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Title

APPLICATION OF CLASSIFICATION TREE MODEL FOR DETERMINING THE EFFECTIVE FACTORS OF MORTALITY AFTER CORONARY BYPASS SURGERY IN DIALYSIS-INDEPENDENT PATIENTS

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Abstract

 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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    APA: Copy

    ZAYERI, FARID, SADEGHI NEJAD, REYHANEH, NOORKOJURI, HODA, BAGHERI, JAMSHID, & GHAZANFARI, ELAHEH. (2012). APPLICATION OF CLASSIFICATION TREE MODEL FOR DETERMINING THE EFFECTIVE FACTORS OF MORTALITY AFTER CORONARY BYPASS SURGERY IN DIALYSIS-INDEPENDENT PATIENTS. DANESHVAR MEDICINE, 19(98), 0-0. SID. https://sid.ir/paper/384557/en

    Vancouver: Copy

    ZAYERI FARID, SADEGHI NEJAD REYHANEH, NOORKOJURI HODA, BAGHERI JAMSHID, GHAZANFARI ELAHEH. APPLICATION OF CLASSIFICATION TREE MODEL FOR DETERMINING THE EFFECTIVE FACTORS OF MORTALITY AFTER CORONARY BYPASS SURGERY IN DIALYSIS-INDEPENDENT PATIENTS. DANESHVAR MEDICINE[Internet]. 2012;19(98):0-0. Available from: https://sid.ir/paper/384557/en

    IEEE: Copy

    FARID ZAYERI, REYHANEH SADEGHI NEJAD, HODA NOORKOJURI, JAMSHID BAGHERI, and ELAHEH GHAZANFARI, “APPLICATION OF CLASSIFICATION TREE MODEL FOR DETERMINING THE EFFECTIVE FACTORS OF MORTALITY AFTER CORONARY BYPASS SURGERY IN DIALYSIS-INDEPENDENT PATIENTS,” DANESHVAR MEDICINE, vol. 19, no. 98, pp. 0–0, 2012, [Online]. Available: https://sid.ir/paper/384557/en

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