ALERT!

This site is not optimized for Internet Explorer 8 (or older).

Please upgrade to a newer version of Internet Explorer or use an alternate browser such as Chrome or Firefox.

A Machine Learning Early Warning System for Intraoperative Hypotension

Thursday, February 20, 2020

Submitted by

Mark Ferguson

Source

Source Name: JAMA Network

Source URL: https://jamanetwork.com/journals/jama/fullarticle/2761469

Author(s)

Marije Wijnberge, Bart F. Geerts, Liselotte Hol, Nikki Lemmers, Marijn P. Mulder, Patrick Berge, Jimmy Schenk, Lotte E. Terwindt, Markus W. Hollmann, Alexander P. Vlaar, Denise P. Veelo

This randomized trial evaluated depth and duration of intraoperative hypotension during noncardiac surgery, comparing a machine learning early warning system to standard care. Hypotension was defined as a MAP <65 mm Hg for one minute or more. The early warning system significantly reduced the degree and duration of hypotension compared to controls. Control patients suffered two adverse events resulting in death (7%), whereas none occured in the intervention group.