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Systemic inflammatory response syndrome after extracorporeal circulation: a predictive algorithm for the patient at
Jens Litmathe1, Udo Boeken, Gabriele Bohlen
1Department of Thoracic and Cardiovascular Surgery, Heinrich Heine University Hospital Düsseldorf, Germany. jens-litmathe@t-online.de
Summary
Identifying patients at risk for systemic inflammatory response syndrome (SIRS) after cardiac surgery is crucial. Preoperative markers like alkaline phosphatase and endothelin-1 can predict SIRS development, enabling personalized operative scheduling.
Area of Science:
- Cardiovascular Surgery
- Critical Care Medicine
- Immunology
Background:
- Perioperative systemic inflammatory response syndrome (SIRS) is a significant complication in cardiac surgery.
- Current patient screening methods for SIRS risk are inadequate.
- This study aimed to identify preoperative predictors for SIRS in open-heart surgery patients.
Purpose of the Study:
- To evaluate postoperative outcomes for predicting SIRS risk.
- To identify a hazard constellation for patients at risk of developing SIRS.
- To establish a basis for improved patient screening and operative scheduling.
Main Methods:
- Prospective trial involving 2315 cardiac surgery patients over 2 years.
- High-risk stratification identified 107 patients likely to develop SIRS.
- Blood samples analyzed for inflammatory markers, coagulation, and fibrinolysis in 12 SIRS patients and 20 controls.
Main Results:
- Significant preoperative differences in leukocytes, lymphocytes, alkaline phosphatase, ICAM-3, and VCAM-1 were observed.
- Elevated endothelin-1 (ET-1) and lactate correlated with SIRS and prolonged extracorporeal circulation.
- A predictive combination included alkaline phosphatase, ET-1, ICAM-1, -2, -3, VCAM-1, and ELAM-1.
Conclusions:
- Perioperative SIRS may stem from pre-existing activation of endothelial cells, lymphocytes, and leukocytes, not solely extracorporeal circulation.
- This activation impairs microcirculation, potentially leading to multi-organ failure.
- The findings enable identification of at-risk patients, potentially influencing operative scheduling.