Garcia-Valencia, Oscar

Patients with chronic kidney disease (CKD) necessitate specialized renal diets to prevent complications such as hyperkalemia and hyperphosphatemia. A comprehensive assessment of food components is pivotal, yet burdensome for healthcare providers. With evolving artificial intelligence (AI) technology, models such as ChatGPT, Bard AI, and Bing Chat can be instrumental in educating patients and assisting professionals. To gauge the efficacy of different AI models in discerning potassium and phosphorus content in foods, four AI models—ChatGPT 3.5, ChatGPT 4, Bard AI, and Bing Chat—were evaluated. A total of 240 food items, curated from the Mayo Clinic Renal Diet Handbook for CKD patients, were input into each model. These items were characterized by their potassium (149 items) and phosphorus (91 items) content. Each model was tasked to categorize the items into high or low potassium and high phosphorus content. The results were juxtaposed with the Mayo Clinic Renal Diet Handbook’s recommendations. The concordance between repeated sessions was also evaluated to assess model consistency. Among the models tested, ChatGPT 4 displayed superior performance in identifying potassium content, correctly classifying 81% of the foods. It accurately discerned 60% of low potassium and 99% of high potassium foods. In comparison, ChatGPT 3.5 exhibited a 66% accuracy rate. Bard AI and Bing Chat models had an accuracy rate of 79% and 81%, respectively. Regarding phosphorus content, Bard AI stood out with a flawless 100% accuracy rate. ChatGPT 3.5 and Bing Chat recognized 85% and 89% of the high phosphorus foods correctly, while ChatGPT 4 registered a 77% accuracy rate. Emerging AI models manifest a diverse range of accuracy in discerning potassium and phosphorus content in foods suitable for CKD patients. ChatGPT 4, in particular, showed a marked improvement over its predecessor, especially in detecting potassium content. The Bard AI model exhibited exceptional precision for phosphorus identification. This study underscores the potential of AI models as efficient tools in renal dietary planning, though refinements are warranted for optimal utility.

Kidney transplantation is a critical treatment option for end-stage kidney disease patients, offering improved quality of life and increased survival rates. However, the complexities of kidney transplant care necessitate continuous advancements in decision making, patient communication, and operational efficiency. This article explores the potential integration of a sophisticated chatbot, an AI-powered conversational agent, to enhance kidney transplant practice and potentially improve patient outcomes. Chatbots and generative AI have shown promising applications in various domains, including healthcare, by simulating human-like interactions and generating contextually appropriate responses. Noteworthy AI models like ChatGPT by OpenAI, BingChat by Microsoft, and Bard AI by Google exhibit significant potential in supporting evidence-based research and healthcare decision making. The integration of chatbots in kidney transplant care may offer transformative possibilities. As a clinical decision support tool, it could provide healthcare professionals with real-time access to medical literature and guidelines, potentially enabling informed decision making and improved knowledge dissemination. Additionally, the chatbot has the potential to facilitate patient education by offering personalized and understandable information, addressing queries, and providing guidance on post-transplant care. Furthermore, under clinician or transplant pharmacist supervision, it has the potential to support post-transplant care and medication management by analyzing patient data, which may lead to tailored recommendations on dosages, monitoring schedules, and potential drug interactions. However, to fully ascertain its effectiveness and safety in these roles, further studies and validation are required. Its integration with existing clinical decision support systems may enhance risk stratification and treatment planning, contributing to more informed and efficient decision making in kidney transplant care. Given the importance of ethical considerations and bias mitigation in AI integration, future studies may evaluate long-term patient outcomes, cost-effectiveness, user experience, and the generalizability of chatbot recommendations. By addressing these factors and potentially leveraging AI capabilities, the integration of chatbots in kidney transplant care holds promise for potentially improving patient outcomes, enhancing decision making, and fostering the equitable and responsible use of AI in healthcare.

This comprehensive critical review critically examines the ethical implications associated with integrating chatbots into nephrology, aiming to identify concerns, propose policies, and offer potential solutions. Acknowledging the transformative potential of chatbots in healthcare, responsible implementation guided by ethical considerations is of the utmost importance. The review underscores the significance of establishing robust guidelines for data collection, storage, and sharing to safeguard privacy and ensure data security. Future research should prioritize defining appropriate levels of data access, exploring anonymization techniques, and implementing encryption methods. Transparent data usage practices and obtaining informed consent are fundamental ethical considerations. Effective security measures, including encryption technologies and secure data transmission protocols, are indispensable for maintaining the confidentiality and integrity of patient data. To address potential biases and discrimination, the review suggests regular algorithm reviews, diversity strategies, and ongoing monitoring. Enhancing the clarity of chatbot capabilities, developing user-friendly interfaces, and establishing explicit consent procedures are essential for informed consent. Striking a balance between automation and human intervention is vital to preserve the doctor–patient relationship. Cultural sensitivity and multilingual support should be considered through chatbot training. To ensure ethical chatbot utilization in nephrology, it is imperative to prioritize the development of comprehensive ethical frameworks encompassing data handling, security, bias mitigation, informed consent, and collaboration. Continuous research and innovation in this field are crucial for maximizing the potential of chatbot technology and ultimately improving patient outcomes.

Literature reviews are valuable for summarizing and evaluating the available evidence in various medical fields, including nephrology. However, identifying and exploring the potential sources requires focus and time devoted to literature searching for clinicians and researchers. ChatGPT is a novel artificial intelligence (AI) large language model (LLM) renowned for its exceptional ability to generate human-like responses across various tasks. However, whether ChatGPT can effectively assist medical professionals in identifying relevant literature is unclear. Therefore, this study aimed to assess the effectiveness of ChatGPT in identifying references to literature reviews in nephrology. We keyed the prompt “Please provide the references in Vancouver style and their links in recent literature on… name of the topic” into ChatGPT-3.5 (03/23 Version). We selected all the results provided by ChatGPT and assessed them for existence, relevance, and author/link correctness. We recorded each resource’s citations, authors, title, journal name, publication year, digital object identifier (DOI), and link. The relevance and correctness of each resource were verified by searching on Google Scholar. Of the total 610 references in the nephrology literature, only 378 (62%) of the references provided by ChatGPT existed, while 31% were fabricated, and 7% of citations were incomplete references. Notably, only 122 (20%) of references were authentic. Additionally, 256 (68%) of the links in the references were found to be incorrect, and the DOI was inaccurate in 206 (54%) of the references. Moreover, among those with a link provided, the link was correct in only 20% of cases, and 3% of the references were irrelevant. Notably, an analysis of specific topics in electrolyte, hemodialysis, and kidney stones found that >60% of the references were inaccurate or misleading, with less reliable authorship and links provided by ChatGPT. Based on our findings, the use of ChatGPT as a sole resource for identifying references to literature reviews in nephrology is not recommended. Future studies could explore ways to improve AI language models’ performance in identifying relevant nephrology literature.

Reports highlighting the problems with the standard practice of using bar graphs to show continuous data have prompted many journals to adopt new visualization policies. These policies encourage authors to avoid bar graphs and use graphics that show the data distribution; however, they provide little guidance on how to effectively display data. We conducted a systematic review of studies published in top peripheral vascular disease journals to determine what types of figures are used, and to assess the prevalence of suboptimal data visualization practices. Among papers with data figures, 47.7% of papers used bar graphs to present continuous data. This primer provides a detailed overview of strategies for addressing this issue by (1) outlining strategies for selecting the correct type of figure depending on the study design, sample size, and the type of variable; (2) examining techniques for making effective dot plots, box plots, and violin plots; and (3) illustrating how to avoid sending mixed messages by aligning the figure structure with the study design and statistical analysis. We also present solutions to other common problems identified in the systematic review. Resources include a list of free tools and templates that authors can use to create more informative figures and an online simulator that illustrates why summary statistics are meaningful only when there are enough data to summarize. Last, we consider steps that investigators can take to improve figures in the scientific literature.

INTRODUCTION: Over-the-scope clips (OTSC) are used for closure of fistulas, leaks, and acute perforations, and for GI bleeding. Adverse events include perforation, migration, and ulceration. Little is know about the natural history of OTSCs and no data addressing the longevity of clips is available. We present an interim analysis of our center’s experience with OTSC focusing on natural history. METHODS: OTSCs used from 1/1/2011 to 1/1/2019 were compiled and retrospective chart review undertaken. Primary endpoint was clip retention time (time when the clip was placed to time the clip was last seen or was physically removed). Secondary endpoints were rate of complications and factors that influence clip retention time and clinical success. Cox proportional hazards were used to evaluate variables impacting clip retention. Univariate regression was used to assess potential risk factors for adverse events. RESULTS: A total of 358 OTSC were placed in 299 patients (55.8% male, n = 184) with mean age 64 + 15.3 years. Procedures and indications presented in Table 1. Clip placement was clinically successful in 81% of cases (N = 265). Median time to clip loss as assessed by Kaplan-Meier curve was 267 days (95% CI 196-406) (Figure 1). Adverse events occurred in 34 clip placements (10.7%) and included bleeding (n = 8, 24.2%), perforation (n = 5, 15.2%), ulceration (n = 3, 9.1%), migration (n = 15, 45.5%), and infection (n = 1, 3.0%). Univariate analysis (Table 2) revealed that age, gender, type of clip used (there are 3 types of OTSC), and performing endoscopist did not impact clip retention rate. A size 14 clip had marginally higher rates of retention compared to others. Clips placed in the rectum or esophagus were lost earlier compared to those in the small/large intestine and stomach. Clips placed for fistulas and those associated with adverse event were associated with earlier clip loss. In evaluation of clinical success, clips placed for fistulas had a relative risk of clinical failure of 2.08 (95% CI 1.29-3.36) compared to all other indications. CONCLUSION: OTSCs are retained for a median of 8.9 months with clip location and indication for placement being key factors in time to clip loss. Clips used for fistula closure were more likely to be lost compared to those placed for other indications, less likely to be clinically successful, and more likely to cause a complication. These data help guide decision-making when considering OTSC use across clinical indications.

Background The endothelial glycocalyx is a vasoprotective barrier between the blood and endothelium. We hypothesized that glycocalyx degradation is present in preeclampsia, a pregnancy‐specific hypertensive disorder characterized by endothelial dysfunction and activation. Methods and Results We examined the sublingual glycocalyx noninvasively using sidestream dark field imaging in the third trimester among women with normotensive pregnancies (n=73), early (n=14) or late (n=29) onset preeclampsia, or gestational diabetes mellitus (n=21). We calculated the width of the glycocalyx that was permeable to red blood cells (called the perfused boundary region , a measure of glycocalyx degradation) and the percentage of vessels that were filled with red blood cells ≥50% of the time (a measure of microvascular perfusion). In addition, we measured circulating levels of glycocalyx components, including heparan sulfate proteoglycans, hyaluronic acid, and SDC1 (syndecan 1), in a subset of participants by ELISA . Repeated‐measures ANOVA was performed to adjust for vessel diameter and caffeine intake. Women with early onset preeclampsia showed higher glycocalyx degradation, indicated by a larger perfused boundary region (mean: 2.14 [95% CI, 2.05–2.20]), than the remaining groups (mean: normotensive: 1.99 [95% CI, 1.95–2.02], P =0.002; late‐onset preeclampsia: 2.01 [95% CI, 1.96–2.07], P =0.024; gestational diabetes mellitus: 1.97 [95% CI, 1.91–2.04], P =0.004). The percentage of vessels that were filled with red blood cells was significantly lower in early onset preeclampsia. These structural glycocalyx changes were accompanied by elevated plasma concentrations of the glycocalyx components, heparan sulfate proteoglycans and hyaluronic acid, in early onset preeclampsia compared with normotensive pregnancy. Conclusions Glycocalyx degradation and reduced microvascular perfusion are associated with endothelial dysfunction and activation and vascular injury in early onset preeclampsia.

Transparent reporting is essential for the critical evaluation of studies. However, the reporting of statistical methods for studies in the biomedical sciences is often limited. This systematic review examines the quality of reporting for two statistical tests, t-tests and ANOVA, for papers published in a selection of physiology journals in June 2017. Of the 328 original research articles examined, 277 (84.5%) included an ANOVA or t-test or both. However, papers in our sample were routinely missing essential information about both types of tests: 213 papers (95% of the papers that used ANOVA) did not contain the information needed to determine what type of ANOVA was performed, and 26.7% of papers did not specify what post-hoc test was performed. Most papers also omitted the information needed to verify ANOVA results. Essential information about t-tests was also missing in many papers. We conclude by discussing measures that could be taken to improve the quality of reporting.