摘要
目的总结分析230例药物性肝损伤(DILI)患者的临床特征。方法2020年3月~2023年3月我院诊治的DILI患者230例,常规行血生化检查,采用免疫印迹法检测血清抗核抗体(ANA),采用免疫散射比浊法检测血清免疫球蛋白(Ig)G和IgM。结果在230例DILI患者中,肥胖占45.7%,2型糖尿病占37.8%,高脂血症占43.5%;基础疾病中感染性疾病占23.5%,心血管疾病占17.0%,肿瘤占13.0%;肝细胞损伤型占61.7%,胆汁淤积型占24.4%,混合型占13.9%;单一用药者占58.3%,双联用药者占22.6%,三联用药者占13.0%,四联用药及以上者占6.1%;<3级(轻中度)肝损害占58.7%,≥3级(重度)肝损害占41.3%;血清IgM水平为(1.2±0.1)mg/ml,IgG水平为(10.6±2.1)g/L,血清抗核抗体阳性占27.5%;经降酶退黄治疗,本组患者痊愈,无死亡病例。结论本组DILI患者较年轻,可能与不适当用药有关。经停药和护肝治疗,大多预后良好。
Objective The aim of this study was to summarize clinical feature of patients with drug-induced liver injury(DILI)in order to improve clinical management.Methods 230 patients with DILI were encountered in our hospital between March 2020 and March 2023,and the demographic data,clinical manifestations,and clinical tests were retrospectively reviewed and summarized.Serum antinuclear antibody(ANA)was assayed by Western blot,and serum IgG and IgM were detected routinely.Results Of 230 patients with DILI,obesity accounted for 45.7%,diabetes type 2 for 37.8%and hyperlipidemia for 43.5%;as for underlying diseases,infection accounted for 23.5%,cardiovascular diseases for 17.0%and tumor for 13.0%;patients with hepatocellular injury accounted for 61.7%,cholestatic injury for 24.4%and mixed type for 13.9%;one single alleged medicines accounted for 58.3%,double for 22.6%,trible for 13.0%and quadruplex for 6.1%;mild to moderate liver injury accounted for 58.7%and severe for 41.3%;serum IgM and IgG levels were normal,and serum ANA positive for 27.5%;all patients in our series recovered without death.Conclusion Patients with DILI in our series is relatively young,inappropriate medication might be involved in pathogenesis and the prognosis is good.
作者
李靖
何海滨
李春婷
石磊
Li Jing;He Haibin;Li Chunting(Department of Hepatobiliary and Pancreatic Medicine,First Hospital,Affiliated to Jilin University,Changchun 130021,Jilin Province,China)
出处
《实用肝脏病杂志》
CAS
2024年第6期870-873,共4页
Journal of Practical Hepatology
基金
中国肝炎防治基金会天晴肝病研究基金资助项目(编号:TQGB20210118)。
关键词
药物性肝损伤
临床特征
预后
Drug-induced liver injury
Clinical feature
Prognosis