ABSTRACT
Abstract Background: A high incidence of acute kidney injury (AKI) has been reported in coronavirus disease 2019 (COVID-19) patients in critical care units and those undergoing invasive mechanical ventilation (IMV). The introduction of dexamethasone (DXM) as treatment for severe COVID-19 has improved mortality, but its effects in other organs remain under study. Objective: The objective of this study was to evaluate the association between DXM and AKI in COVID-19. Methods: In this prospective observational cohort study, we evaluated the incidence of AKI in critically ill COVID-19 patients undergoing mechanical ventilation, and the association of DXM treatment with the incidence, severity, and outcomes of AKI. The association between DXM treatment and AKI was evaluated by multivariable logistic regression. The association of the combination of DXM treatment and AKI on mortality was evaluated by Cox-regression analysis. Results: We included 552 patients. AKI was diagnosed in 311 (56%), of which 196 (63%) corresponded to severe (stage 2 or 3) AKI, and 46 (14.8%) received kidney replacement therapy. Two hundred and sixty-seven (48%) patients were treated with DXM. This treatment was associated to lower incidence of AKI (Odds Radio 0.34, 95% Confidence intervals [CI] 0.22-0.52, p < 0.001) after adjusting for age, body mass index, laboratory parameters, SOFA score, and vasopressor use. DXM treatment significantly reduced mortality in patients with severe AKI (HR 0.63, 95%CI 0.41-0.96, p = 0.032). Conclusions: The incidence of AKI is high in COVID-19 patients under IMV. DXM treatment is associated with a lower incidence of AKI and a lower mortality in the group with severe AKI.
ABSTRACT
Abstract: Objective: To develop a score to predict the need for intensive care unit (ICU) admission in Covid-19. Materials and methods: We assessed patients admitted to a Covid-19 center in Mexico. Patients were segregated into a group that required ICU admission, and a group that never required ICU admission. By logistic regression, we derived predictive models including clinical, laboratory, and imaging findings. The ABC-GOALS was constructed and compared to other scores. Results: We included 329 and 240 patients in the development and validation cohorts, respectively. One-hundred-fifteen patients from each cohort required ICU admission. The clinical (ABC-GOALSc), clinical+laboratory (ABC-GOALScl), clinical+laboratory+image (ABC-GOALSclx) models area under the curve were 0.79 (95%CI=0.74-0.83) and 0.77 (95%CI=0.71-0.83), 0.86 (95%CI=0.82-0.90) and 0.87 (95%CI=0.83-0.92), 0.88 (95%CI=0.84-0.92) and 0.86 (95%CI=0.81-0.90), in the development and validation cohorts, respectively. The ABC-GOALScland ABC-GOALSclxoutperformed other Covid-19 and pneumonia predictive scores. Conclusion: ABC-GOALS is a tool to timely predict the need for admission to ICU in Covid-19.
Resumen: Objetivo: Desarrollar un puntaje predictivo de la necesidad de ingreso a una unidad de cuidados intensivos (UCI) en Covid-19. Material y métodos: Se evaluaron pacientes ingresados por Covid-19 en México. Se dividieron en un grupo que requirió ingreso a UCI y un grupo que nunca lo requirió. Se derivaron modelos predictivos incluyendo variables clínicas, de laboratorio e imagen y se integraron en el puntaje ABC-GOALS. Resultados: Se incluyeron 329 y 240 pacientes en cohortes de desarrollo y validación, respectivamente. Ciento quince pacientes de cada cohorte requirieron ingreso a UCI. Las áreas bajo la curva de los modelos clínico (ABC-GOALSc), clínico+laboratorio (ABC-GOALScl), clínico+laboratorio+imagen (ABC-GOALSclx) fueron 0.79 (IC95%=0.74-0.83) y 0.77 (IC95%=0.71-0.83); 0.86 (IC95%=0.82-0.90) y 0.87 (IC95%=0.83-0.92); 0.88 (IC95%=0.84-0.92) y 0.86 (IC95%=0.81-0.90) en las cohortes de derivación y validación, respectivamente. El desempeño del ABC-GOALS fue superior a otros puntajes de riesgo. Conclusión: ABC-GOALS es una herramienta para predecir oportunamente la necesidad de ingreso a UCI en Covid-19.