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A validation study of UCSD-Mayo risk score in predicting hospital-acquired acute kidney injury in COVID-19 patients

INTRODUCTION: Acute kidney injury (AKI) in coronavirus disease 2019 (COVID-19) patients is associated with poor prognosis. Early prediction and intervention of AKI are vital for improving clinical outcome of COVID-19 patients. As lack of tools for early AKI detection in COVID-19 patients, this study...

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Autores principales: Fang, Zhengying, Gao, Chenni, Cai, Yikai, Lu, Lin, Yu, Haijin, Hussain, Hafiz Muhammad Jafar, Chen, Zijin, Li, Chuanlei, Wei, Wenjie, Huang, Yuhan, Li, Xiang, Yu, Shuwen, Ji, Yinhong, Weng, Qinjie, Ouyang, Yan, Hu, Xiaofan, Tong, Jun, Liu, Jian, Liu, Mingyu, Xu, Xiaoman, Zha, Yixin, Ye, Zhiyin, Jiang, Tingting, Jia, Jieshuang, Liu, Jialin, Bi, Yufang, Chen, Nan, Hu, Weiguo, Wang, Huiming, Liu, Jun, Xie, Jingyuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8274539/
https://www.ncbi.nlm.nih.gov/pubmed/34233570
http://dx.doi.org/10.1080/0886022X.2021.1948429
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author Fang, Zhengying
Gao, Chenni
Cai, Yikai
Lu, Lin
Yu, Haijin
Hussain, Hafiz Muhammad Jafar
Chen, Zijin
Li, Chuanlei
Wei, Wenjie
Huang, Yuhan
Li, Xiang
Yu, Shuwen
Ji, Yinhong
Weng, Qinjie
Ouyang, Yan
Hu, Xiaofan
Tong, Jun
Liu, Jian
Liu, Mingyu
Xu, Xiaoman
Zha, Yixin
Ye, Zhiyin
Jiang, Tingting
Jia, Jieshuang
Liu, Jialin
Bi, Yufang
Chen, Nan
Hu, Weiguo
Wang, Huiming
Liu, Jun
Xie, Jingyuan
author_facet Fang, Zhengying
Gao, Chenni
Cai, Yikai
Lu, Lin
Yu, Haijin
Hussain, Hafiz Muhammad Jafar
Chen, Zijin
Li, Chuanlei
Wei, Wenjie
Huang, Yuhan
Li, Xiang
Yu, Shuwen
Ji, Yinhong
Weng, Qinjie
Ouyang, Yan
Hu, Xiaofan
Tong, Jun
Liu, Jian
Liu, Mingyu
Xu, Xiaoman
Zha, Yixin
Ye, Zhiyin
Jiang, Tingting
Jia, Jieshuang
Liu, Jialin
Bi, Yufang
Chen, Nan
Hu, Weiguo
Wang, Huiming
Liu, Jun
Xie, Jingyuan
author_sort Fang, Zhengying
collection PubMed
description INTRODUCTION: Acute kidney injury (AKI) in coronavirus disease 2019 (COVID-19) patients is associated with poor prognosis. Early prediction and intervention of AKI are vital for improving clinical outcome of COVID-19 patients. As lack of tools for early AKI detection in COVID-19 patients, this study aimed to validate the USCD-Mayo risk score in predicting hospital-acquired AKI in an extended multi-center COVID-19 cohort. METHODS: Five hundred seventy-two COVID-19 patients from Wuhan Tongji Hospital Guanggu Branch, Wuhan Leishenshan Hospital, and Wuhan No. Ninth Hospital was enrolled for this study. Patients who developed AKI or reached an outcome of recovery or death during the study period were included. Predictors were evaluated according to data extracted from medical records. RESULTS: Of all patients, a total of 44 (8%) developed AKI. The UCSD-Mayo risk score achieved excellent discrimination in predicting AKI with the C-statistic of 0.88 (95%CI: 0.84–0.91). Next, we determined the UCSD-Mayo risk score had good overall performance (Nagelkerke R(2) = 0.32) and calibration in our cohort. Further analysis showed that the UCSD-Mayo risk score performed well in subgroups defined by gender, age, and several chronic comorbidities. However, the discrimination of the UCSD-Mayo risk score in ICU patients and patients with mechanical ventilation was not good which might be resulted from different risk factors of these patients. CONCLUSIONS: We validated the performance of UCSD-Mayo risk score in predicting hospital-acquired AKI in COVID-19 patients was excellent except for patients from ICU or patients with mechanical ventilation.
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spelling pubmed-82745392021-07-20 A validation study of UCSD-Mayo risk score in predicting hospital-acquired acute kidney injury in COVID-19 patients Fang, Zhengying Gao, Chenni Cai, Yikai Lu, Lin Yu, Haijin Hussain, Hafiz Muhammad Jafar Chen, Zijin Li, Chuanlei Wei, Wenjie Huang, Yuhan Li, Xiang Yu, Shuwen Ji, Yinhong Weng, Qinjie Ouyang, Yan Hu, Xiaofan Tong, Jun Liu, Jian Liu, Mingyu Xu, Xiaoman Zha, Yixin Ye, Zhiyin Jiang, Tingting Jia, Jieshuang Liu, Jialin Bi, Yufang Chen, Nan Hu, Weiguo Wang, Huiming Liu, Jun Xie, Jingyuan Ren Fail Clinical Study INTRODUCTION: Acute kidney injury (AKI) in coronavirus disease 2019 (COVID-19) patients is associated with poor prognosis. Early prediction and intervention of AKI are vital for improving clinical outcome of COVID-19 patients. As lack of tools for early AKI detection in COVID-19 patients, this study aimed to validate the USCD-Mayo risk score in predicting hospital-acquired AKI in an extended multi-center COVID-19 cohort. METHODS: Five hundred seventy-two COVID-19 patients from Wuhan Tongji Hospital Guanggu Branch, Wuhan Leishenshan Hospital, and Wuhan No. Ninth Hospital was enrolled for this study. Patients who developed AKI or reached an outcome of recovery or death during the study period were included. Predictors were evaluated according to data extracted from medical records. RESULTS: Of all patients, a total of 44 (8%) developed AKI. The UCSD-Mayo risk score achieved excellent discrimination in predicting AKI with the C-statistic of 0.88 (95%CI: 0.84–0.91). Next, we determined the UCSD-Mayo risk score had good overall performance (Nagelkerke R(2) = 0.32) and calibration in our cohort. Further analysis showed that the UCSD-Mayo risk score performed well in subgroups defined by gender, age, and several chronic comorbidities. However, the discrimination of the UCSD-Mayo risk score in ICU patients and patients with mechanical ventilation was not good which might be resulted from different risk factors of these patients. CONCLUSIONS: We validated the performance of UCSD-Mayo risk score in predicting hospital-acquired AKI in COVID-19 patients was excellent except for patients from ICU or patients with mechanical ventilation. Taylor & Francis 2021-07-07 /pmc/articles/PMC8274539/ /pubmed/34233570 http://dx.doi.org/10.1080/0886022X.2021.1948429 Text en © 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Clinical Study
Fang, Zhengying
Gao, Chenni
Cai, Yikai
Lu, Lin
Yu, Haijin
Hussain, Hafiz Muhammad Jafar
Chen, Zijin
Li, Chuanlei
Wei, Wenjie
Huang, Yuhan
Li, Xiang
Yu, Shuwen
Ji, Yinhong
Weng, Qinjie
Ouyang, Yan
Hu, Xiaofan
Tong, Jun
Liu, Jian
Liu, Mingyu
Xu, Xiaoman
Zha, Yixin
Ye, Zhiyin
Jiang, Tingting
Jia, Jieshuang
Liu, Jialin
Bi, Yufang
Chen, Nan
Hu, Weiguo
Wang, Huiming
Liu, Jun
Xie, Jingyuan
A validation study of UCSD-Mayo risk score in predicting hospital-acquired acute kidney injury in COVID-19 patients
title A validation study of UCSD-Mayo risk score in predicting hospital-acquired acute kidney injury in COVID-19 patients
title_full A validation study of UCSD-Mayo risk score in predicting hospital-acquired acute kidney injury in COVID-19 patients
title_fullStr A validation study of UCSD-Mayo risk score in predicting hospital-acquired acute kidney injury in COVID-19 patients
title_full_unstemmed A validation study of UCSD-Mayo risk score in predicting hospital-acquired acute kidney injury in COVID-19 patients
title_short A validation study of UCSD-Mayo risk score in predicting hospital-acquired acute kidney injury in COVID-19 patients
title_sort validation study of ucsd-mayo risk score in predicting hospital-acquired acute kidney injury in covid-19 patients
topic Clinical Study
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8274539/
https://www.ncbi.nlm.nih.gov/pubmed/34233570
http://dx.doi.org/10.1080/0886022X.2021.1948429
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