Machine Learning-Guided Hypotension Prediction and Goal-Directed Therapy During Transcatheter Valve Repair: A Prospective Observational Study

Objectives Percutaneous transcatheter valve repair (PTVR) can result in hemodynamic instability, elevated burden of intraoperative hypotension (IOH) and related postoperative complications. Design Prospective observational study. Setting The aim of this study is to describe the burden of IOH in patients treated with hemodynamic guidance based on an algorithm that predict the likelihood of IOH and optimize cardiac output (the Hypotension Prediction Index – HPI). Participants 69 patients undergoing PTVR were included. Interventions When HPI exceeded 85, a proactive treatment protocol to prevent hypotension was provided. Measurements and Main Results Primary outcome was TWA (time weighted average) - MAP (mean arterial pressure) under 65 mmHg threshold. Secondary outcomes were number of patients with at least one hypotensive event, number of events per patient, depth and duration of hypotensive events,time spent in hypotension. During an average monitoring time per patient of 191.61 ± 52 minutes, the median TWA-MAP < 65 mmHg, was 0.17 [0.01, 0.7] mmHg. Two thirds of the patients experienced IOH. Average of hypotensive events 2.49 [0, 4] per patient, 4,8 % of time spent < 65 mmHg. The majority of hypotensive events occurred after induction of general anesthesia. Conclusions Main result of our study consisted of safe hemodynamic management during PTVR in terms of limiting the incidence and the severity of IOH. This is the first detailed description of characteristics of IOH in patients undergoing PTVR under general anesthesia, following the application of an HPI-based hemodynamic guidance.