Background: ChatGPT has recently emerged as a novel resource for patients’ disease-specific inquiries. There is, however, limited evidence assessing the quality of the information. We evaluated the accuracy and quality of the ChatGPT’s responses on male lower urinary tract symptoms (LUTS) suggestive of benign prostate enlargement (BPE) when compared to two reference resources. Methods: Using patient information websites from the European Association of Urology and the American Urological Association as reference material, we formulated 88 BPE-centric questions for ChatGPT 4.0+. Independently and in duplicate, we compared the ChatGPT’s responses and the reference material, calculating accuracy through F1 score, precision, and recall metrics. We used a 5-point Likert scale for quality rating. We evaluated examiner agreement using the interclass correlation coefficient and assessed the difference in the quality scores with the Wilcoxon signed-rank test. Results: ChatGPT addressed all (88/88) LUTS/BPE-related questions. For the 88 questions, the recorded F1 score was 0.79 (range: 0–1), precision 0.66 (range: 0–1), recall 0.97 (range: 0–1), and the quality score had a median of 4 (range = 1–5). Examiners had a good level of agreement (ICC = 0.86). We found no statistically significant difference between the scores given by the examiners and the overall quality of the responses (p = 0.72). Discussion: ChatGPT demostrated a potential utility in educating patients about BPE/LUTS, its prognosis, and treatment that helps in the decision-making process. One must exercise prudence when recommending this as the sole information outlet. Additional studies are needed to completely understand the full extent of AI’s efficacy in delivering patient education in urology.

Background: Intraoperative complications (ICs) are invariably underreported in urological surgery despite the recent endorsement of new classification systems. We aimed to provide a detailed overview of ICs during Retzius-sparing robot-assisted radical prostatectomy (RS-RARP). Methods: We prospectively collected data from 1891 patients who underwent RS-RARP at a single high-volume European center from January 2010 to December 2022. ICs were collected based on surgery reports and categorized according to the Intraoperative Adverse Incident Classification (EAUiaiC). The quality criteria for accurate and comprehensive reporting of intraoperative adverse events proposed by the Intraoperative Complications Assessment and Reporting with Universal Standards (ICARUS) Global Surgical Collaboration Project were fulfilled. To better classify the role of the RS-RARP approach, ICs were classified into anesthesiologic and surgical ICs. Surgical ICs were further divided according to the timing of the complication in RARP-related ICs and ePNLD-related ICs. Results: Overall, 40 ICs were reported in 40 patients (2.1%). Ten out of thirteen ICARUS criteria were satisfied. According to EAUiaiC grading of ICs, 27 (67.5%), 7 (17.5%), 2 (5%), 2 (5%), and 2 (5%) patients experienced Grade 1, 2, 3, 4A, and 4B, respectively. When we classified the ICs, two cases (5%) were classified as anesthesiologic ICs. Among the 38 surgical ICs, 16 (42%) were ePNLD-related, and 22 (58%) were RARP-related. ICs led to seven (0.37%) post-operative sequelae (four non-permanent and three permanent). Patients who suffered ICs were significantly older (67 years vs. 65 years, p = 0.02) and had a higher median BMI (27.0 vs. 26.1, p = 0.01), but did not differ in terms of comorbidities or tumor characteristics (all p values ≥ 0.05). Conclusions: Intraoperative complications during RS-RARP are relatively infrequent, but should not be underestimated. Patients suffering from ICs are older, have a higher body mass index, a higher rate of intraoperative blood transfusion, and a longer length of stay.