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Urine abnormalities predict acute kidney injury in COVID-19 patients: An analysis of 110 cases in Chennai, South India
BACKGROUND AND AIMS: Renal involvement in Covid-19 infection is varied and can affect glomeruli, tubules, interstitium and can cause acute kidney injury (AKI). AKI is a strong predictor of mortality. Routine urinalysis gives an insight into the renal pathology of the patient. We studied the incidenc...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Diabetes India. Published by Elsevier Ltd.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7832278/ https://www.ncbi.nlm.nih.gov/pubmed/33383438 http://dx.doi.org/10.1016/j.dsx.2020.12.021 |
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author | Sundaram, Supraja Soni, Mamta Annigeri, Rajeev |
author_facet | Sundaram, Supraja Soni, Mamta Annigeri, Rajeev |
author_sort | Sundaram, Supraja |
collection | PubMed |
description | BACKGROUND AND AIMS: Renal involvement in Covid-19 infection is varied and can affect glomeruli, tubules, interstitium and can cause acute kidney injury (AKI). AKI is a strong predictor of mortality. Routine urinalysis gives an insight into the renal pathology of the patient. We studied the incidence of urinary abnormalities in hospitalised Covid-19 patients and analysed their impact on development of AKI and mortality. METHODS: Information on 110 hospitalised patients with confirmed Covid-19 was retrospectively collected and analysed. The demographic data such as age, gender, comorbid conditions such as diabetes mellitus, the need for dialysis and laboratory data such as urine for albumin, glucose, RBC and WBC, and serum creatinine were collected. The diagnosis of AKI was based on the KDIGO criteria. The outcomes studied were development of AKI and hospital mortality. RESULTS: Urine abnormalities were seen in 71% of the patients. Proteinuria in 58.2%, haematuria in 17.3%, pyuria in 8.2% of patients and concurrent proteinuria and haematuria was seen in 13.6% of patients. AKI was seen in 28.2% of patients and hospital mortality was 24.5%. AKI was strongly associated with mortality. Proteinuria and haematuria were good predictors of development of AKI, more strongly when they occurred concurrently (p < 0.01). CONCLUSION: Our results suggest that urine analysis is a simple test, which can be used to predict development of AKI and mortality and may be used for risk stratification of Covid-19 patients, especially in low resource settings. |
format | Online Article Text |
id | pubmed-7832278 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Diabetes India. Published by Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-78322782021-01-26 Urine abnormalities predict acute kidney injury in COVID-19 patients: An analysis of 110 cases in Chennai, South India Sundaram, Supraja Soni, Mamta Annigeri, Rajeev Diabetes Metab Syndr Article BACKGROUND AND AIMS: Renal involvement in Covid-19 infection is varied and can affect glomeruli, tubules, interstitium and can cause acute kidney injury (AKI). AKI is a strong predictor of mortality. Routine urinalysis gives an insight into the renal pathology of the patient. We studied the incidence of urinary abnormalities in hospitalised Covid-19 patients and analysed their impact on development of AKI and mortality. METHODS: Information on 110 hospitalised patients with confirmed Covid-19 was retrospectively collected and analysed. The demographic data such as age, gender, comorbid conditions such as diabetes mellitus, the need for dialysis and laboratory data such as urine for albumin, glucose, RBC and WBC, and serum creatinine were collected. The diagnosis of AKI was based on the KDIGO criteria. The outcomes studied were development of AKI and hospital mortality. RESULTS: Urine abnormalities were seen in 71% of the patients. Proteinuria in 58.2%, haematuria in 17.3%, pyuria in 8.2% of patients and concurrent proteinuria and haematuria was seen in 13.6% of patients. AKI was seen in 28.2% of patients and hospital mortality was 24.5%. AKI was strongly associated with mortality. Proteinuria and haematuria were good predictors of development of AKI, more strongly when they occurred concurrently (p < 0.01). CONCLUSION: Our results suggest that urine analysis is a simple test, which can be used to predict development of AKI and mortality and may be used for risk stratification of Covid-19 patients, especially in low resource settings. Diabetes India. Published by Elsevier Ltd. 2021 2020-12-19 /pmc/articles/PMC7832278/ /pubmed/33383438 http://dx.doi.org/10.1016/j.dsx.2020.12.021 Text en © 2020 Diabetes India. Published by Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Sundaram, Supraja Soni, Mamta Annigeri, Rajeev Urine abnormalities predict acute kidney injury in COVID-19 patients: An analysis of 110 cases in Chennai, South India |
title | Urine abnormalities predict acute kidney injury in COVID-19 patients: An analysis of 110 cases in Chennai, South India |
title_full | Urine abnormalities predict acute kidney injury in COVID-19 patients: An analysis of 110 cases in Chennai, South India |
title_fullStr | Urine abnormalities predict acute kidney injury in COVID-19 patients: An analysis of 110 cases in Chennai, South India |
title_full_unstemmed | Urine abnormalities predict acute kidney injury in COVID-19 patients: An analysis of 110 cases in Chennai, South India |
title_short | Urine abnormalities predict acute kidney injury in COVID-19 patients: An analysis of 110 cases in Chennai, South India |
title_sort | urine abnormalities predict acute kidney injury in covid-19 patients: an analysis of 110 cases in chennai, south india |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7832278/ https://www.ncbi.nlm.nih.gov/pubmed/33383438 http://dx.doi.org/10.1016/j.dsx.2020.12.021 |
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