Zhijun Zhang,1,* Li Yuan,2,* Junqing Zhang,3 Qiang Gu,4 Fang Yan5 

1Department of Minimally Invasive Gastroenterology and Hepatobiliary Surgery, Chengdu Wenjiang District People’s Hospital, Chengdu, Sichuan, People’s Republic of China; 2Department of Clinical Laboratory, Chengdu Fifth People’s Hospital, The Second Clinical Medical College, Affiliated Fifth People’s Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, People’s Republic of China; 3Department of Ultrasound Medicine, Chengdu Wenjiang District People’s Hospital, Chengdu, 611130, People’s Republic of China; 4Department of Medical Record Management, Chengdu Wenjiang District People’s hospital, Chengdu, 611130, People’s Republic of China; 5Geriatric Diseases Institute of Chengdu, Department of Geriatrics, Chengdu Fifth People’s Hospital, The Second Clinical Medical College, Affiliated Fifth People’s Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, People’s Republic of China

*These authors contributed equally to this work

Correspondence: Fang Yan, Email fangyan@cdutcm.edu.cn

Background: Acute liver injury (ALI) is a common complication in critically ill patients and has been strongly associated with adverse clinical outcomes. Early detection and timely management of ALI in these patients are crucial for implementing effective therapeutic strategies to prevent disease progression and improve patient outcomes.
Methods: In this study, 112 critically ill patients with bacterial infectious diseases were categorized into two groups based on the presence or absence of ALI within 24 hours of the intensive care unit (ICU) admission. Serum concentrations of fibroblast growth factor 21 (FGF21), interleukin(IL)-6, IL-22, IL-10, liver enzymes, hypersensitive C-reactive protein (hs-CRP), and D-Dimer (D2) were measured within 24 hours of ICU admission. Demographic and clinical data were recorded. Logistic regression analysis was performed to identify potentially predictive biomarkers for ALI. Receiver operating characteristic (ROC) curve analysis was employed to determine the optimal model for predicting ALI in critically ill patients.
Results: Patients in the ALI group exhibited significantly higher serum levels of IL-6, IL-10, IL-22, FGF21, liver enzymes, lactic acid, procalcitonin, D2, APACHE II scores, shorter survival time and higher 28-day mortality compared to those in the non-ALI group. Logistic regression analysis indicated that age, gender, plasma D2, and serum levels of direct bilirubin (DBIL), IL-22 and FGF21 were valuable predictors of ALI among critically ill patients. ROC curve revealed that this predictive model achieved a high area under the curve of 0.885, demonstrating excellent discriminatory ability.
Conclusion: Elevated levels of serum FGF21 in the early stages of critical illness may represent a promising novel biomarker for predicting ALI.

Keywords: critically ill patients, acute liver injury, FGF21, prediction, biomarkers