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[一种用于鉴别结核性胸膜炎和非结核性胸膜炎的评分模型]

[A scoring model for a differential diagnosis of tuberculous and non-tuberculous pleurisy].

作者信息

Sun Qin, Xiao He-Ping, Sha Wei

机构信息

Department of Tuberculosis, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai 200433, China.

出版信息

Zhonghua Yi Xue Za Zhi. 2011 Sep 13;91(34):2392-6.

Abstract

OBJECTIVE

To evaluate various clinical features and laboratory biochemical markers so as to develop a predictive model for differentiating tuberculous pleurisy (TBP) from non-tuberculous pleurisy (non-TBP).

METHODS

A total of 241 TBP patients and 212 non-TBP patients who were hospitalized between January 2007 and December 2009 at our hospital were studied retrospectively. Their symptoms and laboratory parameters were recorded. The statistically different variables were selected to undergo binary logistic regression to calculate a scoring system (range: 0 - 10) according to their β coefficients. A receiver operating characteristic (ROC) curve was used to calculate the best cut-off value. The performance of the model was tested in a sample of 82 new cases with pleural exudates.

RESULTS

Seven variables were selected in the present scoring model: temperature > 38°C (1.0 point), purified protein derivative testing positive (1.0 point), serum C-reactive protein ≥ 26 mg/L (1.5 points), pleural fluid lymphocyte percentage ≥ 85% (1.0 point), pleural fluid protein ≥ 49 g/L (1.0 point), pleural fluid adenosine deaminase ≥ 43 U/L (2.5 points) and serum and/or pleural fluid mycobacterium tuberculosis antibody positive (2.0 points). With a cut-off value of 6.0 points, the sensitivity, specificity and accuracy of differentiating TBP from non-TBP was 90.1%, 94.3% and 92.1% respectively. With the application of this model, 82 new pleural effusions showed a sensitivity of 94.1%, a specificity of 93.8% and an accuracy of 93.9%.

CONCLUSION

The scoring model provided a simple and feasible way of facilitating a differential diagnosis of TBP and non-TBP patients.

摘要

目的

评估各种临床特征和实验室生化指标,以建立区分结核性胸膜炎(TBP)与非结核性胸膜炎(非TBP)的预测模型。

方法

回顾性研究2007年1月至2009年12月在我院住院的241例TBP患者和212例非TBP患者。记录他们的症状和实验室参数。选择具有统计学差异的变量进行二元逻辑回归,根据其β系数计算评分系统(范围:0 - 10)。采用受试者工作特征(ROC)曲线计算最佳截断值。在82例新发胸腔积液患者样本中测试该模型的性能。

结果

本评分模型选择了7个变量:体温>38°C(1.0分)、结核菌素试验阳性(1.0分)、血清C反应蛋白≥26 mg/L(1.5分)、胸腔积液淋巴细胞百分比≥85%(1.0分)、胸腔积液蛋白≥49 g/L(1.0分)、胸腔积液腺苷脱氨酶≥43 U/L(2.5分)以及血清和/或胸腔积液结核分枝杆菌抗体阳性(2.0分)。截断值为6.0分时,区分TBP与非TBP的敏感性、特异性和准确性分别为90.1%、94.3%和92.1%。应用该模型,82例新发胸腔积液的敏感性为94.1%,特异性为93.8%,准确性为93.9%。

结论

该评分模型为TBP和非TBP患者的鉴别诊断提供了一种简单可行的方法。

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