Intraoperative hypotension is linked to increased incidence of perioperative adverse events such as myocardial and cerebrovascular infarction and acute kidney injury. Hypotension prediction index (HPI) is a novel machine learning guided algorithm which can predict hypotensive events using high fidelity analysis of pulse-wave contour. Goal of this trial is to determine whether use of HPI can reduce the number and duration of hypotensive events in patients undergoing major thoracic procedures.

Inclusion Criteria:

• patients over 18 years of age
• patients scheduled for elective major thoracic procedure (lung resection, pleurectomy or resection of the esophagus)
• planned thoracotomy and intraoperative period of one lung ventilation
• planned postoperative admission to the ICU

Exclusion criteria:

• persistent atrial fibrillation
• structural heart defects (shunting or moderate to severe valvular anomalies)
• preoperative serum hemoglobin levels < 120 g/L
• severe heart failure classified as New York Heart Association (NYHA) grade IV

Will share anonymized data after article publication