Intraoperative hypotension is common in patients having non-cardiac surgery and associated with postoperative acute myocardial injury, acute kidney injury, and mortality. Avoiding intraoperative hypotension is a complex task for anesthesiologists. Using artificial intelligence to predict hypotension from clinical and hemodynamic data is an innovative and intriguing approach. The AcumenTM Hypotension Prediction Index (HPI) software (Edwards Lifesciences; Irvine, CA, USA) was developed using artificial intelligence-specifically machine learning-and predicts hypotension from blood pressure waveform features. We aimed to describe the incidence, duration, severity, and causes of intraoperative hypotension when using HPI monitoring in patients having elective major non-cardiac surgery.

Hypotension Prediction Index Software to Prevent Intraoperative Hypotension during Major Non-Cardiac Surgery: Protocol for a European Multicenter Prospective Observational Registry (EU-HYPROTECT) / Monge García, Manuel Ignacio; García-López, Daniel; Gayat, Étienne; Sander, Michael; Bramlage, Peter; Cerutti, Elisabetta; Davies, Simon James; Donati, Abele; Draisci, Gaetano; Frey, Ulrich H; Noll, Eric; Ripollés-Melchor, Javier; Wulf, Hinnerk; Saugel, Bernd. - In: JOURNAL OF CLINICAL MEDICINE. - ISSN 2077-0383. - 11:19(2022), p. 5585. [10.3390/jcm11195585]

Hypotension Prediction Index Software to Prevent Intraoperative Hypotension during Major Non-Cardiac Surgery: Protocol for a European Multicenter Prospective Observational Registry (EU-HYPROTECT)

Donati, Abele;
2022-01-01

Abstract

Intraoperative hypotension is common in patients having non-cardiac surgery and associated with postoperative acute myocardial injury, acute kidney injury, and mortality. Avoiding intraoperative hypotension is a complex task for anesthesiologists. Using artificial intelligence to predict hypotension from clinical and hemodynamic data is an innovative and intriguing approach. The AcumenTM Hypotension Prediction Index (HPI) software (Edwards Lifesciences; Irvine, CA, USA) was developed using artificial intelligence-specifically machine learning-and predicts hypotension from blood pressure waveform features. We aimed to describe the incidence, duration, severity, and causes of intraoperative hypotension when using HPI monitoring in patients having elective major non-cardiac surgery.
2022
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11566/307661
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