The predictive value of coronary artery calcium score combined with traditional risk factors for obstructive coronary heart disease in young people

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ObjectivesThis study attempts to compare the predictive effects of several prediction models on obstructive coronary artery disease (OCAD) in young patients (30–50 years old), with a view to providing a new evaluation tool for the prediction of premature coronary artery disease (PCAD).MethodsA total of 532 hospitalized patients aged 30–50 were included in the study.All of them underwent coronary computed tomography angiography (CCTA) for suspected symptoms of coronary heart disease.Coronary artery calcium score (CACS) combined with traditional risk factors and pre-test probability models are the prediction models to be compared in this study.The PTP model was selected from the upgraded Diamond-Forrester model (UDFM) and the Duke clinical score (DCS).ResultsAll patients included in the study were aged 30–50 years. Among them, women accounted for 24.4%, and 355 patients (66.7%) had a CACS of 0. OCAD was diagnosed in 43 patients (8.1%). The CACS combined with traditional risk factors to predict the OCAD area under the curve of receiver operating characteristic (ROC) (AUC = 0.794,p < 0.001) was greater than the PTP models (AUCUDFM=0.6977,p < 0.001;AUCDCS=0.6214,p < 0.001). By calculating the net reclassification index (NRI) and the integrated discrimination index (IDI), the ability to predict the risk of OCAD using the CACS combined with traditional risk factors was improved compared with the PTP models (NRI&IDI > 0,p < 0.05).ConclusionThe predictive value of CACS combined with traditional risk factors for OCAD in young patients is better than the PTP models.