Current status and trends of urinary incontinence research in recent 10 years based on VOSviewer visualized analysis: An observational study.

Urinary incontinence (UI) is prevalent and imposes significant social and economic burdens. This study reviews the literature on UI, assesses the current research status, and projects future trends. To visualize and analyze UI-related research, summarize and generalize the knowledge framework of the global UI field, and explore the current state of research and emerging trends, we conducted a comprehensive search of UI-related studies from 2014 to 2024 using the Web of Science Core Collection. Utilizing VOSviewer software, we mapped the scientific landscape and performed visual analytics on collaborative and co-citation networks, keyword co-occurrences, emergent clusters, and timeline mapping to elucidate the research dynamics. A total of 4326 publications were retrieved for further analysis. The United States ranked first in terms of the total number of publications, number of citations, and publication H-index. In terms of institutions, the University of California System had the most total citations and the highest H-index. Neurology and Urodynamics had the most articles published, the highest citation frequency, and the highest H-index. The author with the most citations and the highest average number of citations per article is Abrams P. The author with the highest H-index is Peyronnet B. Based on the keyword analysis, the articles were categorized into several main directions: epidemiological studies, diagnostic studies, treatment studies, female UI studies, and male UI studies. Epidemiology, treatment, and male UI are expected to continue as hot topics. This study demonstrates that UI research is more advanced in Europe and North America and that Neurourology and Urodynamics is the most influential journal in the field. In addition, epidemiology, treatment, and male UI will continue to be prominent topics. Our study contributes to a more comprehensive understanding of the current state of UI research and provides insights into future research directions in the field.

Comparison of temperature and renal tissue thermal damage by holmium laser with different energy parameters during lithotripsy: in vitro porcine kidney model.

OBJECTIVE: Holmium laser percutaneous nephrolithotripsy was simulated by porcine kidney calculus model in vitro to investigate thermal damage of renal tissue by different energy parameters of the holmium laser. METHODS: We placed human kidney calculus specimen in fresh vitro porcine kidney, then insert thermocouple temperature probes into the submucosa of the renal pelvis and reheated in a 37 °C water bath. A percutaneous nephrological sheath was used to penetrate the renal parenchyma with a moderate irrigation rate of 30 ml/min at 18 â„ƒ. The Holmium laser was used to fragment the stones under a nephroscope, and the temperature was recorded. RESULTS: The four independent models were lithotripsy with 30 W and 60 W laser for 5 and 10 min, respectively; the mean temperature of 30 W vs. 60 W within 5 min was 36.06 °C vs. 39.21 °C (t = 5.36, P < 0.01) and the highest temperature was 43.60 °C vs. 46.60 °C; the mean temperature of 30 W vs. 60 W within 10 min was 37.91 °C vs. 40.13 â„ƒ (t = 5.28, P < 0.01), maximum temperature 46.80 â„ƒ vs. 49.20 â„ƒ. Pathologically, each kidney was observed to have different degrees of thermal damage lesions, and the higher power and longer time the more severe the injury, but the injury was mainly limited to the uroepithelial and subepithelial tissues, with rare damage to renal tubules. CONCLUSION: The higher laser excitation power and longer duration raised the intrarenal temperature significantly and caused a certain degree of thermal damage to the kidney tissue, but overall it was found to be safe and reliable. Urologists can avoid further side effects through surgical expertise.

Establishment and validation of serum lipid-based nomogram for predicting the risk of prostate cancer.

BACKGROUND: This study aimed to explore the value of combined serum lipids with clinical symptoms to diagnose prostate cancer (PCa), and to develop and validate a Nomogram and prediction model to better select patients at risk of PCa for prostate biopsy. METHODS: Retrospective analysis of 548 patients who underwent prostate biopsies as a result of high serum prostate-specific antigen (PSA) levels or irregular digital rectal examinations (DRE) was conducted. The enrolled patients were randomly assigned to the training groups (n = 384, 70%) and validation groups (n = 164, 30%). To identify independent variables for PCa, serum lipids (TC, TG, HDL, LDL, apoA-1, and apoB) were taken into account in the multivariable logistic regression analyses of the training group, and established predictive models. After that, we evaluated prediction models with clinical markers using decision curves and the area under the curve (AUC). Based on training group data, a Nomogram was developed to predict PCa. RESULTS: 210 (54.70%) of the patients in the training group were diagnosed with PCa. Multivariate regression analysis showed that total PSA, f/tPSA, PSA density (PSAD), TG, LDL, DRE, and TRUS were independent risk predictors of PCa. A prediction model utilizing a Nomogram was constructed with a cut-off value of 0.502. The training and validation groups achieved area under the curve (AUC) values of 0.846 and 0.814 respectively. According to the decision curve analysis (DCA), the prediction model yielded optimal overall net benefits in both the training and validation groups, which is better than the optimal net benefit of PSA alone. After comparing our developed prediction model with two domestic models and PCPT-RC, we found that our prediction model exhibited significantly superior predictive performance. Furthermore, in comparison with clinical indicators, our Nomogram's ability to predict prostate cancer showed good estimation, suggesting its potential as a reliable tool for prognostication. CONCLUSIONS: The prediction model and Nomogram, which utilize both blood lipid levels and clinical signs, demonstrated improved accuracy in predicting the risk of prostate cancer, and consequently can guide the selection of appropriate diagnostic strategies for each patient in a more personalized manner.

Reasons and risk factors for delayed discharge after day-surgery percutaneous nephrolithotomy.

BACKGROUND: Day-surgery percutaneous nephrolithotomy (PCNL) is being developed quickly but some potential factors are affecting the recovery process. This study is aim to analyze the reasons and risk factors for delayed discharge after day-surgery PCNL. METHODS: The data of 205 patients who accepted day-surgery PCNL in our institution between January 2018 and February 2020 were analyzed, retrospectively. Univariate and multivariate logistic regression analysis were used to analyze the risk factors for delayed discharge. Besides, the nomogram prediction model was established by the multivariable logistic regression analysis. RESULTS: The rate of delayed discharge was 14.6%. Independent risk factors for delayed discharge were larger stone burden (odds ratio [OR] = 3.814, P = 0.046), positive urine nitrite (OR = 1.001, P = 0.030), longer duration of surgery (OR = 1.020, P = 0.044), multiple nephrostomy tubes (OR = 4.282, P = 0.008). The five main reasons that caused delayed discharge included psychological reasons, pain, bleeding, urosepsis, and urine leakage. CONCLUSIONS: This study identified some independent risk factors for a hospital length of stay longer than 24 h. Patients with larger renal stones or positive urine nitrite may be at increased risk of delayed discharge after day-surgery PCNL. Reducing surgery time and nephrostomy tubes will help to facilitate recovery.

Identifying stage-associated hub genes in bladder cancer via weighted gene co-expression network and robust rank aggregation analyses.

BACKGROUND: Bladder cancer (BC) is among the most frequent cancers globally. Although substantial efforts have been put to understand its pathogenesis, its underlying molecular mechanisms have not been fully elucidated. METHODS: The robust rank aggregation approach was adopted to integrate 4 eligible bladder urothelial carcinoma microarray datasets from the Gene Expression Omnibus. Differentially expressed gene sets were identified between tumor samples and equivalent healthy samples. We constructed gene co-expression networks using weighted gene co-expression network to explore the alleged relationship between BC clinical characteristics and gene sets, as well as to identify hub genes. We also incorporated the weighted gene co-expression network and robust rank aggregation to screen differentially expressed genes. RESULTS: CDH11, COL6A3, EDNRA, and SERPINF1 were selected from the key module and validated. Based on the results, significant downregulation of the hub genes occurred during the early stages of BC. Moreover, receiver operating characteristics curves and Kaplan-Meier plots showed that the genes exhibited favorable diagnostic and prognostic value for BC. Based on gene set enrichment analysis for single hub gene, all the genes were closely linked to BC cell proliferation. CONCLUSIONS: These results offer unique insight into the pathogenesis of BC and recognize CDH11, COL6A3, EDNRA, and SERPINF1 as potential biomarkers with diagnostic and prognostic roles in BC.