Kidney Week

Abstract: SA-PO0291

Prediction of AKI in Mechanically Ventilated Patients with COVID-19-Related Septic Shock: An Exploratory Analysis of Nonrenal Organ Dysfunction Markers

Session Information

• AKI: Epidemiology and Risk Factors
  October 24, 2026 | Location: Exhibit Hall A, Convention Center
  Abstract Time: 10:00 AM - 12:00 PM

Category: Acute Kidney Injury

• 101 AKI: Epidemiology, Risk Factors, and Prevention

Authors

• Renoirte, Karina, Hospital Civil de Guadalajara, Guadalajara, Jal., Mexico

Karina Renoirte, PhD

• Arizaga Napoles, Manuel, Hospital Civil de Guadalajara, Guadalajara, Jal., Mexico

Manuel Arizaga Napoles, MD

• Chavez, Jonathan, Hospital Civil de Guadalajara, Guadalajara, Jal., Mexico

Jonathan Chavez, MD, PhD

• Navarro Blackaller, Guillermo, Hospital Civil de Guadalajara, Guadalajara, Jal., Mexico

Guillermo Navarro Blackaller, MD

• Medina, Ramon, Hospital Civil de Guadalajara, Guadalajara, Jal., Mexico

Ramon Medina, MD

• Alcantar Vallin, Maria de la Luz, Hospital Civil de Guadalajara, Guadalajara, Jal., Mexico

Maria de la Luz Alcantar Vallin, MD

• Martínez Gallardo González, Alejandro, Hospital Civil de Guadalajara, Guadalajara, Jal., Mexico

Alejandro Martínez Gallardo González

• Gómez, Juan Alberto, Hospital Civil de Guadalajara, Guadalajara, Jal., Mexico

Juan Alberto Gómez, MD

• Garcia-Garcia, Guillermo, Universidad de Guadalajara, Guadalajara, Jal., Mexico

Guillermo Garcia-Garcia, MD, FASN

• Mendoza Gaitán, Héctor Eduardo, Hospital Civil de Guadalajara, Guadalajara, Jal., Mexico

Héctor Eduardo Mendoza Gaitán, MD

• Zaragoza, Jose Jesus, Hospital Q+, Queretaro, Mexico

Jose Jesus Zaragoza, MD

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.

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.

Conclusion

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.