Effect of a Machine Learning–Derived Early Warning System for Intraoperative Hypotension vs Standard Care on Depth and Duration of Intraoperative Hypotension During Elective Noncardiac Surgery-Reference-Cited by-同舟云学术

Effect of a Machine Learning–Derived Early Warning System for Intraoperative Hypotension vs Standard Care on Depth and Duration of Intraoperative Hypotension During Elective Noncardiac Surgery

Published:2020-03-17 Issue:11 Volume:323 Page:1052
ISSN:0098-7484
Container-title:JAMA
language:en
Short-container-title:JAMA

Author:

Wijnberge Marije¹²,Geerts Bart F.¹,Hol Liselotte¹,Lemmers Nikki¹,Mulder Marijn P.¹³,Berge Patrick¹,Schenk Jimmy¹,Terwindt Lotte E.¹,Hollmann Markus W.¹,Vlaar Alexander P.²,Veelo Denise P.¹

Affiliation:

1. Department of Anesthesiology, Amsterdam UMC, Location AMC, Amsterdam, the Netherlands

2. Department of Intensive Care, Amsterdam UMC, Location AMC, Amsterdam, the Netherlands

3. Department of Technical Medicine, University of Twente, Enschede, the Netherlands

Publisher

American Medical Association (AMA)

Subject

General Medicine

Link

https://jamanetwork.com/journals/jama/articlepdf/2761469/jama_wijnberge_2020_pc_200001.pdf

Reference27 articles.

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3. Hypotension during surgery for high risk patients: cause or consequence of pathology?;Tritapepe;Minerva Anestesiol,2013

4. Predictors of intraoperative hypotension and bradycardia.;Cheung;Am J Med,2015

5. Association between intraoperative hypotension and myocardial injury after vascular surgery.;van Waes;Anesthesiology,2016

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