Clinical Research Directory

Increased Tuberculosis Case Detection - DiOpTB

Sponsor: Aarhus University Hospital

Summary

As estimated by the WHO 10.6 million new Tuberculosis (TB) cases were identified in 2022- while more than three million went undetected and untreated. The low detection rate illustrates the failure to recognise and diagnose TB in the current cascade of healthcare and is a major obstacle to effective TB control programs. This multi-centre cluster-randomised clinical trial will evaluate the effect (i.e., diagnostic yield) of improving the point-of-care diagnostics already in place in most primary health-care centres in low-resource settings. The present study will be conducted in two different geographical settings in the Western and Eastern African countries of Guinea Bissau and Ethiopia. This improved clinical diagnostic pathway may improve case detection rates at primary healthcare level, ensuring prompt commencement of treatment, thereby diminishing transmission risk in the community and improving treatment outcomes. The Optimized Diagnostic Procedure (ODP) will utilize instructed sputum sampling and pooling as well as computer-aided detection (CAD) chest X-ray (CXR) and additional pooled sputum sample as well as non-sputum sampling (faecal and a buccal/tongue swab and saliva) for GeneXpert Ultra PCR (Xpert) as state-of-the-art add-ons to the routine diagnostic pathway for TB. This adds to the key components of the WHO "End TB" strategy - early diagnosis - and if successful, may be rapidly approved by the WHO and implemented by governments globally with potentially major public health benefits. The study will be conducted in close liaison with the national Ministries of Health and TB programs in Guinea-Bissau and Ethiopia. This will facilitate any relevant findings to be taken forward for implementation into policy and practice. Capacity development, training and educational activities will be closely aligned to this study.

Official title: Increased Tuberculosis Case Detection - a Cluster-randomized Trial Combining Available Resources and Novel Strategies for High Endemic Areas

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Locations (2)