Development and Validation of a New Model Including Inflammation Indexes for the Long-Term Prognosis of Hepatitis B-Related Acute-On-Chronic Liver Failure

IF 6.8 3区 医学 Q1 VIROLOGY Journal of Medical Virology Pub Date : 2024-12-09 DOI:10.1002/jmv.70110
Yeqiong Zhang, Qiumin Luo, Xiumei Lin, Lu Wang, Zhipeng Li, Jia Chen, Ruixuan Xu, Lina Wu, Liang Peng, Wenxiong Xu
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Abstract

Acute-on-chronic liver failure (ACLF) is a severe condition characterized by a systemic inflammatory response and associated with high mortality. Currently, there is no reliable prediction model for long-term prognosis in ACLF. This study aimed to develop and validate a prognostic model incorporating inflammation indexes to predict the long-term outcome of patients with hepatitis B virus-related ACLF (HBV-ACLF). A retrospective analysis of clinical data from HBV-ACLF patients (n = 986) treated at the Third Affiliated Hospital of Sun Yat-sen University between January 2014 and December 2018 was conducted. Patients were randomly divided into training (n = 690) and validation (n = 296) cohorts. The Least Absolute Shrinkage and Selection Operator (LASSO) and Cox regression analyses were used to identify independent risk factors for long-term mortality. The following variables were identified as independent predictors of long-term mortality: age, cirrhosis, hepatic encephalopathy, total bilirubin (TBIL), international normalized ratio (INR), monocyte-to-lymphocyte ratio (MLR), and neutrophil-to-platelet ratio (NPR). A novel nomogram was established by assigning weights to each variable. The C-index of the nomogram was 0.777 (95% confidence interval [CI]: 0.752–0.802). In the training set, the area under the curve (AUC) for predicting mortality at 1, 3, and 12 months was 0.841 (95% CI: 0.807–0.875), 0.827 (95% CI: 0.796–0.859), and 0.829 (95% CI: 0.798–0.859), respectively. The nomogram demonstrated superior predictive performance for 12-month survival compared to the model for end-stage liver disease (MELD) score (0.767, 95% CI: 0.730–0.804, p < 0.001) and the clinical overt sepsis in acute liver failure clinical practice Guidelines-ACLF II score (0.807, 95% CI: 0.774–0.840, p = 0.028). Finally, calibration curves and decision curve analysis (DCA) confirmed the clinical utility of the nomogram. The novel inflammation-based scoring system, incorporating MLR and NPR, effectively predicts long-term mortality in HBV-ACLF patients.

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包括炎症指标在内的乙型肝炎相关急慢性肝衰竭长期预后新模型的建立与验证
急性慢性肝衰竭(ACLF)是一种以全身炎症反应为特征的严重疾病,与高死亡率相关。目前,对于ACLF的长期预后尚无可靠的预测模型。本研究旨在建立并验证一种结合炎症指标的预后模型,以预测乙型肝炎病毒相关ACLF (HBV-ACLF)患者的长期预后。回顾性分析2014年1月至2018年12月在中山大学第三附属医院治疗的HBV-ACLF患者(n = 986)的临床资料。患者被随机分为训练组(n = 690)和验证组(n = 296)。最小绝对收缩和选择算子(LASSO)和Cox回归分析用于确定长期死亡率的独立危险因素。以下变量被确定为长期死亡率的独立预测因子:年龄、肝硬化、肝性脑病、总胆红素(TBIL)、国际标准化比率(INR)、单核细胞与淋巴细胞比率(MLR)和中性粒细胞与血小板比率(NPR)。通过对每个变量赋权,建立了新的nomogram。nomogram C-index为0.777(95%可信区间[CI]: 0.752 ~ 0.802)。在训练集中,预测1、3和12个月死亡率的曲线下面积(AUC)分别为0.841 (95% CI: 0.807-0.875)、0.827 (95% CI: 0.796-0.859)和0.829 (95% CI: 0.798-0.859)。与终末期肝病(MELD)评分模型相比,nomogram显示了更优越的12个月生存率预测性能(0.767,95% CI: 0.730-0.804, p
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来源期刊
Journal of Medical Virology
Journal of Medical Virology 医学-病毒学
CiteScore
23.20
自引率
2.40%
发文量
777
审稿时长
1 months
期刊介绍: The Journal of Medical Virology focuses on publishing original scientific papers on both basic and applied research related to viruses that affect humans. The journal publishes reports covering a wide range of topics, including the characterization, diagnosis, epidemiology, immunology, and pathogenesis of human virus infections. It also includes studies on virus morphology, genetics, replication, and interactions with host cells. The intended readership of the journal includes virologists, microbiologists, immunologists, infectious disease specialists, diagnostic laboratory technologists, epidemiologists, hematologists, and cell biologists. The Journal of Medical Virology is indexed and abstracted in various databases, including Abstracts in Anthropology (Sage), CABI, AgBiotech News & Information, National Agricultural Library, Biological Abstracts, Embase, Global Health, Web of Science, Veterinary Bulletin, and others.
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