ArticleInfection and drug resistance2026
A High Sensitive Detection of Droplet Digital PCR for the Diagnosis of Pulmonary Tuberculosis.
Shangying Yang, Mingxiang Huang, Yunfan Xiong, ChunXia Tu, Ye Xu, Kanglin Wan, Xiaohong Chen, Fan Zhang, Xiaoqin Liao, Qiaoqian Chen and 2 more
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In one paragraphArticle in Infection and drug resistance, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Shangying YangDepartment of Clinical Laboratory, Fuzhou Pulmonary Hospital of Fujian Province, Fuzhou, Fujian, People's Republic of China.ORCID 0009-0005-8806-1127 Mingxiang HuangDepartment of Clinical Laboratory, Fuzhou Pulmonary Hospital of Fujian Province, Fuzhou, Fujian, People's Republic of China.
Yunfan XiongEngineering Research Centre of Molecular Diagnostics of the Ministry of Education, State Key Laboratory of Cellular Stress Biology, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, Xiamen, Fujian, People's Republic of China.ORCID 0009-0003-3942-7394 ChunXia TuEngineering Research Centre of Molecular Diagnostics of the Ministry of Education, State Key Laboratory of Cellular Stress Biology, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, Xiamen, Fujian, People's Republic of China.
Ye XuEngineering Research Centre of Molecular Diagnostics of the Ministry of Education, State Key Laboratory of Cellular Stress Biology, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, Xiamen, Fujian, People's Republic of China.ORCID 0000-0001-5066-4698 Kanglin WanNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Changping, Beijing, People's Republic of China.
Xiaohong ChenDepartment of Tuberculosis, Fuzhou Pulmonary Hospital of Fujian Province, Fuzhou, Fujian, People's Republic of China.
Fan ZhangDepartment of Tuberculosis, Fuzhou Pulmonary Hospital of Fujian Province, Fuzhou, Fujian, People's Republic of China.ORCID 0009-0006-6556-5266 Xiaoqin LiaoDepartment of Tuberculosis, Fuzhou Pulmonary Hospital of Fujian Province, Fuzhou, Fujian, People's Republic of China.
Qiaoqian ChenDepartment of Clinical Laboratory, Fuzhou Pulmonary Hospital of Fujian Province, Fuzhou, Fujian, People's Republic of China.ORCID 0009-0000-1026-8949 Jing ZhangDepartment of Clinical Laboratory, Fuzhou Pulmonary Hospital of Fujian Province, Fuzhou, Fujian, People's Republic of China.ORCID 0009-0003-2817-1223 Jie LiuSchool of Medical Technology and Engineering, Fujian Medical University, Fuzhou, Fujian, People's Republic of China.ORCID 0009-0003-8669-9050 Funding
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6 · The paper itselfAbstract
Purpose: Rapid and accurate diagnosis of Patients and Methods: We evaluated the diagnostic performance of a dual-target droplet digital PCR (ddPCR) assay, targeting Results: The ddPCR assay demonstrated a sensitivity of 89.7% (95% CI: 86.3-92.3%), specificity of 89.0% (95% CI: 81.5-94.0%), positive predictive value (PPV) of 96.7% (95% CI: 94.5-98.1%), and negative predictive value (NPV) of 70.3% (95% CI: 61.8-77.6%). The overall concordance rate was 89.5% (95% CI: 86.5-91.9%), with a Kappa value of 0.768 (95% CI: 0.712-0.824). The superior diagnostic performance of ddPCR was further supported by an area under the receiver operating characteristic (ROC) curve (AUC) of 0.893 (95% CI: 0.855-0.931). In a subgroup analysis of 216 bacteriologically negative PTB cases, ddPCR exhibited a sensitivity of 81.9%, which was significantly higher than that of Xpert (34.3%), MMCA (17.6%), and qPCR (31.0%) (all Conclusion: The dual-target ddPCR assay targeting
Indexed as
diagnosisdroplet digital PCRhigh sensitivepulmonary tuberculosis
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PMID42311934
PMCPMC13269033
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