Cargando…

Using dipstick urinalysis to predict development of acute kidney injury in patients with COVID-19

BACKGROUND: Acute kidney injury (AKI) is a common complication in patients hospitalized with COVID-19 and may require renal replacement therapy (RRT). Dipstick urinalysis is frequently obtained, but data regarding the prognostic value of hematuria and proteinuria for kidney outcomes is scarce. METHO...

Descripción completa

Detalles Bibliográficos
Autores principales: McAdams, Meredith C., Li, Michael, Xu, Pin, Gregg, L. Parker, Patel, Jiten, Willett, Duwayne L., Velasco, Ferdinand, Lehmann, Christoph U., Hedayati, S. Susan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8805668/
https://www.ncbi.nlm.nih.gov/pubmed/35105331
http://dx.doi.org/10.1186/s12882-022-02677-y
_version_ 1784643277478166528
author McAdams, Meredith C.
Li, Michael
Xu, Pin
Gregg, L. Parker
Patel, Jiten
Willett, Duwayne L.
Velasco, Ferdinand
Lehmann, Christoph U.
Hedayati, S. Susan
author_facet McAdams, Meredith C.
Li, Michael
Xu, Pin
Gregg, L. Parker
Patel, Jiten
Willett, Duwayne L.
Velasco, Ferdinand
Lehmann, Christoph U.
Hedayati, S. Susan
author_sort McAdams, Meredith C.
collection PubMed
description BACKGROUND: Acute kidney injury (AKI) is a common complication in patients hospitalized with COVID-19 and may require renal replacement therapy (RRT). Dipstick urinalysis is frequently obtained, but data regarding the prognostic value of hematuria and proteinuria for kidney outcomes is scarce. METHODS: Patients with positive severe acute respiratory syndrome-coronavirus 2 (SARS-CoV2) PCR, who had a urinalysis obtained on admission to one of 20 hospitals, were included. Nested models with degree of hematuria and proteinuria were used to predict AKI and RRT during admission. Presence of Chronic Kidney Disease (CKD) and baseline serum creatinine were added to test improvement in model fit. RESULTS: Of 5,980 individuals, 829 (13.9%) developed an AKI during admission, and 149 (18.0%) of those with AKI received RRT. Proteinuria and hematuria degrees significantly increased with AKI severity (P < 0.001 for both). Any degree of proteinuria and hematuria was associated with an increased risk of AKI and RRT. In predictive models for AKI, presence of CKD improved the area under the curve (AUC) (95% confidence interval) to 0.73 (0.71, 0.75), P < 0.001, and adding baseline creatinine improved the AUC to 0.85 (0.83, 0.86), P < 0.001, when compared to the base model AUC using only proteinuria and hematuria, AUC = 0.64 (0.62, 0.67). In RRT models, CKD status improved the AUC to 0.78 (0.75, 0.82), P < 0.001, and baseline creatinine improved the AUC to 0.84 (0.80, 0.88), P < 0.001, compared to the base model, AUC = 0.72 (0.68, 0.76). There was no significant improvement in model discrimination when both CKD and baseline serum creatinine were included. CONCLUSIONS: Proteinuria and hematuria values on dipstick urinalysis can be utilized to predict AKI and RRT in hospitalized patients with COVID-19. We derived formulas using these two readily available values to help prognosticate kidney outcomes in these patients. Furthermore, the incorporation of CKD or baseline creatinine increases the accuracy of these formulas. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12882-022-02677-y.
format Online
Article
Text
id pubmed-8805668
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-88056682022-02-02 Using dipstick urinalysis to predict development of acute kidney injury in patients with COVID-19 McAdams, Meredith C. Li, Michael Xu, Pin Gregg, L. Parker Patel, Jiten Willett, Duwayne L. Velasco, Ferdinand Lehmann, Christoph U. Hedayati, S. Susan BMC Nephrol Research BACKGROUND: Acute kidney injury (AKI) is a common complication in patients hospitalized with COVID-19 and may require renal replacement therapy (RRT). Dipstick urinalysis is frequently obtained, but data regarding the prognostic value of hematuria and proteinuria for kidney outcomes is scarce. METHODS: Patients with positive severe acute respiratory syndrome-coronavirus 2 (SARS-CoV2) PCR, who had a urinalysis obtained on admission to one of 20 hospitals, were included. Nested models with degree of hematuria and proteinuria were used to predict AKI and RRT during admission. Presence of Chronic Kidney Disease (CKD) and baseline serum creatinine were added to test improvement in model fit. RESULTS: Of 5,980 individuals, 829 (13.9%) developed an AKI during admission, and 149 (18.0%) of those with AKI received RRT. Proteinuria and hematuria degrees significantly increased with AKI severity (P < 0.001 for both). Any degree of proteinuria and hematuria was associated with an increased risk of AKI and RRT. In predictive models for AKI, presence of CKD improved the area under the curve (AUC) (95% confidence interval) to 0.73 (0.71, 0.75), P < 0.001, and adding baseline creatinine improved the AUC to 0.85 (0.83, 0.86), P < 0.001, when compared to the base model AUC using only proteinuria and hematuria, AUC = 0.64 (0.62, 0.67). In RRT models, CKD status improved the AUC to 0.78 (0.75, 0.82), P < 0.001, and baseline creatinine improved the AUC to 0.84 (0.80, 0.88), P < 0.001, compared to the base model, AUC = 0.72 (0.68, 0.76). There was no significant improvement in model discrimination when both CKD and baseline serum creatinine were included. CONCLUSIONS: Proteinuria and hematuria values on dipstick urinalysis can be utilized to predict AKI and RRT in hospitalized patients with COVID-19. We derived formulas using these two readily available values to help prognosticate kidney outcomes in these patients. Furthermore, the incorporation of CKD or baseline creatinine increases the accuracy of these formulas. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12882-022-02677-y. BioMed Central 2022-02-01 /pmc/articles/PMC8805668/ /pubmed/35105331 http://dx.doi.org/10.1186/s12882-022-02677-y Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
McAdams, Meredith C.
Li, Michael
Xu, Pin
Gregg, L. Parker
Patel, Jiten
Willett, Duwayne L.
Velasco, Ferdinand
Lehmann, Christoph U.
Hedayati, S. Susan
Using dipstick urinalysis to predict development of acute kidney injury in patients with COVID-19
title Using dipstick urinalysis to predict development of acute kidney injury in patients with COVID-19
title_full Using dipstick urinalysis to predict development of acute kidney injury in patients with COVID-19
title_fullStr Using dipstick urinalysis to predict development of acute kidney injury in patients with COVID-19
title_full_unstemmed Using dipstick urinalysis to predict development of acute kidney injury in patients with COVID-19
title_short Using dipstick urinalysis to predict development of acute kidney injury in patients with COVID-19
title_sort using dipstick urinalysis to predict development of acute kidney injury in patients with covid-19
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8805668/
https://www.ncbi.nlm.nih.gov/pubmed/35105331
http://dx.doi.org/10.1186/s12882-022-02677-y
work_keys_str_mv AT mcadamsmeredithc usingdipstickurinalysistopredictdevelopmentofacutekidneyinjuryinpatientswithcovid19
AT limichael usingdipstickurinalysistopredictdevelopmentofacutekidneyinjuryinpatientswithcovid19
AT xupin usingdipstickurinalysistopredictdevelopmentofacutekidneyinjuryinpatientswithcovid19
AT gregglparker usingdipstickurinalysistopredictdevelopmentofacutekidneyinjuryinpatientswithcovid19
AT pateljiten usingdipstickurinalysistopredictdevelopmentofacutekidneyinjuryinpatientswithcovid19
AT willettduwaynel usingdipstickurinalysistopredictdevelopmentofacutekidneyinjuryinpatientswithcovid19
AT velascoferdinand usingdipstickurinalysistopredictdevelopmentofacutekidneyinjuryinpatientswithcovid19
AT lehmannchristophu usingdipstickurinalysistopredictdevelopmentofacutekidneyinjuryinpatientswithcovid19
AT hedayatissusan usingdipstickurinalysistopredictdevelopmentofacutekidneyinjuryinpatientswithcovid19