Determining risk factors for survival after LMCA stenosis with intelligent data analysis

Abstract

Coronary artery disease is one of the most frequent causes of premature deaths in Slovenia and also in most countries in the world. A ldquogold standardrdquo for treatment of left main coronary artery (LMCA) stenosis is still a surgical therapy; however percutanueous transluminal coronary angioplasty (PTCA) is much simpler for the patients and gives comparable short-term and mid-term results to surgical therapy. PTCA of LMCA stenosis is safe and technically demanding but long-term clinical outcomes are not yet defined. In this paper we present an intelligent data analysis method for inducing a decision tree that was able to outline some anticipated and also some relatively unexpected but useful risk factors for survival after PTCA.