Volume 19, Issue 98 (5-2012)                   Daneshvar Medicine 2012, 19(98): 15-24 | Back to browse issues page

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Zayeri F, Sadeghi Nejad R, Noorkojuri H, Bagheri J, Ghazanfari E. Application of classification tree model for determining the effective factors of mortality after coronary bypass surgery in dialysis-independent patients. Daneshvar Medicine. 2012; 19 (98) :15-24
URL: http://daneshvarmed.shahed.ac.ir/article-1-527-en.html
Assisstant Professor of Cardiovascular Surgery – Cardiology Department of Shariati Hospital, Tehran University of Medical Sciences
Abstract:   (6841 Views)


Background and Objective: Coronary artery disease is one of the most prevalent causes of death. A coronary artery bypass surgery is a common treatment for this disease. In addition, renal dysfunction can lead to increased mortality and post-operative complications. This study aimed to identify the most important factors influencing the mortality of patients who suffer from coronary artery disease and to introduce a classification approach according to Classification Tree (CART) model for predicting the mortality from this disease.




Materials and Methods: This research was conducted based on the information gathered from a cross-sectional study on 1390 patients (except dialysis-dependent) who undergone coronary artery bypass grafting, admitted to Cardiology ward of Shariati hospital during the years 2007-2010. The ordinary logistic regression model and a classification tree were utilized for predicting the probability of death in these patients. The SPSS version 18.0 and CART version 6.0 were used for data analysis.


 Results: In this study, the classification tree model (CART) resulted in an accuracy of 90%. The patients with renal insufficiency, intra-aortic balloon pump placement during and after surgery, prolonged ventilation, and perfusion time over 160 were shown as the high-risk groups, while those patients with heart ventricular post-operative complications regarded as the medium-risk group. The sensitivity and specificity indices for this model were 82% and 89%, respectively, while it was 80.4% and 88%, respectively, for logistic model.




Conclusion: In the present study, the logistic and decision tree models led to nearly similar results, however, the decision tree model seemed to be more accurate. The IABP (Intra-Aortic Balloon Pump) was the most effective factor for mortality. The mortality rate due to this factor during and after surgery for all patients was 19% and 54.1%, respectively.


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Type of Study: Research |

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