Complications and adverse events in lymphadenectomy of the inguinal area: worldwide expert consensus.

BACKGROUND: Inguinal lymph node dissection plays an important role in the management of melanoma, penile and vulval cancer. Inguinal lymph node dissection is associated with various intraoperative and postoperative complications with significant heterogeneity in classification and reporting. This lack of standardization challenges efforts to study and report inguinal lymph node dissection outcomes. The aim of this study was to devise a system to standardize the classification and reporting of inguinal lymph node dissection perioperative complications by creating a worldwide collaborative, the complications and adverse events in lymphadenectomy of the inguinal area (CALI) group. METHODS: A modified 3-round Delphi consensus approach surveyed a worldwide group of experts in inguinal lymph node dissection for melanoma, penile and vulval cancer. The group of experts included general surgeons, urologists and oncologists (gynaecological and surgical). The survey assessed expert agreement on inguinal lymph node dissection perioperative complications. Panel interrater agreement and consistency were assessed as the overall percentage agreement and Cronbach's α. RESULTS: Forty-seven experienced consultants were enrolled: 26 (55.3%) urologists, 11 (23.4%) surgical oncologists, 6 (12.8%) general surgeons and 4 (8.5%) gynaecology oncologists. Based on their expertise, 31 (66%), 10 (21.3%) and 22 (46.8%) of the participants treat penile cancer, vulval cancer and melanoma using inguinal lymph node dissection respectively; 89.4% (42 of 47) agreed with the definitions and inclusion as part of the inguinal lymph node dissection intraoperative complication group, while 93.6% (44 of 47) agreed that postoperative complications should be subclassified into five macrocategories. Unanimous agreement (100%, 37 of 37) was achieved with the final standardized classification system for reporting inguinal lymph node dissection complications in melanoma, vulval cancer and penile cancer. CONCLUSION: The complications and adverse events in lymphadenectomy of the inguinal area classification system has been developed as a tool to standardize the assessment and reporting of complications during inguinal lymph node dissection for the treatment of melanoma, vulval and penile cancer.

Readability Assessment of Patient Education Materials on Uro-oncological Diseases Using Automated Measures.

BACKGROUND AND OBJECTIVE: Readability of patient education materials is of utmost importance to ensure understandability and dissemination of health care information in uro-oncology. We aimed to investigate the readability of the official patient education materials of the European Association of Urology (EAU) and American Urology Association (AUA). METHODS: Patient education materials for prostate, bladder, kidney, testicular, penile, and urethral cancers were retrieved from the respective organizations. Readability was assessed via the WebFX online tool for Flesch Kincaid Reading Ease Score (FRES) and for reading grade levels by Flesch Kincaid Grade Level (FKGL), Gunning Fog Score (GFS), Smog Index (SI), Coleman Liau Index (CLI), and Automated Readability Index (ARI). Layperson readability was defined as a FRES of ≥70 and with the other readability indexes <7 according to European Union recommendations. This study assessed only objective readability and no other metrics such as understandability. KEY FINDINGS AND LIMITATIONS: Most patient education materials failed to meet the recommended threshold for laypersons. The mean readability for EAU patient education material was as follows: FRES 50.9 (standard error [SE]: 3.0), and FKGL, GFS, SI, CLI, and ARI all with scores ≥7. The mean readability for AUA patient material was as follows: FRES 64.0 (SE: 1.4), with all of FKGL, GFS, SI, and ARI scoring ≥7 readability. Only 13 out of 70 (18.6%) patient education materials' paragraphs met the readability requirements. The mean readability for bladder cancer patient education materials was the lowest, with a FRES of 36.7 (SE: 4.1). CONCLUSIONS AND CLINICAL IMPLICATIONS: Patient education materials from leading urological associations reveal readability levels beyond the recommended thresholds for laypersons and may not be understood easily by patients. There is a future need for more patient-friendly reading materials. PATIENT SUMMARY: This study checked whether health information about different cancers was easy to read. Most of it was too hard for patients to understand.

PCa-RadHop: A transparent and lightweight feed-forward method for clinically significant prostate cancer segmentation.

Prostate Cancer is one of the most frequently occurring cancers in men, with a low survival rate if not early diagnosed. PI-RADS reading has a high false positive rate, thus increasing the diagnostic incurred costs and patient discomfort. Deep learning (DL) models achieve a high segmentation performance, although require a large model size and complexity. Also, DL models lack of feature interpretability and are perceived as "black-boxes" in the medical field. PCa-RadHop pipeline is proposed in this work, aiming to provide a more transparent feature extraction process using a linear model. It adopts the recently introduced Green Learning (GL) paradigm, which offers a small model size and low complexity. PCa-RadHop consists of two stages: Stage-1 extracts data-driven radiomics features from the bi-parametric Magnetic Resonance Imaging (bp-MRI) input and predicts an initial heatmap. To reduce the false positive rate, a subsequent stage-2 is introduced to refine the predictions by including more contextual information and radiomics features from each already detected Region of Interest (ROI). Experiments on the largest publicly available dataset, PI-CAI, show a competitive performance standing of the proposed method among other deep DL models, achieving an area under the curve (AUC) of 0.807 among a cohort of 1,000 patients. Moreover, PCa-RadHop maintains orders of magnitude smaller model size and complexity.

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

ABSTRACT 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

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.

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.

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.

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.

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.

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.

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.

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.