Novel Usefulness of M2BPGi for Predicting Severity and Clinical Outcomes in Hospitalized COVID-19 Patients
Mikyoung Park, Mina Hur, Hanah Kim, Chae Hoon Lee, Jong Ho Lee, Hyung Woo Kim, Minjeong Nam, Seungho Lee

TL;DR
This study shows that M2BPGi, a biomarker for liver fibrosis, can predict severity and outcomes in hospitalized COVID-19 patients.
Contribution
The study introduces M2BPGi as a novel prognostic biomarker for hospitalized COVID-19 patients.
Findings
M2BPGi levels significantly correlated with disease severity and mortality in hospitalized patients.
M2BPGi outperformed conventional clinical scores in predicting clinical outcomes.
M2BPGi was identified as an independent prognostic factor for mortality.
Abstract
Background/Objectives: Mac-2 binding protein glycosylation isomer (M2BPGi) is a novel biomarker for liver fibrosis, and its prognostic role has never been explored in coronavirus disease 2019 (COVID-19). We compared the M2BPGi level simultaneously with age, severe/critical disease, the sequential organ failure assessment (SOFA) score, and the National Early Warning Score 2 (NEWS2) in a total of 53 hospitalized patients with COVID-19 (mild/moderate [n = 15] and severe/critical [n = 38]). Methods: M2BPGi levels were measured using the HISCL M2BPGi assay (Sysmex, Kobe, Japan) in an HISCL-5000 analyzer (Sysmex), and clinical outcomes were analyzed according to M2BPGi and the clinical variables, using the receiver operating characteristic (ROC) curve, Kaplan–Meier survival, and Cox proportional hazards regression analyses. Results: M2BPGi levels differed significantly according to disease…
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Taxonomy
TopicsSepsis Diagnosis and Treatment · COVID-19 diagnosis using AI · Machine Learning in Healthcare
