Unsupervised machine learning to explore inflammation following cardiopulmonary bypass

Enrico Squiccimarro, Roberto Lorusso, Paolo Vetuschi, Michela Rauseo, Gianluca Paternoster, Giuseppe Speziale, Richard P Whitlock, Domenico Paparella, Division of Cardiac Surgery, Department of Medical and Surgical Sciences, University of Foggia, Cardio-Thoracic Surgery Department, Vascular Centre, Maastricht University Medical Centre, The Netherlands, Cardiovascular Research Institute Maastricht, The Netherlands, Division of Cardiac Anesthesia, Department of Medical and Surgical Sciences, University of Foggia, Department of Health Science Anesthesia and ICU, San Carlo Hospital, University of Basilicata, Division of Cardiac Surgery, Anthea Hospital, GVM Care , Division of Cardiac Surgery, Santa Maria Hospital, GVM Care , Division of Cardiac Surgery, Department of Surgery, McMaster University, Population Health Research Institute

Perfusion

Published online on August 27, 2025

Abstract

Perfusion, Ahead of Print.
IntroductionCardiac surgery with cardiopulmonary bypass (CPB) often induces systemic inflammatory reaction syndrome (SIRS), affecting postoperative outcome. We aimed to explore adaptive/maladaptive inflammation using unsupervised machine learning.Methods...