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Introduction: BPH/male LUTS is a prevalent condition in the aging male population with multifactorial pathophysiology. Pharmacotherapy remains the cornerstone of treatment in patients who fail conservative treatment. 5-α-Reductase inhibitors (5-ARIs) are the only class of medication shown to reduce the risk of acute retention and BPH-related surgery and, thus, are commonly used along with other "short acting" medications in combination treatments. Areas covered: Combination treatments with α-blockers and 5-ARIs have been investigated extensively in high quality trials that prove the long-term efficacy of such treatments with acceptable rates of side effects. Combination treatments involving 5-ARIs and other classes of medications (anticholinergics, b3 agonists, PDEI) have been shown to be beneficial in the short term and but studies with longer follow-up periods are required to fully establish their role. Expert opinion: A-blocker/5-ARI combination treatment is a reasonable approach for patients with male LUTS/BPH who are at increased risk of disease progression or have incomplete response to monotherapies. Other combination treatments with 5-ARIs and PDEI or anticholinergics/β-3 agonists can be tried based on predominant symptoms or side effect profile, but patients should be informed about the lack of long-term data. [ABSTRACT FROM AUTHOR]

Background: The ASCAPE project aims to improve the health-related quality of life of cancer patients using artificial intelligence (AI)-driven solutions. The current study employs a comprehensive dataset to evaluate sleep and urinary incontinence, thus enabling the development of personalized interventions. Methods: This study focuses on prostate cancer patients eligible for curative treatment with surgery. Forty-two participants were enrolled following their diagnosis and were followed up at baseline and 3, 6, 9, and 12 months after surgical treatment. The data collection process involved a combination of standardized questionnaires and wearable devices, providing a holistic view of patients' QoL and health outcomes. The dataset is systematically organized and stored in a centralized database, with advanced statistical and AI techniques being employed to reveal correlations, patterns, and predictive markers that can ultimately lead to implementing personalized intervention strategies, ultimately enhancing patient QoL outcomes. Results: The correlation analysis between sleep quality and urinary symptoms post-surgery revealed a moderate positive correlation between baseline insomnia and baseline urinary symptoms (r = 0.407, p = 0.011), a positive correlation between baseline insomnia and urinary symptoms at 3 months (r = 0.321, p = 0.049), and significant correlations between insomnia at 12 months and urinary symptoms at 3 months (r = 0.396, p = 0.014) and at 6 months (r = 0.384, p = 0.017). Furthermore, modeling the relationship between baseline insomnia and baseline urinary symptoms showed that baseline insomnia is significantly associated with baseline urinary symptoms (coef = 0.222, p = 0.036). Conclusions: The investigation of sleep quality and urinary incontinence via data analysis through the ASCAPE project suggests that better sleep quality could improve urinary disorders. [ABSTRACT FROM AUTHOR]

Prostate cancer is the second most common cancer among men, with many treatment modalities available for patients, such as radical prostatectomy, external beam radiotherapy, brachytherapy, high-intensity focused ultrasound, cryotherapy, electroporation and other whole-gland or focal ablative novel techniques. Unfortunately, up to 60% of men with prostate cancer experience recurrence at 5 to 10 years. Salvage radical prostatectomy can be offered as an option in the setting of recurrence after a primary non-surgical treatment. However, the complexity of salvage radical prostatectomy is considered to be greater than that of primary surgery, making it the least popular treatment of choice. With the wide use of robotic platforms in urologic oncologic surgery, salvage radical prostatectomy has attracted attention again because, compared to past data, modern series involving salvage Robot-Assisted Radical Prostatectomy have shown promising results. In this narrative literature review, we comprehensively examined data on salvage radical prostatectomy. We investigated the correlation between the different types of primary prostate cancer therapy and the following salvage radical prostatectomy. Furthermore, we explored the concept of a robotic approach and its beneficial effect in salvage surgery. Lastly, we emphasized several promising avenues for future research in this field. [ABSTRACT FROM AUTHOR]

Simple Summary: Robot-assisted surgery facilitates the examination and improvement of artificial intelligence (AI) integration in surgical processes through the provision of comprehensive telemetry data and an advanced viewing interface. Machine learning (ML) techniques enhance the feedback on the development of surgical abilities, the efficacy of the surgical operation, surgical guiding, and predicted results. By incorporating tension sensors on the robotic arms and employing augmented reality techniques, the surgical experience can be greatly improved. This enables the continuous monitoring of organ movements in real time, resulting in enhanced precision and accuracy. The integration of artificial intelligence (AI) into robotic surgery is anticipated to have a substantial influence on the education of upcoming surgeons and improve the entire surgical process. Both endeavours strive for ultimate accuracy in order to enhance the quality of surgical care. With the rapid increase in computer processing capacity over the past two decades, machine learning techniques have been applied in many sectors of daily life. Machine learning in therapeutic settings is also gaining popularity. We analysed current studies on machine learning in robotic urologic surgery. We searched PubMed/Medline and Google Scholar up to December 2023. Search terms included "urologic surgery", "artificial intelligence", "machine learning", "neural network", "automation", and "robotic surgery". Automatic preoperative imaging, intraoperative anatomy matching, and bleeding prediction has been a major focus. Early artificial intelligence (AI) therapeutic outcomes are promising. Robot-assisted surgery provides precise telemetry data and a cutting-edge viewing console to analyse and improve AI integration in surgery. Machine learning enhances surgical skill feedback, procedure effectiveness, surgical guidance, and postoperative prediction. Tension-sensors on robotic arms and augmented reality can improve surgery. This provides real-time organ motion monitoring, improving precision and accuracy. As datasets develop and electronic health records are used more and more, these technologies will become more effective and useful. AI in robotic surgery is intended to improve surgical training and experience. Both seek precision to improve surgical care. AI in ''master–slave" robotic surgery offers the detailed, step-by-step examination of autonomous robotic treatments. [ABSTRACT FROM AUTHOR]

There has been a growing need for enhancements in healthcare delivery, especially for the improvement of surgical outcomes. Therefore, implementing consistent reporting of complications enables the evaluation of data quality and facilitates its comparison. There are currently many available reporting and grading systems each with its own set of benefits and drawbacks. In this comprehensive review, we tried to present and assess each of them by demonstrating their criteria and their strong and weak points. To sum up, it seems that there is a need for developing a new reporting and categorization system for complications that are specific to urology. [ABSTRACT FROM AUTHOR]

Introduction The aim of this review was to assess the outcomes of partial nephrectomy using indocyanine green (ICG) regarding ischemia time, positive surgical margins (PSM), estimated blood loss (EBL) and estimated GFR reduction while also suggesting the optimal dosage scheme. Material and methods A systematic review was performed using Medline (PubMed), ClinicalTrials.gov, and Cochrane Library (CENTRAL) databases, in concordance with the PRISMA statement. Studies in English regarding the use of indocyanine green in partial nephrectomy were reviewed. Reviews and meta-analyses, editorials, perspectives, and letters to the editors were excluded. Results Individual ICG dose was 5 mg in most of the studies. The mean warm ischemia time (WIT) on each study ranged from 11.6 minutes to 27.2 minutes. The reported eGFR reduction ranged from 0% to 15.47%. Lowest mean EBL rate was 48.2 ml and the highest was 347 ml. Positive surgical margin rates were between 0.3% to 11%. Conclusions Indocyanine green seems to be a useful tool in partial nephrectomy as it can assist surgeons in identifying tumor and its related vasculature. Thereby, warm ischemia time can be reduced and, in some cases, selective ischemia can be implemented leading to better renal functional preservation. [ABSTRACT FROM AUTHOR]

Purpose: The high incidence of urinary tract infections (UTIs), often in nosocomial environments, is a major cause of antimicrobial resistance (AMR). The dissemination of antibiotic-resistant infections results in very high health and economic burdens for patients and healthcare systems, respectively. This study aims to determine and present the antibiotic resistance profiles of the most common pathogens in a urology department in Greece. Methods: During the period 2019–2020, we included 12,215 clinical samples of blood and urine specimens that tested positive for the following pathogens: Escherichia coli, Enterococcus faecium, Enterococcus faecalis, Proteus mirabilis, Klebsiella pneumoniae, or Pseudomonas aeruginosa, as these are the most commonly encountered microbes in a urology department. Results: The analysis revealed a 22.30% mean resistance rate of E. coli strains with a 76.42% resistance to ampicillin and a 54.76% resistance rate to ciprofloxacin in the two-year period. It also showed an approximately 19% resistance rate of P. mirabilis strains and a mean resistance rate of 46.205% of K. pneumoniae strains, with a decreasing trend during the four semesters (p-value < 0.001), which presented an 80% resistance rate to ampicillin/sulbactam and 73.33% to ciprofloxacin. The resistance to carbapenems was reported to be 39.82%. The analysis revealed a 24.17% mean resistance rate of P. aeruginosa with a declining rate over the two-year period (p-value < 0.001). The P. aeruginosa strains were 38% resistant to fluoroquinolones and presented varying resistance against carbapenems (31.58% against doripenem and 19.79% against meropenem). Regarding the Enteroccocal strains, a 46.91% mean resistance was noted for E. faecium with 100% resistance to ampicillin, and a 24.247% mean resistance rate for E. faecalis strains that were 41% resistant to ciprofloxacin. Both types showed 100% sensitivity to linezolid. Conclusions: The dissemination of antibiotic-resistant pathogens poses the need to implement surveillance programs and, consequently, to develop strategies to prevent the emergence of such pathogens in order to optimize patient outcomes. [ABSTRACT FROM AUTHOR]

Artificial Intelligence (AI) has shown the ability to enhance the accuracy and efficiency of physicians. ChatGPT is an AI chatbot that can interact with humans through text, over the internet. It is trained with machine learning algorithms, using large datasets. In this study, we compare the performance of using a ChatGPT API 3.5 Turbo model to a general model, in assisting urologists in obtaining accurate, valid medical information. The API was accessed through a Python script that was applied specifically for this study based on 2023 EAU guidelines in PDF format. This custom-trained model leads to providing doctors with more precise, prompt answers about specific urologic subjects, thus helping them, ultimately, providing better patient care. [ABSTRACT FROM AUTHOR]

ASCAPE Project is a study aiming to implement the advances of Artificial Intelligence (AI), to support prostate cancer survivors, regarding quality of life issues. The aim of the study is to determine characteristics of patients who accepted to join ASCAPE project. It results that participants of the study mainly originate from higher-educated societies that are better informed about the potential benefits of AI in medicine. Therefore, efforts should be focused on eliminating patients’ reluctancy by better informing them on the potential benefits of AI. [ABSTRACT FROM AUTHOR]

Sarcopenia, defined as the systemic loss of muscle function and mass, is commonly seen in advanced oncologic states, usually in conjunction with cancer cachexia. Bladder cancer represents one of the most common neoplasms worldwide and affects mainly the elderly who are already frail. The purpose of this study is to review the potential association between sarcopenia and bladder cancer in patients receiving different types of treatments. A thorough MEDLINE/PubMed non-systematic literature review was conducted from 1990 to January 2022, using the following search terms: "sarcopenia and bladder cancer" and "low muscle mass and bladder cancer". Sarcopenia probably poses a negative impact on the prognosis of patients at any stage of bladder cancer, as it is linked with overall worse survival, cancer specific survival and progression-free survival in those treated, with either radical cystectomy or chemotherapy. In addition, sarcopenia seems to be a strong predictor concerning complications and a negative prognostic factor following chemotherapy and surgery for bladder cancer. On the other hand, it seems that sarcopenic patients who receive radiotherapy or immunotherapy are not so severely affected. [ABSTRACT FROM AUTHOR]

Benign prostatic enlargement (BPE) is a common disease in men over 50 years old. The phenotype of patients with BPE is heterogenous, regarding both baseline patient characteristics and disease-related parameters. Treatment can be either medical-conservative or surgical. A great variety of surgical techniques are available for surgical management, with three of the most common being monopolar transurethral resection of the prostate (mTUR-P), bipolar transurethral resection of the prostate (bTUR-P), and bipolar transurethral vaporization of the prostate (bTUVis). The selection of each one of these depends on surgeon reasoning, equipment availability, patient characteristics, and preferences. Since all of these techniques are available in our Urology Department, and surgeons are skilled to perform each one of them, we performed a clustering analysis according to patient pre-operative characteristics, using the k-means algorithm, to compare clustering-related technique assignment with the real-life technique used.

Association rule mining is a very popular unsupervised machine learning technique for discovering patterns in large datasets. Patients with stone disease commonly suffer from urinary tract infections (UTI), complicated by the emergence of antimicrobial resistance (AMR), due to the excessive use of antibiotics. In this study, we explore the use of association rule mining in the AMR profile of patients suffering from stone disease.