Periprocedural quantitative coronary angiography after Palmaz-Schatz stent implantation predicts the restenosis rate at six months

OBJECTIVES We aimed to identify periprocedural quantitative coronary angiographic (QCA) variables that have predictive value on long-term angiographic results and to construct multivariate models using these variables for postprocedural prognosis. BACKGROUND Coronary stent implantation has reduced the restenosis rate significantly as compared with balloon angioplasty in short de novo lesions in coronary arteries >3 mm in size. Although the postprocedural minimal luminal diameter (MLD) is known to have significant bearing on long-term angiographic results, no practically useful model exists for prediction of angiographic outcome based on the periprocedural QCA variables. METHODS The QCA data from patients who underwent Palmaz-Schatz stent implantation for short (<15 mm) de novo lesions in coronary arteries >3 mm and completed six months of angiographic follow-up in the four prospective clinical trials (BENESTENT I, BENESTENT II pilot, BENESTENT II and MUSIC) were pooled. Multiple models were constructed using multivariate analysis. The Hosmer-Lemeshow goodness-of-fit test was used to identify the model of best fit, and this model was used to construct a reference chart for prediction of angiographic outcome on the basis of periprocedural QCA variables. RESULTS Univariate analysis performed using QCA variables revealed that vessel size, MLD before and after the procedure, reference area before and after the procedure, minimal luminal cross-sectional area before and after the procedure, diameter stenosis after the procedure, area of plaque after the procedure and area stenosis after the procedure were significant predictors of angiographic outcome. Using multivariate analysis, the Hosmer-Lemeshow goodness-of-fit test showed that the model containing percent diameter stenosis after the procedure and vessel size best fit the data. A reference chart was then developed to calculate the expected restenosis rate. CONCLUSIONS Restenosis rate after stent implantation for short lesions can be predicted using the variables percent diameter stenosis after the procedure and vessel size. This meta-analysis indicates that the concept of “the bigger the better” holds true for coronary stent implantation. Applicability of the model beyond short lesions should be tested.