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

IF 1.5 Q3 GASTROENTEROLOGY & HEPATOLOGY
Wenkuan Li, J. Alamoudi, N. Gautam, Devendra Kumar, Macro Olivera, Y. Gwon, Sandeep Mukgerjee, Y. Alnouti
{"title":"Urinary BA Indices as Prognostic Biomarkers for Complications Associated with Liver Diseases","authors":"Wenkuan Li, J. Alamoudi, N. Gautam, Devendra Kumar, Macro Olivera, Y. Gwon, Sandeep Mukgerjee, Y. Alnouti","doi":"10.1155/2022/5473752","DOIUrl":null,"url":null,"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.","PeriodicalId":46297,"journal":{"name":"International Journal of Hepatology","volume":"3 1","pages":""},"PeriodicalIF":1.5000,"publicationDate":"2022-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Hepatology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1155/2022/5473752","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"GASTROENTEROLOGY & HEPATOLOGY","Score":null,"Total":0}
引用次数: 1

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.
尿BA指数作为肝脏疾病相关并发症的预后生物标志物
肝胆疾病及其并发症可导致毒性胆汁酸(BA)在肝脏、血液和其他组织中积累,从而加重基础疾病并导致不良预后。为了开发和验证基于尿BA指数预测胆汁淤积性肝病并发症的预后生物标志物,在7年的随访期间,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,采用logistic回归模型预测肝胆疾病相关并发症的预后。尿BA指数用于量化BA谱的组成、代谢、亲水性和毒性。我们利用logistic回归模型建立并验证了基于BA指数的胆汁酸性肝病并发症(BALDC)模型,用于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和MELD(终末期肝病模型)模型相比,BA和非BA混合模型最准确,具有更高的受试者工作特征(ROC)下面积和更小的akaike信息准则(AIC)值。因此,BA和非BA混合模型可用于预测干预早期诊断为肝病患者腹水的发展。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定。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
International Journal of Hepatology
International Journal of Hepatology GASTROENTEROLOGY & HEPATOLOGY-
CiteScore
3.80
自引率
0.00%
发文量
11
审稿时长
15 weeks
期刊介绍: International Journal of Hepatology is a peer-reviewed, Open Access journal that publishes original research articles, review articles, and clinical studies related to the medical, surgical, pathological, biochemical, and physiological aspects of hepatology, as well as the management of disorders affecting the liver, gallbladder, biliary tree, and pancreas.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信