The Uncertainty of CVD Risk Calculation - What is the best risk model for the individual ?

[+] Author and Article Information
Ronald S. LaFleur

Associate Member ASME, Department of Mechanical and Aeronautical Engineering, Clarkson University, Box 5725 Dept. MAE, Potsdam, NY 13699

Laura S. Goshko

Department of Physician Assistant, Seton Hall University, 400 South Orange Avenue, South Orange, NJ 07079

1Corresponding author.

ASME doi:10.1115/1.4039103 History: Received October 26, 2017; Revised January 21, 2018


Cardiovascular disease (CVD) continues to be a leading cause of death. Accordingly, risk models attempt to predict an individual's probability of developing the disease. These risk models are incorporated into calculators to determine the risk for a number of clinical conditions, including the 10-year risk of developing CVD. There is significant variability in the published models in terms of how the clinical measurements are converted to risk factors as well as the specific population used to determine b-weights of these risk factors. Adding to model variability is the fact that numbers are an imperfect representation of a person's health status. Acknowledgement of uncertainty must be addressed for reliable clinical decision making. This paper analyzes thirty-five published risk calculators and then generalizes them into one 'Super Risk Formula' to form a common basis for uncertainty calculations to determine the best risk model to use for an individual. Special error arithmetic, the duals method, is used to faithfully propagate error from model parameters, population averages and patient specific clinical measures to one risk number and its relative uncertainty. A set of sample patients show that the 'best model' is specific to the individual and no one model is appropriate for every patient.

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