Age-adjusted mortality and predictive value of liver chemistries in a Viennese cohort of COVID-19 patients.

BACKGROUND AND AIMS: The coronavirus disease of 2019 (COVID-19) causes considerable mortality worldwide. We aimed to investigate the frequency and predictive role of abnormal liver chemistries in different age groups. METHODS: Patients with positive severe acute respiratory distress syndrome-coronavirus-2 (SARS-CoV-2) polymerase chain reaction (PCR) test between 03/2020-07/2021 at the Vienna General Hospital were included. Patients were stratified for age: 18-39 vs. 40-69 vs. ≥70 years (y). Aspartate aminotransferase (AST), alanine-aminotransferase (ALT), alkaline phosphatase (ALP), gamma-glutamyl transferase (GGT) and total bilirubin (BIL) were recorded. RESULTS: 900 patients (18-39 years: 32.2%, 40-69 years: 39.7%, ≥70 years: 28.1%) were included. Number of comorbidities, median D-dimer and C-reactive protein increased with age. During COVID-19, AST/ALT and ALP/GGT levels significantly increased. Elevated hepatocellular transaminases (AST/ALT) and cholestasis parameters (ALP/GGT/BIL) were observed in 40.3% (n  = 262/650) and 45.0% (n  = 287/638) of patients respectively. Liver-related mortality was highest among patients with pre-existing decompensated liver disease (28.6%, p < .001). 1.7% of patients without pre-existing liver disease died of liver-related causes, that is consequences of hepatic dysfunction or acute liver failure. Importantly, COVID-19-associated liver injury (16.0%, p < .001), abnormal liver chemistries and liver-related mortality (6.5%, p < .001) were most frequent among 40-69 years old patients. Elevated AST and BIL after the first positive SARS-CoV-2 PCR independently predicted mortality in the overall cohort and in 40-69 years old patients. CONCLUSIONS: Almost half of the COVID-19 patients exhibit abnormal hepatocellular and cholestasis-related liver chemistries with 40-69 years old patients being at particularly high risk for COVID-19-related liver injury and liver-related mortality. Elevated AST and BIL after SARS-CoV-2 infection are independent predictors of mortality, especially in patients aged 40-69 years.

Anti-inflammatory adipokines: chemerin, vaspin, omentin concentrations and SARS-CoV-2 outcomes.

Coronavirus disease 2019 (COVID-19) is associated with systemic inflammation. A wide range of adipokines activities suggests they influence pathogenesis and infection course. The aim was to assess concentrations of chemerin, omentin, and vaspin among COVID-19 patients with an emphasis on adipokines relationship with COVID-19 severity, concomitant metabolic abnormalities and liver dysfunction. Serum chemerin, omentin and vaspin concentrations were measured in serum collected from 70 COVID-19 patients at the moment of admission to hospital, before any treatment was applied and 20 healthy controls. Serum chemerin and omentin concentrations were significantly decreased in COVID-19 patients compared to healthy volunteers (271.0 vs. 373.0 ng/ml; p < 0.001 and 482.1 vs. 814.3 ng/ml; p = 0.01, respectively). There were no correlations of analyzed adipokines with COVID-19 severity based on the presence of pneumonia, dyspnea, or necessity of Intensive Care Unit hospitalization (ICU). Liver test abnormalities did not influence adipokines levels. Elevated GGT activity was associated with ICU admission, presence of pneumonia and elevated concentrations of CRP, ferritin and interleukin 6. Chemerin and omentin depletion in COVID-19 patients suggests that this adipokines deficiency play influential role in disease pathogenesis. However, there was no relationship between lower adipokines level and frequency of COVID-19 symptoms as well as disease severity. The only predictive factor which could predispose to a more severe COVID-19 course, including the presence of pneumonia and ICU hospitalization, was GGT activity.

Establishing a model for predicting the outcome of COVID-19 based on combination of laboratory tests.

INTRODUCTION: There are currently no satisfactory methods for predicting the outcome of Coronavirus Disease-2019 (COVID-19). The aim of this study is to establish a model for predicting the prognosis of the disease. METHODS: The laboratory results were collected from 54 deceased COVID-19 patients on admission and before death. Another 54 recovered COVID-19 patients were enrolled as control cases. RESULTS: Many laboratory indicators, such as neutrophils, AST, γ-GT, ALP, LDH, NT-proBNP, Hs-cTnT, PT, APTT, D-dimer, IL-2R, IL-6, IL-8, IL-10, TNF-α, CRP, ferritin and procalcitonin, were all significantly increased in deceased patients compared with recovered patients on admission. In contrast, other indicators such as lymphocytes, platelets, total protein and albumin were significantly decreased in deceased patients on admission. Some indicators such as neutrophils and procalcitonin, others such as lymphocytes and platelets, continuously increased or decreased from admission to death in deceased patients respectively. Using these indicators alone had moderate performance in differentiating between recovered and deceased COVID-19 patients. A model based on combination of four indicators (P = 1/[1 + e-(-2.658+0.587×neutrophils - 2.087×lymphocytes - 0.01×platelets+0.004×IL-2R)]) showed good performance in predicting the death of COVID-19 patients. When cutoff value of 0.572 was used, the sensitivity and specificity of the prediction model were 90.74% and 94.44%, respectively. CONCLUSIONS: Using the current indicators alone is of modest value in differentiating between recovered and deceased COVID-19 patients. A prediction model based on combination of neutrophils, lymphocytes, platelets and IL-2R shows good performance in predicting the outcome of COVID-19.