Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2022 Sep 13;11(18):5369.
doi: 10.3390/jcm11185369.

Liver Fibrosis Indices Predict the Severity of SARS-CoV-2 Infection

Lucilla Crudele  1   2 , Fabio Novielli  1 , Stefano Petruzzelli  1 , Stefano Battaglia  3   4 , Antonio Francesco Maria Giuliano  3 , Rosa Melodia  2   3 , Chiara Maria Morano  2   3 , Paola Dell'Aquila  3 , Renata Moretti  3 , Luigi Castorani  3 , Roberto Salvia  3 , Gianfranco Inglese  1   3 , Nicola Susca  1   3 , Lucrezia dell'Olio  3 , Francesca Falcone  3 , Mariapaola Castaldo  1 , Carlo De Matteis  1 , Carlo Sabbà  1   4 , Antonio Moschetta  1   3   4
Affiliations

Liver Fibrosis Indices Predict the Severity of SARS-CoV-2 Infection

Lucilla Crudele et al. J Clin Med. .

Abstract

Discovering novel risk and prognostic factors for COVID-19 may help not only in reducing severity and mortality but also in creating _targeted therapies considering patients’ individual features. Liver fibrosis is considered a complication in Non-alcoholic Fatty Liver Disease (NAFLD), it is a feature of steatohepatitis (NASH), and it has already been related to an increased risk for a wide range of diseases. Here, we aimed to define if any parameter assessing metabolic status has predictive power in identifying inpatients at risk for poorer prognosis and an increased mortality from COVID-19. This retrospective study was conducted at the Sub-Intensive Medicine Care Unit of the Presidio Maxi-Emergenze Fiera del Levante, Azienda Ospedaliero-Universitaria Policlinico di Bari, Italy. We evaluated 271 inpatients with moderate-to-severe SARS-CoV-2-related respiratory failure by comparing biochemical features and non-invasive liver fibrosis scores among discharged, transferred to Intensive Care Units (ICU) and non-survivor patients. Moreover, by performing ROC curves, we defined cut-off values to predict mortality and disease severity for each score. We found that non-invasive scores of liver fibrosis, obtained at day of admission, such as AAR (p < 0.001), FIB-4 and mFIB-4, FORNS, and AARPRI (p < 0.05) strongly predict not only in-hospital mortality but also the length of hospitalization and eventual admission to ICU. FIB-4 was the best score to identify non-survivor patients (sensitivity of 80% and specificity of 63%) and predict the need for ICU or mortality (71% of sensitivity and 65% of specificity), with a cut-off value of 1.94. Therefore, we present the predictive power and the cut-off values of several liver fibrosis scores here for disease severity and mortality in SARS-CoV-2 in-patients and we proposed the use of the present scores to identify ab initio the clinical therapeutic and diagnostic protocols for high-risk patients.

Keywords: COVID-19; liver fibrosis; non-alcoholic fatty liver disease; non-alcoholic steatohepatitis; non-invasive liver fibrosis scores.

PubMed Disclaimer

Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Comparison of Liver Fibrosis Scores in survivor and non survivor patients. Comparison of AAR (a), FIB-4 (b), mFIB-4 (c), FORNS (d), APRI (e), AARPRI (f) scores between survivors and non survivors. Data are presented as mean ± SEM. Statistical significance was assessed by Student t-test (* p < 0.05, ** p < 0.001). Abbreviations: AST to ALT ratio: AAR; fibrosis-4 index: FIB-4; modified FIB-4: mFIB-4; AST to Platelet Ratio Index: APRI; AAR to Platelet ratio: AARPRI.
Figure 2
Figure 2
Comparison of Liver Fibrosis Scores among discharged, admitted to Intensive Care Unit (ICU), and non-survivor patients. Comparison of AAR (a), FIB-4 (b), mFIB-4 (c), FORNS (d), APRI (e), AARPRI (f) scores among discharged, ICU-admitted, and non survivor patients. Data are presented as mean ± SEM. Comparisons were performed using one-way ANOVA test followed by Bonferroni’s post hoc test. Multiple comparison was performed by Student t-test. Lowercase letter in the subfigures indicates significant difference (* p < 0.05, ** p < 0.001) between two groups: (a) for discharged patients, (b) for ICU admitted patients. Abbreviations: AST to ALT ratio: AAR; fibrosis-4 index: FIB-4; modified FIB-4: mFIB-4; AST to Platelet Ratio Index: APRI; AAR to Platelet ratio: AARPRI.
Figure 3
Figure 3
Correlation analysis of AAR (a), FIB-4 (b), mFIB-4 (c), FORNS (d), APRI (e), AARPRI (f) with hospitalization days in the whole population. The correlation was analysed and estimated using Pearson’s Correlation Coefficient (r). (p) indicates statistical significance. Each black dot represents a single patient. Abbreviations: AST to ALT ratio, AAR; fibrosis 4 index, FIB-4; modified FIB-4, mFIB-4; AAR to Platelet ratio, AARPRI.
Figure 4
Figure 4
Correlation of AAR (a), FIB-4 (b), mFIB-4 (c), FORNS (d), APRI (e), AARPRI (f) with hospitalization days in discharged patients. The correlation was analysed and estimated using Pearson’s Correlation Coefficient (r). (p) indicates statistical significance. Each black dot represents a single patient. Abbreviations: AST to ALT ratio: AAR; fibrosis 4 index: FIB-4; modified FIB-4: mFIB-4; AAR to Platelet ratio: AARPRI.
Figure 5
Figure 5
ROC curves for mortality and severity of disease of FIB-4 (a,b), mFIB-4 (c,d), and FORNS (e,f). The graphs indicate cut off values with respective sensitivity and specificity levels and empirical estimation of area under curve (AUC) with upper 1-sided p-value (p). Abbreviations: fibrosis-4 index, FIB-4; modified FIB-4, mFIB-4.
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

References

    1. Cascella M., Rajnik M., Aleem A., Dulebohn S.C., Di Napoli R. StatPearls. StatPearls Publishing; Treasure Island, FL, USA: 2022. Features, Evaluation, and Treatment of Coronavirus (COVID-19) - PubMed
    1. Sun K., Gu L., Ma L., Duan Y. Atlas of ACE2 Gene Expression Reveals Novel Insights into Transmission of SARS-CoV-2. Heliyon. 2021;7:e05850. doi: 10.1016/j.heliyon.2020.e05850. - DOI - PMC - PubMed
    1. Ackermann M., Verleden S.E., Kuehnel M., Haverich A., Welte T., Laenger F., Vanstapel A., Werlein C., Stark H., Tzankov A., et al. Pulmonary Vascular Endothelialitis, Thrombosis, and Angiogenesis in Covid-19. N. Engl. J. Med. 2020;383:120–128. doi: 10.1056/NEJMoa2015432. - DOI - PMC - PubMed
    1. Crudele L., Piccinin E., Moschetta A. Visceral Adiposity and Cancer: Role in Pathogenesis and Prognosis. Nutrients. 2021;13:2101. doi: 10.3390/nu13062101. - DOI - PMC - PubMed
    1. Dietz W., Santos-Burgoa C. Obesity and Its Implications for COVID-19 Mortality. Obesity. 2020;28:1005. doi: 10.1002/oby.22818. - DOI - PubMed

LinkOut - more resources

  NODES
INTERN 2
todo 1
twitter 2