• Franck Verdonk, Jakob Einhaus, Amy S Tsai, Julien Hedou, Benjamin Choisy, Dyani Gaudilliere, Cindy Kin, Nima Aghaeepour, Martin S Angst, and Brice Gaudilliere.
• Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine.
• Curr Opin Crit Care. 2021 Dec 1; 27 (6): 717725717-725.

Purpose Of ReviewPostoperative complications including infections, cognitive impairment, and protracted recovery occur in one-third of the 300 million surgeries performed annually worldwide. Complications cause personal suffering along with a significant economic burden on our healthcare system. However, the accurate prediction of postoperative complications and patient-targeted interventions for their prevention remain as major clinical challenges.Recent FindingsAlthough multifactorial in origin, the dysregulation of immunological mechanisms that occur in response to surgical trauma is a key determinant of postoperative complications. Prior research, primarily focusing on inflammatory plasma markers, has provided important clues regarding their pathogenesis. However, the recent advent of high-content, single-cell transcriptomic, and proteomic technologies has considerably improved our ability to characterize the immune response to surgery, thereby providing new means to understand the immunological basis of postoperative complications and to identify prognostic biological signatures.SummaryThe comprehensive and single-cell characterization of the human immune response to surgery has significantly advanced our ability to predict the risk of postoperative complications. Multiomic modeling of patients' immune states holds promise for the discovery of preoperative predictive biomarkers, ultimately providing patients and surgeons with actionable information to improve surgical outcomes. Although recent studies have generated a wealth of knowledge, laying the foundation for a single-cell atlas of the human immune response to surgery, larger-scale multiomic studies are required to derive robust, scalable, and sufficiently powerful models to accurately predict the risk of postoperative complications in individual patients.Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.

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