Accuracy of CAD4TB (Computer-Aided Detection for Tuberculosis) on paediatric chest radiographs.

Autor:	Edem VF; Vaccines and Immunity Theme, MRC Unit The Gambia at London School of Hygiene and Tropical Medicine, Fajara, The Gambia.; Department of Immunology, College of Medicine, University of Ibadan, Ibadan, Nigeria.; V.F. Edem and E. Nkereuwem contributed equally to this work., Nkereuwem E; Vaccines and Immunity Theme, MRC Unit The Gambia at London School of Hygiene and Tropical Medicine, Fajara, The Gambia.; Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK.; V.F. Edem and E. Nkereuwem contributed equally to this work., Agbla SC; Department of Health Data Science, University of Liverpool, Liverpool, UK.; Department of Infectious Diseases Epidemiology, London School of Hygiene and Tropical Medicine, London, UK., Owusu SA; Vaccines and Immunity Theme, MRC Unit The Gambia at London School of Hygiene and Tropical Medicine, Fajara, The Gambia.; Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK.; Department of Paediatrics and Child Health, School of Medicine, University for Development Studies, Tamale, Ghana., Sillah AK; Vaccines and Immunity Theme, MRC Unit The Gambia at London School of Hygiene and Tropical Medicine, Fajara, The Gambia., Saidy B; Vaccines and Immunity Theme, MRC Unit The Gambia at London School of Hygiene and Tropical Medicine, Fajara, The Gambia., Jallow MB; National Leprosy and Tuberculosis Control Programme, Ministry of Health, Banjul, The Gambia., Forson AG; Department of Medicine, Korle Bu Teaching Hospital and University of Ghana Medical School, Accra, Ghana., Egere U; Department of International Public Health, Liverpool School of Tropical Medicine, Liverpool, UK., Kampmann B; Vaccines and Immunity Theme, MRC Unit The Gambia at London School of Hygiene and Tropical Medicine, Fajara, The Gambia.; Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK.; Charité Centre for Global Health, Institute of International Health, Charité - Universitätsmedizin Berlin, Berlin, Germany., Togun T; Vaccines and Immunity Theme, MRC Unit The Gambia at London School of Hygiene and Tropical Medicine, Fajara, The Gambia Toyin.Togun@lshtm.ac.uk.; Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK.; TB Centre, London School of Hygiene and Tropical Medicine, London, UK.
Jazyk:	angličtina
Zdroj:	The European respiratory journal [Eur Respir J] 2024 Nov 07; Vol. 64 (5). Date of Electronic Publication: 2024 Nov 07 (Print Publication: 2024).
DOI:	10.1183/13993003.00811-2024
Abstrakt:	Background: Computer-aided detection (CAD) systems hold promise for improving tuberculosis (TB) detection on digital chest radiographs. However, data on their performance in exclusively paediatric populations are scarce. Methods: We conducted a retrospective diagnostic accuracy study evaluating the performance of CAD4TBv7 (Computer-Aided Detection for Tuberculosis version 7) using digital chest radiographs from well-characterised cohorts of Gambian children aged <15 years with presumed pulmonary TB. The children were consecutively recruited between 2012 and 2022. We measured CAD4TBv7 performance against a microbiological reference standard (MRS) of confirmed TB, and also performed Bayesian latent class analysis (LCA) to address the inherent limitations of the MRS in children. Diagnostic performance was assessed using the area under the receiver operating characteristic curve (AUROC) and point estimates of sensitivity and specificity. Results: A total of 724 children were included in the analysis, with confirmed TB in 58 (8%), unconfirmed TB in 145 (20%) and unlikely TB in 521 (72%). Using the MRS, CAD4TBv7 showed an AUROC of 0.70 (95% CI 0.60-0.79), and demonstrated sensitivity and specificity of 19.0% (95% CI 11-31%) and 99.0% (95% CI 98.0-100.0%), respectively. Applying Bayesian LCA with the assumption of conditional independence between tests, sensitivity and specificity estimates for CAD4TBv7 were 42.7% (95% CrI 29.2-57.5%) and 97.9% (95% CrI 96.6-98.8%), respectively. When allowing for conditional dependence between culture and Xpert assay, CAD4TBv7 demonstrated a sensitivity of 50.3% (95% CrI 32.9-70.0%) and specificity of 98.0% (95% CrI 96.7-98.9%). Conclusion: Although CAD4TBv7 demonstrated high specificity, its suboptimal sensitivity underscores the crucial need for optimisation of CAD4TBv7 for detecting TB in children. Competing Interests: Conflict of interest: The authors have no potential conflicts of interest to disclose. (Copyright ©The authors 2024.)
Databáze:	MEDLINE
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