alexa Acute kidney injury-how does automated detection perform?


Journal of Nephrology & Therapeutics

Author(s): Sawhney S, Fluck N, Marks A, Prescott G, Simpson W, , Sawhney S, Fluck N, Marks A, Prescott G, Simpson W,

Abstract Share this page

Abstract BACKGROUND: Early detection of acute kidney injury (AKI) is important for safe clinical practice. NHS England is implementing a nationwide automated AKI detection system based on changes in blood creatinine. Little has been reported on the similarities and differences of AKI patients detected by this algorithm and other definitions of AKI in the literature. METHODS: We assessed the NHS England AKI algorithm and other definitions using routine biochemistry in our own health authority in Scotland in 2003 (adult population 438 332). Linked hospital episode codes (ICD-10) were used to identify patients where AKI was a major clinical diagnosis. We compared how well the algorithm detected this subset of AKI patients in comparison to other definitions of AKI. We also evaluated the potential 'alert burden' from using the NHS England algorithm in comparison to other AKI definitions. RESULTS: Of 127 851 patients with at least one blood test in 2003, the NHS England AKI algorithm identified 5565 patients. The combined NHS England algorithm criteria detected 91.2\% (87.6-94.0) of patients who had an ICD-10 AKI code and this was better than any individual AKI definition. Some of those not captured could be identified by algorithm modifications to identify AKI in retrospect after recovery, but this would not be practical in real-time. Any modifications also increased the number of alerted patients (2-fold in the most sensitive model). CONCLUSIONS: The NHS England AKI algorithm performs well as a diagnostic adjunct in clinical practice. In those without baseline data, AKI may only be seen in biochemistry in retrospect, therefore proactive clinical care remains essential. An alternative algorithm could increase the diagnostic sensitivity, but this would also produce a much greater burden of patient alerts. © The Author 2015. Published by Oxford University Press on behalf of ERA-EDTA.
This article was published in Nephrol Dial Transplant and referenced in Journal of Nephrology & Therapeutics

Relevant Expert PPTs

Relevant Speaker PPTs

Recommended Conferences

  • 15th International Conference on Nephrology & Therapeutics
    August 28-30, 2017 Philadelphia, USA
  • 16th European Nephrology Conference
    October 02-04, 2017 Barcelona, Spain
  • 16th European Nephrology Conference
    October 02-04, 2017 Barcelona, Spain
  • World Nephrology Congress
    Osaka, Japan Oct 09-11, 2017
  • 13th World Nephrology Conference
    October 18-19, 2017 Dubai,UAE
  • 16th International Conference on Nephrology
    NOVEMBER 02-03, 2017 Atlanta, USA

Relevant Topics

Peer Reviewed Journals
Make the best use of Scientific Research and information from our 700 + peer reviewed, Open Access Journals
International Conferences 2017-18
Meet Inspiring Speakers and Experts at our 3000+ Global Annual Meetings

Contact Us

© 2008-2017 OMICS International - Open Access Publisher. Best viewed in Mozilla Firefox | Google Chrome | Above IE 7.0 version