Prediction of acute kidney injury in mechanically ventilated patients with COVID-19-related septic shock: An exploratory analysis of non-renal organ dysfunction markers
Abstract
Background
Acute kidney injury (AKI) is a common and serious complication in critically ill patients with non-kidney organ dysfunction. Early prediction of AKI is crucial for timely intervention and improved outcomes. This study aimed to identify readily available non-renal predictors of AKI and to develop an exploratory prediction model in a specific cohort of critically ill patients with COVID-19-related septic shock requiring mechanical ventilation.
Materials and methods
This was a single-center, observational, retrospective cohort study conducted in the respiratory ICU of Hospital H+ Querétaro between April and December 2020. The study included 42 mechanically ventilated patients with septic shock secondary to SARS-CoV-2 infection and non-kidney organ dysfunction. AKI was defined using the KDIGO criteria. Trend analysis, bivariate and multivariate linear regression, were used to identify predictors of AKI and severe AKI.
Results
AKI occurred in 23 (54.8%) patients, with 6 (14.3%) developing severe AKI. Trend analysis revealed differences in norepinephrine dose, hemoglobin, and lactate trends between groups. A simplified logistic regression model, validated internally with bootstrapping to prevent overfitting, identified a protective trend associated with higher hemoglobin levels on admission. Quantitative analysis of a forecasting model for daily renal function showed moderate predictive accuracy.
Conclusions
This study identified several readily available non-kidney organ dysfunction variables that can predict AKI and its severity in critically ill patients with COVID-19-related septic shock. These findings may help in the early identification of at-risk patients and facilitate timely interventions to potentially improve outcomes. Further validation in larger and more diverse populations is warranted.
© 2026 Jose J. Zaragoza, Jonathan S. Chávez-Iñiguez, Armando Vazquez-Rangel, published by University of Medicine, Pharmacy, Science and Technology of Targu Mures
This work is licensed under the Creative Commons Attribution 4.0 License.