Artificial Intelligence - to Predict and Prevent Hypotension During Surgery

The goal of this medtech clinical trial is to develop and evaluate a machine learning algoritm to predict low blood pressure episodes during major surgery. The main questions it aims to answer are: * Could a novel method for cardiac output estimation through alterations in carbon dioxide improve the performance of a blood pressure based algoritm in order to predict low blood pressure episodes during major abdominal surgery? * Will the predictive performance of the algoritm improve with the addition of other patient specific data? * Do the estimated cardiac output and central venous saturation by the novel method agree with our invasive arterial pressure method for cardiac output, and samples via a central venous line, respectively? 300 participants will be anesthetized with total intravenous anesthesia and ventilated with the novel carbon dioxide based method, and arterial and central venous blood gases will be taken regularly throughout the operation. All physiological data will be stored for later analyses and development of the algoritm by machine learning methods. No other invasive interventions will be performed outside our standard clinical peroperative protocol.