TuberculosisNCT05139940
Validation of Artificial Intelligence Enabled TB Screening and Diagnosis in Zambia
An observational study of Tuberculosis, run by Centre for Infectious Disease Research in Zambia at 3 sites in Zambia.
Trial summary
Tuberculosis (TB) is a global epidemic and for many years has remained a major cause of death throughout the developing world. Zambia is among the top 30 TB/HIV high burden countries. Chest X-ray (CXR) is recommended as a triaging test for TB, and a diagnostic aid when available. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Tuberculosis
- How many people
- 2,432 participants
- Where
- 3 sitesZambia
- Study dates
- 22 Nov 2021to 30 Nov 2022
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: The study will be conducted from Chainda South Clinic, Chawama and Kanyama General Hospitals. These facilities are selected based on existing access to digital radiography. Participants will be drawn from patients attending these health facilities for: * Health services * TB households of those who are close contacts of TB households within the catchment area of these facilities
Who may be able to join
- Participants who are 18 years and older with a known HIV status or are willing to undergo HIV testing if unknown HIV status and meet the following criteria will be included in the study:
- Presumptive TB patients defined as having any of the following:
- ○ Cough, Weight loss, Night sweats, Fever
- Household /close TB contacts regardless of symptoms
- Newly diagnosed HIV regardless of symptoms.
Who cannot join
- Individuals who do meet the above inclusion criteria will be excluded. In addition, individuals with history of TB treatment within 365 days prior to enrolment will be excluded.
Trial locations and contacts
3 sites in 1 country.
Zambia3 sites
Chainda South Health Facility
Lusaka, Lusaka Province, 10101
Chawama first level hospital
Lusaka, Lusaka Province, 10101
Kanyama level 1
Lusaka, Lusaka Province, 10101
About this study
Tuberculosis (TB) is a global epidemic and for many years has remained a major cause of death throughout the developing world. Zambia is among the top 30 TB/HIV high burden countries. Chest X-ray (CXR) is recommended as a triaging test for TB, and a diagnostic aid when available. However, many high-burden settings lack access to experienced radiologists capable of interpreting these images, resulting in mixed sensitivity, poor specificity, and large inter-observer variation. In recognition of this challenge, the World Health Organization has recommended the use of automated systems that utilize artificial intelligence (AI) to read CXRs for screening and triaging for TB. In this study, we primarily evaluate the performance of our AI algorithm for TB, and secondarily for Abnormal/Normal.
- Conditions
- Tuberculosis
- Keywords
- Screening, Diagnosis, Artificial Intelligence, Chest X-ray
- Medical subject headings
- Tuberculosis, Disease
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| Pilot Group to calibrate the operating points for AI algorithms (Estimated Enrollment up to 500) | Diagnostic Test: TB AI algorithm performance in detecting active TB. Diagnostic Test: TB diagnosis from sputum and urine (Smear microscopy, Xpert MTB RIF/ultra, Lipoarabinomannan (LAM) and mycobacterial culture) Diagnostic Test: Abnormal/Normal AI algorithm to detect abnormal/normal CXRs. Diagnostic Test: Radiologist evaluation of CXRs for active TB, abnormal/normal. Diagnostic Test: Labs: Hemoglobin level, HIV status, CD4 count. | |
| Main Cross Sectional Group (Estimated Enrollment 1932 minus the volume in pilot) | Diagnostic Test: TB AI algorithm performance in detecting active TB. Diagnostic Test: TB diagnosis from sputum and urine (Smear microscopy, Xpert MTB RIF/ultra, Lipoarabinomannan (LAM) and mycobacterial culture) Diagnostic Test: Abnormal/Normal AI algorithm to detect abnormal/normal CXRs. Diagnostic Test: Radiologist evaluation of CXRs for active TB, abnormal/normal. Diagnostic Test: Labs: Hemoglobin level, HIV status, CD4 count. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Pilot Group to calibrate the operating points for AI algorithms
- Operating point selection for TB AI algorithm and Abnormal/Normal AI algorithm on CXRs for outcomes listed in Main Cross Sectional Group.
Measured: 2 months
Main Cross Sectional Group
- TB AI algorithm sensitivity and specificity in detecting active TB on CXR compared to panel of radiologists
Measured: 7 months
Secondary outcomes (2)
Main Cross Sectional Group:
- TB AI algorithm sensitivity and specificity in detecting active TB compared to World Health Organisation (WHO) performance guidelines of 90% sensitivity and 70% specificity
Measured: 7 months
Main Cross Sectional Group
- Abnormal/Normal AI algorithm sensitivity and specificity compared to 90% sensitivity and 50% specificity.
Measured: 7 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted1 Dec 2021
- Study start22 Nov 2021
- Primary completion30 Sep 2022
- Study completion30 Nov 2022
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for TuberculosisStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 2,432 participants (actual)
Sponsor and investigators
- Lead sponsor
- Centre for Infectious Disease Research in Zambia
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05139940
- Sponsor's protocol ID
- Google AI
- Status last verified
- May 2025
- First submitted
- 18 Nov 2021
- Last updated
- 15 May 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 15 May 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Validation of Artificial Intelligence Enabled TB Screening and Diagnosis in Zambia
- ClinicalTrials.gov ID
- NCT05139940
- Acronym / sponsor ID
- Google AI
- Conditions
- Tuberculosis
- Keywords
- Screening, Diagnosis, Artificial Intelligence, Chest X-ray
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 2,432 participants (actual)
- Lead sponsor
- Centre for Infectious Disease Research in ZambiaUniversity, hospital or other
- Study start
- 22 Nov 2021 (actual)
- Primary completion
- 30 Sep 2022 (actual)
- Study completion
- 30 Nov 2022 (actual)
- First posted
- 1 Dec 2021 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Tuberculosis (TB) is a global epidemic and for many years has remained a major cause of death throughout the developing world. Zambia is among the top 30 TB/HIV high burden countries. Chest X-ray (CXR) is recommended as a triaging test for TB, and a diagnostic aid when available. However, many high-burden settings lack access to experienced radiologists capable of interpreting these images, resulting in mixed sensitivity, poor specificity, and large inter-observer variation. In recognition of this challenge, the World Health Organization has recommended the use of automated systems that utilize artificial intelligence (AI) to read CXRs for screening and triaging for TB. In this study, we primarily evaluate the performance of our AI algorithm for TB, and secondarily for Abnormal/Normal.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Pilot Group to calibrate the operating points for AI algorithms (Estimated Enrollment up to 500) | – | –Diagnostic Test: TB AI algorithm performance in detecting active TB. Diagnostic Test: TB diagnosis from sputum and urine (Smear microscopy, Xpert MTB RIF/ultra, Lipoarabinomannan (LAM) and mycobacterial culture) Diagnostic Test: Abnormal/Normal AI algorithm to detect abnormal/normal CXRs. Diagnostic Test: Radiologist evaluation of CXRs for active TB, abnormal/normal. Diagnostic Test: Labs: Hemoglobin level, HIV status, CD4 count. |
| Main Cross Sectional Group (Estimated Enrollment 1932 minus the volume in pilot) | – | –Diagnostic Test: TB AI algorithm performance in detecting active TB. Diagnostic Test: TB diagnosis from sputum and urine (Smear microscopy, Xpert MTB RIF/ultra, Lipoarabinomannan (LAM) and mycobacterial culture) Diagnostic Test: Abnormal/Normal AI algorithm to detect abnormal/normal CXRs. Diagnostic Test: Radiologist evaluation of CXRs for active TB, abnormal/normal. Diagnostic Test: Labs: Hemoglobin level, HIV status, CD4 count. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- The study will be conducted from Chainda South Clinic, Chawama and Kanyama General Hospitals. These facilities are selected based on existing access to digital radiography. Participants will be drawn from patients attending these health facilities for: * Health services * TB households of those who are close contacts of TB households within the catchment area of these facilities
Key inclusion criteria (5 listed)
- Participants who are 18 years and older with a known HIV status or are willing to undergo HIV testing if unknown HIV status and meet the following criteria will be included in the study:
- ○ Cough, Weight loss, Night sweats, Fever
Key exclusion criteria (1 listed)
- Individuals who do meet the above inclusion criteria will be excluded. In addition, individuals with history of TB treatment within 365 days prior to enrolment will be excluded.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Pilot Group to calibrate the operating points for AI algorithms
Time frame: 2 months
1. Operating point selection for TB AI algorithm and Abnormal/Normal AI algorithm on CXRs for outcomes listed in Main Cross Sectional Group.
Main Cross Sectional Group
Time frame: 7 months
1. TB AI algorithm sensitivity and specificity in detecting active TB on CXR compared to panel of radiologists
2 secondary outcomes
Main Cross Sectional Group:
Time frame: 7 months
Main Cross Sectional Group
Time frame: 7 months
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 15 May 2025.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
3 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Tuberculosis, run by Centre for Infectious Disease Research in Zambia at 3 sites in Zambia.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 5 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 15 May 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 3 sites in Zambia. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Pilot Group to calibrate the operating points for AI algorithms (time frame: 2 months). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 15 May 2025.