Alcoholic liver disease (ALD) is a consequence of excessive alcohol use. According to many studies, alcohol represents a significant socioeconomic and health risk factor in today’s population. According to data from the World Health Organization, there are about 75 million people who have alcohol disorders, and it is well known that its use leads to serious health problems. ALD is a multimodality spectrum that includes alcoholic fatty liver disease (AFL) and alcoholic steatohepatitis (ASH), consequently leading to liver fibrosis and cirrhosis. In addition, the rapid progression of alcoholic liver disease can lead to alcoholic hepatitis (AH). Alcohol metabolism produces toxic metabolites that lead to tissue and organ damage through an inflammatory cascade that includes numerous cytokines, chemokines, and reactive oxygen species (ROS). In the process of inflammation, mediators are cells of the immune system, but also resident cells of the liver, such as hepatocytes, hepatic stellate cells, and Kupffer cells. These cells are activated by exogenous and endogenous antigens, which are called pathogen and damage-associated molecular patterns (PAMPs, DAMPs). Both are recognized by Toll-like receptors (TLRs), which activation triggers the inflammatory pathways. It has been proven that intestinal dysbiosis and disturbed integrity of the intestinal barrier perform a role in the promotion of inflammatory liver damage. These phenomena are also found in chronic excessive use of alcohol. The intestinal microbiota has an important role in maintaining the homeostasis of the organism, and its role in the treatment of ALD has been widely investigated. Prebiotics, probiotics, postbiotics, and symbiotics represent therapeutic interventions that can have a significant effect on the prevention and treatment of ALD.

Introduction. Mortality among critically ill COVID‐19 patients remains relatively high despite different potential therapeutic modalities being introduced recently. The treatment of critically ill patients is a challenging task, without identified credible predictors of mortality. Methods. We performed an analysis of 160 consecutive patients with confirmed COVID‐19 infection admitted to the Respiratory Intensive Care Unit between June 23, 2020, and October 2, 2020, in University Hospital Center Bezanijska kosa, Belgrade, Serbia. Patients on invasive, noninvasive ventilation and high flow oxygen therapy with moderate to severe ARDS, according to the Berlin definition of ARDS, were selected for the study. Demographic data, past medical history, laboratory values, and CT severity score were analyzed to identify predictors of mortality. Univariate and multivariate logistic regression models were used to assess potential predictors of mortality in critically ill COVID‐19 patients. Results. The mean patient age was 65.6 years (range, 29–92 years), predominantly men, 68.8%. 107 (66.9%) patients were on invasive mechanical ventilation, 31 (19.3%) on noninvasive, and 22 (13.8%) on high flow oxygen therapy machine. The median total number of ICU days was 10 (25^th to 75^th percentile: 6–18), while the median total number of hospital stay was 18 (25^th to 75^th percentile: 12–28). The mortality rate was 60% (96/160). Univariate logistic regression analysis confirmed the significance of age, CRP, and lymphocytes at admission to hospital, serum albumin, D‐dimer, and IL‐6 at admission to ICU, and CT score. Serum albumin, D‐dimer, and IL‐6 at admission to ICU were independently associated with mortality in the final multivariate analysis. Conclusion. In the present study of 160 consecutive critically ill COVID‐19 patients with moderate to severe ARDS, IL‐6, serum albumin, and D‐dimer at admission to ICU, accompanied by chest CT severity score, were marked as independent predictors of mortality.

Metabolic dysfunction-associated steatotic liver disease (MASLD) was previously known as nonalcoholic fatty liver disease (NAFLD). The main characteristic of the disease is the process of long-term liver inflammation, which leads to hepatocyte damage followed by liver fibrosis and eventually cirrhosis. Additionally, these patients are at a greater risk for developing cardiovascular diseases (CVD). They have several pathophysiological mechanisms in common, primarily lipid metabolism disorders and lipotoxicity. Lipotoxicity is a factor that leads to the occurrence of heart disease and the occurrence and progression of atherosclerosis. Atherosclerosis, as a multifactorial disease, is one of the predominant risk factors for the development of ischemic heart disease. Therefore, CVD are one of the most significant carriers of mortality in patients with metabolic syndrome. So far, no pharmacotherapy has been established for the treatment of MASLD, but patients are advised to reduce their body weight and change their lifestyle. In recent years, several trials of different drugs, whose basic therapeutic indications include other diseases, have been conducted. Because it has been concluded that they can have beneficial effects in the treatment of these conditions as well, in this paper, the most significant results of these studies will be presented.

Acute coronary syndrome (ACS) in patients with COVID-19 is triggered by various mechanisms and can significantly affect the patient’s further treatment and prognosis. The study aimed to investigate the characteristics, major complications, and predictors of mortality in COVID-19 patients with ACS. All consecutive patients hospitalized from 5 July 2020 to 5 May 2021 for ACS with confirmed SARS-Co-2 were prospectively enrolled and tracked for mortality until 5 June 2021. Data from the electronic records for age and diagnosis, matched non-COVID-19 and COVID-19 ACS group, were extracted and compared. Overall, 83 COVID-19 ACS patients, when compared to 166 non-COVID ACS patients, had significantly more prevalent comorbidities, unfavorable clinical characteristics on admission (acute heart failure 21.7% vs. 6.6%, p < 0.01) and higher rates of major complications, 33.7% vs. 16.8%, p < 0.01, and intrahospital 30-day mortality, 6.7% vs. 26.5%, p < 0.01. The strongest predictors of mortality were aortic regurgitation, HR 9.98, 95% CI 1.88; 52.98, p < 0.01, serum creatinine levels, HR 1.03, 95% CI 1.01; 1.04, p < 0.01, and respiratory failure therapy, HR 13.05, 95% CI 3.62; 47.01, p < 0.01. Concomitant ACS and COVID-19 is linked to underlying comorbidities, adverse presenting features, and poor outcomes. Urgent strategies are needed to improve the outcomes of these patients.

Introduction. Risk stratification is an important aspect of COVID‐19 management, especially in patients admitted to ICU as it can provide more useful consumption of health resources, as well as prioritize critical care services in situations of overwhelming number of patients. Materials and Methods. A multivariable predictive model for mortality was developed using data solely from a derivation cohort of 160 COVID‐19 patients with moderate to severe ARDS admitted to ICU. The regression coefficients from the final multivariate model of the derivation study were used to assign points for the risk model, consisted of all significant variables from the multivariate analysis and age as a known risk factor for COVID‐19 patient mortality. The newly developed AIDA score was arrived at by assigning 5 points for serum albumin and 1 point for IL‐6, D dimer, and age. The score was further validated on a cohort of 304 patients admitted to ICU due to the severe form of COVID‐19. Results. The study population included 160 COVID‐19 patients admitted to ICU in the derivation and 304 in the validation cohort. The mean patient age was 66.7 years (range, 20–93 years), with 68.1% men and 31.9% women. Most patients (76.8%) had comorbidities with hypertension (67.7%), diabetes (31.7), and coronary artery disease (19.3) as the most frequent. A total of 316 patients (68.3%) were treated with mechanical ventilation. Ninety‐six (60.0%) in the derivation cohort and 221 (72.7%) patients in the validation cohort had a lethal outcome. The population was divided into the following risk categories for mortality based on the risk model score: low risk (score 0–1) and at‐risk (score > 1). In addition, patients were considered at high risk with a risk score > 2. By applying the risk model to the validation cohort (n = 304), the positive predictive value was 78.8% (95% CI 75.5% to 81.8%); the negative predictive value was 46.6% (95% CI 37.3% to 56.2%); the sensitivity was 82.4% (95% CI 76.7% to 87.1%), and the specificity was 41.0% (95% CI 30.3% to 52.3%). The C statistic was 0.863 (95% CI 0.805‐0.921) and 0.665 (95% CI 0.598‐0.732) in the derivation and validation cohorts, respectively, indicating a high discriminative value of the proposed score. Conclusion. In the present study, AIDA score showed a valuable significance in estimating the mortality risk in patients with the severe form of COVID‐19 disease at admission to ICU. Further external validation on a larger group of patients is needed to provide more insights into the utility of this score in everyday practice.

Background: This study aimed to calculate the frequency of elevated liver enzymes in hospitalized patients with coronavirus disease 2019 (COVID-19) infection and to test if liver enzyme biochemistry levels on admission could predict the computed tomography (CT) scan severity score of bilateral interstitial pneumonia. Methods: This single-center study comprised of 323 patients including their demographic data, laboratory analyses, and radiological findings. All the information was taken from electronic health records, followed by statistical analysis. Results: Out of 323 patients, 115 of them (35.60%) had aspartate aminotransferase (AST) and/or alanine aminotransferase (ALT) over 40 U/L on admission. AST was the best predictor of CT scan severity score of bilateral interstitial pneumonia (R² = 0.313, Adjusted R² = 0.299). CT scan severity score in the peak of the infection could be predicted with the value of AST, neutrophils, platelets, and monocytes count (R² = 0.535, Adjusted R² = 0.495). Conclusion: AST, neutrophils, platelets, and monocytes count on admission can account for almost half (49.5%) of the variability in CT scan severity score at peak of the disease, predicting the extensiveness of interstitial pneumonia related to COVID-19 infection. Liver enzymes should be closely monitored in order to stratify COVID-19 patients with a higher risk of developing severe forms of the disease and to plan the beforehand step-up treatment.