GSE208581
Risk assessment with gene expression markers in sepsis development
We investigated the individual phenotypic predisposition to developing uncomplicated infection or sepsis in a large cohort of non-infected patients undergoing major elective surgery. Whole blood RNA sequencing analysis was performed on preoperative samples taken from 267 patients. These comprised patients who developed postoperative infection with (n=77) or without (n=49) sepsis, non-infectious systemic inflammatory response (n=31), or an uncomplicated postoperative course (n=110). Machine learning classification models built on preoperative transcriptomic signatures predicted postoperative outcomes including sepsis. Overall design: Whole blood RNA sequencing analysis was performed on preoperative samples taken from 267 patients. These comprised patients who developed postoperatively infection leading to sepsis (n=77) or an uncomplicated infection outcome (n=49), non-infectious systemic inflammatory response (n=31), or an uncomplicated postoperative course (n=110).