Comparison of Liver Biomarkers in 288 COVID-19 Patients: A Mono-Centric Study in the Early Phase of Pandemic

Autor: Haozhi Fan, Jinyuan Cai, Anran Tian, Yuwen Li, Hui Yuan, Zhengyi Jiang, Yunxi Yu, Lili Ruan, Pingping Hu, Ming Yue, Nian Chen, Jun Li, Chuanlong Zhu
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Frontiers in Medicine, Vol 7 (2021)
Druh dokumentu: article
ISSN: 2296-858X
DOI: 10.3389/fmed.2020.584888
Popis: Background and Aims: Recent reports have indicated that hepatic dysfunction occurred in a proportion of patients with coronavirus disease 2019 (COVID-19). We aimed to compare and describe the liver biomarkers in different subtypes of COVID-19 patients.Methods: This study enrolled 288 COVID-19 patients in Huangshi Hospital of Traditional Chinese Medicine. All patients were divided into ordinary, severe, and critical groups according to the Diagnosis and Treatment Protocol for Novel Coronavirus Pneumonia (Trial Version 7). Demographic, clinical characteristics and liver biomarkers were compared among the three groups.Results: During hospitalization, AST, TBiL, and ALP levels in ordinary and severe patients fluctuated within the normal range with a rising trend in critical patients except AST. ALT and GGT levels fluctuated within the normal range showing an upward trend, while LDH levels in the critical group exceeded the normal range. Prealbumin showed an upward trend, especially in the severe group. At discharge, AST and LDH levels in ordinary and severe groups were lower than their baselines but increased in the critical group. In contrast to albumin, TBiL levels were increased in ordinary and critical groups while decreased in the severe group. The stratified analysis revealed factors affecting liver function in critical cases included highest temperature ≥38.0°C, age ≥60 and symptom of hypoxemia.Conclusions: COVID-19 can cause severe hepatic dysfunction in critical patients, requiring early monitoring and intervention. LDH, ALP, GGT, TBiL, prealbumin, and albumin may be helpful for evaluating and predicting disease prognosis due to their correlation with disease severity in COVID-19.
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