ABSTRACT

The goal of this study is to recognize most important risk factors associated with surgical mortality in patient who underwent CABG by the integration of fuzzy concept and analytical hierarchy process method to represent pairwise comparison of odd ratios and overcome ambiguities involved in the statistical data. A literature search from 1980 to January 2013 using the MEDLINE and Science Direct database is performed and data of the reported predictors were extracted. A fuzzy AHP model for comparing the relative importance of risk factors was developed. Moreover, fuzzy clustering method is applied to classify calculated weight of risk factors. The result indicated that advanced age (over 70 years), sever left ventricular ejection fraction (LVEF<30%), emergency state of patient, elevated creatinin (above 2 mg over dL) and reoperation have the highest calculated weight among other predictors. In addition to, other variables were identified to be contributing risk factors to operative mortality after CABG, although they have not reached the level of importance of core risk factors. This study also, showed that the importance of risk factors varied by geographic region. We conducted that fuzzy clustering and FAHP has successfully detected strongest risk factors to predict mortality rate after CABG and showed the power of the engineering tools in health area. Furthermore, developed model, as a decision support tool, can be helpful for surgeons to determine appropriate technique for better management of individual patient before surgery as well as to provide pertinent information to develop novel scoring model according to importance of risk factors in different regions.