Résumé
The aim of our study was to investigate the role of platelet parameters including mean platelet volume (MPV) and platelet count (PC) in the pathogenesis of penile arteriogenic erectile dysfunction (ED) and to evaluate the association between the platelet parameters and arteriogenic ED. There were 244 patients with ED (based on the International Index of Erectile Function [IIEF]-5 ≤21) and 60 healthy controls (IIEF-5 >21) enrolled. All participants were asked to undergo a laboratory examination, and penile vascular function was evaluated using penile color Doppler ultrasonography (pDUS). Among these ED patients, 24 patients with no abnormality on nocturnal penile tumescence (NPT) and 84 with normal vasculature or mixed vascular abnormalities were excluded. The other patients were classified into three groups as follows: control (n = 60), arteriogenic ED (n = 99), and venous leakage (n = 37) groups. MPV and PC were significantly higher in the arteriogenic ED group compared with the venous and control groups (P < 0.05). Receiver operating characteristic curve analysis revealed that the area under the curve for MPV to predict arteriogenic ED was 0.707. MPV ≥9.65 fl was recognized as a cut-off value for potential arteriogenic ED (sensitivity: 47.5%; specificity: 91.7%). A significant inverse correlation was detected between MPV and 10-min peak systolic velocity (PSV) (r =-0.34; P < 0.001) in the arteriogenic ED group. These findings suggest that the MPV might be a powerful indicator to predict and diagnose arteriogenic ED, and MPV may be a marker for ED when using pDUS.
Résumé
The aim of our study was to investigate the role of platelet parameters including mean platelet volume (MPV) and platelet count (PC) in the pathogenesis of penile arteriogenic erectile dysfunction (ED) and to evaluate the association between the platelet parameters and arteriogenic ED. There were 244 patients with ED (based on the International Index of Erectile Function [IIEF]-5 ≤21) and 60 healthy controls (IIEF-5 >21) enrolled. All participants were asked to undergo a laboratory examination, and penile vascular function was evaluated using penile color Doppler ultrasonography (pDUS). Among these ED patients, 24 patients with no abnormality on nocturnal penile tumescence (NPT) and 84 with normal vasculature or mixed vascular abnormalities were excluded. The other patients were classified into three groups as follows: control (n = 60), arteriogenic ED (n = 99), and venous leakage (n = 37) groups. MPV and PC were significantly higher in the arteriogenic ED group compared with the venous and control groups (P < 0.05). Receiver operating characteristic curve analysis revealed that the area under the curve for MPV to predict arteriogenic ED was 0.707. MPV ≥9.65 fl was recognized as a cut-off value for potential arteriogenic ED (sensitivity: 47.5%; specificity: 91.7%). A significant inverse correlation was detected between MPV and 10-min peak systolic velocity (PSV) (r = -0.34; P < 0.001) in the arteriogenic ED group. These findings suggest that the MPV might be a powerful indicator to predict and diagnose arteriogenic ED, and MPV may be a marker for ED when using pDUS.
Résumé
Objective To explore the method and performance of using multiple indices to diagnose sepsis and to predict the prognosis of severe ill patients.Methods Critically ill patients at first admission to intensive care unit (ICU) of Changzheng Hospital, Second Military Medical University, from January 2014 to September 2015 were enrolled if the following conditions were satisfied: ① patients were 18-75 years old;② the length of ICU stay was more than 24 hours; ③ All records of the patients were available. Data of the patients was collected by searching the electronic medical record system. Logistic regression model was formulated to create the new combined predictive indicator and the receiver operating characteristic (ROC) curve for the new predictive indicator was built. The area under the ROC curve (AUC) for both the new indicator and original ones were compared. The optimal cut-off point was obtained where the Youden index reached the maximum value. Diagnostic parameters such as sensitivity, specificity and predictive accuracy were also calculated for comparison. Finally, individual values were substituted into the equation to test the performance in predicting clinical outcomes.Results A total of 362 patients (218 males and 144 females) were enrolled in our study and 66 patients died. The average age was (48.3±19.3) years old. ① For the predictive model only containing categorical covariants [including procalcitonin (PCT), lipopolysaccharide (LPS), infection, white blood cells count (WBC) and fever], increased PCT, increased WBC and fever were demonstrated to be independent risk factors for sepsis in the logistic equation. The AUC for the new combined predictive indicator was higher than that of any other indictor, including PCT, LPS, infection, WBC and fever (0.930 vs. 0.661, 0.503, 0.570, 0.837, 0.800). The optimal cut-off value for the new combined predictive indicator was 0.518. Using the new indicator to diagnose sepsis, the sensitivity, specificity and diagnostic accuracy rate were 78.00%, 93.36% and 87.47%, respectively. One patient was randomly selected, and the clinical data was substituted into the probability equation for prediction. The calculated value was 0.015, which was less than the cut-off value (0.518), indicating that the prognosis was non-sepsis at an accuracy of 87.47%. ② For the predictive model only containing continuous covariants, the logistic model which combined acute physiology and chronic health evaluation Ⅱ (APACHE Ⅱ) score and sequential organ failure assessment (SOFA) score to predict in-hospital death events, both APACHE Ⅱ score and SOFA score were independent risk factors for death. The AUC for the new predictive indicator was higher than that of APACHE Ⅱ score and SOFA score (0.834 vs. 0.812, 0.813). The optimal cut-off value for the new combined predictive indicator in predicting in-hospital death events was 0.236, and the corresponding sensitivity, specificity and diagnostic accuracy for the combined predictive indicator were 73.12%, 76.51% and 75.70%, respectively. One patient was randomly selected, and the APACHE Ⅱscore and SOFA score was substituted into the probability equation for prediction. The calculated value was 0.570, which was higher than the cut-off value (0.236), indicating that the death prognosis at an accuracy of 75.70%.Conclusion The combined predictive indicator, which is formulated by logistic regression models, is superior toany single indicator in predicting sepsis or in-hospital death events.