AUTHOR=Ripollés-Melchor Javier , Ruiz-Escobar Alicia , Fernández-Valdes-Bango Paula , Lorente Juan V. , Jiménez-López Ignacio , Abad-Gurumeta Alfredo , Carrasco-Sánchez Laura , Monge-García M. Ignacio 

TITLE=Hypotension prediction index: From reactive to predictive hemodynamic management, the key to maintaining hemodynamic stability

JOURNAL=Frontiers in Anesthesiology

VOLUME=2

YEAR=2023

URL=https://www.frontiersin.org/journals/anesthesiology/articles/10.3389/fanes.2023.1138175

DOI=10.3389/fanes.2023.1138175

ISSN=2813-480X

ABSTRACT=<p>Intraoperative hypotension is common and has been associated with adverse events, including acute kidney failure, myocardial infarction, and stroke. Since blood pressure is a multidimensional and measurable variable, artificial intelligence and machine learning have been used to predict it. To date, studies have shown that the prediction and prevention of hypotension can reduce the incidence of hypotension. This review describes the development and evaluation of an artificial intelligence predictive algorithm called Hypotension Prediction (HPI), which can predict hypotension up to 15 min before it occurs.</p>