Prediction of Arterial Hypotension by HPI: a Feasibility Study in Lung Resection Surgery and During Fenestrated Aortic Stenting Under General Anesthesia

Background: Brief review (literature data, pathology, field of study) Thoracic lung resection surgery has specific imperatives (opening of the thorax, unipulmonary ventilation, lateral decubitus operating position) that challenge the accuracy and precision of hemodynamic monitoring tools in general [1] and of systems based on arterial pressure wave analysis in particular.

The ACUMEN ClearSight® medical device enhanced by the HPI algorithm, CE marked in 2023, was developed and marketed by Edwards LifeSciences. It has been the subject of some twenty medical scientific publications since 2018 [2,3]. It is a non-invasive, single-patient sensor-type device that predicts and anticipates the occurrence of intraoperative arterial hypotension episodes and enables an advanced, individualized hemodynamic monitoring strategy.

The prediction of intraoperative arterial hypotension by the HPI machine learning algorithm is based on the invasive or non-invasive analysis of the physiological properties of the arterial pressure wave. The device is designed to optimize blood pressure management during lung resection surgery for cancer or fenestrated thoracic aortic stenting under general anesthesia. It should also enable personalized hemodynamic optimization of vascular filling and intraoperative management of vasopressor agents in patients at cardiac risk, leading ultimately to a reduction in hospital morbidity and mortality.

Non-invasive monitoring with the ClearSight® system is used routinely in the operating room at Hôpital Louis Pradel, but without the intelligent HPI system.