Impact of Inflammation After Cardiac Surgery on 30-Day Mortality and Machine Learning Risk Prediction.

Journal: Journal of cardiothoracic and vascular anesthesia
PMID: 39732570

Abstract

OBJECTIVES: To investigate the impact of systemic inflammatory response syndrome (SIRS) on 30-day mortality following cardiac surgery and develop a machine learning model to predict SIRS.

Authors

  • Enrico Squiccimarro
    Division of Cardiac Surgery, Department of Medical and Surgical Sciences, University of Foggia, Foggia, Italy; Cardio-Thoracic Surgery Department, Heart & Vascular Centre, Maastricht University Medical Centre, Maastricht, The Netherlands.
  • Roberto Lorusso
    Cardio-Thoracic Surgery Department, Heart & Vascular Centre, Maastricht University Medical Centre, Maastricht, The Netherlands; Cardiovascular Research Institute Maastricht, Maastricht, The Netherlands.
  • Antonio Consiglio
    Division of Cardiac Surgery, Department of Medical and Surgical Sciences, University of Foggia, Foggia, Italy.
  • Cataldo Labriola
    Department of Cardiac Anesthesia, Santa Maria Hospital-GVM Care & Research, Bari, Italy. Electronic address: dino.labriola@gmail.com.
  • Renard G Haumann
    Department of Cardio-Thoracic Surgery, Thoraxcentrum Twente, Medisch Spectrum Twente, Enschede, The Netherlands; Department of Biomechanical Engineering, TechMed Centre, University of Twente, Enschede, The Netherlands.
  • Felice Piancone
    Division of Cardiac Surgery, Department of Medical and Surgical Sciences, University of Foggia, Foggia, Italy.
  • Giuseppe Speziale
    Department of Cardiac Surgery, Santa Maria Hospital-GVM Care & Research, Bari, Italy.
  • Richard P Whitlock
    Division of Cardiac Surgery, Department of Surgery, McMaster University, Hamilton, ON, Canada; Population Health Research Institute, Hamilton, ON, Canada.
  • Domenico Paparella
    Division of Cardiac Surgery, University of Bari, Bari, Italy.

Keywords

External Resources

Popular Topics
Recent Journals