ABSTRACT
Background: A high proportion of critically ill patients with COVID-19 develop acute kidney injury (AKI) and die. Early recognition of subclinical AKI could contribute to AKI prevention. Therefore, this study was aimed at exploring the role of the urinary biomarkers NGAL and [TIMP-2]•[IGFBP7] for early detection of AKI in this population. Methods: : This prospective, longitudinal cohort study included critically ill COVID-19 patients without AKI at study entry. Urine samples were collected on admission to critical care areas for determination of NGAL and [TIMP-2]•[IGFBP7] concentrations. Demographic information, comorbidities, clinical and laboratory data were recorded. The study outcomes were development of AKI and mortality during hospitalization. Comparisons of individuals who developed AKI during hospitalization vs. those without AKI were made using chi-squared test for categorical variables and Mann-Whitney U for continuous variables. Urinary biomarkers and their cutoff values were selected based on the highest sensitivity, specificity and area under the receiver-operating characteristics curve with 95% confidence intervals for prediction of AKI. Selected biomarkers and cutoffs were used in the Kaplan-Meier survival analyses for the time to AKI. Logistic regression analysis was used to identify the association between relevant covariates with AKI and mortality. For all analyses, two-sided P values £0.05 were considered statistically significant. Results: : Of the 51 individuals studied, 25 developed AKI during hospitalization (49%). The risk factors for AKI were male gender (HR=7.57, 95% CI: 1.28-44.8; p=0.026) and [TIMP-2]•[IGFBP7] ³ 0.2 (ng/ml) 2 /1000 (HR=7.23 , 95% CI: 0.99-52.4; p=0.050). Mortality during hospitalization was significantly higher in the group with AKI than in the group without AKI (p=0.004). Persistent AKI was a risk factor for mortality (HR=7.42, 95% CI: 1.04-53.04; p=0.046). Conclusions: : The combination of [TIMP-2]•[IGFBP7], together with clinical information, were useful for identification of subclinical AKI in critically ill COVID-19 patients. The role of additional biomarkers and their possible combinations for detection of AKI in critically ill COVID-19 patients remains to be explored in large clinical trials.
Subject(s)
Acute Kidney Injury , COVID-19ABSTRACT
COVID-19 outbreak has caused over 3 million deaths worldwide. Understanding disease pathology and the factors that drive severe and fatal clinical outcomes is of special relevance. Studying the role of the respiratory microbiota in COVID-19 is particularly important since it’s known that the respiratory microbiota interacts with the host immune system, contributing to clinical outcomes in chronic and acute respiratory diseases. Here, we characterized the microbiota in the respiratory tract of patients with mild, severe, or fatal COVID-19, and compared with healthy controls and patients with non-COVID-19-pneumonia. We comparatively studied the microbial composition, diversity, and microbiota structure across study groups and correlated the results with clinical data. We found differences in diversity and abundance of bacteria between groups, higher levels of dysbiosis in the respiratory microbiota of COVID-19 patients (regardless of severity level), differences in diversity structure among mild, severe, and fatal COVID-19, and the presence of specific bacteria that correlated with clinical variables associated with increased mortality risk. Our data suggest that host-related and environmental factors could be affecting the respiratory microbiota before SARS-CoV-2 infection, potentially compromising the immunological response of the host against disease and promoting secondary bacterial infections. For instance, the high levels of dysbiosis coupled with low microbial structural complexity in the respiratory microbiota of COVID-19 patients, possibly resulted from antibiotic uptake and comorbidities, could have consequences for the host and microbial community level. Altogether, our findings identify the respiratory microbiota as a potential factor associated with COVID-19 severity.