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Cardiovascular Psychiatry and Neurology
Volume 2013 (2013), Article ID 814967, 9 pages
Research Article

Combining Personality Traits with Traditional Risk Factors for Coronary Stenosis: An Artificial Neural Networks Solution in Patients with Computed Tomography Detected Coronary Artery Disease

1University of Bergamo, Piazzale S. Agostino 2, P.O. Box 24129, Bergamo, Italy
2Villa Santa Maria Institute, IV Novembre, P.O. Box 22038, Tavernerio, Italy
3Semeion, Research Centre of Sciences of Communication, Via Sersale 117, P.O. Box 00128, Rome, Italy
4Department of Mathematical and Statistical Sciences, University of Colorado at Denver, P.O. Box 173364, Denver, CO, USA
5School of Electronic and Information Engineering, Beihang University, Xueyuan Road No. 37, Haidian District, Beijing, China
6Division of Cardiology, Cardiocentro Lugano CH-6900, Switzerland
7Center of Research on Psychology in Somatic Diseases, CoRPS, Tilburg University, Warandelaan 2, P.O. Box 90153, 5000 LE Tilburg, The Netherlands

Received 11 April 2013; Accepted 29 August 2013

Academic Editor: Janusz K. Rybakowski

Copyright © 2013 Angelo Compare et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Background. Coronary artery disease (CAD) is a complex, multifactorial disease in which personality seems to play a role but with no definition in combination with other risk factors. Objective. To explore the nonlinear and simultaneous pathways between traditional and personality traits risk factors and coronary stenosis by Artificial Neural Networks (ANN) data mining analysis. Method. Seventy-five subjects were examined for traditional cardiac risk factors and personality traits. Analyses were based on a new data mining method using a particular artificial adaptive system, the autocontractive map (AutoCM). Results. Several traditional Cardiovascular Risk Factors (CRF) present significant relations with coronary artery plaque (CAP) presence or severity. Moreover, anger turns out to be the main factor of personality for CAP in connection with numbers of traditional risk factors. Hidden connection map showed that anger, hostility, and the Type D personality subscale social inhibition are the core factors related to the traditional cardiovascular risk factors (CRF) specifically by hypertension. Discussion. This study shows a nonlinear and simultaneous pathway between traditional risk factors and personality traits associated with coronary stenosis in CAD patients without history of cardiovascular disease. In particular, anger seems to be the main personality factor for CAP in addition to traditional risk factors.