Recruiting

AI App

Sponsor:

Timothy Shope

Code:

NCT06876259

Conditions

Acute Otitis Media (AOM)

Upper Respiratory Infection

Eligibility Criteria

Sex: All

Age: 0 - 2

Healthy Volunteers: Not accepted

Interventions

Standard Clinical Ear Exam

AI app ear exam and diagnosis

Study Details

Brief 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.

Conditions

Acute Otitis Media (AOM)

Upper Respiratory Infection

Study ID

NCT06876259

Start date

Dec 4, 2025

Status verified date

Sep, 2025

Completion date

Jul 1, 2027

Anticipated

Primary completion date

Dec 30, 2026

Anticipated

Eligibility Criteria

Eligibility Criteria

Sex: All

Age: 0 - 2

Healthy Volunteers: Not accepted

Inclusion Criteria:

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

Exclusion Criteria:

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

Study Design

Enrollment

300 participants

Anticipated

Intervention Model

Single group

Primary purpose

Diagnostic

Interventions and Outcome Measures

Arms

experimental: AI App + Standard of care clinical exam

Using a within subject design, each child's ear will be in the experimental and standard care group. Each ear will be examined by the AI app and a clinician (blinded to the AI app diagnosis) to provide a diagnosis and treatment recommendation.

Interventions

Standard Clinical Ear Exam

The clinician will examine the child's ear with a standard otoscope and give a clinical diagnosis and decision to treat with antibiotics.

AI app ear exam and diagnosis

Using a standard otoscope with a cell phone mounted to it, research personnel will record a video image of the tympanic membrane and send it to the cloud for analysis using AI enhanced classification software to render a diagnosis and treatment recommendation

Primary outcome measure

  • Antimicrobial prescription rate [ Time Frame: Day 1 ]

Central Contacts and Locations

Central contacts

Timothy R Shope, MD, MPH

412-692-5471timothy.shope@chp.edu

Nader Shaikh, MD, MPH

412-996-2653nader.shaikh@chp.edu

Locations

Children's Community Pediatrics Brentwood

Recruiting

Pittsburgh, Pennsylvania, United States, 15227

Contacts

Patrick Tate, MD

412-443-7980patrick.tate1@chp.edu

Children's Community Pediatrics Castle Shannon

Recruiting

Pittsburgh, Pennsylvania, United States, 15234

Contacts

Marc Yester, MD

336-251-8024yesterma@upmc.edu

More Information

Sponsor

Timothy Shope

Last update posted

Jan 7, 2026

Last verified

Sep, 2025

Keywords

  • acute otitis media
  • diagnosis
  • artificial intelligence
  • diagnostic classifier
  • antimicrobial stewardship

Trial information was received from ClinicalTrials.gov and was last updated on 2026-09-10. This information was provided to ClinicalTrials.gov by Timothy Shope on 2026-01-07.