Antibiotics are a mainstay of the treatment of lower respiratory infections in young children even though most episodes are caused by self-limiting viruses. Innovative child friendly tools that improve the diagnosis of respiratory illnesses, safely reduce the unnecessary use of antibiotics, and are suitable for implementation in resource-constrained settings are urgently required to safely improve antibiotic stewardship and stem the rising rates of antibiotic resistance globally. In the Bangladesh Lung Auscultation Artificial Intelligence for Antibiotic Stewardship Trial (BLAAAST) the investigators aim to determine whether treatment failure frequency among children in rural Bangladesh managed by clinical guidelines enhanced by a commercially available, artificial intelligence (AI)-enabled digital stethoscope is non-inferior to guidelines alone. The investigators hypothesize treatment failure frequency among 'enhanced IMCI' participants will be no worse than standard care by a +/-2% margin, safely reducing antibiotic use by 50-60%. The investigators will also evaluate if a diagnostic strategy enhanced by an AI-enabled digital stethoscope is a sustainable alternative to standard care for children in rural Bangladesh. The investigators hypothesize that care augmented by an AI-enabled digital stethoscope will have additional benefits via reduced antibiotic use that will outweigh digital auscultation costs resulting in cost-effectiveness compared to current practice. BLAAAST affords a unique opportunity to evaluate the efficacy of clinical guidelines enhanced by an AI-enabled digital stethoscope on child pneumonia outcomes in Bangladesh, if digital auscultation may be instrumental in the wider antibiotic stewardship strategy, and whether a digital stethoscope diagnostic tool is cost-effective in the care of children with respiratory illnesses.
Age range
2 Months – 59 Months
Sex
ALL
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Treatment failure
Timeframe: 7 days