Medical-AI trial: AI lung auscultation to curb antibiotic overuse in children (BLAAAST) — tackling antibiotic resistance (rural Bangladesh, RCT) (NCT07362433)

When a child comes in with cough or fever, antibiotics are often prescribed out of concern for a lower-respiratory infection (like pneumonia). But most such episodes are caused by viruses that antibiotics cannot treat and that resolve on their own. Unnecessary antibiotic use, beyond side effects, fuels the global threat of antibiotic resistance (AMR, the rise of bacteria that antibiotics no longer kill).

That is why antibiotic stewardship, telling apart the children who truly need antibiotics and safely reducing needless use, matters.

This study (BLAAAST) tests whether AI-based lung auscultation can aid that distinction, as a randomized controlled trial.

Per the registry summary, noting that antibiotics are a mainstay for childhood lower-respiratory infection although most episodes are viral and self-limiting, it frames child-friendly tools that improve diagnosis, safely cut unnecessary antibiotics, and suit resource-constrained settings as urgently needed to curb AMR. Set in rural Bangladesh, it evaluates how treatment-failure frequency compares for children managed with AI lung auscultation (a digital stethoscope). The primary outcome is treatment failure, and the size is 2,500; it is recruiting.

Antibiotic resistance is a global challenge sometimes called a silent pandemic, rooted in antibiotic overuse. What matters here is reducing use not merely, but safely, without missing the children who truly need treatment. Setting treatment failure as the primary outcome reflects a commitment to confirming that safety head-on.

If a low-cost digital stethoscope plus AI can lift diagnosis even in villages short of specialists, it could benefit global public health. That said, this study evaluates usefulness by treatment failure and the like; it does not establish the effectiveness of AI auscultation.