Epidemiology of AKI: Utilizing large databases to determine the burden of AKI
Epidemiology of AKI: Utilizing large databases to determine the burden of AKI
Large observational databases linking kidney function and other routine patient health data are increasingly being used to study acute kidney injury (AKI). Routine health care data show an apparent rise in the incidence of population AKI and an increase in acute dialysis. Studies also report an excess in mortality and adverse renal outcomes after AKI, although with variation depending on AKI severity, baseline, definition of renal recovery, and the time point during follow-up. However, differences in data capture, AKI awareness, monitoring, recognition, and clinical practice make comparisons between health care settings and periods difficult. In this review, we describe the growing role of large databases in determining the incidence and prognosis of AKI and evaluating initiatives to improve the quality of care in AKI. Using examples, we illustrate this use of routinely collected health data and discuss the strengths, limitations, and implications for researchers and clinicians.
194-204
Sawhney, Simon
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Fraser, Simon
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Sawhney, Simon
f1117f11-d5fd-4c2b-8bcc-6943d8f529d7
Fraser, Simon
135884b6-8737-4e8a-a98c-5d803ac7a2dc
Sawhney, Simon and Fraser, Simon
(2017)
Epidemiology of AKI: Utilizing large databases to determine the burden of AKI.
Advances in Chronic Kidney Disease, 24 (4), .
(doi:10.1053/j.ackd.2017.05.001).
Abstract
Large observational databases linking kidney function and other routine patient health data are increasingly being used to study acute kidney injury (AKI). Routine health care data show an apparent rise in the incidence of population AKI and an increase in acute dialysis. Studies also report an excess in mortality and adverse renal outcomes after AKI, although with variation depending on AKI severity, baseline, definition of renal recovery, and the time point during follow-up. However, differences in data capture, AKI awareness, monitoring, recognition, and clinical practice make comparisons between health care settings and periods difficult. In this review, we describe the growing role of large databases in determining the incidence and prognosis of AKI and evaluating initiatives to improve the quality of care in AKI. Using examples, we illustrate this use of routinely collected health data and discuss the strengths, limitations, and implications for researchers and clinicians.
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Sawhney_ACKD_AKI
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Accepted/In Press date: 1 July 2017
e-pub ahead of print date: 2 August 2017
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Local EPrints ID: 412864
URI: http://eprints.soton.ac.uk/id/eprint/412864
ISSN: 1548-5595
PURE UUID: a6981e5b-8684-4cc2-9e60-4979183804ee
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Date deposited: 03 Aug 2017 16:30
Last modified: 16 Mar 2024 03:58
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Author:
Simon Sawhney
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