The implementation of easily accessible prognostic biomarkers for patients with COVID-19 remains an important area of clinical research. In this large monocentric study at a German tertiary care hospital, we determined the prognostic performance of different liver scores in 605 patients with COVID-19. We evaluated the Fibrosis-4 (FIB-4) index, the Aspartate Aminotransferase-to-Platelet Ratio Index (APRI), the Model for End-Stage Liver Disease (MELD) score, and the De Ritis ratio (DRR; AST/ALT ratio). The 30-day mortality was used as primary COVID-19 outcome measure. The need for intensive care unit (ICU) treatment and overall mortality were secondary endpoints. Univariable analyses showed that most of the investigated liver-related scores (FIB-4, MELD, and DRR), but not APRI for overall mortality, were significantly associated with key outcomes in COVID-19 patients. Concurrently, well-known risk factors-such as advanced age, diabetes, and cardiac or pulmonary comorbidities-were also linked to worse outcomes, except for the female sex having a preventive effect against ICU admission. A history of liver disease was rarely documented among the patients and showed no significant impact on the examined endpoints. Multivariable analyses further revealed that advanced age, DRR, and MELD were independent predictors of both 30-day and overall mortality, while FIB-4 emerged as an independent predictor specifically for overall mortality. Regarding ICU admission, obesity, underlying lung disease, and elevated APRI and MELD scores were identified as independent risk factors, whereas the female sex appeared to be protective. Overall, MELD demonstrated the strongest prognostic value for mortality and ICU admission, with DRR also exhibiting independent predictive power for mortality. These findings suggest that scores originally developed for chronic liver disease assessment-namely FIB-4, APRI, MELD, and DRR-hold promise as prognostic tools in COVID-19. In particular, MELD and DRR emerged as the most powerful biomarkers for predicting severe disease and mortality, highlighting the potential for incorporating these indices into risk stratification models for COVID-19 management. Further prospective multicenter studies are warranted to confirm these observations.

SARS-Cov-2 infection manifests as a wide spectrum of clinical presentation and even now, despite the global spread of the vaccine, contagiousness is still elevated. The aim of the study was the evaluation of the impact of liver fibrosis assessed by FIB-4 and liver impairment, assessed by cytolysis indices, on intrahospital mortality in COVID-19 subjects.

This is a retrospective observational cohort study, which involved 23 COVID Hospital Units in Campania Region, Italy. Exposure variables were collected during hospital admission and at discharge. According to FIB-4 values, we subdivided the overall population in three groups (FIB-4<1.45; 1.453.25), respectively group 1,2,3.

At the end of the study, 938 individuals had complete discharged/dead data. At admission, 428 patients were in group 1 (45.6%), 387 in group 2 (41.3%) and 123 in group 3 (13.1%). Among them, 758 (81%) subjects were discharged, while the remaining 180 (19%) individuals died. Multivariable Cox's regression model showed a significant association between mortality risk and severity of FIB-4 stages (group 3 vs group 1, HR 2.12, 95%CI 1.38-3.28, p<0.001). Moreover, Kaplan-Meier analysis described a progressive and statistically significant difference (p<0.001 Log-rank test) in mortality according to FIB-4 groups. Among discharged subjects, 507 showed a FIB-4<1.45 (66.9%, group 1), 182 a value 1.453.25 (9.0%, group 3). Among dead subjects, 42 showed a FIB-4<1.45 (23.3%, group 1), 62 a value 1.453.25 (42.3%, group 3).

FIB-4 value is significantly associated with intrahospital mortality of COVID-19 patients. During hospitalization, particularly in patients with worse outcomes, COVID-19 seems to increase the risk of acute progression of liver damage.

Non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH) are potential risk factors for severe pneumonia and other infections. Available data on the role of NAFLD/NASH in worsening outcomes for COVID-19 are controversial and might be confounded by comorbidities.

We used the PINC AI™ Healthcare Data Special Release (PHD-SR) to identify patients with COVID-19 (ICD-10) at approximately 900 hospitals in the United States. We performed exact matching (age, gender, and ethnicity) for patients with or without NAFLD/NASH, adjusting for demographics (admission type, region) and comorbidities (e.g., obesity, diabetes) through inverse probability of treatment weighting and then analysed hospitalisation-related outcomes.

Among 513 623 patients with SARS-CoV-2 (COVID-19), we identified 14 667 with NAFLD/NASH who could be matched to 14 667 controls. Mean age was 57.6 (±14.9) years, 50.8% were females and 43.7% were non-Hispanic whites. After matching, baseline characteristics (e.g., age, ethnicity, and gender) and comorbidities (e.g., hypertension, obesity, diabetes, and cardiovascular disease) were well balanced (standard difference (SD) <.10), except for cirrhosis and malignancies. Patients with COVID-19 and NAFLD/NASH had higher FIB-4 scores, a significantly longer hospital length of stay (LOS) and intensive care LOS than controls (9.4 vs. 8.3 days, and 10.4 vs. 9.3, respectively), even after adjusting for cirrhosis and malignancies. Patients with COVID-19 and NAFLD/NASH also had significantly higher risk of needing invasive mandatory ventilation (IMV) (odds ratio 1.0727; 95% CI 1.0095-1.1400). Other outcomes were similar in both groups.

In this large real-world cohort of patients hospitalised for COVID-19 in the United States, NAFLD/NASH were obesity-independent risk factors for complicated disease courses.

We aimed to determine the reliability of using the Fibrosis-4 (FIB-4) index in COVID-19 patients without underlying liver illness.

We employed multivariate logistic regression to identify variables that exhibited statistically significant influence on the ultimate outcome. Multilayer perceptron analysis was employed to develop a prediction model for the FIB-4 index concerning ICU admission and intubation rates. However, the scarcity of cases rendered the assessment of the mortality rate unfeasible. We plotted ROC curves to analyze the predictive strength of the FIB-4 index across various age groups.

In univariate logistic regression, only the FIB-4 index and respiratory rate demonstrated statistical significance on all poor outcomes. The FIB-4 index for mortality prediction had an ROC and AUC of 0.863 (95% CI: 0.781-0.9444). It demonstrates predictive power across age groups, particularly for age ≥65 (AUC: 0.812, 95% CI: 0.6571-0.9673) and age <65 (AUC: 0.878, 95% CI: 0.8012-0.9558). Its sensitivity for intubation and ICU admission prediction is suboptimal.

FIB-4 index had promising power in prediction of mortality rate in all age groups.

Increased values of the FIB-4 index appear to be associated with poor clinical outcomes in COVID-19 patients. This study aimed to develop and validate predictive mortality models, using data upon admission of hospitalized patients in four COVID-19 waves between March 2020 and January 2022. A single-center cohort study was performed on consecutive adult patients with Covid-19 admitted at the Fondazione Policlinico Gemelli IRCCS (Rome, Italy). Artificial intelligence and big data processing were used to retrieve data. Patients and clinical characteristics of patients with available FIB-4 data derived from the Gemelli Generator Real World Data (G2 RWD) were used to develop predictive mortality models during the four waves of the COVID-19 pandemic. A logistic regression model was applied to the training and test set (75%:25%). The model's performance was assessed by receiver operating characteristic (ROC) curves. A total of 4936 patients were included. Hypertension (38.4%), cancer (12.15%) and diabetes (16.3%) were the most common comorbidities. 23.9% of patients were admitted to ICU, and 12.6% had mechanical ventilation. During the study period, 762 patients (15.4%) died. We developed a multivariable logistic regression model on patient data from all waves, which showed that the FIB-4 score > 2.53 was associated with increased mortality risk (OR = 4.53, 95% CI 2.83-7.25; p ≤ 0.001). These data may be useful in the risk stratification at the admission of hospitalized patients with COVID-19.

Liver is unlikely the key organ driving mortality in coronavirus disease 2019 (COVID-19) however, liver function tests (LFTs) abnormalities are widely observed mostly in moderate and severe cases. According to this review, the overall prevalence of abnormal LFTs in COVID-19 patients ranges from 2.5% to 96.8% worldwide. The geographical variability in the prevalence of underlying diseases is the determinant for the observed discrepancies between East and West. Multifactorial mechanisms are implicated in COVID-19-induced liver injury. Among them, hypercytokinemia with "bystander hepatitis", cytokine storm syndrome with subsequent oxidative stress and endotheliopathy, hypercoagulable state and immuno-thromboinflammation are the most determinant mechanisms leading to tissue injury. Liver hypoxia may also contribute under specific conditions, while direct hepatocyte injury is an emerging mechanism. Except for initially observed severe acute respiratory distress syndrome corona virus-2 (SARS-CoV-2) tropism for cholangiocytes, more recent cumulative data show SARS-CoV-2 virions within hepatocytes and sinusoidal endothelial cells using electron microscopy (EM). The best evidence for hepatocellular invasion by the virus is the identification of replicating SARS-CoV-2 RNA, S protein RNA and viral nucleocapsid protein within hepatocytes using in-situ hybridization and immunostaining with observed intrahepatic presence of SARS-CoV-2 by EM and by in-situ hybridization. New data mostly derived from imaging findings indicate possible long-term sequelae for the liver months after recovery, suggesting a post-COVID-19 persistent live injury.

The COVID-19 pandemic is ongoing and places a substantial burden on healthcare systems worldwide. As we further shed light on different disease characteristics, we identify more and more groups of people at higher risk of poor COVID-19 outcomes. Metabolic-associated fatty liver disease (MAFLD) (previously non-alcoholic fatty liver disease or NAFLD) is a common metabolic disorder characterized by fat accumulation and liver fibrosis. Given its close correlation with metabolic syndrome, an established risk factor for severe COVID-19, it is necessary to investigate its interplay with the novel coronavirus. In this study, we review the available data on COVID-19 prognosis, treatment and prevention options in patients with MAFLD, and the effect that the disease and the pandemic have on MAFLD care. Furthermore, we point out the gaps in the current literature to accentuate the work that needs to be done to improve MAFLD care during the pandemic and beyond.