AI-enabled digital stethoscope to guide antibiotic use in young children with pneumonia
Official title: The BLAAAST Trial: Bangladesh Lung Auscultation AI for Antibiotic Stewardship Randomized Controlled Trial
Run by Johns Hopkins University · NCT07362433 · Data updated 2026-11-12
This trial tests whether using an AI-assisted digital stethoscope to guide antibiotic decisions in children with suspected non-severe pneumonia is no worse than standard care at treating them with antibiotics.
Quick facts
| Phase | Phase 4 |
|---|---|
| Study type | Interventional |
| Ages | 2 Months to 59 Months |
| Sex | All |
| Enrollment | 2500 (estimated) |
| Sponsor | Johns Hopkins University Academic / other |
| Locations | 1 site (Sylhet) |
| Status | Recruiting |
| Started | June 2, 2026 |
| Main results expected | June 30, 2029 |
| Study ends | June 30, 2029 |
| Registry record updated | June 8, 2026 |
| Trial ID | NCT07362433 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Children aged 2 to 59 months with non-severe pneumonia meeting IMCI criteria in the trial catchment areas.
✕Probably not a fit
Children whose lung sounds or clinical presentation do not align with the AI algorithm’s classification may not benefit from the AI-guided approach.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This phase 4 trial in rural Bangladesh evaluates whether an AI-enabled digital stethoscope can help clinicians decide when antibiotics are needed for children with non-severe pneumonia, potentially reducing unnecessary antibiotic use. Children aged 2 to 59 months with symptoms up to 14 days and meeting IMCI non-severe pneumonia criteria are enrolled, have lung sounds recorded, and are randomized to an AI-guided antibiotic plan or standard care. In the intervention arm, lung-sound analysis determines antibiotic treatment, while all control participants receive standard antibiotic therapy per IMCI guidelines. The primary aim is to determine non-inferiority in treatment failure between the AI-guided approach and standard care. The study uses encrypted data transfer, randomized allocation after recording, and a 5-day antibiotic course when indicated by IMCI guidance.
Why it matters
Potential benefit: If successful, this approach could reduce unnecessary antibiotic use and help preserve antibiotic effectiveness in resource-limited settings.
How similar studies have gone: Previous work in automated auscultation and AI-assisted diagnosis has shown promise but this exact non-inferiority design in a rural, pediatric population is relatively novel.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * 2 to 59 months of age (60 days to 59 months 29 days), * illness duration 14 days or less, * meeting non-severe pneumonia criteria, and * from the trial catchment areas. Exclusion Criteria: * prior participation, * age \<2 months or \>59 months, * illness duration \>14 days, * not meeting IMCI-defined non-severe pneumonia criteria, * oxygen saturation (SpO2) \<90%, * moderate or severe malnutrition, * known chronic disease, * history of prematurity, * one or more high risk clinical signs (any WHO-defined clinical danger sign and/or WHO-defined emergency sign), * known antibiotic exposure in the past 1 week, * non-respiratory illness requiring systemic antibiotic treatment according to IMCI guidelines.
Where it's running
-
Projahnnmo Research Foundation
Sylhet, Bangladesh Recruiting
Study contacts
- Principal investigator: Eric McCollum, MD, MPH — Johns Hopkins University
- Study coordinator: Eric D McCollum, MD, MPH
- Email: emccoll3@jhmi.edu
- Phone: 410-955-2035
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.