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中华消化病与影像杂志(电子版) ›› 2024, Vol. 14 ›› Issue (04) : 330 -335. doi: 10.3877/cma.j.issn.2095-2015.2024.04.009

论著

构建诺模图模型预测肝硬化食管胃底静脉曲张出血的风险
秦相清1,(), 朱陈1, 张海银1   
  1. 1. 226000 江苏省,南通大学附属南通第三医院消化内科
  • 收稿日期:2023-07-17 出版日期:2024-08-01
  • 通信作者: 秦相清
  • 基金资助:
    江苏省卫生和计划生育委员会项目(H2017057)

Construction of a normogram model for predicting the risk of esophageal and gastric varices bleeding in cirrhosis

Xiangqing Qin1,(), Chen Zhu1, Haiyin Zhang1   

  1. 1. Department of Gastroenterology, Nantong Third Hospital Affiliated to Nantong University, Nantong 226000, China
  • Received:2023-07-17 Published:2024-08-01
  • Corresponding author: Xiangqing Qin
引用本文:

秦相清, 朱陈, 张海银. 构建诺模图模型预测肝硬化食管胃底静脉曲张出血的风险[J]. 中华消化病与影像杂志(电子版), 2024, 14(04): 330-335.

Xiangqing Qin, Chen Zhu, Haiyin Zhang. Construction of a normogram model for predicting the risk of esophageal and gastric varices bleeding in cirrhosis[J]. Chinese Journal of Digestion and Medical Imageology(Electronic Edition), 2024, 14(04): 330-335.

目的

评估HBV相关肝硬化患者食管胃底静脉曲张出血(EVGB)的风险因素,以构建预测EVGB风险的诺模图模型。

方法

以2019年1月至2022年1月南通大学附属南通第三医院收治的300例HBV相关肝硬化患者为研究对象,采用单、多变量Logistic回归分析筛选EVGB的风险因素并构建诺模图。通过受试者特征(ROC)的曲线下面积(AUC),评估模型对EVGB风险的识别能力。绘制校准曲线衡量模型预测风险与实际观测风险之间的一致性。

结果

共131例(43.7%)患者有EVGB史,单、多变量Logistic回归分析显示,腹水(OR=6.186,95% CI 3.286~11.644,P<0.001)、血小板计数(OR=0.983,95% CI 0.978~0.989,P<0.001)、血清白蛋白值(OR=0.963,95% CI 0.928~0.999,P=0.042)以及血糖水平(OR=1.093,95% CI 1.003~1.190,P=0.042)是EVGB的独立风险因素。基于以上变量构建预测肝硬化患者EVGB风险的诺模图,该模型AUC值为0.826(95% CI 0.780~0.872),提示判别能力良好。校准曲线显示模型预测风险与发生EGVB的实际风险之间具有高度一致性。

结论

腹水、血小板计数、血清白蛋白和血糖水平与肝硬化EGVB显著相关,基于这些变量构建的诺模图模型对EGVB风险具有良好的预测能力,可能有助于指导医护人员开展精准预防和临床干预。

Objective

To evaluate the risk factors of esophagogastric variceal bleeding (EVGB) for patients with hepatitis B virus (HBV)-related cirrhosis, and to construct a nomogram model to predict the risk of EVGB.

Methods

A total of 300 HBV-related cirrhotic patients admitted to Nantong Third Hospital Affiliated to Nantong University from January 2019 to January 2022 were selected as the study objects. The independent risk factors of EVGB were determined by the univariate and multivariate Logistic regression analysis, and a nomogram for predicting the risk of EVGB was constructed. The discriminative ability of the nomogram model for high-risk individual with EVGB was evaluated using the area under curve (AUC) of receiver operation characteristics (ROC) curve. Calibration curves were plotted to compare the consistency between the predicted risk and actual risk.

Results

A total of 131 patients (43.7%) had a history of EVGB, and the results of univariate and multivariate Logistic regression analysis revealed that ascites (OR=6.186, 95% CI: 3.286-11.644, P<0.001), platelet count (OR=0.983, 95% CI: 0.978-0.989, P<0.001), serum albumin (OR=0.963, 95% CI: 0.928-0.999, P=0.042) and blood glucose level (OR=1.093, 95% CI: 1.003-1.190, P=0.042) were independent risk factors for EVGB. Based on the above variables, a nomogram was constructed to predict the risk of EVGB in cirrhotic patients. The AUC value was 0.826 (95% CI: 0.780-0.872), suggesting a good predictive ability. The calibration curve showed a high level of consistency between the predicted risk and the actual risk.

Conclusion

Ascites, platelet count, serum albumin and blood glucose level are significantly correlated with the risk of EGVB in liver cirrhosis. The nomogram based on these variables has good predictive ability for the risk of EGVB, and it may help medical staffs make prevention strategy and clinical interventions.

表1 研究人群基线特征的比较
基线特征 食管胃底静脉曲张破裂出血 统计量 P
无(n=169) 有(n=131)
年龄[例(%)]     4.167 0.041
<55岁 100(59.2) 62(47.3)    
≥55岁 69(40.8) 69(52.7)    
性别[例(%)]     0.639 0.424
122(72.2) 89(67.9)    
47(27.8) 42(32.1)    
吸烟史[例(%)] 57(33.7) 42(32.1) 0.093 0.761
酗酒史[例(%)] 52(30.8) 33(25.2) 1.131 0.288
高血压[例(%)] 27(16.0) 27(20.6) 1.074 0.300
糖尿病[例(%)] 18(10.7) 15(11.5) 0.048 0.826
腹水[例(%)]     16.348 <0.001
147(87.0) 67(51.1)    
22(13.0) 64(48.9)    
WBC计数(×109/L,IP25-P75) 5.2(3.9~7.4) 4.4(3.0~6.3) 3.368 0.001
PLT计数(×109/L,IP25-P75) 142.0(102.0~170.0) 82.0(55.0~113.0) 7.974 < 0.001
血红蛋白(g/dL,±s) 12.5±3.1 11.0±3.2 4.111 < 0.001
INR(±s) 1.09±0.18 1.18±0.19 4.328 < 0.001
PT(S,IP25-P75) 12.0(11.1~15.6) 14.4(12.0~17.9) 4.089 < 0.001
ALT(U/L,IP25-P75) 41.0(25.0~97.0) 42.0(28.0~90.0) 0.456 0.648
AST(U/L,IP25-P75) 37.0(27.0~66.0) 42.0(29.0~61.0) 0.798 0.425
总胆红素(μmol/L,IP25-P75) 22.0(16.2~30.8) 27.3(18.8~36.4) 3054 0.002
血清白蛋白(g/L,±s) 38.3±7.9 34.5±8.0 4.189 < 0.001
γ-GT(U/L,IP25-P75) 40.0(19.0~100.0) 48.0(23.0~97.0) 0.837 0.402
ALP(U/L,IP25-P75) 88.0(68.0~120.0) 97.0(72.0~127.0) 1.580 0.114
血肌酐(μmol/L,IP25-P75) 69.6(59.7~83.9) 69.6(59.2~83.1) 0.641 0.521
尿素氮(mmol/L,IP25-P75) 4.8(4.0~6.9) 5.7(4.1~9.3) 1.953 0.053
血钠(mmol/L,±s) 139.5±3.3 138.7±3.4 2.040 0.042
血钾(mmol/L,±s) 3.9±0.6 3.9±0.7 0.313 0.754
血糖(mmol/L,IP25-P75) 5.5(5.0~6.7) 6.0(5.1~7.8) 2.469 0.014
Child-pugh分级[例(%)]     18.969 < 0.001
A 106(62.7) 50(38.2)    
B 58(34.3) 70(53.4)    
C 5(3.0) 11(8.4)    
表2 多变量Logistic回归分析肝硬化食管胃底静脉曲张破裂出血的风险因素
图1 预测肝硬化患者食管胃底静脉曲张破裂出血风险的诺模图
图2 诺模图预测肝硬化食管胃底静脉曲张破裂出血风险的ROC曲线(2A)与校正曲线(2B)
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