Cardiovascular diseases (CVD) are the most common cause of mortality among adults worldwide. The best strategy for CVD prevention is to modify risk factors e.g., high LDL-cholesterol, high blood pressure, obesity, smoking and poor lifestyle practices, such as an unhealthy diet and physical inactivity. Currently physicians utilize a tool for calculating a 10-year CVD risk score, which relies on the pooled cohort equations (PCE). To calculate the PCE risk score, it requires a healthcare provider to collect various laboratory test results, demographic information and other risk factors and performing the risk calculation on a computer.

The 2018-AHA/ACC/Multi-society Guideline on the Management of Blood Cholesterol [1] recommends for primary prevention that a ASCVD risk be calculated on everyone between age 40 and 75 to determine statin eligibility, except for those who are already at a very high or low risk [2]. If a patient has a score greater than 20%, high-dose statins are recommended; if a 10-year risk score is between 7.5 and 20%, it is considered an intermediate risk score for which starting a statin therapy will depend on the presence of other risk factors; if a 10-year risk is below 7.5% - a person is at a low risk but should still follow healthy lifestyle recommendations.

Our goal was to simplify the CVD risk score calculation to help compliance with current recommendations. We created a new risk calculation tool called an estimated ASCVD risk score, eASCVD for short [3]. An eASCVD score can be automatically calculated by the clinical laboratory by utilizing standard lipid panel, age, race and sex, information which is typically already available from Laboratory Information Systems. Software for performing eASCVD lipid risk score can be freely downloaded at the linked website: Using data from National Health and Nutrition Examination Survey, the eASCVD risk score was shown to have a sensitivity of 69% and a specificity of 97.5% for identifying statin-eligible patients with at least intermediate CVD risk (>7.5%/10-year) as determined by the standard PCE risk score. By summing the presence of non-lipid risk factors (SBP>130 mmHg, blood pressure medication usage and smoking) to do a simple adjustment of the threshold for the eASCVD risk score, its overall sensitivity increased to 94%, with a specificity of 92%. Moreover, the eASCVD risk score showed almost 90% agreement with the standard 10-year PCE risk score in predicting CVD events in a cohort of patients from the Atherosclerosis Risk In Communities study.

We propose that this new automated eASCVD lipid risk score be integrated as a primary prevention tool for screening patients at risk for CVD and as a decision aid for statin therapy. Before starting statin therapy, it is still recommended that a standard PCE risk score be calculated to confirm that a patient is at least intermediate risk. Nevertheless, adding the eASCVD score to the laboratory report could help healthcare providers better follow current guidelines without incurring any additional costs. It could also help educate patients by fostering discussions with their physicians about CVD risk factors.


1 Lipoprotein Metabolism Laboratory, Translational Vascular Medicine Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA

To whom correspondence should be addressed

Anna Wolska, Lipoprotein Metabolism Laboratory, Translational Vascular Medicine Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, 9000 Rockville Pike, Bldg. 10/Rm. 5D15, Bethesda, MD 20892, Tel: 301-496-3707, Fax: 301-402-1885, e-mail: [email protected]


This research was supported by the Intramural Research Program of the National Heart, Lung, and Blood Institute (NHLBI) at National Institutes of Health.


  1. Grundy, S.M., et al., 2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA Guideline on the Management of Blood Cholesterol: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Circulation, 2019. 139(25): p. e1082-e1143.
  2. Bonow, R.O. and C.W. Yancy, High-Intensity Statins for Secondary Prevention. JAMA Cardiol, 2017. 2(1): p. 55.
  3. Sampson, M., et al., Estimated Atherosclerotic Cardiovascular Disease Risk Score: An Automated Decision Aid for Statin Therapy. Clinical Chemistry, 2022. 68(10): p. 1302-1310