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The Prediction Score of Acute Kidney Injury in Patients with Severe COVID-19 Infection

Background: The incidence and risk factors for acute kidney injury in COVID-19 patients vary across studies, and predicting models for AKI are limited. This study aimed to identify the risk factors for AKI in severe COVID-19 infection and develop a predictive model for AKI. Method: Data were collect...

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Autores principales: Anumas, Suthiya, Chueachinda, Supoj, Tantiyavarong, Pichaya, Pattharanitima, Pattharawin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10342471/
https://www.ncbi.nlm.nih.gov/pubmed/37445447
http://dx.doi.org/10.3390/jcm12134412
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author Anumas, Suthiya
Chueachinda, Supoj
Tantiyavarong, Pichaya
Pattharanitima, Pattharawin
author_facet Anumas, Suthiya
Chueachinda, Supoj
Tantiyavarong, Pichaya
Pattharanitima, Pattharawin
author_sort Anumas, Suthiya
collection PubMed
description Background: The incidence and risk factors for acute kidney injury in COVID-19 patients vary across studies, and predicting models for AKI are limited. This study aimed to identify the risk factors for AKI in severe COVID-19 infection and develop a predictive model for AKI. Method: Data were collected from patients admitted to the ICU at Thammasat University Hospital in Thailand with PCR-confirmed COVID-19 between 1 January 2021, and 30 June 2022. Results: Among the 215 severe-COVID-19-infected patients, 102 (47.4%) experienced AKI. Of these, 45 (44.1%), 29 (28.4%), and 28 (27.4%) patients were classified as AKI stage 1, 2, and 3, respectively. AKI was associated with 30-day mortality. Multivariate logistic regression analysis revealed that prior diuretic use (odds ratio [OR] 7.87, 95% confidence interval [CI] 1.98–31.3; p = 0.003), use of a mechanical ventilator (MV) (OR 5.34, 95%CI 1.76–16.18; p = 0.003), and an APACHE II score ≥ 12 (OR 1.14, 95%CI 1.05–1.24; p = 0.002) were independent risk factors for AKI. A predictive model for AKI demonstrated good performance (AUROC 0.814, 95%CI 0.757–0.870). Conclusions: Our study identified risk factors for AKI in severe COVID-19 infection, including prior diuretic use, an APACHE II score ≥ 12, and the use of a MV. The predictive tool exhibited good performance for predicting AKI.
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spelling pubmed-103424712023-07-14 The Prediction Score of Acute Kidney Injury in Patients with Severe COVID-19 Infection Anumas, Suthiya Chueachinda, Supoj Tantiyavarong, Pichaya Pattharanitima, Pattharawin J Clin Med Article Background: The incidence and risk factors for acute kidney injury in COVID-19 patients vary across studies, and predicting models for AKI are limited. This study aimed to identify the risk factors for AKI in severe COVID-19 infection and develop a predictive model for AKI. Method: Data were collected from patients admitted to the ICU at Thammasat University Hospital in Thailand with PCR-confirmed COVID-19 between 1 January 2021, and 30 June 2022. Results: Among the 215 severe-COVID-19-infected patients, 102 (47.4%) experienced AKI. Of these, 45 (44.1%), 29 (28.4%), and 28 (27.4%) patients were classified as AKI stage 1, 2, and 3, respectively. AKI was associated with 30-day mortality. Multivariate logistic regression analysis revealed that prior diuretic use (odds ratio [OR] 7.87, 95% confidence interval [CI] 1.98–31.3; p = 0.003), use of a mechanical ventilator (MV) (OR 5.34, 95%CI 1.76–16.18; p = 0.003), and an APACHE II score ≥ 12 (OR 1.14, 95%CI 1.05–1.24; p = 0.002) were independent risk factors for AKI. A predictive model for AKI demonstrated good performance (AUROC 0.814, 95%CI 0.757–0.870). Conclusions: Our study identified risk factors for AKI in severe COVID-19 infection, including prior diuretic use, an APACHE II score ≥ 12, and the use of a MV. The predictive tool exhibited good performance for predicting AKI. MDPI 2023-06-30 /pmc/articles/PMC10342471/ /pubmed/37445447 http://dx.doi.org/10.3390/jcm12134412 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Anumas, Suthiya
Chueachinda, Supoj
Tantiyavarong, Pichaya
Pattharanitima, Pattharawin
The Prediction Score of Acute Kidney Injury in Patients with Severe COVID-19 Infection
title The Prediction Score of Acute Kidney Injury in Patients with Severe COVID-19 Infection
title_full The Prediction Score of Acute Kidney Injury in Patients with Severe COVID-19 Infection
title_fullStr The Prediction Score of Acute Kidney Injury in Patients with Severe COVID-19 Infection
title_full_unstemmed The Prediction Score of Acute Kidney Injury in Patients with Severe COVID-19 Infection
title_short The Prediction Score of Acute Kidney Injury in Patients with Severe COVID-19 Infection
title_sort prediction score of acute kidney injury in patients with severe covid-19 infection
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10342471/
https://www.ncbi.nlm.nih.gov/pubmed/37445447
http://dx.doi.org/10.3390/jcm12134412
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