Rapid Research in Diagnostics Development for TB Network (R2D2 Kids) and Assessing Diagnostics At POC for TB in Children (ADAPT for Kids)
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ClinicalTrials.gov Identifier: NCT05989802 |
Recruitment Status :
Recruiting
First Posted : August 14, 2023
Last Update Posted : January 31, 2024
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Condition or disease | Intervention/treatment | Phase |
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Tuberculosis Diagnostics Global Health | Diagnostic Test: Oral swab molecular testing Diagnostic Test: Automated Cough Sound Analysis Diagnostic Test: Automated Lung Sound Analysis Other: Chest X Ray Computer Aided Detection | Not Applicable |
Study Type : | Interventional (Clinical Trial) |
Estimated Enrollment : | 2100 participants |
Allocation: | N/A |
Intervention Model: | Single Group Assignment |
Masking: | None (Open Label) |
Primary Purpose: | Diagnostic |
Official Title: | Rapid Research in Diagnostics Development for Tuberculosis Network (R2D2 Kids) and Assessing Diagnostics At Point-of-care for Tuberculosis in Children (ADAPT for Kids) |
Actual Study Start Date : | January 26, 2024 |
Estimated Primary Completion Date : | September 1, 2026 |
Estimated Study Completion Date : | September 1, 2026 |
Arm | Intervention/treatment |
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Experimental: Evaluation of various novel TB triage and diagnostic tests
The investigators will conduct evaluation of novel TB triage and diagnostic tests in a cohort of children with presumed TB. The investigators aim to enroll 250 participants per year at each of three enrollment sites for evaluation of various novel TB triage and diagnostic tests and 30 health workers to assess test usability. Novel test evaluations will be conducted on a rolling basis as new tests ready for field evaluation are identified.
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Diagnostic Test: Oral swab molecular testing
Swab-based testing provides a non-invasive approach to collect respiratory specimens for TB testing. Data in adults suggests that swab-based testing could be valuable when sputum collection is not feasible or available. Diagnostic Test: Automated Cough Sound Analysis Cough sounds can be collected through a mobile phone and tablet, and then analyzed with machine learning algorithms to predict TB. Diagnostic Test: Automated Lung Sound Analysis Lung sounds can be collected with a non-invasive digital stethoscope, and then saved on a tablet or phone and analyzed by machine learning algorithms to predict TB. Other: Chest X Ray Computer Aided Detection Several artificial intelligence algorithms have been developed to predict TB, though this has not yet been validated in children.
Other Name: Artificial Intelligence algorithm |
- Proportion with positive index test result among participants with tuberculosis (TB) [ Time Frame: 2 years ]Sensitivity - Number with positive index test result/(Number with positive or negative index t test result) among participants with TB. TB will be defined based on a microbiological reference standard (sputum mycobacterial culture results)
- Proportion with negative index test result among participants without tuberculosis (TB) [ Time Frame: 2 years ]Specificity - Number with negative index test results/(Number with positive or negative index t test result) among participants without TB. TB will be defined based on a microbiological reference standard (sputum mycobacterial culture results)
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Ages Eligible for Study: | up to 65 Years (Child, Adult, Older Adult) |
Sexes Eligible for Study: | All |
Accepts Healthy Volunteers: | Yes |
Participant eligibility criteria:
Participants will include children (age <15 years) who present to care with:
A. 2 or more of the following:
- Unexplained cough for any duration
- TB contact or tuberculin skin test or interferon gamma release assay positive
- Abnormal chest X-ray (any abnormality) OR
B. Any one of criteria A AND any one of the following:
- Unexplained weight loss OR unexplained failure to thrive OR Severe Acute Malnutrition
- Unexplained fever ≥2 weeks
- Unexplained lethargy or reduced playfulness ≥2 weeks
The study will exclude participants who:
- Completed preventive or active TB treatment within the past 12 months (to increase TB prevalence and reduce false-positive results, respectively);
- Have taken any medication with anti-mycobacterial activity for any reason for greater than 3 days at the time of enrollment (to reduce false-negatives);
- Are unable to return for follow-up visits; or
- Whose parents/guardians are unwilling to provide informed consent or who are unwilling to provide assent if applicable (age determined by local IRB)
Assessment of the usability of novel TB tests:
The study will also include health workers at each clinical site who are 1) aged ≥18 years and 2) involved in routine TB testing (collecting specimens for or performing TB tests). Personnel who are unwilling to provide informed consent will be excluded.
To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.
Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT05989802
Contact: Devan Jaganath, MD | 415-514-4692 | devan.jaganath@ucsf.edu | |
Contact: Brittney Sweetser, MPH | bsweetse@hs.uci.edu |
Mozambique | |
Instituto Nacional de Saúde | Recruiting |
Maputo, Mozambique | |
Contact: Celso Khosa celso.khosa@ins.gov.mz | |
South Africa | |
Dora Nginza Hospital | Not yet recruiting |
Cape Town, South Africa | |
Contact: Heather Zar heather.zar@uct.ac.za | |
Uganda | |
Mulago National Referral Hospital | Not yet recruiting |
Kampala, Uganda | |
Contact: Eric Wobudeya ewobudeya@mujhu.org |
Principal Investigator: | Adithya Cattamanchi, MD, MAS | University of California, Irvine | |
Principal Investigator: | Nilesh Bhatt | Elizabeth Glazer Pediatric AIDS Foundation |
Responsible Party: | University of California, San Francisco |
ClinicalTrials.gov Identifier: | NCT05989802 |
Other Study ID Numbers: |
R01HL169449 ( U.S. NIH Grant/Contract ) U01AI152087 ( U.S. NIH Grant/Contract ) 7200AA22RFA00004 ( Other Grant/Funding Number: USAID ) |
First Posted: | August 14, 2023 Key Record Dates |
Last Update Posted: | January 31, 2024 |
Last Verified: | January 2024 |
Individual Participant Data (IPD) Sharing Statement: | |
Plan to Share IPD: | No |
Studies a U.S. FDA-regulated Drug Product: | No |
Studies a U.S. FDA-regulated Device Product: | Yes |
Device Product Not Approved or Cleared by U.S. FDA: | Yes |
Product Manufactured in and Exported from the U.S.: | Yes |
Tuberculosis Mycobacterium Infections Actinomycetales Infections Gram-Positive Bacterial Infections |
Bacterial Infections Bacterial Infections and Mycoses Infections |