Accuracy, readability, and understandability of large language models for prostate cancer information to the public.

BACKGROUND: Generative Pretrained Model (GPT) chatbots have gained popularity since the public release of ChatGPT. Studies have evaluated the ability of different GPT models to provide information about medical conditions. To date, no study has assessed the quality of ChatGPT outputs to prostate cancer related questions from both the physician and public perspective while optimizing outputs for patient consumption. METHODS: Nine prostate cancer-related questions, identified through Google Trends (Global), were categorized into diagnosis, treatment, and postoperative follow-up. These questions were processed using ChatGPT 3.5, and the responses were recorded. Subsequently, these responses were re-inputted into ChatGPT to create simplified summaries understandable at a sixth-grade level. Readability of both the original ChatGPT responses and the layperson summaries was evaluated using validated readability tools. A survey was conducted among urology providers (urologists and urologists in training) to rate the original ChatGPT responses for accuracy, completeness, and clarity using a 5-point Likert scale. Furthermore, two independent reviewers evaluated the layperson summaries on correctness trifecta: accuracy, completeness, and decision-making sufficiency. Public assessment of the simplified summaries' clarity and understandability was carried out through Amazon Mechanical Turk (MTurk). Participants rated the clarity and demonstrated their understanding through a multiple-choice question. RESULTS: GPT-generated output was deemed correct by 71.7% to 94.3% of raters (36 urologists, 17 urology residents) across 9 scenarios. GPT-generated simplified layperson summaries of this output was rated as accurate in 8 of 9 (88.9%) scenarios and sufficient for a patient to make a decision in 8 of 9 (88.9%) scenarios. Mean readability of layperson summaries was higher than original GPT outputs ([original ChatGPT v. simplified ChatGPT, mean (SD), p-value] Flesch Reading Ease: 36.5(9.1) v. 70.2(11.2), <0.0001; Gunning Fog: 15.8(1.7) v. 9.5(2.0), p < 0.0001; Flesch Grade Level: 12.8(1.2) v. 7.4(1.7), p < 0.0001; Coleman Liau: 13.7(2.1) v. 8.6(2.4), 0.0002; Smog index: 11.8(1.2) v. 6.7(1.8), <0.0001; Automated Readability Index: 13.1(1.4) v. 7.5(2.1), p < 0.0001). MTurk workers (n = 514) rated the layperson summaries as correct (89.5-95.7%) and correctly understood the content (63.0-87.4%). CONCLUSION: GPT shows promise for correct patient education for prostate cancer-related contents, but the technology is not designed for delivering patients information. Prompting the model to respond with accuracy, completeness, clarity and readability may enhance its utility when used for GPT-powered medical chatbots.

Open versus Robot-Assisted Radical Cystectomy for the Treatment of pT4a Bladder Cancer: Comparison of Perioperative Outcomes.

We compared the perioperative outcomes of open (ORC) vs. robot-assisted (RARC) radical cystectomy in the treatment of pT4a MIBC. In total, 212 patients underwent ORC (102 patients, Group A) vs. RARC (110 patients, Group B) for pT4a bladder cancer. Patients were prospectively followed and retrospectively reviewed. We assessed operative time, estimated blood loss (EBL), intraoperative and postoperative complications, length of stay, transfusion rate, and oncological outcomes. Preoperative features were comparable. The mean operative time was 232.8 vs. 189.2 min (p = 0.04), and mean EBL was 832.8 vs. 523.7 mL in Group A vs. B (p = 0.04). An intraoperative transfusion was performed in 32 (31.4%) vs. 11 (10.0%) cases during ORC vs. RARC (p = 0.03). The intraoperative complications rate was comparable. The mean length of stay was shorter after RARC (12.6 vs. 7.2 days, p = 0.02). Postoperative transfusions were performed in 36 (35.3%) vs. 13 (11.8%) cases (p = 0.03), and postoperative complications occurred in 37 (36.3%) vs. 29 (26.4%) patients in Groups A vs. B (p = 0.05). The positive surgical margin (PSM) rate was lower after RARC. No differences were recorded according to the oncological outcomes. ORC and RARC are feasible treatments for the management of pT4a bladder tumors. Minimally invasive surgery provides shorter operative time, bleeding, transfusion rate, postoperative complications, length of stay, and PSM rate.

Study protocol for the Intraoperative Complications Assessment and Reporting with Universal Standards (ICARUS) global cross-specialty surveys and consensus.

Annually, about 300 million surgeries lead to significant intraoperative adverse events (iAEs), impacting patients and surgeons. Their full extent is underestimated due to flawed assessment and reporting methods. Inconsistent adoption of new grading systems and a lack of standardization, along with litigation concerns, contribute to underreporting. Only half of relevant journals provide guidelines on reporting these events, with a lack of standards in surgical literature. To address these issues, the Intraoperative Complications Assessment and Reporting with Universal Standard (ICARUS) Global Surgical Collaboration was established in 2022. The initiative involves conducting global surveys and a Delphi consensus to understand the barriers for poor reporting of iAEs, validate shared criteria for reporting, define iAEs according to surgical procedures, evaluate the existing grading systems' reliability, and identify strategies for enhancing the collection, reporting, and management of iAEs. Invitation to participate are extended to all the surgical specialties, interventional cardiology, interventional radiology, OR Staffs and anesthesiology. This effort represents an essential step towards improved patient safety and the well-being of healthcare professionals in the surgical field.

Generative artificial intelligence in surgery.

Generative artificial intelligence is able to collect, extract, digest, and generate information in an understandable way for humans. As the first surgical applications of generative artificial intelligence are applied, this perspective paper aims to provide a comprehensive overview of current applications and future perspectives for the application of generative artificial intelligence in surgery, from preoperative planning to training. Generative artificial intelligence can be used before surgery for planning and decision support by extracting patient information and providing patients with information and simulation regarding the procedure. Intraoperatively, generative artificial intelligence can document data that is normally not captured as intraoperative adverse events or provide information to help decision-making. Postoperatively, GAIs can help with patient discharge and follow-up. The ability to provide real-time feedback and store it for later review is an important capability of GAIs. GAI applications are emerging as highly specialized, task-specific tools for tasks such as data extraction, synthesis, presentation, and communication within the realm of surgery. GAIs have the potential to play a pivotal role in facilitating interaction between surgeons and artificial intelligence.

ESRU-ESU-YAU_UROTECH Survey on Urology Residents Surgical Training: Are We Ready for Simulation and a Standardized Program?

Background: Currently, the landscape of surgical training is undergoing rapid evolution, marked by the initial implementation of standardized surgical training programs, which are further facilitated by the emergence of new technologies. However, this proliferation is uneven across various countries and hospitals. Objective: To offer a comprehensive overview of the existing surgical training programs throughout Europe, with a specific focus on the accessibility of simulation resources and standardized surgical programs. Design setting and participants: A dedicated survey was designed and spread in May 2022 via the European Association of Urology (EAU) mail list, to Young Urologist Office (YUO), Junior membership, European Urology Residents Education Program participants between 2014 and 2022, and other urologists under 40 yr, and via the EAU Newsletter. Intervention: A 64-item, online-based survey in accordance with the Checklist for Reporting Results of Internet E-Surveys (CHERRIES) using the platform of Survey Monkey (Portland, OR, USA) was realized. Outcome measurements and statistical analysis: The study involved an assessment of the demographic characteristics. Additionally, it explored the type of center, availability of various surgical approaches, presence of training infrastructure, participation in courses, organization of training, and participants' satisfaction with the training program. The level of satisfaction was evaluated using a Likert-5 scale. The subsequent sections delved into surgical training within the realms of open, laparoscopic, robotic, and endoscopic surgery, each explored separately. Finally, the investigation encompassed the presence of a structured training course and the availability of a duly validated final evaluation process. Results and limitations: There were 375 responders with a completion rate of 82%. Among them, 75% were identified as male, 50.6% were young urologists, 31.7% were senior residents, and 17.6% were junior residents. A significant majority of participants (69.6%) were affiliated with academic centers. Regarding the presence of dry lab training facilities, only 50.3% of respondents indicated its availability. Among these centers, 46.7% were primarily focused on laparoscopy training. The availability of virtual and wet lab training centers was even more limited, with rates of 31.5% and 16.2%, respectively. Direct patient involvement was reported in 80.5% of cases for open surgery, 58.8% for laparoscopy, 25.0% for robotics, and 78.6% for endourology. It is worth noting that in <25% of instances, training followed a well-defined standardized program comprising both preclinical and clinical modular phases. Finally, the analysis of participant feedback showed that 49.7% of respondents expressed a satisfaction rating of either 4 or 5 points with respect to the training program. The limitations of our study include the low response rate, predominance of participants from academic centers, and absence of responses from individuals not affiliated with the EAU network. Conclusions: The current distribution of surgical training centers falls short of ensuring widespread access to standardized training programs. Although dry lab facilities are relatively well spread, the availability of wet lab resources remains restricted. Additionally, it appears that many trainees' initial exposure to surgery occurs directly with patients. There is a pressing need for continued endeavors to establish uniform training routes and assessment techniques across various surgical methodologies. Patient summary: Nowadays, the surgical training landscape is heterogeneous across different countries. The implementation of a standardized training methodology to enhance the overall quality of surgical training and thereby improving patient outcomes is needed.

Publishers' and journals' instructions to authors on use of generative artificial intelligence in academic and scientific publishing: bibliometric analysis.

OBJECTIVES: To determine the extent and content of academic publishers' and scientific journals' guidance for authors on the use of generative artificial intelligence (GAI). DESIGN: Cross sectional, bibliometric study. SETTING: Websites of academic publishers and scientific journals, screened on 19-20 May 2023, with the search updated on 8-9 October 2023. PARTICIPANTS: Top 100 largest academic publishers and top 100 highly ranked scientific journals, regardless of subject, language, or country of origin. Publishers were identified by the total number of journals in their portfolio, and journals were identified through the Scimago journal rank using the Hirsch index (H index) as an indicator of journal productivity and impact. MAIN OUTCOME MEASURES: The primary outcomes were the content of GAI guidelines listed on the websites of the top 100 academic publishers and scientific journals, and the consistency of guidance between the publishers and their affiliated journals. RESULTS: Among the top 100 largest publishers, 24% provided guidance on the use of GAI, of which 15 (63%) were among the top 25 publishers. Among the top 100 highly ranked journals, 87% provided guidance on GAI. Of the publishers and journals with guidelines, the inclusion of GAI as an author was prohibited in 96% and 98%, respectively. Only one journal (1%) explicitly prohibited the use of GAI in the generation of a manuscript, and two (8%) publishers and 19 (22%) journals indicated that their guidelines exclusively applied to the writing process. When disclosing the use of GAI, 75% of publishers and 43% of journals included specific disclosure criteria. Where to disclose the use of GAI varied, including in the methods or acknowledgments, in the cover letter, or in a new section. Variability was also found in how to access GAI guidelines shared between journals and publishers. GAI guidelines in 12 journals directly conflicted with those developed by the publishers. The guidelines developed by top medical journals were broadly similar to those of academic journals. CONCLUSIONS: Guidelines by some top publishers and journals on the use of GAI by authors are lacking. Among those that provided guidelines, the allowable uses of GAI and how it should be disclosed varied substantially, with this heterogeneity persisting in some instances among affiliated publishers and journals. Lack of standardization places a burden on authors and could limit the effectiveness of the regulations. As GAI continues to grow in popularity, standardized guidelines to protect the integrity of scientific output are needed.

Biophotonics-Intraoperative Guidance During Partial Nephrectomy: A Systematic Review and Meta-analysis.

CONTEXT: Partial nephrectomy (PN) with intraoperative guidance by biophotonics has the potential to improve surgical outcomes due to higher precision. However, its value remains unclear since high-level evidence is lacking. OBJECTIVE: To provide a comprehensive analysis of biophotonic techniques used for intraoperative real-time assistance during PN. EVIDENCE ACQUISITION: We performed a comprehensive database search based on the PICO criteria, including studies published before October 2022. Two independent reviewers screened the titles and abstracts followed by full-text screening of eligible studies. For a quantitative analysis, a meta-analysis was conducted. EVIDENCE SYNTHESIS: In total, 35 studies were identified for the qualitative analysis, including 27 studies on near-infrared fluorescence (NIRF) imaging using indocyanine green, four studies on hyperspectral imaging, two studies on folate-targeted molecular imaging, and one study each on optical coherence tomography and 5-aminolevulinic acid. The meta-analysis investigated seven studies on selective arterial clamping using NIRF. There was a significantly shorter warm ischemia time in the NIRF-PN group (mean difference [MD]: -2.9; 95% confidence interval [CI]: -5.6, -0.1; p = 0.04). No differences were noted regarding transfusions (odds ratio [OR]: 0.5; 95% CI: 0.2, 1.7; p = 0.27), positive surgical margins (OR: 0.7; 95% CI: 0.2, 2.0; p = 0.46), or major complications (OR: 0.4; 95% CI: 0.1, 1.2; p = 0.08). In the NIRF-PN group, functional results were favorable at short-term follow-up (MD of glomerular filtration rate decline: 7.6; 95% CI: 4.6, 10.5; p < 0.01), but leveled off at long-term follow-up (MD: 7.0; 95% CI: -2.8, 16.9; p = 0.16). Remarkably, these findings were not confirmed by the included randomized controlled trial. CONCLUSIONS: Biophotonics comprises a heterogeneous group of imaging modalities that serve intraoperative decision-making and guidance. Implementation into clinical practice and cost effectiveness are the limitations that should be addressed by future research. PATIENT SUMMARY: We reviewed the application of biophotonics during partial removal of the kidney in patients with kidney cancer. Our results suggest that these techniques support the surgeon in successfully performing the challenging steps of the procedure.

Artificial intelligence and urology: ethical considerations for urologists and patients.

The use of artificial intelligence (AI) in medicine and in urology specifically has increased over the past few years, during which time it has enabled optimization of patient workflow, increased diagnostic accuracy and enhanced computer analysis of radiological and pathological images. However, before further use of AI is undertaken, possible ethical issues need to be evaluated to improve understanding of this technology and to protect patients and providers. Possible ethical issues that require consideration when applying AI in clinical practice include patient safety, cybersecurity, transparency and interpretability of the data, inclusivity and equity, fostering responsibility and accountability, and the preservation of providers' decision-making and autonomy. Ethical principles for the application of AI to health care and in urology are proposed to guide urologists, patients and regulators to improve use of AI technologies and guide policy-making.

Quality of information and appropriateness of ChatGPT outputs for urology patients.

BACKGROUND: The proportion of health-related searches on the internet is continuously growing. ChatGPT, a natural language processing (NLP) tool created by OpenAI, has been gaining increasing user attention and can potentially be used as a source for obtaining information related to health concerns. This study aims to analyze the quality and appropriateness of ChatGPT's responses to Urology case studies compared to those of a urologist. METHODS: Data from 100 patient case studies, comprising patient demographics, medical history, and urologic complaints, were sequentially inputted into ChatGPT, one by one. A question was posed to determine the most likely diagnosis, suggested examinations, and treatment options. The responses generated by ChatGPT were then compared to those provided by a board-certified urologist who was blinded to ChatGPT's responses and graded on a 5-point Likert scale based on accuracy, comprehensiveness, and clarity as criterias for appropriateness. The quality of information was graded based on the section 2 of the DISCERN tool and readability assessments were performed using the Flesch Reading Ease (FRE) and Flesch-Kincaid Reading Grade Level (FKGL) formulas. RESULTS: 52% of all responses were deemed appropriate. ChatGPT provided more appropriate responses for non-oncology conditions (58.5%) compared to oncology (52.6%) and emergency urology cases (11.1%) (p = 0.03). The median score of the DISCERN tool was 15 (IQR = 5.3) corresponding to a quality score of poor. The ChatGPT responses demonstrated a college graduate reading level, as indicated by the median FRE score of 18 (IQR = 21) and the median FKGL score of 15.8 (IQR = 3). CONCLUSIONS: ChatGPT serves as an interactive tool for providing medical information online, offering the possibility of enhancing health outcomes and patient satisfaction. Nevertheless, the insufficient appropriateness and poor quality of the responses on Urology cases emphasizes the importance of thorough evaluation and use of NLP-generated outputs when addressing health-related concerns.

A nomogram to predict the absence of clinically significant prostate cancer in males with negative MRI

PURPOSE: To create a nomogram to predict the absence of clinically significant prostate cancer (CSPCa) in males with non-suspicion multiparametric magnetic resonance imaging (mpMRI) undergoing prostate biopsy (PBx). MATERIALS AND METHODS: We identified consecutive patients who underwent 3T mpMRI followed by PBx for suspicion of PCa or surveillance follow-up. All patients had Prostate Imaging Reporting and Data System score 1-2 (negative mpMRI). CSPCa was defined as Grade Group ≥2. Multivariate logistic regression analysis was performed via backward elimination. Discrimination was evaluated with area under the receiver operating characteristic (AUROC). Internal validation with 1,000x bootstrapping for estimating the optimism corrected AUROC. RESULTS: Total 327 patients met inclusion criteria. The median (IQR) age and PSA density (PSAD) were 64 years (58-70) and 0.10 ng/mL2 (0.07-0.15), respectively. Biopsy history was as follows: 117 (36%) males were PBx-naive, 130 (40%) had previous negative PBx and 80 (24%) had previous positive PBx. The majority were White (65%); 6% of males self-reported Black. Overall, 44 (13%) patients were diagnosed with CSPCa on PBx. Black race, history of previous negative PBx and PSAD ≥0.15ng/mL2 were independent predictors for CSPCa on PBx and were included in the nomogram. The AUROC of the nomogram was 0.78 and the optimism corrected AUROC was 0.75. CONCLUSIONS: Our nomogram facilitates evaluating individual probability of CSPCa on PBx in males with PIRADS 1-2 mpMRI and may be used to identify those in whom PBx may be safely avoided. Black males have increased risk of CSPCa on PBx, even in the setting of PIRADS 1-2 mpMRI.

Awareness and Use of ChatGPT and Large Language Models: A Prospective Cross-sectional Global Survey in Urology.

BACKGROUND: Since its release in November 2022, ChatGPT has captivated society and shown potential for various aspects of health care. OBJECTIVE: To investigate potential use of ChatGPT, a large language model (LLM), in urology by gathering opinions from urologists worldwide. DESIGN, SETTING, AND PARTICIPANTS: An open web-based survey was distributed via social media and e-mail chains to urologists between April 20, 2023 and May 5, 2023. Participants were asked to answer questions related to their knowledge and experience with artificial intelligence, as well as their opinions of potential use of ChatGPT/LLMs in research and clinical practice. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Data are reported as the mean and standard deviation for continuous variables, and the frequency and percentage for categorical variables. Charts and tables are used as appropriate, with descriptions of the chart types and the measures used. The data are reported in accordance with the Checklist for Reporting Results of Internet E-Surveys (CHERRIES). RESULTS AND LIMITATIONS: A total of 456 individuals completed the survey (64% completion rate). Nearly half (47.7%) reported that they use ChatGPT/LLMs in their academic practice, with fewer using the technology in clinical practice (19.8%). More than half (62.2%) believe there are potential ethical concerns when using ChatGPT for scientific or academic writing, and 53% reported that they have experienced limitations when using ChatGPT in academic practice. CONCLUSIONS: Urologists recognise the potential of ChatGPT/LLMs in research but have concerns regarding ethics and patient acceptance. There is a desire for regulations and guidelines to ensure appropriate use. In addition, measures should be taken to establish rules and guidelines to maximise safety and efficiency when using this novel technology. PATIENT SUMMARY: A survey asked 456 urologists from around the world about using an artificial intelligence tool called ChatGPT in their work. Almost half of them use ChatGPT for research, but not many use it for patients care. The resonders think ChatGPT could be helpful, but they worry about problems like ethics and want rules to make sure it's used safely.

Gender disparities among publications within international sexual medicine urology journals and the impact of blinding in the review process.

BACKGROUND: While female urologists are known to publish at less frequency than their male peers, The Journal of Sexual Medicine was reported to have among the highest growth in female authorship from 2002 to 2020 in urology journals. AIM: We sought to assess the frequency of female authorship in sexual medicine journals worldwide and the factors that affect this, including the blinded/unblinded review process. METHODS: Eleven sexual medicine journals were assessed for geographic location, peer review method, and SCImago Journal Rank citation index (a metric of citation frequency and prestige). Journals were grouped into top, middle, and bottom quartiles based on metric score. Web of Science was used to access the publications' first, second, last, and corresponding authors from the past 5 years. An internet search or Gender-API.com was used to determine the gender identities of authors. Univariate and multivariable logistic regression models were performed. OUTCOMES: Outcomes included the likelihood of female authorship (first, second, last, and corresponding) based on journal location and ranking, the clustering of female authors, the journal's peer review process, and the frequency of female editorial board members. RESULTS: Overall, 8938 publications were identified. Women represented 30.7%, 31.3%, 21.3%, and 18.7% of the first, second, last, and corresponding authors, respectively; gender was unable to be assessed for 2.6%, 17.2%, 7.3%, and 2.7%. On univariate analysis, journals from North America, in the top quartile, and with a double-blind review process were more likely to have female authors (P < .001). On multivariate analysis, articles were more likely to have a female first author if they had a double-blind peer review process (odds ratio [OR], 1.20; 95% CI, 1.02-1.40), a female second author (OR, 2.54; 95% CI, 2.26-2.85), or a female corresponding author (OR, 7.80; 95% CI, 6.69-9.10). CLINICAL IMPLICATIONS: Gender-concordant mentoring and universal double-blind manuscript review processes may minimize the impact of gender bias and increase female authorship rates, in turn producing more diverse research. STRENGTHS AND LIMITATIONS: This is the first study assessing female authorship in sexual medicine journals. Limitations include not assessing every author listed on articles and being unable to determine gender identities for some authors. CONCLUSION: Female authorship rates are higher than reported rates of practicing female urologists but still lower than their male peers. Female authors were more likely to be published in journals with double-blind peer review processes and when publishing with additional female authors.

A new era and future of education: the impact of pandemic on online learning - a study from the European School of Urology.

Introduction: In contemporary times, the online learning process has become indispensable for healthcare education. In this direction, the European School of Urology (ESU) has taken the challenge to implement new technologies to bring down knowledge barriers. Web-based seminars (webinars) are one of the tools that help us move towards such inclusivity, and in front-facing COVID-19 pandemic, when face-to-face meetings were forbidden. Material and methods: Data from ESU webinars was collected from 2016 to 2022. We described the trends through years of: a) number of webinars per year; b) number of oncological versus non-oncological webinars per year; c) number of registrations per year; d) attendance rate; e) YouTube visualisations. We also analysed audience demographics and COVID-19 impact. Results: We found a 60% increase in webinars launched per year with a trend towards more non-oncological webinars. A 94% rise in the number of registrations and an 85% increase in the attendance ratio from 2016 to 2022 was observed. The mean YouTube visualisations per webinar decreased over 200%. Among registrations, we had a 3:1 male: female ratio, 53% were older than 40, and a 51% were of European precedence. COVID-19 positively impacted webinars with a remarkable increase on the amount of webinars launched, number of registrations and attendance ratio. Conclusions: Webinars are a powerful tool to spread healthcare knowledge, bridging the gap in medical educational access. COVID-19 was a determinant that reinforced its implantation, but our data show that this new learning tool had a positive uptake, and has come to stay.

Framework for a living systematic review and meta-analysis for the surgical treatment of bladder cancer: introducing EVIglance to urology.

Background: Knowledge of current and ongoing studies is critical for identifying research gaps and enabling evidence-based decisions for individualized treatment. However, the increasing number of scientific publications poses challenges for healthcare providers and patients in all medical fields to stay updated with the latest evidence. To overcome these barriers, we aim to develop a living systematic review and open-access online evidence map of surgical therapy for bladder cancer (BC), including meta-analyses. Methods: Following the guidelines provided in the Cochrane Handbook for Systematic Reviews of Interventions and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Statement, a systematic literature search on uro-oncological therapy in BC will be performed across various literature databases. Within the scope of a meta-analysis and living systematic review, relevant randomized controlled trials will be identified. Data extraction and quantitative analysis will be conducted, along with a critical appraisal of the quality and risk of bias of each study. The available research evidence will be entered into an open-access framework (www.evidencemap.surgery) and will also be accessible via the EVIglance app. Regular semi-automatic updates will enable the implementation of a real-living review concept and facilitate resource-efficient screening. Discussion: A regularly updated evidence map provides professionals and patients with an open-access knowledge base on the current state of research, allowing for decision-making based on recent evidence. It will help identify an oversupply of evidence, thus avoiding redundant work. Furthermore, by identifying research gaps, new hypotheses can be formulated more precisely, enabling planning, determination of sample size, and definition of endpoints for future trials.