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Predicting acute kidney injury: current status and future challenges
Acute kidney injury (AKI) is characterized by an acute decline in renal function and is associated to increased mortality rate, hospitalization time, and total health-related costs. The severity of this ‘fearsome’ clinical complication might depend on, or even be worsened by, the late detection of A...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5829133/ https://www.ncbi.nlm.nih.gov/pubmed/28624882 http://dx.doi.org/10.1007/s40620-017-0416-8 |
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author | Pozzoli, Simona Simonini, Marco Manunta, Paolo |
author_facet | Pozzoli, Simona Simonini, Marco Manunta, Paolo |
author_sort | Pozzoli, Simona |
collection | PubMed |
description | Acute kidney injury (AKI) is characterized by an acute decline in renal function and is associated to increased mortality rate, hospitalization time, and total health-related costs. The severity of this ‘fearsome’ clinical complication might depend on, or even be worsened by, the late detection of AKI, when the diagnosis is based on the elevation of serum creatinine (SCr). For these reasons, in recent years a great number of new tools, biomarkers and predictive models have been proposed to clinicians in order to improve diagnosis and prevent the development of AKI. The purpose of this narrative paper is to review the current state of the art in prediction and early detection of AKI and outline future challenges. |
format | Online Article Text |
id | pubmed-5829133 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-58291332018-03-01 Predicting acute kidney injury: current status and future challenges Pozzoli, Simona Simonini, Marco Manunta, Paolo J Nephrol Review Acute kidney injury (AKI) is characterized by an acute decline in renal function and is associated to increased mortality rate, hospitalization time, and total health-related costs. The severity of this ‘fearsome’ clinical complication might depend on, or even be worsened by, the late detection of AKI, when the diagnosis is based on the elevation of serum creatinine (SCr). For these reasons, in recent years a great number of new tools, biomarkers and predictive models have been proposed to clinicians in order to improve diagnosis and prevent the development of AKI. The purpose of this narrative paper is to review the current state of the art in prediction and early detection of AKI and outline future challenges. Springer International Publishing 2017-06-17 2018 /pmc/articles/PMC5829133/ /pubmed/28624882 http://dx.doi.org/10.1007/s40620-017-0416-8 Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Review Pozzoli, Simona Simonini, Marco Manunta, Paolo Predicting acute kidney injury: current status and future challenges |
title | Predicting acute kidney injury: current status and future challenges |
title_full | Predicting acute kidney injury: current status and future challenges |
title_fullStr | Predicting acute kidney injury: current status and future challenges |
title_full_unstemmed | Predicting acute kidney injury: current status and future challenges |
title_short | Predicting acute kidney injury: current status and future challenges |
title_sort | predicting acute kidney injury: current status and future challenges |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5829133/ https://www.ncbi.nlm.nih.gov/pubmed/28624882 http://dx.doi.org/10.1007/s40620-017-0416-8 |
work_keys_str_mv | AT pozzolisimona predictingacutekidneyinjurycurrentstatusandfuturechallenges AT simoninimarco predictingacutekidneyinjurycurrentstatusandfuturechallenges AT manuntapaolo predictingacutekidneyinjurycurrentstatusandfuturechallenges |