2008 Volume 20 Issue 1 Pages 100-107
We estimated the cardiac risk in non-cardiac surgery. We developed predictors for perioperative cardiac accidents, including hard events (cardiac death and myocardial infarction), using a total of 22 clinical properties such as surgical risk, patient's clinical information, and results from nuclear scanning. A total of 1351 surgery records including intermediate and low risk surgery, the risk prediction of which is often difficult were used and we analyzed them using linear and support vector machine (SVM) classification models. Our linear and SVM models achieved superior prediction results to conventional ones; 80% in sensitivity (SE) and 66% in specificity (SP) for all cardiac accidentsand 85% in SE and 81% in SP for hard events with a leave-one-out cross-validation strategy. Several parameters measured by nuclear scanning were commonly selected and we can therefore conclude that the nuclear scanning is effective for estimating perioperative cardiac risk in advance.
