Objectives: The main objective of this study is to evaluate the ability of the Large Language Model Chat Generative Pre-Trained Transformer (ChatGPT) to accurately answer the United States Medical Licensing Examination (USMLE) board-style medical ethics questions compared to medical knowledge-based questions. This study has the additional objectives of comparing the overall accuracy of GPT-3.5 to GPT-4 and assessing the variability of responses given by each version.
View Article and Find Full Text PDFBackground: The epidemiology of cytomegalovirus (CMV) after chimeric antigen receptor-modified T-cell immunotherapy (CARTx) is poorly understood owing to a lack of routine surveillance.
Methods: We prospectively enrolled 72 adult CMV-seropositive CD19-, CD20-, or BCMA-targeted CARTx recipients and tested plasma samples for CMV before and weekly up to 12 weeks after CARTx. We assessed CMV-specific cell-mediated immunity (CMV-CMI) before and 2 and 4 weeks after CARTx, using an interferon γ release assay to quantify T-cell responses to IE-1 and pp65.