Department of Respiratory and Critical Care Medicine, Dongguan People's Hospital, 78 Wandao Road South, Dongguan, 523059, Guangdong, China.
Department of Pathophysiology, Key Laboratory of State Administration of Traditional Chinese Medicine of the People's Republic of China, School of Medicine, Jinan University, Guangzhou, 510632, Guangdong, China.
BMC Pulm Med. 2022 Sep 2;22(1):332. doi: 10.1186/s12890-022-02131-7.
Due to the low efficiency of a single clinical feature or laboratory variable in the diagnosis of tuberculous pleural effusion (TBPE), the diagnosis of TBPE is still challenging. This study aimed to build a scoring diagnostic model based on laboratory variables and clinical features to differentiate TBPE from non-tuberculous pleural effusion (non-TBPE).
A retrospective study of 125 patients (63 with TBPE; 62 with non-TBPE) was undertaken. Univariate analysis was used to select the laboratory and clinical variables relevant to the model composition. The statistically different variables were selected to undergo binary logistic regression. Variables B coefficients were used to define a numerical score to calculate a scoring model. A receiver operating characteristic (ROC) curve was used to calculate the best cut-off value and evaluate the performance of the model. Finally, we add a validation cohort to verify the model.
Six variables were selected in the scoring model: Age ≤ 46 years old (4.96 points), Male (2.44 points), No cancer (3.19 points), Positive T-cell Spot (T-SPOT) results (4.69 points), Adenosine Deaminase (ADA) ≥ 24.5U/L (2.48 point), C-reactive Protein (CRP) ≥ 52.8 mg/L (1.84 points). With a cut-off value of a total score of 11.038 points, the scoring model's sensitivity, specificity, and accuracy were 93.7%, 96.8%, and 99.2%, respectively. And the validation cohort confirms the model with the sensitivity, specificity, and accuracy of 92.9%, 93.3%, and 93.1%, respectively.
The scoring model can be used in differentiating TBPE from non-TBPE.
由于单个临床特征或实验室变量在结核性胸腔积液（TBPE）诊断中的效率较低，因此 TBPE 的诊断仍然具有挑战性。本研究旨在建立基于实验室变量和临床特征的评分诊断模型，以区分 TBPE 和非结核性胸腔积液（non-TBPE）。
对 125 例患者（63 例 TBPE；62 例 non-TBPE）进行回顾性研究。采用单因素分析筛选与模型组成相关的实验室和临床变量。对统计学差异的变量进行二项逻辑回归分析。变量 B 系数用于定义数值评分以计算评分模型。采用受试者工作特征（ROC）曲线计算最佳截断值并评估模型性能。最后，我们添加验证队列来验证模型。
评分模型中选择了 6 个变量：年龄≤46 岁（4.96 分）、男性（2.44 分）、无癌症（3.19 分）、T 细胞斑点（T-SPOT）阳性结果（4.69 分）、腺苷脱氨酶（ADA）≥24.5U/L（2.48 分）、C 反应蛋白（CRP）≥52.8mg/L（1.84 分）。总评分的截断值为 11.038 分，评分模型的敏感性、特异性和准确性分别为 93.7%、96.8%和 99.2%。验证队列证实该模型的敏感性、特异性和准确性分别为 92.9%、93.3%和 93.1%。
评分模型可用于区分 TBPE 和 non-TBPE。
