METHODS: In-patients, who developed tuberculous PE (TPE), malignant PE (MPE), complicated parapneumonic effusion (CPPE), uncomplicated PPE (UPPE), or PE caused by connective tissue diseases (CTDs) and underwent thoracentesis at Peking University People\'s Hospital from November 2016 to April 2019, were included in this study. Eleven biomarkers and their ratios in serum and PF were investigated and compared between pairs of the different PE groups, and a decision-tree was developed.
RESULTS: Totally 112 PE cases, including 25 MPE, 33 TPE, 19 CPPE, 27 UPPE, and 8 PE caused by CTDs, were reviewed. Biomarkers and ratios showed good diagnostic performance with high area under the curve values, sensitivities, and specificities for the differential diagnosis of the multiple types of PE. According to the decision-tree analysis, the combination of adenosine deaminase (ADA), serum albumin, serum lactate dehydrogenase, total protein, PF-LDH/ADA, and PF-LDH/TP provided the best predictive capacity with an overall accuracy of 84.8%; the sensitivity and specificity for TPE diagnosis were 100% and 98.7%, respectively.
CONCLUSIONS: The biomarkers and ratios showed good diagnostic performance, and a decision-tree with an overall accuracy of 84.8% was developed to differentiate the five types of PE in clinical settings.
方法:住院患者,谁开发了结核性PE(TPE),恶性PE(MPE),复杂的肺炎旁积液(CPPE),简单的PPE(UPPE),本研究纳入2016年11月至2019年4月在北京大学人民医院接受胸腔穿刺术的结缔组织病(CTDs)引起的PE。研究了11种生物标志物及其在血清和PF中的比例,并在不同的PE组之间进行了比较。并建立了决策树。
结果:共112例PE,包括25个MPE,33TPE,19CPPE,27UPPE,和8个由CTD引起的PE,被审查了。生物标志物和比率显示出良好的诊断性能,曲线下面积值高,敏感性,以及对多种类型PE的鉴别诊断的特异性。根据决策树分析,腺苷脱氨酶(ADA)的组合,血清白蛋白,血清乳酸脱氢酶,总蛋白质,PF-LDH/ADA,PF-LDH/TP提供了最佳预测能力,总体准确率为84.8%;TPE诊断的敏感性和特异性分别为100%和98.7%,分别。
结论:生物标志物和比率显示出良好的诊断性能,并建立了总体准确率为84.8%的决策树来区分临床环境中的五种类型的PE。