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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

Interested in this study? View the official listing for contact and enrollment details.

View on ClinicalTrials.gov

Source: ClinicalTrials.gov (NCT06876259). StuddyBuddy aggregates publicly available trial information.