|
摘要:
|
| 目的:探讨乙型肝炎病毒(HBV)感染合并妊娠患者肝内胆汁淤积症(ICP)发生的危险因素,构建相关风险预测Nomogram模型,并进行效能验证。方法:回顾性分析2022年1月至2024年1月就诊于本院的592例HBV感染合并妊娠患者的临床资料,根据其是否发生ICP分为发生组(n=76)和未发生组(n=516)。比较两组临床资料,Logistic回归分析HBV感染合并妊娠患者ICP发生的影响因素;基于多因素分析结果应用R3.4.3软件制作Nomogram模型;绘制受试者工作特征(ROC)曲线评估Nomogram模型的风险预测能力,绘制校准曲线,使用Bootstrap法检测Nomogram模型的校准度,采用决策曲线分析(DCA)验证模型的临床净获益率。结果:HBV感染合并妊娠患者ICP发生率为12.84%;ICP家族史(OR=1.411,95%CI 1.049~1.896)、妊娠期高血压综合征(OR=1.228,95%CI 1.015~1.485)、自体免疫性疾病(OR=1.280,95%CI 1.046~1.567)、高雌激素水平(OR=1.281,95%CI 1.037~1.584)、低硒摄入量(OR=1.369,95%CI 1.123~1.669)、低锌摄入量(OR=1.342,95%CI 1.116~1.613)、谷丙转氨酶(ALT)(OR=1.338,95%CI 1.095~1.634)、总胆红素(TBIL)(OR=1.334,95%CI 1.103~1.613)、尿酸(UA)(OR=1.280,95%CI 1.054~1.554)为HBV感染合并妊娠患者ICP发生的影响因素(P<0.05)。Nomogram模型预测ICP发生的曲线下面积、灵敏度、特异度分别为0.950(95%CI 0.902~0.979)、94.74%、89.15%,Hosmer-Lemeshow拟合优度检验(χ2=1.987,P=0.415)显示拟合良好,Nomogram模型在阈值概率为0~93%时可提供临床净获益。结论:HBV感染合并妊娠患者ICP发生的影响因素包括ICP家族史、妊娠期高血压综合征、自体免疫性疾病、高雌激素水平、低硒摄入量、低锌摄入量、ALT、TBIL和UA,综合上述因素构建风险预测Nomogram模型对ICP发生风险有一定预测价值。 |
| Objective: To explore the risk factors of intrahepatic cholestasis(ICP) in pregnant women with hepatitis B virus(HBV) infection, establish a Nomogram model for risk prediction, and verify its efficacy. Methods: The clinical data of 592 cases of HBV infection patients complicated with pregnancy in our hospital from January 1, 2022 to January 31, 2024 were retrospectively analyzed, and they were divided into the occurrence group(n=76) and the non-occurrence group(n=516) according to whether ICP occurred or not. The clinical data of the two groups were compared, and the influencing factors of ICP in patients with HBV infection complicated with pregnancy were analyzed by multivariate Logistic regression. Based on the results of multi-factor analysis, the Nomogram model was made by R3.4.3 software. Receiver operating characteristic(ROC) curve was drawn to evaluate the risk prediction ability of Nomogram model, calibration curve was drawn and the calibration degree of Nomogram model was tested by Bootstrap method, and the clinical net benefit rate of the model was verified by decision curve analysis(DCA). Results: The occurrence rate of ICP in pregnant women with HBV infection was 12.84%. Family history of ICP(OR=1.411,95%CI 1.049-1.896), pregnancy-induced hypertension syndrome(OR=1.228,95%CI 1.015-1.485), autoimmune diseases(OR=1.280,95%CI 1.046-1.567), hyperestronemia(OR=1.281,95%CI 1.037-1.584), low selenium intake(OR=1.369, 95%CI 1.123-1.669), low zinc intake(OR=1.342, 95%CI 1.116-1.613), alanine transaminase(ALT)(OR=1.280,95%CI 1.095-1.634), total bilirubin(TBIL)(OR=1.334, 95%CI 1.103-1.613) and uric acid(UA)(OR=1.280, 95%CI 1.054-1.554) were the influencing factors of ICP in pregnant women with HBV infection(P<0.05). The area under curve, sensitivity and specificity predicted by Nomogram model were 0.950(95% CI 0.902-0.979), 94.74% and 89.15%, respectively. Hosmer-Lemeshow goodness-of-fit test(χ2=1.987, P=0.415) showed a good fit, and Nomogram model could provide clinical net benefits when the threshold probability was 0-93%. Conclusion: The influencing factors of ICP in pregnant women with HBV infection include family history of ICP, pregnancy-induced hypertension syndrome, autoimmune diseases, hyperestrogenism, low selenium intake, low zinc intake, ALT, TBIL and UA, it is of certain predictive value to construct a risk prediction Nomogram model based on the above factors. |
|
参考文献:
|
[1] IANNACONE M, GUIDOTTI L G.Immunobiology and pathogenesis of hepatitis B virus infection[J].Nat Rev Immunol, 2022, 22(1): 19-32. [2] WU S, WANG J, CHEN Y.'Prevalence of human immunodeficiency virus, syphilis, and hepatitis B and C virus infections in pregnant women: a systematic review and meta-analysis’: author's response[J].Clin Microbiol Infect, 2024, 30(1): 145-146. [3] ZHANG L, TANG C, YE C, et al.Intrahepatic cholestasis of pregnancy can increase the risk of metabolic disorders: a meta-analysis[J].J Med Biochem, 2022, 41(4): 549-558. [4] JIANG R, WANG T, YAO Y, et al.Hepatitis B infection and intrahepatic cholestasis of pregnancy: a systematic review and meta-analysis[J].Medicine, 2020, 99(31): e21416. [5] 沈佳雷, 曹克旦, 王芳.血清PTX3、SULT2A1、AFABP预测妊娠期肝内胆汁淤积症价值及其危险因素分析[J].肝脏, 2024, 29(12): 1553-1557. [6] LAZZARO R S, INRA M L.Commentary: Nomogram to the rescue: validate and show me the money[J].J Thorac Cardiovasc Surg, 2022, 164(1): 276-277. [7] 胡鹏, 任红.2017年欧洲肝病年会乙型肝炎病毒感染临床实践指南要点[J].中华肝脏病杂志, 2017, 25(6): 415-418. [8] 中国营养学会.中国居民膳食指南-2022[M].北京: 人民卫生出版社, 2022: 166. [9] 陈子江, 林其德, 王谢桐, 等.孕激素维持早期妊娠及防治流产的中国专家共识[J].中华妇产科杂志, 2016, 51(7): 481-483. [10] 中国营养学会.中国居民膳食营养素参考摄入量——2023版[M].北京: 人民卫生出版社, 2023: 35. [11] 中华医学会妇产科学分会产科学组.妊娠期肝内胆汁淤积症诊疗指南(2015)[J].临床肝胆病杂志, 2015, 31(10): 1575-1578. [12] 富晓敏.妊娠期肝内胆汁淤积症合并乙型肝炎病毒感染对妊娠结局的影响[D].太原: 山西医科大学, 2010. [13] MASHBURN S, SCHLECKMAN E, CACKOVIC P, et al.Intrahepatic cholestasis of pregnancy: risk factors for severe disease[J].J Matern Fetal Neonatal Med, 2022, 35(25): 8566-8570. [14] LI P, JIANG Y, XIE M, et al.Factors associated with intrahepatic cholestasis of pregnancy and its influence on maternal and infant outcomes[J].Medicine, 2023, 102(1): e32586. [15] TOPRAK K, YıLDıZ Z, AKDEMIR S, et al.Low pregnancy-specific beta-1-glycoprotein is associated with nondipper hypertension and increased risk of preeclampsia in pregnant women with newly diagnosed chronic hypertension[J].Scand J Clin Lab Invest, 2023, 83(7): 479-488. [16] 余玲, 贾颖娜, 王轶.妊娠期肝内胆汁淤积症患者凝血功能相关指标的临床意义[J].实用临床医药杂志, 2022, 26(20): 119-123, 135. [17] 张静, 孟璐, 刘辰, 等.妊娠期肝内胆汁淤积症发生的危险因素及对妊娠结局的影响[J].临床与病理杂志, 2022, 42(8): 1868-1874. [18] 冯俊英, 王乐霞, 刘岚, 等.硒锌摄入量、肝胆疾病与妊娠期肝内胆汁淤积症患者的相关性研究[J].现代消化及介入诊疗, 2019, 24(12): 1440-1442. [19] 吴玮, 余菁雯, 蒋晖.孕妇发生妊娠期肝内胆汁淤积症的风险列线图模型的建立研究[J].实用临床医药杂志, 2022, 26(4): 18-23. [20] TANG V W.Role of pathologists in nomogram development[J].Pathology, 2023, 55(7): 1048-1049. [21] QI W, YIN Z, SUN Y, et al.Nomogram for predicting the 12-year risk of ADL disability among older adults[J].Aging Clin Exp Res, 2022, 34(7): 1583-1591. |
|
服务与反馈:
|
|
【文章下载】【发表评论】【查看评论】【加入收藏】
|
| 提示:您还未登录,请登录!点此登录 |
|