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

Recruiting now · Not applicable

Conditions studied: Acute Otitis Media (AOM), Upper Respiratory Infection

In brief

Ear infections are common in young children with cold symptoms, but they can be difficult to diagnose due to small ear canals, child movement, and limited viewing time. In this study, investigators will take photos of the eardrums of children 6-24 months of age with upper respiratory symptoms. The photos will be reviewed by imaging software enhanced with artificial intelligence (AI app) to determine whether the AI app changes how ear infections are diagnosed and treated. The AI app has undergone rigorous study and was found to be highly accurate; but how using this technology affects the diagnosis and treatment by clinicians has not been studied. This research may help improve diagnostic accuracy for ear infections and ensure antibiotics are prescribed only for those children who have definite ear infections.

Key facts

Study ID

NCT06876259

Run by

Timothy Shope

People needed

300

Starts

2025-12-04

Expected to finish

2027-07-01

Last updated by the study team

2026-01-07

Who can join

Age: 1 and older, up to 2. Sex: any. Healthy volunteers: not accepted.

You may qualify if…

• Age 6-24 months
• Presence of upper respiratory infection

You may not qualify if…

• No upper respiratory infection
• Otorrhea
• Tympanostomy tubes
• Currently taking antimicrobials

Where it is running

• Children's Community Pediatrics Brentwood — Pittsburgh, Pennsylvania, United States (enrolling)
• Children's Community Pediatrics Castle Shannon — Pittsburgh, Pennsylvania, United States (enrolling)

Full record on ClinicalTrials.gov

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