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Methods Inf Med 2001; 40(01): 6-11
DOI: 10.1055/s-0038-1634457
Original Article
Schattauer GmbH

Identification of Patients at High Cardiovascular Risk: a Critical Appraisal of Applicability of Statistical Risk Prediction Models

H. Dréau
1   Public Health and Medical Informatics, Broussais – Hôtel Dieu University, Paris, France
,
I. Colombet
1   Public Health and Medical Informatics, Broussais – Hôtel Dieu University, Paris, France
,
P. Degoulet
1   Public Health and Medical Informatics, Broussais – Hôtel Dieu University, Paris, France
,
G. Chatellier
1   Public Health and Medical Informatics, Broussais – Hôtel Dieu University, Paris, France
› Author Affiliations
Further Information

Publication History

Publication Date:
08 February 2018 (online)

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Abstract

Assessment of cardiovascular risk is widely proposed as a basis for taking management decisions about patients presenting with hypertension or hypercholesterolemia. Our aim was to critically assess the use of risk equations derived from epidemiological studies for the purpose of identifying high-risk patients.

Risk equations were retrieved from the MEDLINE database and then applied to a data set of 118 patients. This data set was an evaluation study of the clinical value of the World Health Organization 1993 hypertension guidelines for the decision to treat mild hypertensive patients. We calculated agreement: 1) between equations and 2) between equations and the decision to treat taken by the physician.

Most models were not applicable to our population, mainly because the original population had a narrow age range or comprised only males. Between-model agreement was better for the lower and upper risk quintiles than for the three other risk quintiles (0.58, 0.33, 0.34, 0.45, 0.70, from the lower to the upper risk quintile). When using an arbitrary threshold for defining high-risk patients (i.e. >2% per year), we observed a huge variation of the proportion of patients classified at high risk (from 0 to 17%). There was a poor agreement between risk models and the decision to treat taken by the physician. These results suggest that risk-based guidelines should be validated before their diffusion.

Keywords

Prediction - Risk Models - Cardiovascular Disease
 

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