Actively Recruiting

Age: 12Years +
All Genders
NCT05317247

Cough Audio Classification as a TB Triage Test

Led by University of Stellenbosch · Updated on 2026-05-06

1751

Participants Needed

2

Research Sites

297 weeks

Total Duration

On this page

Sponsors

U

University of Stellenbosch

Lead Sponsor

A

Amsterdam Institute for Global Health and Development

Collaborating Sponsor

AI-Summary

What this Trial Is About

TB is the single biggest infectious cause of death (1.5 million died in 2018), killing more HIV-positive people than any other disease, and is arguably the most important poverty-related disease in the world. TB's estimated incidence in Africa has been declining over recent years but progress is slow and plateauing. To avert stagnation, truly innovative and ambitious technologies are needed, especially those that improve case finding and time-to-diagnosis as, in mathematical models based on the TB care cascade framework, interventions that accomplish this will have the most impact on disrupting population-level transmission, including when deployed at facilities where patients are readily accessible. Critically, these interventions (triage tests) must promote access to confirmatory testing (e.g., Xpert MTB/RIF Ultra) by enabling patients to be referred rapidly and efficiently during the same visit. The investigators will optimise and evaluate a technology that, aside from the investigators early case-controlled study to show feasibility, is hitherto not meaningfully investigated for TB. This gap is alarming given, on one hand, the enormity of the TB epidemic and the need for a triage test and, on the other hand, promising proofs-of-concept that demonstrate high diagnostic accuracy of cough audio classifier for respiratory diseases such as pneumonia, asthma. pertussis, croup, and COPD. In some cases, these classification systems are CE-marked, awaiting FDA-approval, and subject to late-stage clinical trials. This demonstrates the promise of the underlying technological principle. CAGE-TB's innovation is further enhanced by: applying advanced machine learning methods that the team have specifically developed for TB patient cough audio analysis, use of mixed methods research - drawing from health economics, implementation science, and medical anthropology - to inform product design and assess barriers and facilitators to implementation, and uniquely for a TB diagnostic test, its potential deployment as a pure mHealth (smartphone-based) innovation that mitigates many barriers that typically jeopardise TPP criteria fulfilment.

CONDITIONS

Official Title

Cough Audio Classification as a TB Triage Test

Who Can Participate

Age: 12Years +
All Genders

Eligibility Criteria

Eligible

You may qualify if you...

  • Participant must be at least 12 years old
  • Participant must have a cough lasting at least two weeks
  • Participant must provide informed consent
  • Participant must have a known HIV status or be willing to undergo HIV testing and counseling
Not Eligible

You will not qualify if you...

  • Refusal to provide informed consent
  • Received tuberculosis treatment within 60 days prior to enrollment
  • Unable to provide a sputum sample for microbiological testing
  • Presence of blood in cough or coughing up blood during forced coughs for audio recording

AI-Screening

AI-Powered Screening

Complete this quick 3-step screening to check your eligibility

1
2
3
+1

Trial Site Locations

Total: 2 locations

1

Stellenbosch University

Cape Town, Western Cape, South Africa, 7505

Actively Recruiting

2

Makerere University

Kampala, Kampala, Uganda, 7062

Actively Recruiting

Loading map...

Research Team

G

Grant Theron, PhD

CONTACT

D

Daphne Naidoo, Hons

CONTACT

How is the study designed?

Study Type

OBSERVATIONAL

Masking

N/A

Allocation

N/A

Model

N/A

Primary Purpose

N/A

Number of Arms

2

Not the Right Trial for You?

Explore thousands of other clinical trials that might be a better match.
Sign up to get personalized trial recommendations delivered to your inbox.

Already have an account? Log in here