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Development of a prognostic factors model for severe hepatitis
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摘要:
目的研究重型肝炎患者预后的危险因素,建立预后判断模型。方法回顾性收集2008年6月至2011年6月在广西医科大学第八附属医院收治的145例重型肝炎患者的临床资料,运用Logistic进行单因素和多因素分析,建立预后模型。用独立的临床肝病资料进行验证,评判模型判断能力。结果 145名患者中好转54例,死亡91例,病死率62.8%(94/145)。Logistic回归分析结果显示肝性脑病、腹水、肌酐、血氨、凝血酶原活动度是独立危险因素。对构建的预后判断模型的预测能力进行研究发现:模型预测的灵敏度为92.0%,特异度为88.0%,总正确率为90.0%。结论肝性脑病、腹水、肌酐、血氨、凝血酶原活动度作为独立的危险因素可用于预后判断模型的构建。本研究构建的预后模型能够较为准确的预测重型肝炎患者的短期预后。
Abstract:Objective To generate a prognostic factors model for severe hepatitis.Methods The clinical data of 145 in-patients with severe hepatitis who had been treated in the Eighth Affiliated Hospital of Guangxi Medical University from June 2008 to June 2011 were retrospectively analyzed.Logistic regression analysis was used to develop a prognostic factors model.Results Among the 145 patients, 54 recovered and 91 died (case fatality rate: 62.8%) .Logistic regression analysis identified hepatic encephalopathy, ascites, creatinine, ammonia, and prothrombin activity as independent prognostic factors of severe hepatitis.Conclusion A prognostic factors model composed of hepatic encephalopathy, ascites, creatinine, ammonia, and prothrombin activity, can accurately predict the short-term prognosis of patients with severe hepatitis.
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[1]明全, 邱绍勤, 陈长寅.人工肝支持系统治疗重型肝炎临床研究[J].中华肝脏病杂志, 2004, 12 (5) :315. [2]中华医学会传染病与寄生虫病学分会、肝病学分会.病毒性肝炎防治方案[J].中华传染病杂志, 2001, 19 (1) :56-62. [3]丁惠国, 郜桂菊, 陈涛, 等.影响重型病毒性肝炎患者预后的危险因素研究[J].临床肝胆病杂志, 2002, 18 (5) :297-299. [4]赖宁, 郭树华, 张大志, 等.重型肝炎患者预后因素分析与评估系统研究[J].中华肝脏病杂志, 2005, 8 (13) :586-589. [5]张南, 王宇明, 邓国宏, 等.慢性重型肝炎患者的预后因素分析及预后模型的建立[J].中华肝脏病杂志, 2005, 13 (10) :730-733. [6]吕超, 陆建, 辛海光, 等.影响慢性重型肝炎预后相关指标的多因素回归分析[J].临床肝胆病杂志, 2008, 24 (6) :428-431. [7]骆抗先.乙型肝炎基础和临床[M].北京:人民卫生出版社, 2001:602-627. [8]Forman LM, Lucey MR.Predicting the prognosis of chronicliver disease:an evolution from child to MELD.Mayo End-stage Liver Disease[J].Hepatology, 2001, 33 (2) :473-475. [9]陆伦根.肝性脑病的发病机制[J].中华肝脏病杂志, 2004, 12 (5) :304. [10]汪杨, 辛桂杰, 王峰, 等.重型肝炎血氨检测的价值的研究[J].临床肝胆病杂志, 2008, 24 (3) :185-186. -
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