International Neurourology Journal最新文献

Purpose: This investigation was conducted to elucidate the effects of eugenol on bladder contractility through experimental and in silico approaches.

Methods: To assess the impact of eugenol on muscular contractility, longitudinal strips of bladder tissue, measuring 2 mm by 6 mm, were mounted in perfusion chambers connected to an isometric force transducer. Furthermore, molecular docking studies were conducted to explore the potential of eugenol to target the M3 muscarinic acetylcholine receptor (M3R) and voltage-operated calcium channels (VOCCs) in muscle cells, utilizing in silico techniques.

Results: Eugenol exhibited a concentration-dependent inhibitory effect on both the phasic and tonic components of the contraction induced by 60mM K+ and carbachol, completely suppressing this contraction at a concentration of 3mM. Additionally, eugenol inhibited the concentration-contraction curve elicited by Ba2+.

Conclusion: The in vitro and in silico results suggest that the mechanism of eugenol likely involves blockade of VOCCs and/or M3R, implicating eugenol as a promising molecule for the treatment of overactive bladder.

Purpose: While pump manipulation is rarely problematic in male patients with artificial urinary sphincters (AUSs), the situation may differ in female patients due to anatomical or cultural factors. This study aimed to evaluate the prevalence of difficulties in pump manipulation among female AUS patients, identify associated risk factors, and explore management strategies for this challenging issue.

Methods: Data were collected from all female patients who underwent a robotic AUS implantation at a single academic center between 2014 and 2022. The primary endpoint was temporary difficulties, defined by at least one other short hospitalization to learn pump manipulation.

Results: Out of the 88 female AUS patients included in the study, 20 experienced initial difficulties manipulating the pump, accounting for 22.7% of the group. Temporary difficulties were reported by 16 patients (18.2%), while 4 patients (4.5%) had their devices permanently deactivated. Surgical reoperations to reposition the pump were necessary for 5 patients, representing 5.6% of the sample. The only variables significantly associated with temporary difficulties were longer operative time (183.4 minutes vs. 159.1 minutes, P=0.04) and the overall experience of the center (32 vs. 50, P=0.04). The sole variable significantly linked to serious difficulties was the overall experience of the center (11 vs. 47, P=0.004). Although the median age and body mass index were higher in the group with temporary difficulties, these differences were not statistically significant.

Conclusion: Difficulties in manipulating the pump are relatively common among female AUS patients. Most of these difficulties can be resolved through repeated patient education and careful follow-up. However, some may lead to serious complications. Raising awareness of this issue, along with ongoing patient education and meticulous follow-up, may help to minimize these consequences.

Purpose: Precise electrode placement is crucial for the success of sacral neuromodulation (SNM). The aim of this study was to explore a more accurate and convenient method for positioning punctures during the first stage of SNM.

Methods: This retrospective study compared preoperative baseline values, intraoperative indicators, postoperative scores, and other clinical data from 130 patients who underwent SNM electrode implantation at our department between 2018 and 2023. The patients were divided into an experimental group and a control group to assess the advantages and feasibility of augmented reality (AR)-guided sacral nerve electrode implantation.

Results: The experimental group experienced fewer intraoperative puncture attempts and achieved more accurate AR-guided localization punctures. Additionally, there were more responsive electrode contact points (2.74±0.51 vs. 2.46±0.74) and a lower initial voltage postimplantation (1.09±0.39 V vs. 1.69±0.43 V). The number of intraoperative x-ray fluoroscopies was significantly lower in the experimental group than in the control group (5.94±1.46 vs. 9.22±1.93), leading to a shorter overall operation time (61.32±11.27 minutes vs. 83.49±15.84 minutes). Furthermore, there was no need for additional local anesthetic drugs during the surgery in the experimental group. Comparative observations revealed no significant differences in intraoperative blood loss or the sacral hole location for electrode implantation between the 2 groups. Although the incidence of wound infection and the rate of permanent implantation in stage 2 were similar in both groups, the pain score on the first day postoperation was significantly lower in the experimental group than in the control group (2.62±0.697 vs. 2.83±0.816).

Conclusion: AR-guided sacral nerve modulation implantation can reduce both the number of punctures and the duration of the operation while ensuring safety and effectiveness. This technique can enhance the contact points of the response electrode, effectively lower the initial response voltage, and stabilize the electrode.

Purpose: This study aims to explore the potential of digital therapeutics in managing voiding dysfunction associated with benign prostatic hyperplasia (BPH). To achieve this, we collected and analyzed news and community data from major Korean platforms to assess the trends in media and community discussions and examine how digital therapeutics can contribute to personalized care and support self-management for patients with BPH-related voiding dysfunction.

Methods: Data was collected over a 3-year period from October 2021 to September 2024 using the keywords 'prostate,' 'urinary,' and 'treatment.' Key terms and patterns were then identified through word frequency analysis, TF-IDF (term frequency-inverse document frequency) analysis, and N-gram analysis to examine the potential applicability of digital therapeutics in this area.

Results: The news data primarily focused on expert-oriented medical information related to the treatment, surgical options, and diagnosis of BPH. In contrast, community data centered on discussions about everyday symptoms and solutions, such as urinary issues and self-care tips. This suggests that patients are particularly interested in practical problem-solving and selfmanagement strategies.

Conclusion: This study suggests that digital therapeutics can empower patients with BPH to self-manage their urinary disorders through personalized management tools. Future research can be done to focus on empirically examining the clinical validity and practical applicability of digital therapeutics for BPH through clinical trials.

The metaverse, a 3-dimensional digital platform that enables users to interact and engage in realistic virtual activities beyond time and space limitations, has garnered significant investment across industries, particularly in healthcare. In the medical field, the metaverse shows promise as a digital therapeutic platform to enhance interaction between medical professionals and patients. Concurrently, generative artificial intelligence, especially large language models, is being integrated into healthcare for applications in data analysis, image recognition, and natural language processing. In urology, large language models (LLMs) support are increasingly used in urology for tasks such as image diagnosis, data processing, patient education, and treatment assistance in order to provide significant support in clinical settings. By combining LLMs with the immersive capabilities of the metaverse, new possibilities emerge to improve urologic treatment in areas that require consistent treatments, habit formation, and long-term management. This paper reviews current research and applications of LLMs in urology, discusses the challenges associated with their use including data quality, bias, security, and ethical issues, and explores the need for regulatory standards. Furthermore, it highlights the potential of a metaverse-based digital platform to improve urologic care and streamline information exchange to maximize the benefits of this integrated approach in future healthcare applications.

Purpose: This study aimed to develop and evaluate machine learning models, specifically CatBoost and extreme gradient boosting (XGBoost), for diagnosing lower urinary tract symptoms (LUTS) in male patients. The objective is to differentiate between bladder outlet obstruction (BOO) and detrusor underactivity (DUA) using a comprehensive dataset that includes patient-reported outcomes, uroflowmetry measurements, and ultrasound-derived features.

Methods: The dataset used in this study was collected from male patients aged 40 and older who presented with LUTS and sought treatment at the urology department of Samsung Medical Center. We developed and trained CatBoost and XGBoost models using this dataset. These models incorporated features like prostate size, voiding parameters, and responses from questionnaires. Their performance was assessed using standard metrics such as accuracy, precision, recall, F1-score, and area under the receiver operating characteristic curve (AUROC).

Results: The results indicated that the CatBoost models displayed greater sensitivity, rendering them effective for initial screenings by accurately identifying true positive cases. Conversely, the XGBoost models showed higher specificity and precision, making them more suitable for confirming diagnoses and reducing false positives. In terms of overall performance for both BOO and DUA, XGBoost surpassed CatBoost, achieving an AUROC of 0.826 and 0.819, respectively.

Conclusion: Integrating these machine learning models into the diagnostic workflow for LUTS can significantly enhance clinical decision-making by offering noninvasive, cost-effective, and patient-friendly diagnostic alternatives. The combined application of CatBoost and XGBoost models has the potential to improve diagnostic accuracy and provide customized treatment plans for patients, ultimately leading to better clinical outcomes.

Purpose: Predicting improvements in voiding symptoms following deobstructive surgery for male lower urinary tract symptoms/benign prostatic hyperplasia (LUTS/BPH) is challenging when detrusor contractility is impaired. This study aimed to develop an artificial intelligence model that predicts symptom improvement after holmium laser enucleation of the prostate (HoLEP), focusing on changes in maximum flow rate (MFR) and voiding efficiency (VE) 1-month postsurgery.

Methods: We reviewed 1,933 patients who underwent HoLEP at Samsung Medical Center from July 2008 to January 2024. The study employed a deep neural network (DNN) for multiclass classification to predict changes in MFR and VE, each divided into 3 categories. For comparison, additional machine learning (ML) models such as extreme gradient boosting, random forest classification, and support vector machine were utilized. To address class imbalance, we applied the least squares method and multitask learning.

Results: A total of 1,142 patients with complete data were included in the study, with 992 allocated for model training and 150 for external validation. In predicting MFR, the DNN achieved a microaverage area under the receiver operating characteristic curve (AUC) of 0.884±0.006, sensitivity of 0.783±0.020, and specificity of 0.891±0.010. For VE prediction, the microaverage AUC was 0.817±0.007, with sensitivity and specificity values of 0.660±0.014 and 0.830±0.007, respectively. These results indicate that the DNN's predictive performance was superior to that of other ML models.

Conclusion: The DNN model provides detailed and accurate predictions for recovery after HoLEP, providing valuable insights for clinicians managing patients with LUTS/BPH.

Purpose: The purpose of this study is to identify social perceptions and public concerns related to male hormone levels and prostate cancer. To do so, we analyzed news and community data from Naver, Daum, and Google, the three most active social media platforms in South Korea, to explore how male hormone levels and benign prostatic hyperplasia (BPH) are covered in the media and discussed within online communities.

Methods: We analyzed three years of data from community discussions and news articles from July 2021 to June 2024. Text mining techniques were used to collect data with the keyword 'male hormone levels' to understand the portrayal of these issues in news and online communities as well as the public's social perceptions and concerns.

Results: The analysis showed that news coverage of 'male hormone levels' initially drew public attention by highlighting information related to celebrities and events while discussion on 'prostate enlargement' largely focused on medical treatments and information. The online community served as a platform where news-triggered issues were rediscussed through personal experiences and opinions, thus influencing public perceptions. However, the community discussions leaned more towards sexual dysfunction rather than prostate enlargement. These findings suggest that while news and online communities shape public awareness in different way, they both contribute to shaping social understanding of male hormone level and BPH.

Conclusion: This study highlights the significant roles that news and online communities play in shaping social perceptions of male hormone levels and BPH. However, sensationalism in media coverage may lead to biased information and reinforce false stereotypes. Future studies can be done to incorporate data from diverse cultural contexts and extend the data collection period to further explore shifts in public perceptions and the evolution of social discussions surrounding male hormone levels and BPH.

Purpose: The purpose of this paper is to explore public perceptions and key issues related to vasectomy in South Korea. In particular, this paper seeks to analyze how vasectomy is discussed on question-and-answer (Q&A) social platforms including NAVER Jisik iN (knowledge exchange service between NAVER users) and to identify topics that capture public interest.

Methods: In this study, based on data collected on NAVER Jisik iN from July 2019 to July 2024 with the keyword 'vasectomy,' this paper performs a co-occurrence matrix analysis on the Q&A data to identify key terms related to the topic. By applying connection centrality and community detection techniques, this paper visualizes and examines the network graph to uncover relationships between words and identify the primary topics of discussion.

Results: The co-occurrence matrix analysis reveals that keywords such as 'surgery,' 'vasectomy,' and 'contraception' play a central role in discussions about vasectomies. Both the Q&A data highlight the vasectomy procedure and contraceptive effectiveness as primary topics of discussion. The visualization graphs intuitively display the centrality and strength of connections between these keywords, as well as the interrelatedness of topics through distinct community groups.

Conclusion: The analysis shows that the questions primarily focused on the surgical procedure, while the answers were more concerned with contraceptive effectiveness and physiological aspects. These results suggest that the public's interest in vasectomy is closely linked to its effectiveness, potential side effects, and related social issues.