Early detection of tuberculosis: a systematic review

被引：3

作者：

Yayan, Josef ^{[1
]}

Franke, Karl-Josef ^{[2
]}

Berger, Melanie ^{[3
]}

Windisch, Wolfram ^{[3
]}

Rasche, Kurt ^{[1
]}

机构：

[1] Witten Herdecke Univ, Dept Internal Med, Div Pulm Allergy & Sleep Med, HELIOS Clin Wuppertal, Heusnerstr 40, D-42283 Wuppertal, Germany

[2] Witten Herdecke Univ, Internal Intens Care Med Infectiol & Sleep Med, Mark Clin Hlth Holding Ltd, Clin Ludenscheid,Dept Internal Med,Pulm Div, Ludenscheid, Germany

[3] Witten Herdecke Univ, Cologne Merheim Hosp, Dept Pneumol, Cologne, Germany

来源：

PNEUMONIA | 2024年 / 16卷 / 01期

关键词：

Early diagnosis; Screening; Diagnostic tests; Tuberculosis; GAMMA RELEASE ASSAY; MTB/RIF ASSAY; PULMONARY TUBERCULOSIS; CARE DIAGNOSTICS; AMPLIFICATION; RESISTANCE; TESTS; CHALLENGES; INFECTION; DISEASE;

D O I：

10.1186/s41479-024-00133-z

中图分类号：

R56 [呼吸系及胸部疾病];

学科分类号：

摘要：

Tuberculosis remains a significant global health challenge. Tuberculosis affects millions of individuals worldwide. Early detection of tuberculosis plays a relevant role in the management of treatment of tuberculosis. This systematic review will analyze the findings of several published studies on the topic of the early detection of tuberculosis. This systematic review highlights their methodologies and limitations as well as their contributions to our understanding of this pressing issue. Early detection of tuberculosis can be achieved through tuberculosis screening for contacts. Comprehensive health education for household contacts can be used as early detection. The in-house deep learning models can be used in the X-ray used for automatic detection of tuberculosis. Interferon gamma release assay, routine passive and active case detection, portable X-ray and nucleic acid amplification testing, and highly sensitive enzyme-linked immunosorbent assay tests play critical roles in improving tuberculosis detection.

引用

页数：15

共 81 条

[21] Deep Learning Algorithms with Demographic Information Help to Detect Tuberculosis in Chest Radiographs in Annual Workers' Health Examination Data [J].