Background: ChatGPT is a 175-billion-parameter natural language processing model that is already involved in scientific content and publications. Its influence ranges from providing quick access to information on medical topics, assisting in generating medical and scientific articles and papers, performing medical data analyses, and even interpreting complex data sets.Objective: The future role of ChatGPT remains uncertain and a matter of debate already shortly after its release. This review aimed to analyze the role of ChatGPT in the medical literature during the first 3 months after its release.Methods: We performed a concise review of literature published in PubMed from December 1, 2022, to March 31, 2023. To find all publications related to ChatGPT or considering ChatGPT, the search term was kept simple (“ChatGPT” in AllFields). All publications available as full text in German or English were included. All accessible publications were evaluated according to specifications by the author team (eg, impact factor, publication modus, article type, publication speed, and type of ChatGPT integration or content). The conclusions of the articles were used for later SWOT (strengths, weaknesses, opportunities, and threats) analysis. All data were analyzed on a descriptive basis.Results: Of 178 studies in total, 160 met the inclusion criteria and were evaluated. The average impact factor was 4.423 (range 0-96.216), and the average publication speed was 16 (range 0-83) days. Among the articles, there were 77 editorials (48,1%), 43 essays (26.9%), 21 studies (13.1%), 6 reviews (3.8%), 6 case reports (3.8%), 6 news (3.8%), and 1 meta-analysis (0.6%). Of those, 54.4% (n=87) were published as open access, with 5% (n=8) provided on preprint servers. Over 400 quotes with information on strengths, weaknesses, opportunities, and threats were detected. By far, most (n=142, 34.8%) were related to weaknesses. ChatGPT excels in its ability to express ideas clearly and formulate general contexts comprehensibly. It performs so well that even experts in the field have difficulty identifying abstracts generated by ChatGPT. However, the time-limited scope and the need for corrections by experts were mentioned as weaknesses and threats of ChatGPT. Opportunities include assistance in formulating medical issues for nonnative English speakers, as well as the possibility of timely participation in the development of such artificial intelligence tools since it is in its early stages and can therefore still be influenced.Conclusions: Artificial intelligence tools such as ChatGPT are already part of the medical publishing landscape. Despite their apparent opportunities, policies and guidelines must be implemented to ensure benefits in education, clinical practice, and research and protect against threats such as scientific misconduct, plagiarism, and inaccuracy.

Background: The increasing development and spread of artificial and assistive intelligence is opening up new areas of application not only in applied medicine but also in related fields such as continuing medical education (CME), which is part of the mandatory training program for medical doctors in Germany. This study aimed to determine whether medical laypersons can successfully conduct training courses specifically for physicians with the help of a large language model (LLM) such as ChatGPT-4. This study aims to qualitatively and quantitatively investigate the impact of using artificial intelligence (AI; specifically ChatGPT) on the acquisition of credit points in German postgraduate medical education. Objective: Using this approach, we wanted to test further possible applications of AI in the postgraduate medical education setting and obtain results for practical use. Depending on the results, the potential influence of LLMs such as ChatGPT-4 on CME will be discussed, for example, as part of a SWOT (strengths, weaknesses, opportunities, threats) analysis. Methods: We designed a randomized controlled trial, in which adult high school students attempt to solve CME tests across six medical specialties in three study arms in total with 18 CME training courses per study arm under different interventional conditions with varying amounts of permitted use of ChatGPT-4. Sample size calculation was performed including guess probability (20% correct answers, SD=40%; confidence level of 1–α=.95/α=.05; test power of 1–β=.95; P<.05). The study was registered at open scientific framework. Results: As of October 2024, the acquisition of data and students to participate in the trial is ongoing. Upon analysis of our acquired data, we predict our findings to be ready for publication as soon as early 2025. Conclusions: We aim to prove that the advances in AI, especially LLMs such as ChatGPT-4 have considerable effects on medical laypersons’ ability to successfully pass CME tests. The implications that this holds on how the concept of continuous medical education requires reevaluation are yet to be contemplated. Trial Registration: OSF Registries 10.17605/OSF.IO/MZNUF; https://osf.io/mznuf International Registered Report Identifier (IRRID): PRR1-10.2196/63887

Background ChatGPT (Chat Generative Pre-trained Transformer) has initiated widespread conversation across various human sciences. We here performed a concise review combined with a SWOT (strengths, weaknesses, opportunities, threats) analysis on ChatGPT potentials in natural science including medicine. Methods This is a concise review of literature published in PUBMED from 01.12.2022 to 31.03.2023. The only search term used was “ChatGPT”. Publications metrics (author, journal, and subdisciplines thereof) as well as findings of the SWOT analysis are presented. Findings Of 178 studies in total, 160 could be evaluated. The average impact factor was 4,423 (0 – 96,216), average publication speed was 16 days (0-83 days). Of all articles, there were 77 editorials, 43 essays, 21 studies, six reviews, six case reports, six news, and one meta-analyses. Strengths of ChatGPT include well-formulated expression as well as the ability to formulate general contexts flawlessly and comprehensibly, whereas the time-limited scope as well as the need for correction by experts were identified as weaknesses and threats. Opportunities include assistance in formulating medical issues for non-native speakers as well as the chance to be involved in the development of such AI in a timely manner. Interpretation Artificial intelligences such as ChatGPT will revolutionize more than just the medical publishing landscape. One of the biggest dangers in this is uncontrolled use, so we would do well to establish control and security measures at an early stage. Evidence before this study Since its release in 11/ 2022, only a few randomized controlled trials using ChatGPT have been published. To date, the majority of data stems from short notes or communication. Given the enormous interest (and also potential for misuse), we conducted a PUBMED literature search to create the most comprehensive evidence base currently available. We searched PUBMED for publications including the quote “ChatGPT” in English or German from 01.12.2022 until 31.03.2023. In order not risk any bias of evidence all related publications were screened initially. Added value of this study This is the most concise review for ChatGPT up to date. By means of a SWOT analysis, readers and researchers gain comprehensive insight to strengths, weaknesses, opportunities and threats of ChatGPT especially in the context of medical literature. Implications of all the available evidence Our review may well serve as origin for further research related to the topic in order to create more evidence, strict regulations and policies in dealing with ChatGPT.

Lymph node metastases are common in pelvic urological tumors, and the age-related remodeling process of the pelvic lymph nodes influences metastatic behavior. The aim of this work is to characterize age-related degenerative changes in the pelvic lymph nodes with respect to their occurrence and extent. A total of 5173 pelvic lymph nodes of 390 patients aged 44 to 79 years (median 68 years, IQR 62–71 years) were histologically examined for degenerative structural changes. Lymph node size, lipomatous atrophy, capsular fibrosis, framework fibrosis, and calcifications were recorded semi-quantitatively and evaluated by age group. Significantly more lymph nodes <10 mm were found in older patients (p = 0.001). The incidence of framework fibrosis, capsular fibrosis, and calcifications increased significantly with increasing patient age (p < 0.001). In lipomatous atrophy, an increase in mild to moderate lipomatous atrophy was observed with increasing age (p < 0.001). In this, the largest study to date on this topic, age-related degenerative changes in pelvic lymph nodes were proven. Due to the consecutive decrease in hte filtration function of pelvic lymph nodes with increasing age, staging and therapy of metastatic pelvic urologic carcinomas should be reconsidered.

(1) Background: Injuries related to resuscitation are not usually systematically recorded and documented. By evaluating this data, conclusions could be drawn about the quality of the resuscitation, with the aim of improving patient care and safety. (2) Methods: We are planning to conduct a multicentric, retrospective 3-phased study consisting of (1) a worldwide literature review (scoping review), (2) an analysis of anatomical pathological findings from local institutions in North Rhine-Westphalia, Germany to assess the transferability of the review data to the German healthcare system, and (3) depending on the results, possibly establishing potential prospective indicators for resuscitation-related injuries as part of quality assurance measures. (3) Conclusions: From the comparison of literature and local data, the picture of resuscitation-related injuries will be focused on and quality indicators will be derived.

To evaluate the incidence of lymph node degeneration and its association with nodal metastatic pattern in prostate cancer. A retrospective analysis of the submitted lymph node specimen of 390 prostatectomies in 2011 was performed. All lymph nodes were histologically re-evaluated and the degree of lymph node degeneration e.g. lipomatous atrophy, capsular and framework fibrosis, and calcifications as well as the lymph node size were recorded. Lymph node degeneration was compared in the anatomic regions of the pelvis as well as in lymph nodes with and without metastases of prostatic cancer. Eighty-one of 6026 lymph nodes demonstrated metastases. Complete histologic examination with analysis of a complete cross-section was possible in 5173 lymph nodes including all lymph nodes with metastases. The incidence of lymph node degeneration was different across the various landing sites. Lymph node metastases were primarily detected in less degenerative and therefore more functional lymph nodes. In metastatic versus non-metastatic lymph nodes low lipomatous atrophy was reported in 84.0% versus 66.7% (p = 0.004), capsular fibrosis in 14.8% versus 35.4% (p < 0.001), calcifications in 35.8% versus 46.1% (p = 0.072) and framework fibrosis in 69.8% versus 75.3% (p = 0.53). Metastases were also identified more frequently in larger than in smaller lymph nodes (63.0% vs. 47.5%; p = 0.007). Degenerative changes in pelvic lymph nodes are commonly detectable but occur with variable frequency in the various nodal landing sites in the pelvis. The degree of lymph node degeneration of single lymph nodes has a significant influence on whether a lymph node is infiltrated by tumor cells and may harbour metastases.