摘要: |
目的 评价鉴别诊断浆膜腔积液良恶性的超声特征。方法 观察浆膜腔积液患者的超声特征,根据其恶性可能性评分;利用Logistic回归模型分析筛选出主要诊断指标并建立诊断恶性可能性的公式。结果 判断恶性浆膜腔积液有意义的指标包括胆囊壁厚度、大网膜增厚/结节、肠壁增厚、大网膜血流情况、肠管浮游、后腹膜淋巴结肿大。经过二变量Logistic逐步回归,得到以下方程:恶性可能性=1/(1+e- z),其中z=4.226×胆囊壁厚度+5.218×大网膜增厚/结节+3.024×肠壁增厚+4.892×肠管浮游-29.387。其中大网膜增厚/结节的OR值高于其他自变量。当浆膜腔积液患者出现胆囊壁薄、具有大网膜增厚/结节、肠壁增厚且肠管浮游征消失时恶性可能性为0.99。结论 胆囊壁厚度、大网膜增厚/结节、肠壁增厚、肠管浮游征是超声预测浆膜腔积液良恶性的有效特征指标,建立的Logistic回归模型对鉴别浆膜腔积液良恶性有较高价值。 |
关键词: 浆膜腔积液 Logistic回归模型 良恶性 |
DOI: |
投稿时间:2017-03-15修订日期:2017-04-21 |
基金项目: |
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Evaluation of ultrasound inSdifferentiating benign and malignant serous cavity fluids using Logistic regression modelJiang Zhi-ming |
Jiang Zhi-ming |
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Abstract: |
Objective To evaluate the grey-scale and color Doppler ultrasound on differentiating benign and malignant serous cavity fluids. Methods To study the characters of grey-scale and color Doppler ultrasound on differentiating benign and malignant serous cavity fluids, and score according to the probability of malignancy. The main diagnostic indicators were screened out by Logistic regression model and then got the formula which could calculate the probability of malignancy. Meaningful indicators of malignant serous cavity fluids were thickness of gall bladder wall, greater omental thickening/nodules, intestinal wall thickening, blood flow of the greater omentum, bowel floating and retroperitoneal lymph node. The following formula were obtained by two-variable logistic regression model: Probability of malignancy = 1/ (1+e-z), which z=4.226×thickness of gall bladder wall +5.218× greater omental thickening/nodules +3.024× intestinal wall thickening +4.892× bowel floating -29.387. The OR of the greater omental thickening/nodules was higher than other independent variables. If serous cavity fluids with thin gallbladder wall, greater omental thickening/nodules, intestinal wall thickening and bowel floating, the probability of malignancy was 0.99. Results The thickness of gall bladder wall, greater omental thickening/nodules, intestinal wall thickening and bowel floating were effective indicators to predict malignant serous cavity fluids by ultrasound, and the established Logistic regression model has a higher value inSdifferentiating benign and malignant serous cavity fluids. Keywordserous cavity fluids, Logistic regression model, benign and malignant |
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