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Original research article
Selective screening for atrial fibrillation using multivariable risk models
  1. David T Linker1,
  2. Tasha B Murphy2,
  3. Ali H Mokdad3
  1. 1 Division of Cardiology, Department of Medicine, University of Washington, Seattle, Washington, USA
  2. 2 School of Social Work, University of Washington, Seattle, Washington, USA
  3. 3 Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, USA
  1. Correspondence to Dr David T Linker, Division of Cardiology, Department of Medicine, University of Washington, Seattle, WA 98195, USA; dtlinker{at}uw.edu

Abstract

Objective Atrial fibrillation can lead to stroke if untreated, and identifying those at higher risk is necessary for cost-effective screening for asymptomatic, paroxysmal atrial fibrillation. Age has been proposed to identify those at risk, but risk models may provide better discrimination. This study compares atrial fibrillation risk models with age for screening for atrial fibrillation.

Methods Nine atrial fibrillation risk models were compared using the Atherosclerosis Risk in Communities study (11 373 subjects, 60.0±5.7 years old). A new risk model (Screening for Asymptomatic Atrial Fibrillation Events—SAAFE) was created using data collected in the Monitoring Disparities in Chronic Conditions study (3790 subjects, 58.9±15.3 years old). The primary measure was the fraction of incident atrial fibrillation subjects who should receive treatment due to a high CHA2DS2-VASc score identified when screening a fixed number equivalent to the age criterion. Secondary measures were the C statistic and net benefit.

Results Five risk models were significantly better than age. Age identified 71 (61%) of the subjects at risk for stroke who subsequently developed atrial fibrillation, while the best risk model identified 96 (82%). The newly developed SAAFE model identified 95 (81%), primarily based on age, congestive heart failure and coronary artery disease.

Conclusions Use of a risk model increases identification of subjects at risk for atrial fibrillation. One of the best performing models (SAAFE) does not require an ECG for its application, so that it could be used instead of age as a screening criterion without adding to the cost.

  • atrial fibrillation
  • cardiac risk factors and prevention
  • stroke

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Footnotes

  • Contributors AHM conceived and designed the MDCC study and critically revised the current manuscript. TBM acquired the data in the MDCC study and critically revised the current manuscript. DTL conceived and designed the SAAFE study, conceived and designed the current study, performed the statistical analysis and drafted the manuscript.

  • Funding Life Sciences Discovery Fund of Washington State, Seattle, WA (Grant 5628758) and National Heart, Lung and Blood Institute of the NIH, Bethesda, MD (Grant RC2HL101759).

  • Disclaimer This paper does not necessarily reflect the opinions or views of ARIC or the NHLBI.

  • Competing interests DTL reports stock ownership in Cardiac Insight, a company developing new ambulatory cardiac monitoring solutions, and patents related to automated detection of atrial fibrillation.

  • Ethics approval Institutional Review Board of the University of Washington.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data sharing statement No new data were collected in this study. The ARIC data set is available from the NHLBI Biologic Specimen and Data Repository Information Coordinating Center. The MDCC data will be available as soon as it has been deidentified.

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