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The goal of this randomized clinical trial is to compare different types of advanced hemodynamic monitoring in patients undergoing major abdominal surgery.
Participants undergoing major abdominal surgery will receive anesthesia with two different types of hemodynamic monitoring - group A will receive arterial pressure cardiac output algorithm with the FloTrac sensor and group B will receive hemodynamic monitoring with the Hypotension Prediction Index.
The main question the study aims to answer is:
• will the hypotension prediction index algorithm reduce the rate of hypotension in comparison to arterial pressure cardiac output algorithm.
Full description
The fundamental aspect of the anesthetics perioperative management is to maintain hemodynamic stability, with special attention on the avoidance or reduction of the episodes of intraoperative hypotension (IOH). The incidence of intraoperative hypotension is related to an increased rate of perioperative morbidity and mortality. Even a short period of hypotension can be related to an increased risk of postoperative stroke, myocardial injury and acute kidney injury. Patients undergoing major abdominal surgery are at a high-risk of IOH because such surgeries typically require more than 2h to complete and require blood transfusion or inotrope administration. Hemodynamic monitoring and the use of goal directed therapy protocols helps to diminish the incidence of perioperative complications, however the hypotension management remains a reactive approach, an intervention is made when the hypotension has already occured. The Hypotension Prediction Index is an machine learning algorithm which allows to predict the episodes of hypotension and intervene before mean arterial pressure drops below 65 mmHg. The aim of the current study is to compare the rate of hypotension in patients undergoing major abdominal surgery with the arterial pressure cardiac output algorithm and the hypotension prediction index algorithm.
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226 participants in 2 patient groups
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Agata Gradys, Ph.D.; Jakub Szrama, Ph.D.
Data sourced from clinicaltrials.gov
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