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Recruiting
NCT06876259
Artificial Intelligence Diagnostic Decision Support to Reduce Antimicrobial Prescriptions in Young Children With Colds
Conditions: Acute Otitis Media (AOM), Upper Respiratory Infection
Sex: All
Ages: 6 Months – 24 Months
Healthy volunteers: No
Phase: NA
Enrollment: 300
Sponsor: Timothy Shope
Location: Children's Community Pediatrics Brentwood Pittsburgh Pennsylvania
Summary
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.
Eligibility Criteria
Inclusion Criteria:
* Age 6-24 months
* Presence of upper respiratory infection
Exclusion Criteria:
* No upper respiratory infection
* Otorrhea
* Tympanostomy tubes
* Currently taking antimicrobials
Source: ClinicalTrials.gov (NCT06876259). StuddyBuddy aggregates publicly available trial information.