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12-06-2012 | General practice | Article

Risk tool could aid CAD diagnosis

Abstract

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MedWire News: A novel risk prediction tool could help to identify those patients presenting with chest pain who are most likely to have coronary artery disease (CAD) and should be referred for further diagnostic work-up, researchers report in the BMJ.

In their analysis in a low-prevalence population, the tool was more accurate than the Duke Clinical Score currently recommended in NICE guidance.

Dr Myriam Hunink (Erasmus University Medical Center, the Netherlands) and colleagues say the new tool does not require a resting electrocardiogram, making it better suited to use in primary care, and could easily be integrated into electronic patient records or mobile applications.

The team developed their clinical predictive model using data on 5677 patients (3283 men) with chest pain but no history of heart disease, of whom 1634 were found to have obstructive CAD on coronary angiography.

The model - which includes age, sex, symptoms, setting, diabetes, hypertension, dyslipidemia and smoking - performed well in predicting the pretest probability of CAD. It gave predictions ranging from 2% for a 50-year-old woman with nonspecific chest pain without any risk factors to 91% for an 80-year-old man with typical chest pain and multiple risk factors.

Addition of a coronary calcium score improved the accuracy of the model even further, which the authors note could prove useful if its inclusion altered the probability of CAD to the extent that clinical management would change.

By contrast, the Duke Clinical Score, which the authors note does not include hypertension, significantly overestimated the risk of CAD in this population.

The authors conclude that their model could "allow doctors to make better decisions as to which diagnostic test is best in a particular patient and to decide on further management based on the results of such tests".

MedWire News is an independent clinical news service provided by Springer Healthcare Limited. © Springer Healthcare Ltd; 2012

By Caroline Price