Li Chun-Hua, Fan Xiao, Lv Sheng-Xiu, Liu Xue-Yan, Wang Jia-Nan, Li Yong-Mei, Li Qi
Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, People's Republic of China.
Department of Radiology, Chongqing Public Health Medical Center, Chongqing, People's Republic of China.
Infect Drug Resist. 2023 Jan 30;16:651-659. doi: 10.2147/IDR.S394071. eCollection 2023.
To explore the value of integrating clinical and computed tomography (CT) features to predict multidrug-resistant pulmonary tuberculosis (MDR-PTB).
The study included 212 patients with MDR-PTB and 180 patients with drug-sensitive pulmonary tuberculosis (DS-PTB) who referred to our institute in China between January 2016 and March 2021. The clinical and CT characteristics were analyzed and compared between both groups. Multivariable logistic regression analysis was performed to identify independent factors that can be used to predict MDR-PTB. Furthermore, 115 patients admitted to another center from January 2019 to January 2022 were included as external validation cohort.
For clinical characteristics, five parameters were significantly different between the two groups (all < 0.05). With regard to CT features, nine parameters were significantly different between the two groups (all < 0.05). Multivariable logistic regression analysis using the aforementioned differential features showed that male sex, retreated history, longer duration of previous anti-TB treatment, lower CD4 T lymphocyte count, thick-walled cavity, centrilobular micronodules and tree-in-bud sign, bronchial stenosis, pleural and pericardial thickening were the most effective variations associated with MDR-PTB with an area under the curve (AUC) of 0.849 and accuracy of 78.6%. Furthermore, the external validation cohort that contains 115 patients obtained an AUC of 0.933 and accuracy of 81.7%.
MDR-PTB and DS-PTB have different clinical and imaging characteristics. A combined model incorporating these differential features can promptly diagnose MDR-PTB and develop subsequent therapeutic strategies.
探讨整合临床特征与计算机断层扫描（CT）特征对预测耐多药肺结核（MDR-PTB）的价值。
本研究纳入了2016年1月至2021年3月间在中国我院就诊的212例耐多药肺结核患者和180例药物敏感肺结核（DS-PTB）患者。分析并比较了两组患者的临床和CT特征。采用多变量逻辑回归分析确定可用于预测耐多药肺结核的独立因素。此外，将2019年1月至2022年1月在另一个中心收治的115例患者作为外部验证队列。
就临床特征而言，两组间有5个参数存在显著差异（均P<0.05）。关于CT特征，两组间有9个参数存在显著差异（均P<0.05）。使用上述差异特征进行的多变量逻辑回归分析显示，男性、复治史、既往抗结核治疗时间较长、CD4 T淋巴细胞计数较低、厚壁空洞、小叶中心微结节和树芽征、支气管狭窄、胸膜和心包增厚是与耐多药肺结核相关的最有效变量，曲线下面积（AUC）为0.849，准确率为78.6%。此外，包含115例患者的外部验证队列的AUC为0.933，准确率为81.7%。
耐多药肺结核和药物敏感肺结核具有不同的临床和影像学特征。结合这些差异特征的联合模型可及时诊断耐多药肺结核并制定后续治疗策略。
