BACKGROUND AND AIM: In this study we addressed some open questions in patients with coronary artery disease (CAD). First, we analysed which of the traditional risk factors was associated with the spreading of coronary stenosis and second, we aimed to identify if any variable was predictive of post-percutaneous transluminal coronary angioplasty (PTCA) clinical events. METHODS AND RESULTS: We collected a consecutive series of patients with CAD (n=301) and in the subgroup of patients undergoing PTCA (n=135) we performed a prospective one-year follow-up study recording cardiovascular morbidity and total mortality. According to the extension of coronary atherosclerosis, we found a significant relationship with the prevalence of diabetes in men and with plasma HDL-cholesterol concentrations in women. The follow-up was completed in 95% of patients; we did not document any death whereas clinical events were registered in 16% of patients. At univariate analysis, we found that patients with clinical events had a higher prevalence of family history of CAD (43% vs 14%, p<0.005), diabetes (52% vs 21%, p<0.005) and multivessel disease (52% vs 35%, p<0.05). Multivariate analysis (logistic regression) confirmed that family history of CAD (OR 4.6, 95% CI 1.7-12.8, p<0.005), diabetes (OR 4.0, 95% CI 1.5-10.6, p<0.01) and multivessel disease (OR 2.8, 95% CI 1.1-7.4, p<0.05) were the only variables predictive of clinical events. CONCLUSIONS: In this study, factors associated with the spreading of coronary stenosis were different according to the gender. Moreover, the presence of diabetes and multivessel disease had a negative impact on the long-term prognosis of patients undergoing PTCA. In addition, the family history of CAD represented in our study a strong predictor of clinical events. We suggest that in the management of post-PTCA patients, the role of individual baseline clinical characteristics must be taken into account and that subjects with a family history of premature CAD, diabetes and a wide extension of coronary disease represent those with the highest risk.