Coronavirus Disease 2019 (COVID-19) has created a global pandemic. Global epidemiological results show that elderly men are susceptible to infection of COVID-19. The difference in the number of cases reported by gender increases progressively in favor of male subjects up to the age group ≥60–69 (66.6%) and ≥70–79 (66.1%). Through literature search and analysis, we also found that men are more susceptible to SARS-CoV-2 infection than women. In addition, men with COVID-19 have a higher mortality rate than women. Male represents 73% of deaths in China, 59% in South Korea, and 61.8% in the United States. Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is the pathogen of COVID-19, which is transmitted through respiratory droplets, direct and indirect contact. Genomic analysis has shown that SARS-CoV-2 is 79% identical to SARS-CoV, and both use angiotensin-converting enzyme 2 (ACE2) as the receptor for invading cells. In addition, Transmembrane serine protease 2 (TMPRSS2) can enhance ACE2-mediated virus entry. However, SARS-CoV-2 has a high affinity with human ACE2, and its consequences are more serious than other coronaviruses. ACE2 acts as a “gate” for viruses to invade cells and is closely related to the clinical manifestations of COVID-19. Studies have found that ACE2 and TMPRSS2 are expressed in the testis and male reproductive tract and are regulated by testosterone. Mature spermatozoon even has all the machinery required to bind SARS-CoV-2, and these considerations raise the possibility that spermatozoa could act as potential vectors of this highly infectious disease. This review summarizes the gender differences in the pathogenesis and clinical manifestations of COVID-19 and proposes the possible mechanism of orchitis caused by SARS-CoV-2 and the potential transmission route of the virus. In the context of the pandemic, these data will improve the understanding of the poor clinical outcomes in male patients with COVID-19 and the design of new strategies to prevent and treat SARS-CoV-2 infection.

Prostatitis is a common urinary tract condition but bring innumerable trouble to clinicians in treatment, as well as great financial burden to patients and the society. Bacterial prostatitis (acute bacterial prostatitis plus chronic bacterial prostatitis) accounting for approximately 20% among all prostatitis have made the urological clinics complain about the genital and urinary systems all over the world. The international challenges of antibacterial treatment (emergence of multidrug-resistant bacteria, extended-spectrum beta-lactamaseproducing bacteria, bacterial biofilms production and the shift in bacterial etiology) and the transformation of therapeutic strategy for classic therapy have attracted worldwide attention. To the best of our knowledge currently, there is not a single comprehensive review, which can completely elaborate these important topics and the corresponding treatment strategy in an effective way. This review summarizes the general treatment choices for bacterial prostatitis also provides the alternative pharmacological therapies for those patients resistant or intolerant to general treatment.

The severe acute respiratory coronavirus 2 (SARS-CoV-2) has become a life-threatening pandemic. Clinical evidence suggests that kidney involvement is common and might lead to mild proteinuria and even advanced acute kidney injury (AKI). Moreover, AKI caused by coronavirus disease 2019 (COVID-19) has been reported in several countries and regions, resulting in high patient mortality. COVID-19‐induced kidney injury is affected by several factors including direct kidney injury mediated by the combination of virus and angiotensin-converting enzyme 2, immune response dysregulation, cytokine storm driven by SARS-CoV-2 infection, organ interactions, hypercoagulable state, and endothelial dysfunction. In this review, we summarized the mechanism of AKI caused by SARS-CoV-2 infection through literature search and analysis.

Coronavirus disease 2019(COVID-19) has become a public health emergency of concern worldwide. COVID-19 is a new infectious disease arising from Coronavirus 2 (SARS-CoV-2). It has a strong transmission capacity and can cause severe and even fatal respiratory diseases. It can also affect other organs such as the heart, kidneys and digestive tract. Clinical evidence indicates that kidney injury is a common complication of COVID-19, and acute kidney injury (AKI) may even occur in severely ill patients. Data from China and the United States showed that male sex, Black race, the elderly, chronic kidney disease, diabetes, hypertension, cardiovascular disease, and higher body mass index are associated with COVID-19‐induced AKI. In this review, we found gender and ethnic differences in the occurrence and development of AKI in patients with COVID-19 through literature search and analysis. By summarizing the mechanism of gender and ethnic differences in AKI among patients with COVID-19, we found that male and Black race have more progress to COVID-19-induced AKI than their counterparts.

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PurposeTo develop and validate nomograms for pre-treatment prediction of malignant histology (MH) and unfavorable pathology (UP) in patients with endophytic renal tumors (ERTs).MethodsWe retrospectively reviewed the clinical information of 3245 patients with ERTs accepted surgical treatment in our center. Eventually, 333 eligible patients were included and randomly enrolled into training and testing sets in a ratio of 7:3. We performed univariable and multivariable logistic regression analyses to determine the independent risk factors of MH and UP in the training set and developed the pathological diagnostic models of MH and UP. The optimal model was used to construct a nomogram for MH and UP. The area under the receiver operating characteristics (ROC) curves (AUC), calibration curves and decision curve analyses (DCA) were used to evaluate the predictive performance of models.ResultsOverall, 172 patients with MH and 50 patients with UP were enrolled in the training set; and 74 patients with MH and 21 patients with UP were enrolled in the validation set. Sex, neutrophil-to-lymphocyte ratio (NLR), R score, N score and R.E.N.A.L. score were the independent predictors of MH; and BMI, NLR, tumor size and R score were the independent predictors of UP. Single-variable and multiple-variable models were constructed based on these independent predictors. Among these predictive models, the malignant histology-risk nomogram consisted of sex, NLR, R score and N score and the unfavorable pathology-risk nomogram consisted of BMI, NLR and R score performed an optimal predictive performance, which reflected in the highest AUC (0.842 and 0.808, respectively), the favorable calibration curves and the best clinical net benefit. In addition, if demographic characteristics and laboratory tests were excluded from the nomograms, only the components of the R.E.N.A.L. Nephrometry Score system were included to predict MH and UP, the AUC decreased to 0.781 and 0.660, respectively (P=0.001 and 0.013, respectively).ConclusionIn our study, the pathological diagnostic models for predicting malignant and aggressive histological features for patients with ERTs showed outstanding predictive performance and convenience. The use of the models can greatly assist urologists in individualizing the management of their patients.

ObjectivesTo construct and validate unfavorable pathology (UFP) prediction models for patients with the first diagnosis of bladder cancer (initial BLCA) and to compare the comprehensive predictive performance of these models.Materials and MethodsA total of 105 patients with initial BLCA were included and randomly enrolled into the training and testing cohorts in a 7:3 ratio. The clinical model was constructed using independent UFP‐risk factors determined by multivariate logistic regression (LR) analysis in the training cohort. Radiomics features were extracted from manually segmented regions of interest in computed tomography (CT) images. The optimal CT‐based radiomics features to predict UFP were determined by the optimal feature filter and the least absolute shrinkage and selection operator algorithm. The radiomics model consist with the optimal features was constructed by the best of the six machine learning filters. The clinic‐radiomics model combined the clinical and radiomics models via LR. The area under the curve (AUC), accuracy, sensitivity, specificity, positive and negative predictive value, calibration curve and decision curve analysis were used to evaluate the predictive performance of the models.ResultsPatients in the UFP group had a significantly older age (69.61 vs. 63.93 years, p = 0.034), lager tumor size (45.7% vs. 11.1%, p = 0.002) and higher neutrophil to lymphocyte ratio (NLR; 2.76 vs. 2.33, p = 0.017) than favorable pathologic group in the training cohort. Tumor size (OR, 6.02; 95% CI, 1.50–24.10; p = 0.011) and NLR (OR, 1.50; 95% CI, 1.05–2.16; p = 0.026) were identified as independent predictive factors for UFP, and the clinical model was constructed using these factors. The LR classifier with the best AUC (0.817, the testing cohorts) was used to construct the radiomics model based on the optimal radiomics features. Finally, the clinic‐radiomics model was developed by combining the clinical and radiomics models using LR. After comparison, the clinic‐radiomics model had the best performance in comprehensive predictive efficacy (accuracy = 0.750, AUC = 0.817, the testing cohorts) and clinical net benefit among UFP‐prediction models, while the clinical model (accuracy = 0.625, AUC = 0.742, the testing cohorts) was the worst.ConclusionOur study demonstrates that the clinic‐radiomics model exhibits the best predictive efficacy and clinical net benefit for predicting UFP in initial BLCA compared with the clinical and radiomics model. The integration of radiomics features significantly improves the comprehensive performance of the clinical model.

PurposeThe study aimed to compare operative, functional, and oncological outcomes between partial nephrectomy (PN) and radical nephrectomy (RN) for entophytic renal tumors (ERTs) by propensity score matching (PSM) analysis.MethodsA total of 228 patients with ERTs who underwent PN or RN between August 2014 and December 2021 were assessed. A PSM in a 1:1 ratio was conducted to balance the differences between groups. Perioperative characteristics, renal functional, and oncological outcomes were compared between groups. Univariate and multivariate logistic and Cox proportional hazard regression analyses were used to determine the predictors of functional and survival outcomes.ResultsAfter PSM, 136 cases were matched to the PN group (n = 68) and the RN group (n = 68). Patients who underwent RN had shorter OT, less EBL, and lower high-grade complications (all p <0.05) relative to those who underwent PN. However, better perseveration of renal function was observed in the PN group, which was reflected in 48-h postoperative AKI (44.1% vs. 70.6%, p = 0.002), 1-year postoperative 90% eGFR preservation (45.6% vs. 22.1%, p = 0.004), and new-onset CKD Stage ≥III at last follow-up (2.9% vs. 29.4%, p <0.001). RN was the independent factor of short-term (OR, 2.812; 95% CI, 1.369–5.778; p = 0.005) and long-term renal function decline (OR, 10.242; 95% CI, 2.175–48.240; p = 0.003). Furthermore, PN resulted in a better OS and similar PFS and CSS as compared to RN (p = 0.042, 0.15, and 0.21, respectively). RN (OR, 7.361; 95% CI, 1.143–47.423; p = 0.036) and pT3 stage (OR, 4.241; 95% CI, 1.079–16.664; p = 0.039) were independent predictors of overall mortality.ConclusionAmong patients with ERTs, although the PN group showed a higher incidence of high-grade complications than RN, when technically feasible and with experienced surgeons, PN is recommended for better preservation of renal function, longer OS, and similar oncological outcomes.