Back to Journals » Clinical Interventions in Aging » Volume 15

Acute Kidney Injury Can Predict In-Hospital Mortality in Elderly Patients with COVID-19 in the ICU: A Single-Center Study

Authors Li Q, Zhang T, Li F, Mao Z, Kang H, Tao L, Zhou F, Cai Y

Received 28 July 2020

Accepted for publication 20 September 2020

Published 9 November 2020 Volume 2020:15 Pages 2095—2107

DOI https://doi.org/10.2147/CIA.S273720

Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 2

Editor who approved publication: Prof. Dr. Zhi-Ying Wu


Qinglin Li, 1,* Tianyi Zhang, 2,* Fei Li, 3, 4,* Zhi Mao, 1 Hongjun Kang, 1 Ling Tao, 3,* Feihu Zhou, 1,* Yue Cai  3, 4,*

1Department of Critical Care Medicine, The First Medical Centre, Chinese PLA General Hospital, Beijing 100853, People’s Republic of China; 2Institution of Hospital Management, Medical Innovation Research Division of Chinese PLA General Hospital, Beijing 100853, People’s Republic of China; 3Department of Cardiology, Xijing Hospital, Xi’an 710032, People’s Republic of China; 4Department of Infectious Diseases, Huo Shen Shan Hospital, Wuhan, People’s Republic of China

*These authors contributed equally to this work

Correspondence: Feihu Zhou Tel +86 10 6693 8148
Email feihuzhou301@126.com
Yue Cai Tel + 86 159 0238 8078
Email caiyueclear1981@163.com

Objective: Severe or critical patients with coronavirus disease 2019 (COVID-19) are at increased risk for developing acute kidney injury (AKI). However, the rate of AKI in patients of different severities and independent predictive factors associated with AKI are not well understood.
Patients and Methods: We enrolled 107 severely or critically ill elderly patients with COVID-19 who were admitted to the intensive care unit (ICU) in Wuhan, China. AKI was defined according to the 2012 KDIGO criteria. We explored the association between AKI and in-hospital mortality using logistic regression. A predictive nomogram was formulated to predict the AKI development of patients with COVID-19 based on multivariate logistic regression.
Results: A total of 107 elderly patients were enrolled during the study period. The mean age was 70 (64– 78) years, and 69 (64.5%) were men. For the 107 patients, the degree of severity of COVID-19 was categorized as 37 patients with the severe type (34.6%) and 70 patients with the critical type (65.4%). Overall, 48 of the 107 patients (44.9%) developed AKI during their hospitalization, while AKI occurred in 7 (18.9%) out of the 37 severe patients and 41 (44.9%) out of the 70 critical patients. Of the AKI patients, 35.4% (17/48) required continuous renal replacement therapy, including 14.3% of AKI patients in severe cases and 39.0% of AKI patients in critical cases. Kaplan–Meier analysis demonstrated that patients with AKI had a significantly higher risk for in-hospital mortality than severely and critically ill patients without AKI. Multivariate logistic regression analysis showed that AKI (OR = 33.74; 95% CI = 3.34– 341.29; P = 0.003), septic shock (OR = 15.58; 95% CI = 2.08– 116.78; P = 0.008), invasive mechanical ventilation (OR = 18.44; 95% CI = 2.35– 144.69; P = 0.006), and oxygenation index (OR = 0.99; 95% CI = 0.98– 1.000; P = 0.014) were independent risk factors for in-hospital mortality. A nomogram was established based on the multivariate analysis results. The C-index for the developed AKI model was 0.935 (95% CI, 0.892– 0.978); when 10-fold cross validation was used to validate the model, the corrected C-index was 0.825.
Conclusion: AKI is common among COVID-19 patients admitted to the ICU and is recognized as a marker of disease severity. The proposed nomogram accurately predicted AKI development in ICU patients with COVID-19 based on individual characteristics. Therefore, the strategy for kidney protection against severe or critical pneumonia is appropriate.

Keywords: coronavirus disease 2019, acute kidney injury, diagnosis, nomogram, in-hospital mortality

Creative Commons License This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution - Non Commercial (unported, v3.0) License. By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms.

Download Article [PDF]  View Full Text [HTML][Machine readable]