Artificial Intelligence for Anesthesiology Board-Style Examination Questions: Role of Large Language Models.

New artificial intelligence tools have been developed that have implications for medical usage. Large language models (LLMs), such as the widely used ChatGPT developed by OpenAI, have not been explored in the context of anesthesiology education. Understanding the reliability of various publicly available LLMs for medical specialties could offer insight into their understanding of the physiology, pharmacology, and practical applications of anesthesiology. An exploratory prospective review was conducted using 3 commercially available LLMs--OpenAI's ChatGPT GPT-3.5 version (GPT-3.5), OpenAI's ChatGPT GPT-4 (GPT-4), and Google's Bard--on questions from a widely used anesthesia board examination review book. Of the 884 eligible questions, the overall correct answer rates were 47.9% for GPT-3.5, 69.4% for GPT-4, and 45.2% for Bard. GPT-4 exhibited significantly higher performance than both GPT-3.5 and Bard (p = 0.001 and p < 0.001, respectively). None of the LLMs met the criteria required to secure American Board of Anesthesiology certification, according to the 70% passing score approximation. GPT-4 significantly outperformed GPT-3.5 and Bard in terms of overall performance, but lacked consistency in providing explanations that aligned with scientific and medical consensus. Although GPT-4 shows promise, current LLMs are not sufficiently advanced to answer anesthesiology board examination questions with passing success. Further iterations and domain-specific training may enhance their utility in medical education.

Point-of-Care Thromboelastography for Intrathecal Drain Management in Patients With Coagulopathy and Thoracic Aorta Surgery: A Case Report.

Spinal drain placement to prevent spinal cord ischemia during thoracic aorta surgery is a necessary yet complex undertaking in patients with coagulopathies. Thromboelastography (TEG) can be used as a point-of-care management tool to monitor coagulation status before drain placement and removal. We present 2 cases: a case of a patient with factor VII deficiency and a case of a patient with thrombocytopenia for whom TEG was an important procedural adjunct during coagulopathy reversal. TEG parameters are also discussed to encourage more frequent TEG use as an adjunct during these complex cases.