Mohammed El‐Mowafy

OBJECTIVE: Evidence-based characterization of the diagnostic and prognostic value of the hematological and immunological markers related to the epidemic of Coronavirus Disease 2019 (COVID-19) is critical to understand the clinical course of the infection and to assess in development and validation of biomarkers. METHODS: Based on systematic search in Web of Science, PubMed, Scopus, and Science Direct up to April 22, 2020, a total of 52 eligible articles with 6,320 laboratory-confirmed COVID-19 cohorts were included. Pairwise comparison between severe versus mild disease, Intensive Care Unit (ICU) versus general ward admission and expired versus survivors were performed for 36 laboratory parameters. The pooled standardized mean difference (SMD) and 95% confidence intervals (CI) were calculated using the DerSimonian Laird method/random effects model and converted to the Odds ratio (OR). The decision tree algorithm was employed to identify the key risk factor(s) attributed to severe COVID-19 disease. RESULTS: Cohorts with elevated levels of white blood cells (WBCs) (OR = 1.75), neutrophil count (OR = 2.62), D-dimer (OR = 3.97), prolonged prothrombin time (PT) (OR = 1.82), fibrinogen (OR = 3.14), erythrocyte sedimentation rate (OR = 1.60), procalcitonin (OR = 4.76), IL-6 (OR = 2.10), and IL-10 (OR = 4.93) had higher odds of progression to severe phenotype. Decision tree model (sensitivity = 100%, specificity = 81%) showed the high performance of neutrophil count at a cut-off value of more than 3.74x109/L for identifying patients at high risk of severe COVID-19. Likewise, ICU admission was associated with higher levels of WBCs (OR = 5.21), neutrophils (OR = 6.25), D-dimer (OR = 4.19), and prolonged PT (OR = 2.18). Patients with high IL-6 (OR = 13.87), CRP (OR = 7.09), D-dimer (OR = 6.36), and neutrophils (OR = 6.25) had the highest likelihood of mortality. CONCLUSIONS: Several hematological and immunological markers, in particular neutrophilic count, could be helpful to be included within the routine panel for COVID-19 infection evaluation to ensure risk stratification and effective management.

Inflammatory bowel diseases (IBD) are chronic medical disorders characterized by recurrent gastrointestinal inflammation. While the etiology of IBD is still unknown, the pathogenesis of the disease results from perturbations in both gut microbiota and the host immune system. Gut microbiota dysbiosis in IBD is characterized by depleted diversity, reduced abundance of short chain fatty acids (SCFAs) producers and enriched proinflammatory microbes such as adherent/invasive E. coli and H 2 S producers. This dysbiosis may contribute to the inflammation through affecting either the immune system or a metabolic pathway. The immune responses to gut microbiota in IBD are extensively discussed. In this review, we highlight the main metabolic pathways that regulate the host-microbiota interaction. We also discuss the reported findings indicating that the microbial dysbiosis during IBD has a potential metabolic impact on colonocytes and this may underlie the disease progression. Moreover, we present the host metabolic defectiveness that adds to the impact of symbiont dysbiosis on the disease progression. This will raise the possibility that gut microbiota dysbiosis associated with IBD results in functional perturbations of host-microbiota interactions, and consequently modulates the disease development. Finally, we shed light on the possible therapeutic approaches of IBD through targeting gut microbiome.

BACKGROUND: Coronavirus disease-2019 (COVID-19) has a deleterious effect on several systems, including the cardiovascular system. We aim to systematically explore the association of COVID-19 severity and mortality rate with the history of cardiovascular diseases and/or other comorbidities and cardiac injury laboratory markers. METHODS: The standardized mean difference (SMD) or odds ratio (OR) and 95% confidence intervals (CIs) were applied to estimate pooled results from the 56 studies. The prognostic performance of cardiac markers for predicting adverse outcomes and to select the best cutoff threshold was estimated by receiver operating characteristic curve analysis. Decision tree analysis by combining cardiac markers with demographic and clinical features was applied to predict mortality and severity in patients with COVID-19. RESULTS: A meta-analysis of 17 794 patients showed patients with high cardiac troponin I (OR = 5.22, 95% CI = 3.73-7.31, P < .001) and aspartate aminotransferase (AST) levels (OR = 3.64, 95% CI = 2.84-4.66, P < .001) were more likely to develop adverse outcomes. High troponin I more than 13.75 ng/L combined with either advanced age more than 60 years or elevated AST level more than 27.72 U/L was the best model to predict poor outcomes. CONCLUSIONS: COVID-19 severity and mortality are complicated by myocardial injury. Assessment of cardiac injury biomarkers may improve the identification of those patients at the highest risk and potentially lead to improved therapeutic approaches.

Abstract Objective Evidence-based characterization of the diagnostic and prognostic value of the hematological and immunological markers related to the epidemic of Coronavirus Disease 2019 (COVID-19) is critical to understand the clinical course of the infection and to assess in development and validation of biomarkers. Methods Based on systematic search in Web of Science, PubMed, Scopus, and Science Direct up to April 22, 2020, a total of 52 eligible articles with 6,320 laboratory-confirmed COVID-19 cohorts were included. Pairwise comparison between severe versus mild disease, Intensive Care Unit (ICU) versus general ward admission, and expired versus survivors were performed for 36 laboratory parameters. The pooled standardized mean difference (SMD) and 95% confidence intervals (CI) were calculated using the DerSimonian Laird method/random effects model and converted to Odds ratio (OR). The decision tree algorithm was employed to identify the key risk factor(s) attributed to severe COVID-19 disease. Results Cohorts with elevated levels of white blood cells (WBCs) (OR=1.75), neutrophil count (OR=2.62), D-dimer (OR=3.97), prolonged prothrombin time (PT) (OR=1.82), fibrinogen (OR=3.14), erythrocyte sedimentation rate (OR=1.60), procalcitonin (OR=4.76), IL-6 (OR=2.10), and IL-10 (OR=4.93) had higher odds of progression to severe phenotype. Decision tree model (sensitivity=100%, specificity=81%) showed the high performance of neutrophil count at a cut-off value of more than 3.74□x10 9 /L for identifying patients at high risk of severe COVID□19. Likewise, ICU admission was associated with higher levels of WBCs (OR=5.21), neutrophils (OR=6.25), D-dimer (OR=4.19), and prolonged PT (OR=2.18). Patients with high IL-6 (OR=13.87), CRP (OR=7.09), D-dimer (OR=6.36), and neutrophils (OR=6.25) had the highest likelihood of mortality. Conclusions Several hematological and immunological markers, in particular neutrophilic count, could be helpful to be included within the routine panel for COVID-19 infection evaluation to ensure risk stratification and effective management.

The gut-liver-axis is a bidirectional coordination between the gut, including microbial residents, the gut microbiota, from one side and the liver on the other side. Any disturbance in this crosstalk may lead to a disease status that impacts the functionality of both the gut and the liver. A major cause of liver disorders is hepatitis C virus (HCV) infection that has been illustrated to be associated with gut microbiota dysbiosis at different stages of the disease progression. This dysbiosis may start a cycle of inflammation and metabolic disturbance that impacts the gut and liver health and contributes to the disease progression. This review discusses the latest literature addressing this interplay between the gut microbiota and the liver in HCV infection from both directions. Additionally, we highlight the contribution of gut microbiota to the metabolism of antivirals used in HCV treatment regimens and the impact of these medications on the microbiota composition. This review shed light on the potential of the gut microbiota manipulation as an alternative therapeutic approach to control the liver complications post HCV infection.