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慢性肝衰竭急性发作患者的血清代谢组学特征及其对90天预后的预测价值。

Serum metabolomic characteristics and their predictive value for ninety-day prognosis in patients with acute-on-chronic liver failure.

作者信息

Liu Yan, Xiao Ying, Ai Lian-Feng, Zhang Jing-Jing, Zhang Jian-Dong, Qi Ze-Qiang, Dong Lei, Wang Ya-Dong

机构信息

Department of Clinical Laboratory, The Hebei Medical University Third Hospital, Shijiazhuang 050051, Hebei Province, China.

Department of Infectious Diseases, The Hebei Medical University Third Hospital, Shijiazhuang 050000, Hebei Province, China.

出版信息

World J Gastroenterol. 2025 Aug 14;31(30):110401. doi: 10.3748/wjg.v31.i30.110401.

Abstract

BACKGROUND

Acute-on-chronic liver failure (ACLF) is characterized by severe metabolic disturbances; however, the specific metabolomic features and their predictive value on 90-day prognosis remain unclear.

AIM

To identify serum metabolomic changes in patients with ACLF with different prognoses to support clinical prediction of outcomes and treatment decisions.

METHODS

This non-interventional, observational case-control study enrolled 58 patients with ACLF. Fasting venous blood samples were analyzed using targeted metabolomics. Univariate and multivariate statistical analyses identified differential metabolites among 18 amino acids, 11 fatty acids, 5 gut microbiota-related metabolites, and 4 bile acid metabolites. Binary logistic regression identified independent mortality risk factors, visualized forest plots and receiver operating characteristic curves.

RESULTS

Significant differences ( < 0.05) were observed between the death and survival groups in baseline age, model for end-stage liver disease score, model for end-stage liver disease with sodium, neutrophil-to-lymphocyte ratio (NLR), total bilirubin, serum creatinine, blood urea nitrogen, and platelet count. Metabolites, including L-carnitine, creatinine, alanine, arginine (Arg), proline, choline, and oleic acid, also showed statistically significant differences between the groups. Multivariate analysis identified age, NLR, and Arg as independent risk factors for 90-day mortality in patients with ACLF. The predictive model, age-NLR-Arg = -15.481 + 0.135 × age + 0.156 × NLR + 0.203 × Arg, with a cutoff of 0.759, achieved an area under the receiver operating characteristic curve of 0.945 with sensitivity of 84.0% and specificity of 87.9%.

CONCLUSION

The age-NLR-Arg model demonstrates a strong predictive value for 90-day mortality risk in patients with ACLF.

摘要

背景

慢加急性肝衰竭(ACLF)的特征是严重的代谢紊乱;然而,其具体的代谢组学特征及其对90天预后的预测价值仍不清楚。

目的

识别不同预后的ACLF患者血清代谢组学变化,以支持临床结局预测和治疗决策。

方法

这项非干预性观察性病例对照研究纳入了58例ACLF患者。采用靶向代谢组学分析空腹静脉血样本。单变量和多变量统计分析确定了18种氨基酸、11种脂肪酸、5种肠道微生物群相关代谢物和4种胆汁酸代谢物中的差异代谢物。二元逻辑回归确定独立的死亡风险因素,绘制森林图和受试者工作特征曲线。

结果

死亡组和存活组在基线年龄、终末期肝病模型评分、含钠终末期肝病模型、中性粒细胞与淋巴细胞比值(NLR)、总胆红素、血清肌酐、血尿素氮和血小板计数方面存在显著差异(<0.05)。包括左旋肉碱、肌酐、丙氨酸、精氨酸(Arg)、脯氨酸、胆碱和油酸在内的代谢物在两组之间也显示出统计学上的显著差异。多变量分析确定年龄、NLR和Arg是ACLF患者90天死亡率的独立风险因素。预测模型age-NLR-Arg = -15.481 + 0.135×年龄 + 0.156×NLR + 0.203×Arg,截断值为0.759,受试者工作特征曲线下面积为0.945,灵敏度为84.0%,特异性为87.9%。

结论

年龄-NLR-Arg模型对ACLF患者90天死亡风险具有较强的预测价值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/66ff/12404127/646773b7f346/wjg-31-30-110401-g001.jpg

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