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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 exce...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
W.B. Saunders
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5648688/ https://www.ncbi.nlm.nih.gov/pubmed/28778358 http://dx.doi.org/10.1053/j.ackd.2017.05.001 |
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author | Sawhney, Simon Fraser, Simon D. |
author_facet | Sawhney, Simon Fraser, Simon D. |
author_sort | Sawhney, Simon |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-5648688 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | W.B. Saunders |
record_format | MEDLINE/PubMed |
spelling | pubmed-56486882017-10-25 Epidemiology of AKI: Utilizing Large Databases to Determine the Burden of AKI Sawhney, Simon Fraser, Simon D. Adv Chronic Kidney Dis Article 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. W.B. Saunders 2017-07 /pmc/articles/PMC5648688/ /pubmed/28778358 http://dx.doi.org/10.1053/j.ackd.2017.05.001 Text en © 2017 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Sawhney, Simon Fraser, Simon D. Epidemiology of AKI: Utilizing Large Databases to Determine the Burden of AKI |
title | Epidemiology of AKI: Utilizing Large Databases to Determine the Burden of AKI |
title_full | Epidemiology of AKI: Utilizing Large Databases to Determine the Burden of AKI |
title_fullStr | Epidemiology of AKI: Utilizing Large Databases to Determine the Burden of AKI |
title_full_unstemmed | Epidemiology of AKI: Utilizing Large Databases to Determine the Burden of AKI |
title_short | Epidemiology of AKI: Utilizing Large Databases to Determine the Burden of AKI |
title_sort | epidemiology of aki: utilizing large databases to determine the burden of aki |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5648688/ https://www.ncbi.nlm.nih.gov/pubmed/28778358 http://dx.doi.org/10.1053/j.ackd.2017.05.001 |
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