| Literature DB >> 36233419 |
Tatiana Sidiropoulou1, Marina Tsoumpa1, Panayota Griva1, Vasiliki Galarioti1, Paraskevi Matsota1.
Abstract
Intraoperative hypotension is common and has been associated with adverse events. Although association does not imply causation, predicting and preventing hypotension may improve postoperative outcomes. This review summarizes current evidence on the development and validation of an artificial intelligence predictive algorithm, the Hypotension Prediction (HPI) (formerly known as the Hypotension Probability Indicator). This machine learning model can arguably predict hypotension up to 15 min before its occurrence. Several validation studies, retrospective cohorts, as well as a few prospective randomized trials, have been published in the last years, reporting promising results. Larger trials are needed to definitively assess the usefulness of this algorithm in optimizing postoperative outcomes.Entities:
Keywords: hypotension prediction index; intraoperative hypotension; machine learning
Year: 2022 PMID: 36233419 PMCID: PMC9571689 DOI: 10.3390/jcm11195551
Source DB: PubMed Journal: J Clin Med ISSN: 2077-0383 Impact factor: 4.964