A sepsis early warning system is associated with improved patient outcomes
- PMID: 36130478
- PMCID: PMC9512693
- DOI: 10.1016/j.xcrm.2022.100746
A sepsis early warning system is associated with improved patient outcomes
Abstract
In a real-world implementation of a machine-learning (ML)-based sepsis early warning system (EWS), Adams et al.1,2 found that timely provider response to an alert was associated with improved mortality, highlighting the potential utility of these systems in patient care.
Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.
Conflict of interest statement
Declaration of interests K.E.R. declares consulting fees from Janssen Pharmaceuticals.
Comment on
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Prospective, multi-site study of patient outcomes after implementation of the TREWS machine learning-based early warning system for sepsis.Nat Med. 2022 Jul;28(7):1455-1460. doi: 10.1038/s41591-022-01894-0. Epub 2022 Jul 21. Nat Med. 2022. PMID: 35864252
References
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- Adams R., Henry K.E., Sridharan A., Soleimani H., Zhan A., Rawat N., Johnson L., Hager D.N., Cosgrove S.E., Markowski A., et al. Prospective, multi-site study of patient outcomes after implementation of the TREWS machine learning-based early warning system for sepsis. Nat. Med. 2022;28:1455–1460. doi: 10.1038/s41591-022-01894-0. - DOI - PubMed
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- Shimabukuro D.W., Barton C.W., Feldman M.D., Mataraso S.J., Das R. Effect of a machine learning-based severe sepsis prediction algorithm on patient survival and hospital length of stay: a randomised clinical trial. BMJ Open Respir. Res. 2017;4:e000234. doi: 10.1136/bmjresp-2017-000234. - DOI - PMC - PubMed
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