Electronic health records accurately predict renal replacement therapy in acute kidney injury

Electronic health records accurately predict renal replacement therapy in acute kidney injury

Abstract Background Electronic health records (EHR) detect the onset of acute kidney injury (AKI) in hospitalized patients, and may identify those at highest risk of mortality and renal replacement therapy (RRT), for earlier targeted intervention. Methods Prospective observational study to derive pr...

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Bibliographic Details
Main Authors: Sanmay Low, Anantharaman Vathsala, Tanusya Murali Murali, Long Pang, Graeme MacLaren, Wan-Ying Ng, Sabrina Haroon, Amartya Mukhopadhyay, Shir-Lynn Lim, Bee-Hong Tan, Titus Lau, Horng-Ruey Chua
Format: Article
Language:English
Published: BMC 2019-01-01
Series:BMC Nephrology
Subjects:
Acute kidney injury
Decision support techniques
Electronic health records
Epidemiology
Mortality
Outcomes and process assessment
Online Access:http://link.springer.com/article/10.1186/s12882-019-1206-4

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http://link.springer.com/article/10.1186/s12882-019-1206-4

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