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Comment
. 2023 Oct;18(7):2063-2073.
doi: 10.1007/s11739-023-03316-6. Epub 2023 Jun 3.

Metabolic-associated fatty liver disease and liver fibrosis scores as COVID-19 outcome predictors: a machine-learning application

Affiliations
Comment

Metabolic-associated fatty liver disease and liver fibrosis scores as COVID-19 outcome predictors: a machine-learning application

Mirko Zoncapè et al. Intern Emerg Med. 2023 Oct.

Abstract

Patients with COVID-19 and metabolic-dysfunction associated fatty liver disease (MAFLD) appear to be at higher risk for severe manifestations, especially in the youngest decades. Our aim was to examine whether patients with MAFLD and/or with increased liver fibrosis scores (FIB-4) are at risk for severe COVID-19 illness, using a machine learning (ML) model. Six hundred and seventy two patients were enrolled for SARS-CoV-2 pneumonia between February 2020 and May 2021. Steatosis was detected by ultrasound or computed tomography (CT). ML model valuated the risks of both in-hospital death and prolonged hospitalizations (> 28 days), considering MAFLD, blood hepatic profile (HP), and FIB-4 score. 49.6% had MAFLD. The accuracy in predicting in-hospital death was 0.709 for the HP alone and 0.721 for HP + FIB-4; in the 55-75 age subgroup, 0.842/0.855; in the MAFLD subgroup, 0.739/ 0.772; in the MAFLD 55-75 years, 0.825/0.833. Similar results were obtained when considering the accuracy in predicting prolonged hospitalization. In our cohort of COVID-19 patients, the presence of a worse HP and a higher FIB-4 correlated with a higher risk of death and prolonged hospitalization, regardless of the presence of MAFLD. These findings could improve the clinical risk stratification of patients diagnosed with SARS-CoV-2 pneumonia.

Keywords: FIB-4; Liver steatosis; MAFLD; Machine learning.

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Conflict of interest statement

All authors declare no conflict of interest.

Figures

Fig. 1
Fig. 1
Bar graph showing the accuracy in death prediction with the fivefold cross validation test in our COVID-19 population, considering different sample, considering different subgroups (“Panel A” describe the all-ages cohort, while “Panel B” describe 55–75 age group) comparing the use of HP alone or the combined use of HP and FIB-4. *p < 0.05, **p < 0.01, ***p < 0.001, 5-FC fivefold cross validation test, FIB-4 Fibrosis-4 score, HP Hepatic profile blood tests, MAFLD metabolic-associated fatty liver disease, ns not significant, y years
Fig. 2
Fig. 2
Bar graph showing the accuracy in prolonged hospitalization (> 28 days) prediction with the fivefold cross validation test in our COVID-19 sample, considering different subgroups (“Panel A” describe the all-ages cohort, while “Panel B” describe 55–75 age group) and comparing the use of HP alone or the combined use of HP and FIB-4. *p < 0.05, **p < 0.01, ***p < 0.001, 5-FC fivefold cross validation test, FIB-4 Fibrosis-4 score, HP Hepatic profile blood tests, MAFLD metabolic-associated fatty liver disease, ns not significant, y years

Comment on

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