Abstract

The classification of subjects as low or high cardiovascular (CV) risk is usually performed by risk engines, based upon multivariate prediction algorithms. However, their accuracy in predicting major adverse CV events (MACEs) is lower in high-risk populations as they take into account only conventional risk factors. To evaluate the accuracy of Progetto Cuore risk engine in predicting MACE in subjects with erectile dysfunction (ED) and to test the role of unconventional CV risk factors, specifically identified for ED. A consecutive series of 1,233 men (mean age 53.33 ± 9.08 years) attending our outpatient clinic for sexual dysfunction was longitudinally studied for a mean period of 4.4 ± 2.6 years. Several clinical, biochemical, and instrumental parameters were evaluated. Subjects were classified as high or low risk, according to previously reported ED-specific risk factors. In the overall population, Progetto Cuore-predicted population survival was not significantly different from the observed one (P = 0.545). Accordingly, receiver operating characteristic (ROC) analysis shows that Progetto Cuore has an accuracy of 0.697 ± 0.037 (P < 0.001) in predicting MACE. Considering subjects at high risk according to ED-specific risk factors, the observed incidence of MACE was significantly higher than the expected for both low educated and patients reporting partner's hypoactive sexual desire (HSD, both <0.05), but not for other described factors. The area under ROC curves of Progetto Cuore for MACE in subjects with low education and reported partner's HSD were 0.659 ± 0.053 (P = 0.008) and 0.550 ± 0.076 (P = 0.570), respectively. Overall, Progetto Cuore is a proper instrument for evaluating CV risk in ED subjects. However, in ED, other factors such as low education and partner's HSD concur to risk profile. At variance with low education, Progetto Cuore is not accurate enough to predict MACE in subjects with partner's HSD, suggesting that the latter effect is not mediated by conventional risk factors included in the algorithm.

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