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Defining Acute Kidney Injury Episodes

Authors :
Gareth Davies
James Chess
Timothy Scale
Ronan A Lyons
Ashley Akbari
Source :
International Journal of Population Data Science, Vol 5, Iss 5 (2020), International Journal of Population Data Science, Vol 4, Iss 3 (2019)
Publication Year :
2019
Publisher :
Swansea University, 2019.

Abstract

IntroductionAcute Kidney Injury (AKI) is a common, serious condition effecting up to 20% of all hospital admissions in the UK. AKI has an agreed definition for its recognition, however there is no consensus for the duration of an AKI episode. Objectives and ApproachWe aimed to describe four different potential definitions of an AKI episode. AKI was identified using an SQL (Structured Query Language) based algorithm (an implementation of the NHS England eAlert algorithm) applied to serum creatinine (SCr) results from a South Wales population of ~518,000 people, held in the Secure Anonymised Information Linkage (SAIL) Databank. Using a person’s index AKI case, we applied four different rules to define an episode of AKI. These definitions are: ALERTS - until they no longer trigger an AKI eAlert, 90 DAYS - until 90 days post first AKI test and

Details

Language :
English
Database :
OpenAIRE
Journal :
International Journal of Population Data Science, Vol 5, Iss 5 (2020), International Journal of Population Data Science, Vol 4, Iss 3 (2019)
Accession number :
edsair.doi.dedup.....8a27f312419436ebe4113d2ad60eae2d