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1型肝肾综合征患者90天预后危险因素分析及预测模型构建
DOI: 10.3969/j.issn.1001-5256.2022.07.019
伦理学声明：本研究于2021年2月7日通过北京地坛医院的伦理审查委员会的伦理审查，批号：DTZZLX-202104。患者均知情同意。
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：王宪波、杨晋翔负责课题设计和拟定论文思路；朱冰冰负责收集、分析统计数据、论文撰写；张群、高方媛参与资料收集统计和图表制作；王宪波指导撰写文章并最终定稿。
Risk factors for the 90-day prognosis of patients with type I hepatorenal syndrome and establishment of a predictive model
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摘要:
目的 探讨影响失代偿期肝硬化合并1型肝肾综合征(HRS)患者90 d预后的相关危险因素。 方法 回顾性收集北京地坛医院2008年10月—2018年10月299例失代偿期肝硬化合并1型HRS的住院患者的临床资料，按照患者90 d的预后情况分为生存组(n=135)和死亡组(n=164)。符合正态分布的计量资料两组间比较用t检验，非正态分布的计量资料两组间比较采用Mann-Whitney U检验；计数资料两组间比较用χ2检验。采用多因素二元logistic回归分析影响HRS患者90 d预后的因素，绘制不同因素受试者工作特征曲线(ROC曲线)。 结果 单因素分析显示，两组间终末期肝病模型(MELD)评分、Child-Turcotte-Pugh (CTP)评分、肝性脑病、血清钠(Na)、血肌酐(SCr)、血尿素氮(BUN)、尿酸(UA)、ALT、AST、TBil、Alb、胆碱酯酶(ChE)、WBC、中性粒细胞(NE)、中性粒细胞与淋巴细胞比值(NLR)、红细胞(RBC)、红细胞分布宽度(RDW)、PLT、国际标准化比值(INR)比较，差异均有统计学意义(P值均＜0.05)。logistic多因素分析发现，Na、BUN、RDW、INR是失代偿期肝硬化合并HRS患者90 d预后不良的独立影响因素[OR(95%CI)分别为0.918(0.880~0.957)、1.077(1.029~1.127)、1.019(1.005~1.032)、3.478(2.096~5.771)，P值均＜0.05]。针对以上4个因素建立预测模型HRS-D，绘制各个因素的ROC曲线并计算曲线下面积，HRS-D的ROC曲线下面积为0.813(95%CI：0.762~0.864)，诊断界值为-1.264，灵敏度为76.50%，特异度为72.50%。HRS-D和MELD相比，差异有统计学意义(Z=3.804，P＜0.001)，HRS-D评分与CTP评分、CTP评分与MELD评分相比，差异均无统计学意义(P值均＞0.05)。 结论 Na、BUN、RDW、INR是失代偿期肝硬化合并1型HRS患者90 d预后不良的独立影响因素，据此建立的预测模型可以较好预测患者的90 d预后情况。 Abstract:Objective To investigate the risk factors for the 90-day prognosis of patients with decompensated liver cirrhosis and type I hepatorenal syndrome (HRS). Methods A retrospective analysis was performed for the clinical data of 299 patients with decompensated liver cirrhosis and type I HRS who were hospitalized in Beijing Ditan Hospital from October 2008 to October 2018, and according to the 90-day prognosis, they were divided into survival group with 135 patients and death group with 164 patients. The t-test was used for comparison of normally distributed continuous data between groups, and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between groups; the chi-square test was used for comparison of categorical data between groups. A multivariate binary logistic regression analysis was used to investigate the influencing factors for 90-day prognosis, and the receiver operating characteristic (ROC) curve was plotted for each factor. Results The univariate analysis showed that there were significant differences between the two groups in Model for End-Stage Liver Disease (MELD) score, Child-Turcotte-Pugh (CTP) score, hepatic encephalopathy, serum Na, serum creatinine (Cr), blood urea nitrogen (BUN), uric acid (UA), alanine aminotransferase (ALT), aspartate aminotransferase (AST), total bilirubin (TBil), albumin (Alb), cholinesterase (CHE), white blood cell count (WBC), neutrophil (NE), neutrophil-to-lymphocyte ratio (NLR), red blood cell count (RBC), red blood cell distribution width (RDW), platelet count (PLT), and international normalized ratio (INR) (P < 0.05). The multivariate logistic regression analysis showed that Na (odds ratio [OR]=0.918, 95% confidence interval [CI]: 0.880-0.957, P < 0.05), BUN (OR=1.077, 95% CI: 1.029-1.127, P < 0.05), RDW (OR=1.019, 95% CI: 1.005-1.032, P < 0.05), and INR (OR=3.478, 95% CI: 2.096-5.771, P < 0.05) were independent influencing factors for poor 90-day prognosis in patients with decompensated liver cirrhosis and type I HRS. A predictive model, HRS-D, was established using the four factors above, and the ROC curves were plotted for each factor to calculate the area under the ROC curve (AUC), which showed that HRS-D had an AUC of 0.813 (95% CI: 0.762-0.864), with a sensitivity of 76.50% and a specificity of 72.50% at the diagnostic cut-off value of -1.264. There was a significant difference between HRS-D score and MELD score (Z=3.804, P < 0.001), while there was no significant difference between HRS-D score and CTP score and between CTP score and MELD score (both P > 0.05). Conclusion Na, BUN, RDW, and INR are independent influencing factors for poor 90-day prognosis in patients with decompensated liver cirrhosis and type I HRS, and the predictive model based on these indices can better predict the 90-day prognosis of HRS patients. -
Key words:
- Hepatorenal Syndrome /
- Liver Cirrhosis /
- Prognosis /
- Risk Factors
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表 1 HRS患者的基线特征
Table 1. Baseline characteristics of patients with HRS
指标 生存组(n=135) 死亡组(n=164) 统计值 P值 年龄(岁) 54±12 54±13 t=0.168 0.867 男/女(例) 105/30 127/37 χ2=0.005 0.944 慢性乙型肝炎[例(%)] 53(39.3) 63(38.4) χ2=0.022 0.881 慢性丙型肝炎[例(%)] 7(5.2) 11(6.7) χ2=0.303 0.582 酒精性肝病[例(%)] 40(29.6) 44(26.8) χ2=0.287 0.607 免疫性肝病[例(%)] 9(6.7) 18(11.0) χ2=1.674 0.196 肝性脑病[例(%)] 16(11.9) 42(25.6) χ2=8.964 0.003 自发性腹膜炎[例(%)] 93(69.4) 117(71.8) χ2=0.200 0.654 消化道出血[例(%)] 25(18.5) 32(19.5) χ2=0.047 0.828 K(mmol/L) 4.34(3.86~4.82) 4.31(3.54~5.28) Z=-0.226 0.821 Na(mmol/L) 134.46±6.43 130.29±7.73 t=-5.085 ＜0.001 SCr(μmol/L) 143.00(137.50~177.00) 154.80(138.50~188.52) Z=-2.391 0.017 BUN(μmol/L) 13.59±5.36 17.86±8.76 t=5.191 ＜0.001 UA(mmol/L) 499.00(348.00~606.00) 414.00(243.25~577.78) Z=-3.204 0.001 ALT(U/L) 23.80(14.90~53.10) 43.60(24.18~103.48) Z=-5.731 ＜0.001 AST(U/L) 36.20(28.00~70.30) 68.80(38.30~150.30) Z=-4.124 ＜0.001 TBil(mmol/L) 38.00(20.70~106.6) 251.90(80.150~418.15) Z=-7.900 ＜0.001 Alb(g/L) 30.16±6.22 27.70±5.36 t=-5.074 ＜0.001 GGT(mmol/L) 41.40(18.20~73.60) 39.30(21.68~66.13) Z=-0.716 0.474 ChE(U/L) 2099(1548~3536) 1563(1064~2224) Z=-6.598 ＜0.001 WBC(×109/L) 5.96(4.20~8.69) 8.54(5.84~12.34) Z=-4.258 ＜0.001 NE(×109/L) 3.74(2.80~6.33) 6.45(4.23~10.53) Z=-4.694 ＜0.001 LY(×109/L) 0.96(0.62~1.57) 0.98(0.61~1.37) Z=-0.826 0.409 NLR 4.83(2.65~9.62) 7.94(4.57~13.98) Z=-4.843 ＜0.001 RBC(×1012/L) 2.93±0.79 2.53±0.93 t=-3.979 ＜0.001 Hb(g/L) 96.74±26.75 87.25±30.47 t=-3.198 ＜0.001 HCT(%) 28.50(24.42~33.90) 19.69(14.26~24.10) Z=-2.870 0.004 RDW(fL) 48.50(17.18~59.70) 56.75(20.39~63.48) Z=-4.139 ＜0.001 PLT(×109/L) 80.00(48.00~116.00) 67.00(35.28~99.50) Z=-2.802 0.005 INR 4.26(2.75~6.92) 6.68(4.39~13.05) Z=-7.438 ＜0.001 PT(s) 56.00(43.00~67.00) 34.50(21.90~47.65) Z=-8.226 ＜0.001 注：K，钾；LY，淋巴细胞计数。 
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表 2 logistic单因素回归分析
Table 2. logistic regression univariate analysis
变量 B值 OR(95%CI) P值 年龄 0.034 1.002(0.984~1.020) 0.866 肝性脑病 0.940 0.391(0.208~0.732) 0.035 CTP 0.493 1.637(1.434~1.868) ＜0.001 MELD 0.098 1.103(1.062~1.146) ＜0.001 Na(mmol/L) -0.082 1.637(1.434~1.868) ＜0.001 SCr(μmol/L) 0.008 1.008(1.002~1.014) ＜0.001 BUN(μmol/L) 0.090 1.094(1.053~1.138) ＜0.001 UA(mmol/L) -0.002 0.998(0.997~0.999) 0.003 ALT(U/L) 0.005 1.005(1.002~1.009) 0.006 AST(U/L) 0.005 1.005(1.002~1.008) 0.003 TBil(mmol/L) 0.005 1.005(1.004~1.007) ＜0.001 Alb(g/L) -0.105 0.900(0.862~0.940) ＜0.001 ChE(U/L) -0.001 0.999(0.999~1.000) ＜0.001 WBC(×109/L) 0.078 1.081(1.032~1.133) 0.001 NE(×109/L) 0.087 1.091(1.036~1.149) 0.001 NLR 0.047 1.071(1.031~1.111) ＜0.001 RBC(×1012/L) -0.528 0.590(0.448~0.778) ＜0.001 RDW(fL) 0.016 1.017(1.006~1.027) 0.002 PLT(×109/L) -0.006 0.994(0.989~0.999) 0.010 INR 1.384 3.989(2.449~6.497) ＜0.001
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表 3 logistic多因素回归分析
Table 3. logistic regression multivariate analysis
变量 B值 SE Wald P值 OR(95%CI) Na(mmol/L) -0.086 0.021 15.999 ＜0.001 0.918(0.880~0.957) BUN(μmol/L) 0.074 0.023 10.071 0.002 1.077(1.029~1.127) RDW(fL) 0.018 0.007 7.712 0.005 1.019(1.005~1.032) INR 1.246 0.258 23.263 ＜0.001 3.478(2.096~5.771)
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表 4 两组3种评分模型的比较
Table 4. Characteristics comparison of three scoring models in two group
模型 生存组(n=135) 死亡组(n=164) 统计值 P值 HRS-D -8.43±0.91 -7.38±1.40 t=-7.155 ＜0.001 MELD 30.67±5.59 35.41±8.07 t=5.864 ＜0.001 CTP 9(8~11) 12(11~13) Z=-8.119 ＜0.001
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表 5 3种评分模型ROC曲线特点及比较
Table 5. Comparison of the characteristics of the ROC curves of three scoring models
模型 约登指数 cut-off值 灵敏度 特异度 HRS-D 0.49 -1.264 0.765 0.725 CTP 0.43 9.50 0.860 0.570 MELD 0.31 33.25 0.610 0.700
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