Does prior PCNL affect RIRS? A retrospective analysis of a single center data.

PURPOSE: The aim of this study is to investigate the results and safety of retrograde intrarenal surgery (RIRS) in patients who have previously undergone percutaneous nephrolithotomy (PCNL). METHODS: A retrospective analysis included patients who underwent RIRS for kidney stones between August 2018 and April 2023. Group 1 comprised 396 patients who underwent primary RIRS, while Group 2 included 231 individuals who had RIRS after previous PCNL. Evaluation parameters included preoperative characteristics, stone attributes, operative details, treatment outcomes, stone-free status, and complications. Statistical analysis utilized Student's t test, Mann-Whitney U test, and Pearson Chi-square test (p < 0.05). RESULTS: The mean age, body mass index, stone number, mean stone burden, and SFS were not statistically different between the groups. Lower pole stones were identified in 144 patients in Group 1 and 88 patients in Group 2 (p = 0.315). In Group 1 and Group 2, the mean operation time and fluoroscopy time were 65.23 ± 18.1 min, 81.32 ± 14.3 min, 26.34 ± 8.31 s, 46.61 ± 7.6 s, respectively, showing statistically significant differences between the groups (p = 0.013, p < 0.001, respectively). Infundibulum stenosis was identified and treated with a laser in 12% of Group 2 cases. Complications occurred in 12 patients in Group 1 and 14 patients in Group 2 (p = 0.136). CONCLUSION: A history of PCNL may contribute to extended operation times and increased fluoroscopy exposure in subsequent RIRS without significantly affecting postoperative SFS or complication rates.

The Status of Spermatogenesis in Germ Cell Tumor Bearing Testis and Its Association with Metastatic Disease.

INTRODUCTION: We aimed to evaluate the status of spermatogenesis detected by histological examination of non-tumoral testicular tissues in tumor bearing testis and its association with advanced stage disease. PATIENTS AND METHODS: We retrospectively reviewed patients with testicular germ cell tumors (TGCTs) that undergone radical orchiectomy. All non-tumoral areas of the orchiectomy specimens were examined for the status of spermatogenesis. Patients were divided into two groups as localized (stage I) and metastatic (stage II-III) disease and analyzed separately for seminomatous (SGCT) and nonseminomatous germ cell tumors (NSGCT). RESULTS: Four hundred fifty-four patients were included in our final analysis. Of those, 195 patients had SGCT, and 259 patients had NSGCT. Three hundred and six patients had localized disease at the time of diagnosis. Median (Q1-Q3) age was 31 (26 - 38) years and 102 (22.5%) patients had normal spermatogenesis, 177 (39.0%) patients had hypospermatogenesis and 175 (38.5%) patients had no mature spermatozoa. On multivariate logistic regression analysis, embryonal carcinoma >50% (1.944, 95 %CI 1.054-3.585, P = .033) and spermatogenesis status (2.796 95% CI 1.251-6.250, P = .012 for hypospermatogenesis, and 3.907, 95% CI 1.692-9.021, P = .001 for absence of mature spermatozoa) were independently associated with metastatic NSGCT. However, there was not any variables significantly associated with metastatic SGCT on multivariate logistic regression analysis. CONCLUSION: Our study demonstrated that only 22.5% of patients with TGCTs had normal spermatogenesis in tumor bearing testis. Impaired spermatogenesis (hypospermatogenesis or no mature spermatozoa) and predominant embryonal carcinoma are associated with advanced stage NSGCT.

Introducing a New Smartphone Applied Semen Analyzer, SpermCell™: A Cross-Sectional Validation Study with a Comparative Analysis and a Mini Patient Questionnaire on a Large Sample Cohort.

(1) Background: Standard semen analysis methods may exhibit variability between observers and/or human error; therefore, additional methods are needed to overcome these handicaps. We aimed to present a new smartphone-applied semen analyzer, Sperm Cell™, investigate its diagnostic efficacy by comparing it with the standard analysis method, and determine its user-friendly nature. (2) Methods: A cross-sectional study was conducted on a large sample cohort, including 102 men. Three semen analyses were performed for each semen sample. The first employed the standard manual method, whereas the others were smartphone-based analyses performed by technicians and patients. We compared major semen parameters between the three semen analyses. The user-friendly nature of the analyzer was also evaluated with a mini-questionnaire completed by the participants. (3) Results: The determined median sperm count, motile sperm count, and percentage of motile sperms, on standard manual semen analysis, were 50.00 × 106/mL (0-160 × 106/mL), 23.94 × 106/mL (0-108 × 106/mL) and 50.00% (0-73.00%), respectively. Median sperm count and motile sperm count were 50.52 × 106/mL (<1-150 × 106/mL) vs. 55.77 × 106/mL (<1-160 × 106/mL) and 23.34 × 106/mL (0-105 × 106/mL) vs. 23.53 × 106/mL (0-104 × 106/mL) for SpermCell™-based semen analysis performed by a technician and patients themselves, respectively. The percentages of motile sperms were 47.40% (0-67.00%) vs. 47.61% (0-80.20%), respectively. All the parameters were statistically similar between the three semen analysis methods (p > 0.05 for each). The SpermCell™ analysis results were correlated with the standard manual method with up to 0.85 correlation coefficients. Moreover, substantial diagnostic accuracy, sensitivity and specificity were obtained in determining the oligospermia and asthenozoospermia via the device-based analyses performed by technician and patients. The mini-questionnaire results revealed that the analyzer is useful. (4) Conclusions: The novel smartphone-applied semen analyzer is a helpful tool with acceptable diagnostic accuracy in determining the major semen parameters. It can be used as an efficient at-home point-of-care testing method in the initial assessment of couples with infertility concerns.

The efficacy of artificial intelligence in urology: a detailed analysis of kidney stone-related queries.

PURPOSE: The study aimed to assess the efficacy of OpenAI's advanced AI model, ChatGPT, in diagnosing urological conditions, focusing on kidney stones. MATERIALS AND METHODS: A set of 90 structured questions, compliant with EAU Guidelines 2023, was curated by seasoned urologists for this investigation. We evaluated ChatGPT's performance based on the accuracy and completeness of its responses to two types of questions [binary (true/false) and descriptive (multiple-choice)], stratified into difficulty levels: easy, moderate, and complex. Furthermore, we analyzed the model's learning and adaptability capacity by reassessing the initially incorrect responses after a 2 week interval. RESULTS: The model demonstrated commendable accuracy, correctly answering 80% of binary questions (n:45) and 93.3% of descriptive questions (n:45). The model's performance showed no significant variation across different question difficulty levels, with p-values of 0.548 for accuracy and 0.417 for completeness, respectively. Upon reassessment of initially 12 incorrect responses (9 binary to 3 descriptive) after two weeks, ChatGPT's accuracy showed substantial improvement. The mean accuracy score significantly increased from 1.58 ± 0.51 to 2.83 ± 0.93 (p = 0.004), underlining the model's ability to learn and adapt over time. CONCLUSION: These findings highlight the potential of ChatGPT in urological diagnostics, but also underscore areas requiring enhancement, especially in the completeness of responses to complex queries. The study endorses AI's incorporation into healthcare, while advocating for prudence and professional supervision in its application.