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JOURNAL ARTICLE
MULTICENTER STUDY
RESEARCH SUPPORT, NON-U.S. GOV'T
A clinical prediction model for the presence of peripheral arterial disease--the benefit of screening individuals before initiation of measurement of the ankle-brachial index: an observational study.
Vascular Medicine 2007 Februrary
Measurement of the ankle-brachial index (ABI) can provide important information about the presence of subclinical atherosclerosis. Performing the ABI in the overall population is not feasible, but it can be used in a selected population. A simple prediction rule could be of much use to estimate the risk of an abnormal ABI. This was designed as an observational study in the setting of 955 general practices in The Netherlands. A total of 7454 patients aged > or = 55 years presenting with at least one vascular risk factor (smoking, hypertension, diabetes, and hypercholesterolemia) and no complaints of intermittent claudication were included. Patients were selected by the general practitioner during visiting hours and from medical records. Main outcome measures included the prevalence of PAD, defined as an ABI below 0.9, which was related to vascular risk factors using regression analyses on which the PREVALENT clinical prediction model was developed. The overall prevalence of PAD was 18.4%. Since the treatment of individuals with a history of coronary heart disease and cerebrovascular disease will not be influenced by the finding of asymptomatic PAD, these individuals were not taken into account for the development of the clinical prediction model. Analyses showed a significantly increased risk for PAD with increasing age, smoking, and hypertension. The clinical prediction model giving risk factor points per factor (age: 1 point per 5 years starting at 55 years; ever smoked: 2 points; currently smoking: 7 points; and hypertension: 3 points), showed a proportional increase of the PAD prevalence with each increasing risk profile (range: 7.0-40.6%). In conclusion, based on the PREVALENT clinical prediction model, the general practitioner is able to identify a high-risk population in which measurement of ABI is useful.
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