机构：[1]Department of Laboratory Medicine, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China[2]Institute for Genome and Bioinformatics, Shanghai Institute for Biomedical and Pharmaceutical Technologies, Shanghai, China[3]Prevention & Treatment Department, Changning District Mental Health Center, Shanghai, China
Background: At present, the diagnosis of tuberculosis (TB) is still challenging, and improving the efficiency of diagnosis can help prevent and control TB. This retrospective clinical study aimed to assess the diagnostic efficiency of GeneXpert MTB/RIF for pulmonary TB. Methods: A total of 620 newly-diagnosed patients who visited the pulmonary clinic of Shanghai Tongren Hospital between 2018 and 2021 were enrolled in the study. All 620 patients had acid-fast Bacilli (AFB) identified by Ziehl Neelsen staining (ZNS) test, BECTEC MGIT 960 liquid culture (LC), and GeneXpert MTB/RIF assay (GX). A total of 53 patients also underwent interferon-?? release assay (IGRA). The diagnostic efficacy of ZNS, LC, GX alone or in combination in pulmonary TB was evaluated, with clinical diagnosis as the gold standard. Moreover, the IGRA for pulmonary TB diagnosis was preliminarily assessed. Results: Eventually, 185 cases were clinically confirmed (which included 36 etiologically negative cases) in the total enrolled 620 first-diagnosed patients. Overall, the 3 methods ZNS, LC, and GX showed sensitivities of 55.68%, 64.32%, and 68.64%, specificities of 98.39%, 95.40%, and 99.08%, positive predictive values (PPV) of 93.64%, 85.61%, and 96.95%, and negative predictive values (NPV) of 83.92%, 86.28%, and 88.14%, respectively. The GX method showed the highest specificity and PPV for a solitary single method, with 99.08% and 96.95%, respectively. Regarding pairwise combination methods, all showed superior sensitivity to a single test, reaching a maximum of 80.00%. Among them, the LC + GX combination showed both the highest sensitivity (80.00%) and NPV (91.78%), and the corresponding area under the receiver operating characteristic curve (0.875) was the largest. Among the 53 patients who underwent IGRA testing, 42 were positive (including 4 etiologically negative cases), and 11 were negative. The overall sensitivity of IGRA for diagnosing pulmonary TB was 90.00%, specificity was 27.27%, PPV was 42.86%, and NPV was 81.82%. Conclusions: The GX method shows promise as a first-line diagnostic method for pulmonary TB. Furthermore, the sensitivity was significantly improved when combined with LC. This combination will screen out some etiologically negative patients plus IGRA, so their combination is recommended for practice optimization.
基金：
Changning District Health Commission Medical Key Specialty Laboratory [20191001]
第一作者机构：[1]Department of Laboratory Medicine, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
共同第一作者：
通讯作者：
通讯机构：[1]Department of Laboratory Medicine, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China[3]Prevention & Treatment Department, Changning District Mental Health Center, Shanghai, China[*1]Prevention & Treatment Department, Changning District Mental Health Center, Shanghai 200335, China.[*2]Department of Laboratory, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, 1111 Xianxia Road, Shanghai 200336, China.
推荐引用方式(GB/T 7714)：
Zhang Huanhuan,Li Hong,Tan Meiyu,et al.GeneXpert MTB/RIF combined with conventional methods for tuberculosis in Shanghai Regional Medical Center: a retrospective diagnostic study[J].ANNALS OF TRANSLATIONAL MEDICINE.2022,10(10):doi:10.21037/atm-22-1374.
APA：
Zhang, Huanhuan,Li, Hong,Tan, Meiyu,Liu, Zhenhao,Gu, Jie...&Sheng, Huiming.(2022).GeneXpert MTB/RIF combined with conventional methods for tuberculosis in Shanghai Regional Medical Center: a retrospective diagnostic study.ANNALS OF TRANSLATIONAL MEDICINE,10,(10)
MLA：
Zhang, Huanhuan,et al."GeneXpert MTB/RIF combined with conventional methods for tuberculosis in Shanghai Regional Medical Center: a retrospective diagnostic study".ANNALS OF TRANSLATIONAL MEDICINE 10..10(2022)
