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Research Papers

# The Uncertainty of Cardiovascular Disease Risk Calculation—What is the Best Risk Model for the Individual?

[+] Author and Article Information
Ronald S. LaFleur

Mem. ASME
Department of Mechanical and
Aeronautical Engineering,
Clarkson University,
Box 5725,
Potsdam, NY 13699
e-mail: rlafleur@clarkson.edu

Laura S. Goshko

Department of Physician Assistant,
Seton Hall University,
400 South Orange Avenue,
South Orange, NJ 07079
e-mail: laura.goshko@shu.edu

Manuscript received October 26, 2017; final manuscript received January 21, 2018; published online February 28, 2018. Assoc. Editor: Stavroula Balabani.

ASME J of Medical Diagnostics 1(2), 021005 (Feb 28, 2018) (11 pages) Paper No: JESMDT-17-2049; doi: 10.1115/1.4039103 History: Received October 26, 2017; Revised January 21, 2018

## Abstract

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. Risk models are incorporated into calculators to determine the risk for a number of clinical conditions, including the ten-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. Acknowledgment of uncertainty must be addressed for reliable clinical decision-making. This paper analyzes 35 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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Topics: Errors , Uncertainty , Risk

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## Figures

Fig. 1

208 components of the relative uncertainty vector for the best model for the example black male patient

Fig. 2

Distribution of best model outcomes from four groups of 1000 random patients

## Errata

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