Using computer-assisted diagnosis to improve TB and COVID-19 case finding in communities

Evaluating the Impact of Computer-assisted X-ray Diagnosis and Other Triage Tools to Optimise Xpert Orientated Community-based Active Case Finding for TB and COVID-19

This study is testing if using computer-assisted X-ray and other tools can help find more cases of tuberculosis and COVID-19 in communities in sub-Saharan Africa.

Quick facts

• Phase: NA
• Study type: Interventional
• Enrollment: 26200 (estimated)
• Ages: 18 Years and up
• Sex: All
• Sponsor: University of Cape Town (other)
• Locations: 3 sites (Cape Town, Western Cape and 2 other locations)
• Trial ID: NCT05220163 on ClinicalTrials.gov

What this trial studies

This study evaluates the effectiveness of computer-assisted X-ray diagnosis and other triage tools to enhance community-based active case finding for tuberculosis (TB) and COVID-19. The research aims to address the significant number of undiagnosed TB cases in sub-Saharan Africa by utilizing advanced diagnostic technologies, including urine-based biosignatures. Participants will undergo symptom screening and various diagnostic tests to identify potential cases, thereby optimizing resource allocation in healthcare settings. The study builds on previous findings that demonstrated the utility of molecular Xpert-based screening in identifying missing TB cases in peri-urban areas.

Who should consider this trial

Good fit: Ideal candidates include individuals aged 18 and older, both HIV-positive and negative, who are willing to participate in community-based screening and diagnostic testing.

Not a fit: Patients who have recently completed TB treatment, are currently being evaluated for suspected TB, or are unable to provide informed consent may not benefit from this study.

Why it matters

Potential benefit: If successful, this approach could significantly reduce the number of undiagnosed TB and COVID-19 cases, improving patient outcomes and public health.

How similar studies have performed: Previous studies have shown success with similar community-based screening approaches, indicating potential for this method to be effective.

Eligibility criteria

Inclusion Criteria:

* Participants willing to complete community-based symptom screening, finger-prick and venepuncture blood sampling, urine testing, and/or undergo TB and/or COVID-19 diagnostic testing.
* Provision of informed consent.
* Participant 18 years or above.
* HIV-positive or negative participants will be included.

Exclusion Criteria:

* Inability to provide informed consent (e.g., mentally impaired).
* Participants who have completed TB treatment in the last two months, or who have self-presented to their local TB clinic and are currently being worked up for suspected TB.
* Participants already diagnosed with active TB on treatment.
* Participants unable to commit to at least a two-month follow-up.
* Female participants who are pregnant or who refuse a urine pregnancy test.
* Participants in the community who cannot access healthcare due to severe ill health or lack of access to the local clinic.

Where this trial is running

Cape Town, Western Cape and 2 other locations

• University of Cape Town — Cape Town, Western Cape, South Africa (RECRUITING)
• Helen Ayles — Lusaka, Zambia (RECRUITING)
• Junior Mutsvangwa — Harare, Zimbabwe (RECRUITING)

Study contacts

• Principal investigator: Keertan Dheda, PhD — University of Cape Town
• Study coordinator: Alex J Scott, MBChB

Conditions: Tuberculosis, COVID-19, HIV Infections, Active case finding, Computer assisted diagnosis, Screening