Computerized algorithms compared with a nephrologist's diagnosis of acute kidney injury in the emergency department.
To access publisher's full text version of this article click on the hyperlink below The aim of this study was to examine acute kidney injury (AKI) diagnosis based on different computerized algorithms compared with a nephrologist's diagnosis in patients visiting an emergency department (ED...
Published in: | European Journal of Internal Medicine |
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Elsevier Science
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Online Access: | http://hdl.handle.net/2336/620876 https://doi.org/10.1016/j.ejim.2018.11.013 |
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ftlandspitaliuni:oai:www.hirsla.lsh.is:2336/620876 2023-05-15T16:51:49+02:00 Computerized algorithms compared with a nephrologist's diagnosis of acute kidney injury in the emergency department. Jonsson, Arnar Jan Kristjansdottir, Ingibjorg Lund, Sigrun Helga Palsson, Runolfur Indridason, Olafur S 1 University of Iceland, Reykjavik, Iceland; Internal Medicine Services, Landspitali - The National University Hospital of Iceland, Reykjavik, Iceland. 2 Internal Medicine Services, Landspitali - The National University Hospital of Iceland, Reykjavik, Iceland. 3 University of Iceland, Reykjavik, Iceland. 4 University of Iceland, Reykjavik, Iceland; Division of Nephrology, Landspitali - The National University Hospital of Iceland, Reykjavik, Iceland. 5 Division of Nephrology, Landspitali - The National University Hospital of Iceland, Reykjavik, Iceland. Electronic address: olasi@landspitali.is. 2019-04 http://hdl.handle.net/2336/620876 https://doi.org/10.1016/j.ejim.2018.11.013 en eng Elsevier Science https://www.sciencedirect.com/science/article/pii/S0953620518304655 Computerized algorithms compared with a nephrologist's diagnosis of acute kidney injury in the emergency department. 2019, 60:78-82 Eur J Intern Med 1879-0828 30545589 doi:10.1016/j.ejim.2018.11.013 http://hdl.handle.net/2336/620876 European journal of internal medicine National Consortium - Landsaðgangur European journal of internal medicine Acute kidney injury Computer algorithms Diagnosis KDIGO criteria Serum creatinine Nýrnabilun Reiknirit Algorithms Article 2019 ftlandspitaliuni https://doi.org/10.1016/j.ejim.2018.11.013 2022-05-29T08:22:25Z To access publisher's full text version of this article click on the hyperlink below The aim of this study was to examine acute kidney injury (AKI) diagnosis based on different computerized algorithms compared with a nephrologist's diagnosis in patients visiting an emergency department (ED) of a university hospital. In this retrospective study, we used electronic medical records at the University Hospital in Reykjavik to identify all patients aged ≥18 years, who presented to the ED in the year 2010 with an elevated serum creatinine (SCr) level. All SCr values were reviewed and a nephrologist determined whether AKI was present using the KDIGO SCr criteria and clinical data. Computerized algorithms based on the KDIGO SCr criteria, accounting for various time intervals for baseline SCr and changes in follow-up SCr, were constructed using the statiscal software R. At 53,816 ED visits, SCr was measured in 15,588 patients for a total of 21,559 measurements. Elevated SCr was observed in 2878 (18.4%) patients. Strict adherence to the KDIGO SCr criteria yielded a 79% sensitivity, 94% specificity, 68% positive predictive value (PPV) and 96% negative predictive value (NPV) for the diagnosis of AKI. Allowing for a longer time frame (>365 days) for baseline SCr, resulted in 93% sensitivity, 96% specificity, 80% PPV and 99% NPV. The algorithms which included a decrease in SCr from the index ED value yielded a sensitivity of 97% but lower specificity, 74% and 80%. The algorithms that perform best yield excellent sensitivity and specificity and could be used to identify patients with AKI in the ED to enhance early diagnosis and treatment. Landspitali University Hospital Science Fund, Reykjavik, Iceland Article in Journal/Newspaper Iceland Hirsla - Landspítali University Hospital research archive European Journal of Internal Medicine 60 78 82 |
institution |
Open Polar |
collection |
Hirsla - Landspítali University Hospital research archive |
op_collection_id |
ftlandspitaliuni |
language |
English |
topic |
Acute kidney injury Computer algorithms Diagnosis KDIGO criteria Serum creatinine Nýrnabilun Reiknirit Algorithms |
spellingShingle |
Acute kidney injury Computer algorithms Diagnosis KDIGO criteria Serum creatinine Nýrnabilun Reiknirit Algorithms Jonsson, Arnar Jan Kristjansdottir, Ingibjorg Lund, Sigrun Helga Palsson, Runolfur Indridason, Olafur S Computerized algorithms compared with a nephrologist's diagnosis of acute kidney injury in the emergency department. |
topic_facet |
Acute kidney injury Computer algorithms Diagnosis KDIGO criteria Serum creatinine Nýrnabilun Reiknirit Algorithms |
description |
To access publisher's full text version of this article click on the hyperlink below The aim of this study was to examine acute kidney injury (AKI) diagnosis based on different computerized algorithms compared with a nephrologist's diagnosis in patients visiting an emergency department (ED) of a university hospital. In this retrospective study, we used electronic medical records at the University Hospital in Reykjavik to identify all patients aged ≥18 years, who presented to the ED in the year 2010 with an elevated serum creatinine (SCr) level. All SCr values were reviewed and a nephrologist determined whether AKI was present using the KDIGO SCr criteria and clinical data. Computerized algorithms based on the KDIGO SCr criteria, accounting for various time intervals for baseline SCr and changes in follow-up SCr, were constructed using the statiscal software R. At 53,816 ED visits, SCr was measured in 15,588 patients for a total of 21,559 measurements. Elevated SCr was observed in 2878 (18.4%) patients. Strict adherence to the KDIGO SCr criteria yielded a 79% sensitivity, 94% specificity, 68% positive predictive value (PPV) and 96% negative predictive value (NPV) for the diagnosis of AKI. Allowing for a longer time frame (>365 days) for baseline SCr, resulted in 93% sensitivity, 96% specificity, 80% PPV and 99% NPV. The algorithms which included a decrease in SCr from the index ED value yielded a sensitivity of 97% but lower specificity, 74% and 80%. The algorithms that perform best yield excellent sensitivity and specificity and could be used to identify patients with AKI in the ED to enhance early diagnosis and treatment. Landspitali University Hospital Science Fund, Reykjavik, Iceland |
author2 |
1 University of Iceland, Reykjavik, Iceland; Internal Medicine Services, Landspitali - The National University Hospital of Iceland, Reykjavik, Iceland. 2 Internal Medicine Services, Landspitali - The National University Hospital of Iceland, Reykjavik, Iceland. 3 University of Iceland, Reykjavik, Iceland. 4 University of Iceland, Reykjavik, Iceland; Division of Nephrology, Landspitali - The National University Hospital of Iceland, Reykjavik, Iceland. 5 Division of Nephrology, Landspitali - The National University Hospital of Iceland, Reykjavik, Iceland. Electronic address: olasi@landspitali.is. |
format |
Article in Journal/Newspaper |
author |
Jonsson, Arnar Jan Kristjansdottir, Ingibjorg Lund, Sigrun Helga Palsson, Runolfur Indridason, Olafur S |
author_facet |
Jonsson, Arnar Jan Kristjansdottir, Ingibjorg Lund, Sigrun Helga Palsson, Runolfur Indridason, Olafur S |
author_sort |
Jonsson, Arnar Jan |
title |
Computerized algorithms compared with a nephrologist's diagnosis of acute kidney injury in the emergency department. |
title_short |
Computerized algorithms compared with a nephrologist's diagnosis of acute kidney injury in the emergency department. |
title_full |
Computerized algorithms compared with a nephrologist's diagnosis of acute kidney injury in the emergency department. |
title_fullStr |
Computerized algorithms compared with a nephrologist's diagnosis of acute kidney injury in the emergency department. |
title_full_unstemmed |
Computerized algorithms compared with a nephrologist's diagnosis of acute kidney injury in the emergency department. |
title_sort |
computerized algorithms compared with a nephrologist's diagnosis of acute kidney injury in the emergency department. |
publisher |
Elsevier Science |
publishDate |
2019 |
url |
http://hdl.handle.net/2336/620876 https://doi.org/10.1016/j.ejim.2018.11.013 |
genre |
Iceland |
genre_facet |
Iceland |
op_source |
European journal of internal medicine |
op_relation |
https://www.sciencedirect.com/science/article/pii/S0953620518304655 Computerized algorithms compared with a nephrologist's diagnosis of acute kidney injury in the emergency department. 2019, 60:78-82 Eur J Intern Med 1879-0828 30545589 doi:10.1016/j.ejim.2018.11.013 http://hdl.handle.net/2336/620876 European journal of internal medicine |
op_rights |
National Consortium - Landsaðgangur |
op_doi |
https://doi.org/10.1016/j.ejim.2018.11.013 |
container_title |
European Journal of Internal Medicine |
container_volume |
60 |
container_start_page |
78 |
op_container_end_page |
82 |
_version_ |
1766041937002889216 |