2 research outputs found
Active close contact investigation of tuberculosis through computer-aided detection and stool Xpert MTB/RIF among people living in Oromia Region, Ethiopia (CADOOL Study): protocol for a prospective, cross-sectional study
No full textIntroduction Pulmonary tuberculosis (TB) is an infectious disease with high incidence in low-income countries (LICs); it remains one of the infectious diseases with the highest mortality in the world, especially in LICs. It is crucial to recognise and diagnose TB as soon as possible, but microbiological tests on sputum are not always sensitive enough. New methods for an early diagnosis of TB are needed. In this study, we will investigate the role of two different tests to detect TB in Ethiopia (where the prevalence of TB is high): molecular search for TB in stool samples with Xpert assay and detection of pulmonary TB signs on chest X-rays with CAD4TB technology.
Methods and analysis A prospective diagnostic test accuracy study during TB active contact investigation will be conducted. In the referral hospital in Southwest Shoa Zone, Oromia Region, Ethiopia, patients with pulmonary TB and a sputum sample positive for Mycobacterium tuberculosis and household contacts of at least 4 years
of age will be enrolled, with a target sample size of 231 patients. Trained staff will label household contacts as ‘possible TB’ cases or not according to their symptoms; when TB is possible, a stool Xpert and computer-aided detection on chest X-ray will be performed, alongside standard diagnostic methods, assessing the diagnostic accuracy of CAD4TB compared with Xpert MTB/RIF during TB contact investigation and the accuracy of stool Xpert compared with sputum Xpert
Improving Tuberculosis Diagnosis Through Artificial Intelligence (CAD4TB) and Stool Xpert MTB/RIF Testing: A Prospective Study From Oromia, Ethiopia
No full textBackground
Tuberculosis remains the leading cause of death by a single infectious agent globally, with Ethiopia among the highest tuberculosis- and human immunodeficiency virus/tuberculosis–burden countries. Diagnostic gaps—particularly among household contacts (HHCs) unable to expectorate—hinder early case detection. Computer-aided detection software for chest radiography and nonrespiratory molecular assays, such as stool-based Xpert MTB/RIF testing, represent promising strategies for scalable screening.
Methods
We conducted a prospective diagnostic accuracy study at St Luke Catholic Hospital, Oromia, Ethiopia, enrolling 478 participants (152 tuberculosis index patients and 326 HHCs). All HHCs ≥4 years underwent digital chest radiographic screening, with or without CAD4TB (Delft Imaging) software assistance, and provided stool and sputum samples for Xpert MTB/RIF testing. The accuracy of CAD4TB and stool Xpert testing was evaluated against sputum Xpert testing as the reference.
Results
CAD4TB showed strong diagnostic performance, with a sensitivity of 0.77 (95% confidence interval, .70–.83) and specificity of 0.93 (.90–.96). Performance was higher among adults (sensitivity and specificity, 0.79 and 0.94) than in children (0.64 and 0.92). Stool and sputum Xpert testing demonstrated high concordance (Cohen’s κ = 0.76), with a sensitivity of 0.77 (95% confidence interval, .70–.84) and specificity of 0.97 (.93–.99). During the study, 10.6% of HHCs (34 of 321) were newly diagnosed microbiologically with tuberculosis.
Conclusions
The combined use of CAD4TB and stool Xpert testing significantly improves tuberculosis detection, particularly among HHCs in high-burden, low-resource settings. This strategy is especially valuable in children and adults unable to produce sputum and where radiological expertise is limited
