Dewland, M.C. Mandyam, S.R. Heckbert, D.S. Siscovick, P.K. Stein, B.M. Psaty, N. Sotoodehnia, J.S. Gottdeiner, G.M. Marcus.


Ann Intern Med. 2013;159(11):721-728. doi:10.7326/0003-4819-159-11-201312030-00004
Text Size: A A A

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.

Figures

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Appendix Figure.

AF risk discrimination, by follow-up time.

The c-statistics for AF risk discrimination using the Framingham (square), PAC (circle), and Framingham and PAC (triangle) models are shown after censoring follow-up at 5, 10, and 15 y. All models used competing risk method with spline-transformed PAC counts. Error bars denote 95% CIs. AF = atrial fibrillation; PAC = premature atrial contraction.

* For comparison of the Framingham model c-statistic with the PAC model c-statistic.† For comparison of the Framingham model c-statistic with the combined Framingham and PAC model c-statistic.

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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.

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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.

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