Collateral donor artery physiology and the influence of a chronic total occlusion on fractional flow reserve

Background— The presence of a concomitant chronic total coronary occlusion (CTO) and a large collateral contribution might alter the fractional flow reserve (FFR) of an interrogated vessel, rendering the FFR unreliable at predicting ischemia should the CTO vessel be revascularized and potentially affecting the decision on optimal revascularization strategy. We tested the hypothesis that donor vessel FFR would significantly change after percutaneous coronary intervention of a concomitant CTO. Methods and Results— In consecutive patients undergoing percutaneous coronary intervention of a CTO, coronary pressure and flow velocity were measured at baseline and hyperemia in proximal and distal segments of both nontarget vessels, before and after percutaneous coronary intervention. Hemodynamics including FFR, absolute coronary flow, and the coronary flow velocity–pressure gradient relation were calculated. After successful percutaneous coronary intervention in 34 of 46 patients, FFR in the predominant donor vessel increased from 0.782 to 0.810 (difference, 0.028 [0.012 to 0.044]; P=0.001). Mean decrease in baseline donor vessel absolute flow adjusted for rate pressure product: 177.5 to 139.9 mL/min (difference −37.6 [−62.6 to −12.6]; P=0.005), mean decrease in hyperemic flow: 306.5 to 272.9 mL/min (difference, −33.5 [−58.7 to −8.3]; P=0.011). Change in predominant donor vessel FFR correlated with angiographic (%) diameter stenosis severity (r=0.44; P=0.009) and was strongly related to stenosis severity measured by the coronary flow velocity–pressure gradient relation (r=0.69; P<0.001). Conclusions— Recanalization of a CTO results in a modest increase in the FFR of the predominant collateral donor vessel associated with a reduction in coronary flow. A larger increase in FFR is associated with greater coronary stenosis severity

Knowledge Discovery from Data: Comparative Study

Abstract—Knowledge discovery of data is very much necessary in order to deliver a correct decision to the user, in decision making process. In this paper efficiency of knowledge learnt by SVM transparent approach is compared with opaque approach. We have selected DT, and NBTree as transparent approaches to evaluate the eclectic rule extraction approach of SVM. Where the training dataset available is modified according to the predictions of learned SVM. This modified data is expected to represent the knowledge learnt by SVM during training. Transparent approaches are then employed and the understanding of SVM is evaluated in the form of rules. The conclusion drawn after extensive experimentation is that improved comprehensibility is achieved. Index Terms — SVM, Rule induction techniques, DT, NBTree I