Faculty Bibliography

BACKGROUND/UNASSIGNED:Recent developments in artificial intelligence (AI), particularly in large language models, have shown promise in various fields, including health care. However, their performance on specialized medical board examinations, such as interventional cardiology assessments, remains relatively unexplored. METHODS/UNASSIGNED:A cross-sectional study was conducted using a data set comprising 360 questions from the Cath Self Assessment Program (CathSAP) question bank. This study aimed to assess the overall performance of Chat Generative Pre-trained Transformer (ChatGPT) and compare it to that of average test takers. Additionally, the study evaluated the impact of pertinent educational materials on ChatGPT's responses, both before and after exposure. The primary outcome measures included ChatGPT's overall percentage score on the CathSAP examination and its performance across various subsections. Statistical significance was determined using the Kruskal-Wallis equality-of-populations rank test. RESULTS/UNASSIGNED:= .0003). Notably, the improved score was comparable with the average score achieved by typical test takers (as reported by CathSAP). ChatGPT demonstrated proficiency in sections covering basic science, pharmacology, and miscellaneous topics, although it struggled with anatomy, anatomic variants, and anatomic pathology questions. CONCLUSIONS/UNASSIGNED:The study demonstrates ChatGPT's potential for learning and adapting to medical examination scenarios, with a notable enhancement in performance after exposure to educational materials. However, limitations such as the model's inability to process certain visual materials and potential biases in AI models warrant further consideration. These findings underscore the need for continued research to optimize the use of AI in medical education and assessment.

Coronavirus disease 2019 (COVID-19), currently a worldwide pandemic, is a viral illness caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The suspected contribution of thrombotic events to morbidity and mortality in COVID-19 patients has prompted a search for novel potential options for preventing COVID-19-associated thrombotic disease. In this article by the Global COVID-19 Thrombosis Collaborative Group, we describe novel dosing approaches for commonly used antithrombotic agents (especially heparin-based regimens) and the potential use of less widely used antithrombotic drugs in the absence of confirmed thrombosis. Although these therapies may have direct antithrombotic effects, other mechanisms of action, including anti-inflammatory or antiviral effects, have been postulated. Based on survey results from this group of authors, we suggest research priorities for specific agents and subgroups of patients with COVID-19. Further, we review other agents, including immunomodulators, that may have antithrombotic properties. It is our hope that the present document will encourage and stimulate future prospective studies and randomized trials to study the safety, efficacy, and optimal use of these agents for prevention or management of thrombosis in COVID-19.