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收稿:2018-06-25,
纸质出版:2018-11-15
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徐征国, 刘恩, 赵泳冰, 等. 基于CT或超声的两种无创模型预测肝硬化后食管胃静脉曲张出血风险[J]. 第三军医大学学报, 2018,40(21):1978-1984.
Zhengguo XU, En LIU, Yongbing ZHAO, et al. Prediction of bleeding risk for gastroesophageal varices by CT/ultrasound-based noninvasive models[J]. Journal of Third Military Medical University, 2018, 40(21): 1978-1984.
徐征国, 刘恩, 赵泳冰, 等. 基于CT或超声的两种无创模型预测肝硬化后食管胃静脉曲张出血风险[J]. 第三军医大学学报, 2018,40(21):1978-1984. DOI: 10.16016/j.1000-5404.201806160.
Zhengguo XU, En LIU, Yongbing ZHAO, et al. Prediction of bleeding risk for gastroesophageal varices by CT/ultrasound-based noninvasive models[J]. Journal of Third Military Medical University, 2018, 40(21): 1978-1984. DOI: 10.16016/j.1000-5404.201806160.
Objective
2
To establish 2 noninvasive models based on laboratory serum indexes
enhanced CT or ultrasonographic parameters to predict hemorrhagic risk of gastroesophageal varices in the patients with post-hepatitis B cirrhosis in order to replace the invasive methods.
Methods
2
A total of 3 643 patients with hepatitis B cirrhosis admitted in our hospital between July 2010 and July 2017 were enrolled and retrospectively analyzed. Among them
there were 412 cases with complete data of gastroesophageal variceal hemorrhage and 340 cases with a clear diagnosis of cirrhosis
but no gastroesophageal varices. According to the propensity score analysis (PSA)
these patients were divided into the research group (varicose bleeding) and the control group (no varicose veins) at a ratio of 1 :1
and eventually
248 cases were included in each group
with a total of 496 cases. Two Logistic risk prediction models were established by using the dip matching method and SPSS 24.0 statistical software
and were further verified in 164 patients with variceal bleeding and 92 patients without varicose veins who were not enrolled in the study.
Results
2
Risk factors of esophageal and gastric variceal bleeding included total bilirubin (TBIL)
platelet (PLT)
red b cell count (RBC)
portal vein diameter
and spleen length and width. There were 2 risk pred
iction models established: model P1 based on the laboratory indicators combined with the abdominal ultrasound indicators
and model P2 based on the laboratory indicators combined with the abdominal CT indicators. The area under the ROC curve of the P1 model was 0.970 (0.956~0.985)
and the predicted area of the ROC was 0.938 (0.906~0.970) (
P
<
0.001). The area under the ROC curve of the P2 model was 0.967 (0.950~0.984)
and the predicted ROC area was 0.946 (0.916~0.975) (
P
<
0.001). The sensitivity and specificity of the 2 models for prediction and the overall prediction accuracy were all
>
90%
with sound stablity.
Conclusion
2
The 2 noninvasive models are of high accuracy in prediction of bleeding risk of gastroesophageal varices
and may modify or replace the invasive methods after further improvements.
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