Background Chronic Prostatitis/Chronic Pelvic Pain Syndrome (CP/CPPS) is a disease with diverse clinical manifestations, such as pelvic pain or perineal pain. Although recent studies found several risk factors related to the pain severity of CP/CPPS patients, results were inconsistent. Here, we aimed to identify novel risk factors that are closely related to the severity of pain in patients with CP/CPPS. Methods We retrospectively collected the clinical records from patients with CP/CPPS from March 2019 to October 2019. The questionnaire was used to obtain related parameters, such as demographics, lifestyle, medical history, etc. To identify potential risk factors related to pain severity, we used the methods of univariate and multivariate logistic regression analyses. Further, to confirm the relationship between these confirmed risk factors and CP/CPPS, we randomly divided CP/CPPS patients into the training and the validation cohorts with a ratio of 7:3. According to the co-efficient result of each risk factor calculated by multivariate logistic regression analysis, a predicting model of pain severity was established. The receiver operating characteristic curve (ROC), discrimination plot, calibration plot, and decision curve analyses (DCA) were used to evaluate the clinical usage of the current model in both the training and validation cohorts. Results A total of 272 eligible patients were enrolled. The univariate and multivariate logistic regression analysis found that age [odds ratio (OR): 2.828, 95% confidence intervals (CI): 1.239–6.648, P = 0.004], holding back urine (OR: 2.413, 95% CI: 1.213–4.915, P = 0.005), anxiety or irritability (OR: 3.511, 95% CI: 2.034–6.186, P < 0.001), contraception (OR: 2.136, 95% CI:1.161–3.014, P = 0.029), and smoking status (OR: 1.453, 95% CI: 1.313–5.127, P = 0.013) were the risk factors of pain severity. We then established a nomogram model, to test whether these factors could be used to predict the pain severity of CP/CPPS patients in turn. Finally, ROC, DCA, and calibration analyses proved the significance and stability of this nomogram, further confirmed that these factors were closely related to the pain severity of CP/CPPS patients. Conclusions We identify age, holding back urine, anxiety or irritability, contraception, and smoking are risk factors closely related to the pain severity in patients with CP/CPPS. Our results provide novel inspirations for clinicians to design the personalized treatment plan for individual CP/CPPS patient who has suffered different encounters.
Chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS) is a very common urological disorder and has been gradually regarded as an immune-mediated disease. Multiple studies have indicated that the gut microflora plays a pivotal part in immune homeostasis and autoimmune disorder development. However, whether the gut microflora affects the CP/CPPS, and the underlying mechanism behind them remain unclear. Here, we built an experimental autoimmune prostatitis (EAP) mouse model by subcutaneous immunity and identified that its Th17/Treg frequency was imbalanced. Using fecal 16s rRNA sequencing and untargeted/targeted metabolomics, we discovered that the diversity and relative abundance of gut microflora and their metabolites were obviously different between the control and the EAP group. Propionic acid, a kind of short-chain fatty acid (SCFA), was decreased in EAP mice compared to that in controls, and supplementation with propionic acid reduced susceptibility to EAP and corrected the imbalance of Th17/Treg cell differentiation in vivo and in vitro. Furthermore, SCFA receptor G-protein-coupled receptor 43 and intracellular histone deacetylase 6 regulated by propionic acid in Th17 and Treg cells were also evaluated. Lastly, we observed that fecal transplantation from EAP mice induced the decrease of Treg cell frequency in recipient mice. Our data showed that gut dysbiosis contributed to a Th17/Treg differentiation imbalance in EAP via the decrease of metabolite propionic acid and provided valuable immunological groundwork for further intervention in immunologic derangement of CP/CPPS by targeting propionic acid.
BACKGROUND Depression and anxiety are top contributors to non-fatal health loss globally. Several studies have indicated the association between residential greenness and mental health. METHOD The participants (n = 27,366) were recruited from four counties in Henan Province, China during 2015-2017. Symptoms of depression and anxiety were evaluated using the Patient Health Questionnaire-2 (PHQ-2) and the Generalized Anxiety Disorder-2 (GAD-2) in the baseline survey. The level of residential greenness during the 3-year period before the baseline survey was assessed using the Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI). The mixed-effect linear regression model was applied to examine the associations of residential greenness with depression and anxiety. RESULTS The results of adjusted models showed that the score of PHQ-2 (Dscore and 95% confidence interval [CI]) decreased by À0.024 (À0.041, À0.006) and À0.022 (À0.038, À0.004) with an interquartile range (IQR) increase in NDVI and EVI within a 1,000-m buffer radius, respectively. The score of GAD-2 (Dscore and 95% CI) decreased by À0.024 (À0.040, À0.006) and À0.028 (À0.044, À0.011), in relation to an IQR increase in NDVI and EVI within a 1,000-m buffer radius, respectively. CONCLUSIONS A higher level of residential greenness was significantly associated with lower risk of depression and anxiety in rural areas of Henan Province. Improving residential greenness accessibility may help to promote the mental health of rural populations.
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