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尿胆汁酸指标作为肝病相关并发症的预后生物标志物

Urinary BA Indices as Prognostic Biomarkers for Complications Associated with Liver Diseases.

作者信息

Li Wenkuan, Alamoudi Jawaher Abdullah, Gautam Nagsen, Kumar Devendra, Olivera Macro, Gwon Yeongjin, Mukgerjee Sandeep, Alnouti Yazen

机构信息

Department of Pharmaceutical Sciences, College of Pharmacy, University of Nebraska Medical Center, Omaha, NE 68198, USA.

Department of Internal Medicine, College of Medicine, University of Nebraska Medical Center, Omaha, NE 68198, USA.

出版信息

Int J Hepatol. 2022 Mar 30;2022:5473752. doi: 10.1155/2022/5473752. eCollection 2022.

Abstract

Hepatobiliary diseases and their complications cause the accumulation of toxic bile acids (BA) in the liver, blood, and other tissues, which may exacerbate the underlying condition and lead to unfavorable prognosis. To develop and validate prognostic biomarkers for the prediction of complications of cholestatic liver disease based on urinary BA indices, liquid chromatography-tandem mass spectrometry was used to analyze urine samples from 257 patients with cholestatic liver diseases during a 7-year follow-up period. The urinary BA profile and non-BA parameters were monitored, and logistic regression models were used to predict the prognosis of hepatobiliary disease-related complications. Urinary BA indices were applied to quantify the composition, metabolism, hydrophilicity, and toxicity of the BA profile. We have developed and validated the bile-acid liver disease complication (BALDC) model based on BA indices using logistic regression model, to predict the prognosis of cholestatic liver disease complications including ascites. The mixed BA and non-BA model was the most accurate and provided higher area under the receiver operating characteristic (ROC) and smaller akaike information criterion (AIC) values compared to both non-BA and MELD (models for end stage liver disease) models. Therefore, the mixed BA and non-BA model could be used to predict the development of ascites in patients diagnosed with liver disease at early stages of intervention. This will help physicians to make a better decision when treating hepatobiliary disease-related ascites.

摘要

肝胆疾病及其并发症会导致有毒胆汁酸(BA)在肝脏、血液和其他组织中蓄积,这可能会加重潜在病情并导致预后不良。为了开发并验证基于尿BA指标预测胆汁淤积性肝病并发症的预后生物标志物,在7年随访期内,采用液相色谱-串联质谱法分析了257例胆汁淤积性肝病患者的尿液样本。监测尿BA谱和非BA参数,并使用逻辑回归模型预测肝胆疾病相关并发症的预后。尿BA指标用于量化BA谱的组成、代谢、亲水性和毒性。我们使用逻辑回归模型,基于BA指标开发并验证了胆汁酸肝病并发症(BALDC)模型,以预测包括腹水在内的胆汁淤积性肝病并发症的预后。与非BA模型和终末期肝病模型(MELD)相比,混合BA和非BA模型最为准确,受试者操作特征曲线(ROC)下面积更大,赤池信息准则(AIC)值更小。因此,混合BA和非BA模型可用于预测在干预早期被诊断为肝病的患者腹水的发生情况。这将有助于医生在治疗肝胆疾病相关腹水时做出更好的决策。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f9fd/8986411/6427636012f2/IJH2022-5473752.001.jpg

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