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Aims: Previous study on association between pro-inflammatory cytokines and mortality in PD population is limited. We aimed to investigate here. Methods: Total 50 patients who underwent incident PD were enrolled in this study. We measured the titers of pro-inflammatory cytokines Interleukin-18(IL-18), Interleukin-6 (IL-6), and Interleukin-1ß (IL-1ß). Study outcomes were all-cause mortality, cardiovascular-related mortality, and infection-caused mortality. Cox-regression model was used. Results: In this 7 year prospective study, IL-18 ≥ 804.3pg/ml, IL-6 ≥ 3.92 pg/ml, IL-1ß ≥ 0.86pg/ml, age ≥ 50 years-old, and existence of diabetes could be used as individual significant predictors for mortality in PD patients. Higher titers of IL-6 were associated with lower averaging albumin levels within 1st year of PD. Increasing numbers of these risk markers of mortality was associated with decreasing survival advantages (P = 0.001). Conclusion: Age ≥ 50 years-old, diabetes, and inflammatory cytokines profiles at the start of PD therapy could predict for 7-year mortality in PD population.

Background: The aim of this study is to evaluate the ability of generative artificial intelligence (AI) models to handle specialized medical knowledge and problem-solving in a formal examination context., Methods: This research utilized internal medicine exam questions provided by the Taiwan Internal Medicine Society from 2020 to 2023, testing three AI models: GPT-4o, Claude_3.5 Sonnet, and Gemini Advanced models. Rejected queries for Gemini Advanced were translated into French for resubmission. Performance was assessed using IBM SPSS Statistics 26, with accuracy percentages calculated and statistical analyses such as Pearson correlation and analysis of variance (ANOVA) performed to gauge AI efficacy., Results: GPT-4o's top annual score was 86.25 in 2022, with an average of 81.97. Claude_3.5 Sonnet reached a peak score of 88.13 in 2021 and 2022, averaging 84.85, while Gemini Advanced lagged with an average score of 69.84. In specific specialties, Claude_3.5 Sonnet scored highest in Psychiatry (100%) and Nephrology (97.26%), with GPT-4o performing similarly well in Hematology & oncology (97.10%) and Nephrology (94.52%). Gemini's best scores were in Psychiatry (86.96%) and Hematology & Oncology (82.76%). Gemini Advanced models struggled with Neurology, scoring below 60%. Additionally, all models performed better on text-based questions than on image-based ones, without significant differences. Claude 3 Opus scored highest on COVID-19-related questions at 89.29%, followed by GPT-4o at 75.00% and Gemini Advanced at 67.86%., Conclusions: AI models showed varied proficiency across medical specialties and question types. GPT-4o demonstrated higher image-based correction rates. Claude_3.5 Sonnet generally and consistently outperformed others, highlighting significant potential for AI in assisting medical education., Competing Interests: The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s) 2024.)