Hypotension Prediction With HPI Algorithm During Major Gynecologic Oncologic Surgery

Intraoperative hypotension (IOH) is a rather common event during general surgery, with variable incidence that ranges between 5 and 99% based on the definition used. It is associated to significant complications including acute renal failure, myocardial damage, stroke and overall increased mortality, reason why the prevention and the reduction of hypotensive events through an appropriate proactive approach can potentially improve the patient's outcome. The Hypotension Prediction Index (HPI) is an algorithm derived from the analysis of the arterial waveform and it is expressed as an absolute value from 0 to 100. It has been demonstrated that the HPI is able to predict the occurrence of hypotensive events of patients undergoing major surgery under general anesthesia, providing also a guide for the appropriate treatment based on further calculated secondary hemodynamic variables that estimate patient's preload, cardiac contractility and afterload. Aim of this prospective randomized study is to compare the incidence of IOH during major gynecologic oncologic surgery among two groups of patients receiving standard hemodynamic monitoring versus HPI monitoring. The primary hypothesis is that hemodynamic management HPI-guided reduces the incidence, entity and duration of intraoperative hypotensive events, defined as mean arterial pressure (MAP) lower than 65 mmHg lasting more than one minute.