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AFP-HINAT联合评分预测乙型病毒性肝炎相关慢加急性肝衰竭患者短期预后的价值

The value of AFP-HINAT combined score in predicting the short-term prognosis of patients with hepatitis B-related acute-on-chronic liver failure
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摘要 目的探讨甲胎蛋白(alpha fetoprotein,AFP)-HINAT模型联合评分对乙型病毒性肝炎相关慢加急性肝衰竭(hepatitis B virus-related acute-on-chronic liver failure,HBV-ACLF)患者预后的预测价值,并与其他评分模型对比。方法纳入2020年1月至2024年12月在郑州大学第二附属医院消化内科就诊的75例HBV-ACLF患者作为研究对象,按确诊后90 d的预后情况分为存活组(n=31)和死亡组(n=44)。分析HBV-ACLF患者短期预后的影响因素,并分析AFP、HINAT模型及AFP-HINAT联合评分与其他评分模型在患者短期预后预测方面的效能。结果AFP和HINAT模型是HBV-ACLF患者预后的独立危险因素(P<0.05),对比AFP、HINAT模型和其他评分模型,AFP-HINAT联合评分的预测效能更好(AUC=0.891),临床有效性更高(NRI>0,IDI>0)。结论AFP-HINAT联合评分评估HBV-ACLF患者短期预后有较高的价值和净收益。 Objective To investigate the predictive value of the alpha-fetoprotein(AFP)-HINAT model combined with other scoring models for the prognosis of patients with hepatitis B virus-related acute-on-chronic liver failure(HBV-ACLF).Methods A total of 75 HBV-ACLF patients treated in the Department of Gastroenterology,the Second Affiliated Hospital of Zhengzhou University from Jan.2020 to Dec.2024 were enrolled.Based on their 90-day prognosis after diagnosis,they were divided into a survival group(n=31)and a death group(n=44).The factors influencing short-term prognosis were analyzed,and the predictive efficacy of AFP,HINAT model,AFP-HINAT combined score,and other scoring models was evaluated.Results AFP and HINAT model were independent risk factors for HBV-ACLF prognosis(P<0.05).Compared to AFP,HINAT model and other scoring models,the AFP-HINAT combined score demonstrated superior predictive efficacy(AUC=0.891)and higher clinical validity(NRI>0,IDI>0).Conclusion The AFP-HINAT score has high predictive value and net benefit in assessing the short-term prognosis of HBV-ACLF patients.
作者 许龙星 XU Longxing(Department of Gastroenterology,the Second Affiliated Hospital of Zhengzhou University,Zhengzhou 450000,China)
出处 《胃肠病学和肝病学杂志》 2025年第7期1032-1038,共7页 Chinese Journal of Gastroenterology and Hepatology
关键词 慢加急性肝衰竭 甲胎蛋白 HINAT模型 预后 Acute-on-chronic liver failure Alpha-fetoprotein HINAT model Prognosis
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