Intelligent Medical Assessment for Guiding Ear Infection Treatment in Young Children With Upper Respiratory Symptoms

What this Trial Is About

Researchers are evaluating the use of an artificial intelligence (AI) app to improve the diagnosis and treatment of ear infections in young children aged 6 to 24 months who have cold symptoms. Ear infections can be hard to diagnose accurately in this age group due to small ear canals and limited examination time. The study aims to see how the AI app affects clinical decisions about ear infections and antibiotic use compared to standard clinical exams. The study involves 300 children who will have their ears examined both with the AI app using a smartphone-attached otoscope and by a clinician using a standard otoscope. Each child will receive two ear exams during a single visit. The AI app records and analyzes images to provide a diagnosis and treatment recommendation, which is compared to the clinician's diagnosis. Clinicians will then review the AI app's findings before making a final treatment decision. The study uses a within-subject design where each child's ears are assessed by both methods to compare antimicrobial prescription rates and diagnosis accuracy. Participants will be monitored for 10 days after enrollment to track symptom changes and any side effects from antibiotic use, such as diarrhea or diaper rash. Parents will enter daily symptom scores in electronic diaries. Medical records will be reviewed for three months to identify any recurrences of ear infections. The primary outcome is the rate of antimicrobial prescriptions on the day of diagnosis. Secondary outcomes include diagnostic rates, image quality, symptom severity scores, and infection recurrences. The total study participation involves one visit for exams and follow-up symptom tracking and record review.

Artificial Intelligence Diagnostic Decision Support to Reduce Antimicrobial Prescriptions in Young Children With Colds