Jose B Cruz Rodriguez1,2, Khan O Mohammad3, Haider Alkhateeb4. 1. Division of Cardiovascular Diseases, Department of Internal Medicine, Texas Tech University Health Sciences Center, El Paso, TX, USA. jcruzrodriguez@health.ucsd.edu. 2. Division of Cardiovascular Medicine, Department of Medicine, University of California San Diego, 9452 Medical Center Drive #7411, San Diego, CA, 92037, USA. jcruzrodriguez@health.ucsd.edu. 3. Department of Internal Medicine, Dell Seton Medical Center, at The University of Texas, Austin, TX, USA. 4. Division of Cardiovascular Diseases, Department of Internal Medicine, Texas Tech University Health Sciences Center, El Paso, TX, USA.
Abstract
PURPOSE OF REVIEW: Explore the current literature supporting risk stratification scores for prediction of coronary and cardiovascular disease deaths. RECENT FINDINGS: Accurate risk prediction remains the foundation of management choice in primary prevention. When applied to new populations, the calibration of a predictive model will deteriorate, although discrimination changes minimally. One of the approaches with better performance and validation is the initial use of pooled cohort equation to identify low and high-risk patients, followed by coronary artery calcium scoring in those with borderline to intermediate risk. It is important to utilize a risk stratification tool that has been validated in a patient population that resembles the one used to develop the original tool to maintain adequate calibration. It is likely that the future of mortality risk prediction will develop in combined clinical risk predictors and cardiovascular imaging, such coronary artery calcium (CAC) scoring that renders the highest predictive accuracy.
PURPOSE OF REVIEW: Explore the current literature supporting risk stratification scores for prediction of coronary and cardiovascular disease deaths. RECENT FINDINGS: Accurate risk prediction remains the foundation of management choice in primary prevention. When applied to new populations, the calibration of a predictive model will deteriorate, although discrimination changes minimally. One of the approaches with better performance and validation is the initial use of pooled cohort equation to identify low and high-risk patients, followed by coronary artery calcium scoring in those with borderline to intermediate risk. It is important to utilize a risk stratification tool that has been validated in a patient population that resembles the one used to develop the original tool to maintain adequate calibration. It is likely that the future of mortality risk prediction will develop in combined clinical risk predictors and cardiovascular imaging, such coronary artery calcium (CAC) scoring that renders the highest predictive accuracy.
Authors: Ralph B D'Agostino; Ramachandran S Vasan; Michael J Pencina; Philip A Wolf; Mark Cobain; Joseph M Massaro; William B Kannel Journal: Circulation Date: 2008-01-22 Impact factor: 29.690
Authors: Kjersti Stormark Rabanal; Haakon Eduard Meyer; Romana Pylypchuk; Suneela Mehta; Randi Marie Selmer; Rodney T Jackson Journal: Open Heart Date: 2018-07-11