ISSN : 1301-5680
e-ISSN : 2149-8156
Turkish Journal of Thoracic and Cardiovascular Surgery     
Risk group classification for bleeding after coronary artery bypass graft surgery: a comparison of the logistic regression with decision tree models
Reza Safiarian1, Payam Amini2, Elham Khodayari Moez2, Fatemeh Mohammadzadeh2, Mohammad Tavakoli3, Farid Zayeri4
1Baqiyatallah University of Medical Science, Tehran, Iran
2School of Medical Sciences, Tarbiat Modares University, Tehran, Iran
3Ministry of Health Treatments and Medical Education, Tehran, Iran
4Proteomics Research Center, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
DOI : 10.5606/tgkdc.dergisi.2013.7680
Background: This study aims to identify high-risk patient groups for bleeding after coronary artery bypass graft (CABG) surgery.

Methods: We retrospectively evaluated 205 patients (143 males, 62 females; mean age 59.7±10.1 years; range, 28 to 83 years) undergoing CABG surgery between June 2001 and August 2008 at Jamaran Heart Hospital, Tehran, Iran. Baseline characteristics of the patients and postoperative bleeding status were recorded. For classifying the bleeders and non-bleeders, classic logistic regression and decision tree models were utilized.

Results: Logistic regression analysis showed that sex was significantly related to postoperative bleeding. Decision tree model revealed that age (score= 100), diabetes mellitus (score= 16.38), sex (score= 13.67), capital residency (score= 7.31) and dyslipidemia (score= 5.06) were found to have an impact on bleeding. We also observed that the decision tree model provided a better classification of the patients than logistic regression.

Conclusion: Surgeons should be aware of risk indicators of bleeding such as older age, male sex, absence of diabetes mellitus and presence of dyslipidemia in patients with three bypassed vessels before CABG. We also recommend statisticians to utilize the decision tree model instead of logistic regression analysis in classification of risk groups.

Keywords : Bleeding; classification; coronary artery bypass graft; decision tree; logistic regression
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