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核苷(酸)类似物序贯派格宾治疗慢性乙型肝炎实现功能性治愈的预测因素
DOI: 10.3969/j.issn.1001-5256.2023.02.008
伦理学声明：本研究于2022年9月1日经青岛市市立医院伦理委员会审批通过，批号：2022临审字第056号，所有患者已签署干扰素治疗知情同意书。
利益冲突声明：本研究不存在研究者、伦理委员会成员、受试者监护人以及与公开研究成果有关的利益冲突。
作者贡献声明：辛永宁、周永负责研究的设计与实施；臧海洋、李伟娜、刘守胜共同负责资料的收集以及数据的分析；臧海洋负责文章的撰写；辛永宁、周永负责文章的修改与定稿。
Predictive factors for functional cure after sequential therapy with nucleos(t)ide analogues and pegylated interferon alfa-2b in treatment of chronic hepatitis B
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摘要:
目的 探究长期核苷(酸)类似物(NUC)抗病毒治疗后序贯派格宾(聚乙二醇干扰素α-2b)治疗的慢性乙型肝炎(CHB)患者实现功能性治愈的独立预测因素。 方法 以青岛市多家医院2018年—2021年收治的CHB患者共162例为研究对象，所有患者均应用派格宾治疗至少48周，且在派格宾治疗前经过了1年及以上的NUC治疗。根据派格宾治疗48周时是否实现HBsAg阴转将入组患者分为功能性治愈组(79例)和未治愈组(82例)，比较两组患者相关临床指标的差异。定量资料两组间比较采用两独立样本t检验和Mann-Whitney U秩和检验；定性资料两组间比较采用χ2检验。相关性分析采用Spearman检验。单因素和多因素Logistic回归分析实现功能性治愈的独立预测因素。绘制相关变量的受试者工作特征曲线(ROC曲线)，以曲线下面积(AUC)评估变量的预测准确度。 结果 功能性治愈组患者的基线HBsAg显著低于未治愈组[21.63(3.33~157.60)IU/mL vs 794.70(336.10~1 185.34)IU/mL，Z=-8.869，P＜0.001]，派格宾治疗12周的HBsAg显著低于未治愈组[1.34(0.04~16.59)IU/mL vs 567.11(226.09~1 047.86)IU/mL，Z=-9.847，P＜0.001]，派格宾治疗24周的HBsAg显著低于未治愈组[0.01(0.00~0.34)IU/mL vs 304.79(89.24~772.23)IU/mL，Z=-10.474，P＜0.001]，派格宾治疗12周的HBsAg下降程度显著高于未治愈组[89.6%(57.5%~99.4%) vs 21.8%(2.0%~40.9%)，Z=-7.926，P＜0.001]，派格宾治疗24周的HBsAg下降程度显著高于未治愈组[99.9%(99.0%~100.0%) vs 44.1%(20.6%~73.8%)，Z=-9.593，P＜0.05]，基线HBeAg阳性率显著低于未治愈组(8.9% vs 25.3%，χ2=7.652，P=0.006)，基线HBV DNA＞1000 IU/mL的比例显著低于未治愈组(0 vs 8.4%，χ2=5.073，P=0.024)，基线总胆红素显著低于未治愈组[12.60(10.12~15.93)μmol/L vs 15.50(11.80~24.10)μmol/L，Z=-3.611，P＜0.001]，治疗12周的AST显著高于未治愈组[47.00(34.00~68.00)U/L vs 41.00(30.00~56.50)U/L，Z=-2.031，P=0.042]，治疗12周AST＞2倍正常值上限比例显著高于未治愈组(16.5% vs 4.8%，χ2=5.835，P=0.016)。多因素Logistic回归分析显示，基线HBsAg(OR=0.996，95%CI：0.995~0.997)、派格宾治疗12周HBsAg(OR=0.990，95%CI: 0.986~0.994)、派格宾治疗24周HBsAg(OR=0.983，95%CI: 0.975~0.991)、基线总胆红素(OR=0.885，95%CI: 0.826~0.949)为功能性治愈的独立预测因素(P值均＜0.05)。基线HBsAg对应的AUC为0.904，最佳界值为118.24 IU/mL；派格宾治疗12周HBsAg对应的AUC为0.948，最佳界值为73.74 IU/mL；派格宾治疗24周HBsAg对应的AUC为0.975，最佳界值为11.01 IU/mL；基线总胆红素对应的AUC为0.664，最佳界值为19.9 μmol/L。 结论 NUC序贯派格宾治疗CHB时基线HBsAg、派格宾治疗12周HBsAg、派格宾治疗24周HBsAg以及基线总胆红素水平是派格宾治疗48周时患者实现功能性治愈的独立预测因素。 -
关键词:
- 乙型肝炎，慢性 /
- 抗病毒药 /
- 聚乙二醇干扰素α-2b /
- 乙型肝炎表面抗原
Abstract:Objective To investigate the independent predictive factors for functional cure after long-term nucleos(t)ide analogue (NUC) antiviral therapy followed by pegylated interferon α-2b therapy in chronic hepatitis B (CHB) patients. Methods A total of 162 CHB patients who were admitted to several hospitals in Qingdao, China, from 2018 to 2021 were enrolled as subjects, and all patients received pegylated interferon α-2b for at least 48 weeks after NUC therapy for one year or longer. According to whether HBsAg clearance was achieved at week 48 of pegylated interferon α-2b treatment, the patients were divided into functional cure group with 79 patients and non-cure group with 83 patients, and related clinical indices were compared between the two groups. The two-independent-samples t test and the Mann-Whitney U rank sum test were used for comparison of continuous data between two groups, and the chi-square test was used for comparison of categorical data between two groups. The Spearman correlation analysis was performed, and the univariate and multivariate logistic regression analyses were used to investigate the independent predictive factors for functional cure. The receiver operating characteristic (ROC) curve was plotted for related variables, and the area under the ROC curve (AUC) was used to evaluate the prediction accuracy of the variables. Results Compared with the non-cure group, the functional cure group had a significantly lower HBsAg level at baseline [21.63 (3.33-157.60) IU/mL vs 794.70 (336.10-1 185.34) IU/mL, Z=-8.869, P < 0.001], at week 12 of pegylated interferon α-2b treatment [1.34 (0.04-16.59) IU/mL vs 567.11 (226.09-1 047.86) IU/mL, Z=-9.847, P < 0.001), and at week 24 of pegylated interferon α-2b treatment [0.01 (0.00-0.34) IU/mL vs 304.79 (89.24-772.23) IU/mL, Z=-10.474, P < 0.001) and a significantly greater reduction in HBsAg at weeks 12 and 24 of pegylated interferon α-2b treatment [week 12: 89.6% (57.5%-99.4%) vs 21.8% (2.0%-40.9%), Z=-7.926, P < 0.001; week 24: 99.9% (99.0%-100.0%) vs 44.1% (20.6%-73.8%), Z=-9.593, P < 0.001]. Compared with the non-cure group, the functional cure group had a significantly lower HBeAg positive rate at baseline (8.9% vs 25.3%, χ2=7.652, P=0.006), a significantly lower proportion of patients with baseline HBV DNA > 1000 IU/mL (0 vs 8.4%, χ2=5.073, P=0.024), a significantly lower level of total bilirubin at baseline [12.60 (10.12-15.93) μmol/L vs 15.50 (11.80-24.10) μmol/L, Z=-3.611, P < 0.001], a significantly higher level of aspartate aminotransferase (AST) at week 12 of treatment [47.00 (34.00-68.00) U/L vs 41.00 (30.00-56.50) U/L, Z=-2.031, P=0.042], and a significantly higher proportion of patients with AST > 2×upper limit of normal (16.5% vs 4.8%, χ2=5.835, P=0.016). The multivariate logistic regression analysis showed that baseline HBsAg (odds ratio [OR]=0.996, 95% confidence interval [CI]: 0.995-0.997, P < 0.001), HBsAg at week 12 of pegylated interferon α-2b treatment (OR=0.990, 95%CI: 0.986-0.994, P < 0.001), HBsAg at week 24 of pegylated interferon α-2b treatment (OR=0.983, 95%CI: 0.975-0.991, P < 0.001), and baseline total bilirubin (OR=0.885, 95%CI: 0.826-0.949, P=0.001) were independent predictive factors for functional cure. The ROC curve of baseline HBsAg showed an AUC of 0.904 and the optimal cut-off value of 118.24 IU/mL; the ROC curve of HBsAg at week 12 of pegylated interferon α-2b treatment showed an AUC of 0.948 and the optimal cut-off value of 73.74 IU/mL; the ROC curve of HBsAg at week 24 of pegylated interferon α-2b treatment showed an AUC of 0.975 and the optimal cut-off value of 11.01 IU/mL; the ROC curve of baseline total bilirubin showed an AUC of 0.664 and the optimal cut-off value of 19.9 μmol/L. Conclusion Baseline HBsAg, HBsAg at week 12 of pegylated interferon α-2b treatment, HBsAg at week 24 of pegylated interferon α-2b, and baseline total bilirubin are independent predictive factors for functional cure at week 48 of pegylated interferon α-2b treatment in CHB patients receiving sequential therapy with NUC and pegylated interferon α-2b. -
针对肝硬化上消化道出血，无论是传统的外科手术，还是内镜下治疗或经颈静脉肝内门体分流术的微创治疗，治疗时机是非常重要的，因而成功的预测出血风险则显得极为重要[1-3]。因为乙型肝炎肝硬化的肝脏及脾脏在密度及血流灌注上存在特异性表现，因而ΔCT值具有特殊变化规律[4]。笔者拟基于现有数据，寻找乙型肝炎肝硬化患者CT上的特征性表现，以建立肝硬化患者上消化道出血的预测模型，旨在预测出血风险，为治疗方案的制订提供理论依据。
1. 资料与方法
1.1 研究对象
回顾性分析2015年1月—2021年6月天津市第一中心医院101例乙型肝炎肝硬化患者的临床资料。年龄26~70周岁，平均年龄50岁，其中男85例，女16例。所有患者后期均接受肝脏移植手术，病理证实符合我国慢性乙型肝炎肝硬化诊断标准[5]。纳入标准：年龄为18~70周岁乙型肝炎肝硬化患者。排除标准：合并其他类型肝病；长期大量饮酒史；合并肝癌；肝内存在动静脉瘘；干细胞治疗史；脾切除史；肝部分切除史；门奇静脉曲张断流手术史；门腔静脉分流手术史。根据是否出血，分为出血组(n=58)和非出血组(n=43)。
1.2 观察指标
出血组记录出血即刻的血清TBil、血清肌酐(Cr)、凝血时间、国际标准化比值(INR)、WBC、PLT等指标。并记录同时期强化CT检查测得的肝脏及脾脏平扫期(Plain)、动脉期(A)、门脉期(P)以及静脉期(V)的CT值，并计算各期间CT值的变化(ΔCT)，包括Δ动脉期－平扫期(ΔA-Plain)、Δ门脉期－平扫期(ΔP-Plain)、Δ静脉期－平扫期(ΔV-Plain)、Δ门脉期－动脉期(ΔP-A)、Δ静脉期－动脉期(ΔV-A)以及Δ静脉期－门脉期(ΔV-P)。非出血组记录肝移植评估时的实验室及影像学数据。
1.3 CT检查方法
所有患者均使用SOMATOM Definition Flash (Siemens Healthineers Co., Ltd，Germany) 128层螺旋CT进行扫描。参数设置为：管球电压120 kV，自动管电流200-420 mAs，扫描层厚5 mm，重建层厚1.2 mm，螺距0.8。使用双筒高压注射器自右肘正中静脉位置团注非离子型碘对比剂碘海醇注射液80 mL(350 mgI/mL)与生理盐水40 mL，团注速率为3.5 mL/s。动脉期采用团注智能跟踪启动扫描，对比剂团注后45~55 s进行门脉期扫描，70~75 s后行静脉期扫描。扫描后图像数据传输至工作站进行后处理。由同一名医生对于每例观察对象，于各个期像分别选取同一层面做为观察点进行CT值测量。为减少误差，观察点的选取需避开血管、胆管及韧带，同时为了减少观察点的差异，选取了该层面全部肝、脾组织的数据。
1.4 统计学方法
使用IBM SPSS Statistics 26.0进行统计分析。符合正态分布的计量资料以x±s表示，两组间的比较使用t检验；偏态分布的计量资料以M(P25~P75)表示，两组间的比较使用Mann-Whitney U检验。使用logistic回归分析方法，预测相关危险因素。通过计算受试者工作特征曲线下的面积(AUC，或c-统计量)来评估模型辨别力，而模型校准则通过Hosmer-Lemeshow确定。在多变量logistic回归分析结果的基础上，使用Rstudio4.1.2软件的R包(rms)构建预测的列线图模型，并绘制相应的ROC曲线、校准曲线以及临床决策曲线。用Bootstrap重抽样(1000次迭代)进行内部验证。临床决策曲线可以描述列线图给出的净效益，有助于确定在该模型上做出临床决策是否利大于弊。P＜0.05为差异有统计学意义。
2. 结果
2.1 出血组与无出血组实验室指标比较
无出血组血清TBil、WBC、PLT与出血组比较，差异均有统计学意义(P值均＜0.05)；而两组Cr、INR比较，差异均无统计学意义(P值均＞0.05)(表 1)。
表 1 合并上消化道出血与无上消化道出血两组间各项实验室检查指标Table 1. The difference of laboratory examination between the two groups with and without upper gastrointestinal bleeding项目 非出血组(n=43) 出血组(n=58) Z值 P值 TBil(μmol/L) 43.20(21.93~109.54) 27.74(18.88~56.63) -2.284 0.022 Cr(μmol/L) 62.00(52.00~86.00) 64.96(58.57~75.25) -0.289 0.773 INR 1.54(1.36~2.06) 1.49(1.28~1.78) -1.202 0.229 WBC(×109/L) 3.93(2.68~5.57) 2.80(1.95~3.60) -3.197 0.001 PLT(×109/L) 70.00(51.00~92.00) 52.50(37.00~77.00) -2.865 0.004 2.2 出血组与非出血组间肝脏及脾脏ΔCT的变化
两组在肝-Plain、脾-P-Plain、脾-P-A ΔCT值存在统计学差异(P值均＜0.05)，而肝脏在其他期像的CT值和各期间的ΔCT以及脾脏所有期像与ΔCT均无统计学差异(P值均＞0.05)(表 2)。
表 2 出血组与非出血组间肝脏及脾脏ΔCT的变化情况Table 2. The difference of ΔCT of liver and spleen between the two groups with and without upper gastrointestinal bleeding项目 非出血组(n=43) 出血组(n=58) 统计值 P值 肝-Plain 51.70±6.77 56.28±5.13 t=-3.870 ＜0.001 肝-A 62.28±6.84 64.88±6.34 t=-1.971 0.052 肝-P 85.67±13.83 86.48±11.23 t=-0.324 0.747 肝-V 92.88±12.19 94.19±12.19 t=-0.532 0.596 肝-A-Plain 9.00(8.00~15.00) 9.00(4.00~12.00) Z=-1.848 0.065 肝-P-Plain 30.00(27.00~41.00) 30.00(21.75~37.25) Z=-1.395 0.163 肝-V-Plain 41.19±11.37 37.91±10.64 t=1.484 0.141 肝-P-A 20.00(16.00~30.00) 21.00(15.00~27.00) Z=-0.426 0.670 肝-V-A 30.60±12.20 29.31±10.82 t=0.563 0.575 肝-V-P 7.21±8.23 7.71±9.22 t=-0.281 0.780 脾-Plain 45.00±3.16 46.02±3.05 t=-1.634 0.105 脾-A 81.00(71.00~90.00) 82.50(73.00~93.25) Z=-0.722 0.470 脾-P 116.81±23.81 110.07±16.44 t=1.684 0.095 脾-V 105.81±17.73 103.16±14.02 t=0.836 0.405 脾-A-Plain 37.09±14.02 38.00±14.01 t=-0.322 0.748 脾-P-Plain 71.81±22.58 64.05±16.43 t=2.012 0.047 脾-V-Plain 60.81±16.80 57.14±14.15 t=1.192 0.236 脾-P-A 34.72±16.39 26.05±17.00 t=2.577 0.011 脾-V-A 23.72±13.16 19.14±17.50 t=1.441 0.153 脾-V-P -9.00(-17.00~-4.00) -8.00(-11.00~-2.75) Z=-1.836 0.066 2.3 乙型肝炎肝硬化上消化道出血的危险因素分析及预测模型的建立
综合上述指标，发现乙型肝炎肝硬化患者WBC、PLT、肝-Plain、脾-P-Plain、脾-P-A ΔCT值在两组间具有统计学差异(P值均＜0.05)；应用多因素logistic分析结果显示PLT、肝-Plain、脾-P-A间ΔCT值为上消化道出血的独立危险因素(P值均＜0.05) (表 3)。基于PLT、肝-Plain、脾-P-A间ΔCT值这3个危险因素，使用Rstudio4.1.2软件的R包(rms)构建预测乙型肝炎肝硬化上消化道出血的预测模型。该模型的AUC为0.801(95%CI：0.713~0.889)，敏感度是0.814，特异度是0.776。模型的校准曲线贴近理想曲线(斜率为1.007)。临床决策曲线显示构建的列线图做出的临床决策给患者带来的净收益高于所有患者的净收益，表明患者可以从模型中获益(图 1~3)。
表 3 上消化道出血单因素和多因素的logistic分析结果Table 3. Univariate and multivariate logistic analysis of upper gastrointestinal bleeding参数 单因素分析 多因素分析 OR值 95%CI P值 OR值 95%CI P值 WBC 0.770 0.624~0.952 0.016 PLT 0.979 0.965~0.994 0.006 0.968 0.944~0.993 0.011 肝-Plain 1.142 1.058~1.233 0.001 1.148 1.047~1.259 0.003 脾-V-Plain 0.979 0.959~1.000 0.050 脾-P-A 0.968 0.944~0.994 0.015 0.951 0.908~0.995 0.030 
图 1 用于预测乙型肝炎肝硬化患者发生上消化道出血的列线图注：为了使用列线图，单个患者的值位于每个变量轴上，并向上绘制一条线以确定每个变量值接收到的点数。这些数字的总和位于总点轴上，并向下画一条线到概率轴以预测发生上消化道出血的可能性。Figure 1. Nomogram for predicting upper gastrointestinal bleeding in patients with hepatitis B cirrhosis
图 2 模型的ROC曲线以及校准曲线注：a, 列线图的ROC曲线; b, 预测模型的校准曲线。Figure 2. ROC curve and calibration curve of the model
图 3 临床决策曲线注：灰色实线, 治疗所有患者的净收益; 黑色实线, 不治疗患者的净收益; 红线, 根据构建的列线图做出临床决策给患者带来的净收益。Figure 3. Clinical decision curve3. 讨论
上消化道出血是肝硬化最常见的并发症之一，也是导致患者死亡的主要原因之一[6]。准确的判断出血风险是制订临床决策的关键因素。首选的检查方法是内镜检查，既可以直观的看到食道胃底静脉的曲张程度，也能发现胃黏膜病变以及溃疡的存在。但是内镜检查同样也有一定的局限性，比如患者拒绝有创检查；危重患者不具备检查条件等。因此需要更加简便且准确的方法。CT及核磁检查可以反映静脉曲张、脾肾分流等情况，可以对上消化道出血的风险预测起到帮助，但也存在影像学表现与临床不符以及无法量化的缺点。Yan等[7]研究发现肝脾体积比是门静脉高压以及上消化道出血的危险因素，并以此为基础构建了预测模型，该模型的敏感度为92.9%，特异度为87.0%。Yang等[8]研究发现肝脾体积比、脾脏扩大比以及AST是上消化道出血的危险因素，同样也建立了预测模型，该模型的敏感度为94.6%，特异度为84.9%。这些研究均对于肝硬化患者的上消化道出血风险进行了很好的预测。
本研究发现，上消化道出血的发生与PLT减少存在密切联系，而肝硬化时PLT下降的主要原因是由于脾大、脾功能亢进。而脾脏增大也是门静脉高压的直接表现，进一步证实了上消化道出血与门静脉高压之间的关系。
通过灌注CT的研究[9]证实，肝硬化时肝脏在动脉期及门静脉期呈现了高血流灌注的状态。本研究发现两组间脾脏动脉期CT值相近，而出血组脾脏的门脉期CT值则更低，造成脾脏门脉期－动脉期的ΔCT的统计学差异。这说明肝硬化合并上消化道出血患者的脾脏处于血流高循环的状态，增加了门静脉高压，进而更具有出血倾向。
本结果显示合并上消化道出血患者血清总胆红素、白细胞、血小板、肝脏平扫期、脾脏门脉期－平扫期、脾脏门脉期－动脉期间ΔCT值存在统计学差异。应用多因素logistic分析结果显示血小板、肝脏平扫期、脾脏门脉期－动脉期间ΔCT值为上消化道出血的独立危险因素。基于上述结果，使用Rstudio4.1.2软件的R包(rms)构建乙型肝炎肝硬化上消化道出血的预测模型。此模型预测上消化道出血的敏感度是81.4%，特异度是77.6%，对于上消化道出血具有良好的预测能力。将这一研究结果应用于临床，将有效的预测上消化道出血风险，为外科手术、内镜及经颈静脉肝内门体分流术等治疗的临床决策提供依据。
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图 1 基线、12周、24周HBsAg以及基线总胆红素对应的ROC曲线
Figure 1. ROC curve of baseline HBsAg, HBsAg of week 12, HBsAg of week 24 as well as baseline total bilirubin
表 1 两组患者基本临床资料的比较
Table 1. Comparison of basic clinical data between two groups
指标 功能性治愈组(n=79) 未治愈组(n=83) 统计值 P值 男/女(例) 64/15 68/15 χ2=0.022 0.881 年龄(岁) 43.68±9.54 43.11±9.40 t=0.387 0.700 基线HBeAg阳性率[例(%)] 7(8.9) 21(25.3) χ2=7.652 0.006 基线HBsAg定量(IU/mL) 21.63(3.33~157.60) 794.70(336.10~1 185.34) Z=-8.869 ＜0.001 治疗12周HBsAg定量(IU/mL) 1.34(0.04~16.59) 567.11(226.09~1 047.86) Z=-9.847 ＜0.001 治疗24周HBsAg定量(IU/mL) 0.01(0.00~0.34) 304.79(89.24~772.23) Z=-10.474 ＜0.001 治疗12周HBsAg下降程度(%) 89.6(57.5~99.4) 21.8(2.0~40.9) Z=-7.926 ＜0.001 治疗24周HBsAg下降程度(%) 99.9(99.0~100.0) 44.1(20.6~73.8) Z=-9.593 ＜0.001 HBV DNA＞1000 IU/mL [例(%)] 0 7(8.4) χ2=5.073 0.024 血红蛋白(g/L) 152(139~159) 151(141~161) Z=-0.096 0.924 白细胞(×109/L) 4.90(3.71~5.89) 5.20(3.98~6.52) Z=-0.953 0.340 中性粒细胞(×109/L) 2.54(1.91~3.39) 2.63(1.92~3.60) Z=-0.518 0.605 血小板(×109/L) 160(127~203) 160(125~203) Z=-0.380 0.704 基线ALT(U/L) 32.00(19.50~44.50) 31.80(21.00~47.50) Z=-0.550 0.583 派格宾治疗12周时ALT(U/L) 55.52(40.61~74.29) 45.00(33.50~68.25) Z=-1.741 0.082 派格宾治疗12周时ALT＞2×ULN[例(%)] 15(19.0) 16(19.3) χ2=0.002 0.963 基线AST(U/L) 24.00(20.58~31.00) 24.70(20.00~35.62) Z=-0.701 0.484 派格宾治疗12周时AST(U/L) 47.00(34.00~68.00) 41.00(30.00~56.50) Z=-2.031 0.042 派格宾治疗12周时AST＞2×ULN[例(%)] 13(16.5) 4(4.8) χ2=5.835 0.016 基线总胆红素(μmol/L) 12.60(10.12~15.78) 15.50(11.80~24.10) Z=-3.611 ＜0.001 基线总蛋白(g/L) 73.9±54.83 74.01±5.65 t=-0.065 0.949 基线白蛋白(g/L) 46.20(43.22~47.85) 45.70(43.25~48.05) Z=-0.188 0.851 
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表 2 功能性治愈影响因素的多因素Logistic回归分析(基线HBsAg)
Table 2. Multivariate logistic regression analysis about influence facter of functional cure (baseline HBsAg)
预测因素 回归系数 SE Wald值 P值 OR(95%CI) 基线HBsAg(IU/mL) -0.004 0.001 35.418 ＜0.001 0.996(0.995~0.997) 基线总胆红素(μmol/L) -0.122 0.036 11.693 0.001 0.885(0.826~0.949) 治疗12周AST＞2×ULN 1.634 0.761 4.606 0.032 5.125(1.152~22.790) 基线HBeAg状态 -1.535 0.747 4.219 0.040 0.215(0.050~0.932)
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表 3 功能性治愈影响因素的多因素Logistic回归分析(治疗12、24周HBsAg)
Table 3. Multivariate logistic regression analysis about influence facter of functional cure (HBsAg of week 12、24)
预测因素 回归系数 SE Wald值 P值 OR(95%CI) 治疗12周HBsAg(IU/mL) -0.010 0.002 27.695 ＜0.001 0.990(0.986~0.994) 基线总胆红素(μmol/L) -0.126 0.041 9.526 0.002 0.882(0.814~0.955) 治疗24周HBsAg(IU/mL) -0.017 0.004 16.074 ＜0.001 0.983(0.975~0.991) 基线总胆红素(μmol/L) -0.085 0.037 5.356 0.021 0.919(0.855~0.987)
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百度学术2. 王华丽，颜文娟，严继诗. 细节干预对肝硬化合并上消化道出血患者的效果及生存质量的影响. 中外医疗. 2023(08): 170-173+198 . 百度学术3. 张莉，吴凤丽. 裸花紫珠胶囊结合生长抑素治疗老年肝硬化上消化道出血患者的临床效果. 河南医学研究. 2023(16): 3023-3026 . 百度学术4. 赵润玲. 乙型肝炎肝硬化上消化道出血患者血清TPO、YKL-40水平变化及对DIC发生风险的指导意义. 国际检验医学杂志. 2023(20): 2521-2525 . 百度学术5. 孔敏，靳欣，赵琴. 微信群为基础的短视频远程干预联合IMB模型在肝硬化患者居家护理效果指导. 国际医药卫生导报. 2023(18): 2649-2654 . 百度学术6. 阚丽娜，杨昊龙，刘微，孙小媚，贾春霞，丁秀婷. 不同剂量泮托拉唑联合奥曲肽治疗肝硬化上消化道出血患者止血效果比较及其对血清一氧化氮、皮质醇影响. 临床军医杂志. 2023(12): 1317-1320 . 百度学术7. 丁敏，刘庭玮，张立波，陈鸿鑫，祁兴顺. 常见肝良性疾病造成胆囊形态改变机制、影像学评估及意义. 临床军医杂志. 2022(09): 887-889+893 . 百度学术8. 孙海霞. 探讨多层螺旋CT增强扫描用于肝血管瘤与肝转移癌鉴别诊断的临床价值. 影像研究与医学应用. 2022(24): 70-72 . 百度学术其他类型引用(4)
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