涂阴肺结核诊断记分系统的研究

Study of A Scoring System for Diagnosing Smear Negative Pulmonary Tuberculosis

目的建立涂阴肺结核诊断记分系统,并研究其诊断性能。方法利用建模样本筛选出对诊断涂阴肺结核有意义的单项参数指标,再对单因素分析有意义的指标进行多因素非条件Logistic回归分析,用多因素Logistic回归模型中独立预告因素的!系数建立诊断记分系统。然后通过测试样本做诊断记分系统的诊断性能评价。结果体重下降、盗汗、乏力、胸闷、胸片异常表现的部位及胸膜粘连等6个变量最终进入多因素Logistic回归模型,根据!系数研制的记分系统得分范围为-3至13。得分小于4的患者,为涂阴肺结核的可能性小;得分大于等于4是涂阴肺结核的可能性大。建模样本和测试样本诊断的正确率、灵敏度及特异度分别为88.4%和86.6%,91.3%和84.8%,86.4%和89.1%,ROC曲线下面积分别为0.888±0.017和0.870±0.037。结论记分系统可作为涂阴肺结核的诊断预测工具,有良好的诊断预测性能,值得进一步探讨。

Objective To develop a scoring system for predicting smear-negative pulmonary tuberculosis and to evaluate its performance. Methods The derivation sample was used to screen out potential predictor variables for SNPT by using univariate logistic regression analysis. Multiple logistic regression analysis was conducted to identify independent predictors of SNPT from the potential predictor variables. Using the β-coefficients derived from the independent predictors in our logistic regression model, we developed a scoring system. The validation sample was used to evaluate the diagnostic performances of the scoring system. Results Six variables including weight loss, night sweats, lack of strength, chest tight, abnormal sites of chest radiograph and pleural adhesions entered into the final multiple logistic regression model. Based on β-coefficients, the scoring system with scores ranging from -3 to 13 was developed. The patient under 4 scores was more likely non-SNPT than SNPT, while the patient with more than 4 scores had very high probability of SNPT. When the system was applied to the derivation sample and validation sample, the area under the receiver operator characteristic curve, accuracy, sensitivity and specificity were 0.888±0.017 and 0.870±0.037, 88.4% and 86.6%, 91.3% and 84.8%, 86.4% and 89.1%, respectively. Conclusion The scoring system used in diagnosing SNPT has high diagnostic capability, which can be used as a tool for the diagnosis of SNPT and deserve further investigation.