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Coronary Heart Disease Risk Estimation in Asymptomatic Adults

Boo, Sunjoo; Waters, Catherine M.; Froelicher, Erika Sivarajan

doi: 10.1097/NNR.0b013e31823b1429
Methods

Background: Accurate estimation of coronary heart disease (CHD) risk is requisite for effective primary prevention of the disease. The Framingham Risk Score is the most commonly used method for estimating 10-year risk for CHD in asymptomatic individuals. Further noninvasive tests of atherosclerosis are widely available and may be added to enhance risk estimation. However, the ability to combine different test results explicitly in a quantitative way is limited, and a substantial gap remains in identification ofthose at high risk for future CHD.

Objectives: The aims of this paper are to present information about and examples of how to estimate 10-year risk of developing CHD with the Framingham Risk Score and todemonstrate how to combine two different test results with Bayes’ theorem.

Method: Bayes’ theorem of conditional probability is presented as a method by which to combine two different test results in a quantitative way to better identify high-risk asymptomatic individuals.

Discussion: Applying Bayes’ theorem will help nurses to better estimate CHD risk, leading to optimal intervention plans. This method of refining risk estimation is especially useful for individuals who would fall into an intermediate-risk category based on the Framingham Risk Score.

Sunjoo Boo, PhD, RN, is Doctoral Student, Department of Physiological Nursing; Catherine M. Waters, PhD, RN, is Professor, Department of Community Health Systems; and Erika Sivarajan Froelicher, PhD, RN, FAAN, is Professor, Department of Physiological Nursing and Department of Epidemiology and Biostatistics, University of California San Francisco.

Accepted for publication September 22, 2011.

The authors thank Nancy Stotts, RN, EdD, and Dianne Christopherson, PhD, RN, for their advice during manuscript preparation and Christine Hansen for her editorial effort. In addition, the authors thank the School of Nursing, University of California San Francisco, for providing the Graduate Dean’s Health Science Fellowships that helped sponsor the lead author’s current doctoral work.

The authors have no funding or conflicts of interest to disclose.

Corresponding author: Sunjoo Boo, PhD, RN, Formerly a doctoral student, School of Nursing, University of California San Francisco, 2 Koret Way, San Francisco, CA. 94143-0610 (e-mail: sunjoo.boo@ucsf.edu).

© 2012 Lippincott Williams & Wilkins, Inc.