An Observational, Prospective Multi-centre Study of the Hypotension Prediction Index (HPI) in Patients Undergoing Lung Resections Using One-Lung Ventilation

What this Trial Is About

Researchers are evaluating the Hypotension Prediction Index (HPI), an artificial intelligence-based algorithm designed to predict intraoperative hypotension (low blood pressure during surgery) by analyzing arterial pressure waveforms. This observational study aims to validate the HPI technology specifically in adult patients undergoing lung resection surgeries with one-lung ventilation, as this setting has unique physiological challenges that may affect the algorithm's accuracy. The study is prospective and multi-center, focusing on patients having thoracic surgeries such as lobectomies or pneumonectomies. During the surgical procedure, 60 adult patients will be monitored using standard invasive arterial pressure devices alongside the HemoSphere monitor equipped with the HPI software. The clinicians will not see the HPI readings to avoid bias. Data will be collected continuously from arterial cannula insertion until the end of surgery, covering seven distinct time periods reflecting different surgical and ventilation conditions, including closed chest with two-lung ventilation and open chest with one-lung ventilation. Participants will undergo routine monitoring during the operation, with hemodynamic waveforms and HPI prediction data recorded for analysis. Researchers will evaluate the HPI's ability to predict hypotensive episodes, focusing on its positive predictive value and event rate throughout the surgery. The study will follow STARD guidelines for accuracy and reporting, aiming to understand the HPI's performance in this specific surgical context without affecting patient care. Total participation is limited to the intraoperative period.

Hypotension Prediction Index (HPI) in Lung Resections