Standard Clinical Ear Exam
Diagnostic TestThe clinician will examine the child's ear with a standard otoscope and give a clinical diagnosis and decision to treat with antibiotics.
NCT Number: NCT06876259
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.
Interested in participating?
Request Info6 month–24 month
All sexes
Interventional
Not applicable
Children's Community Pediatrics Brentwood, Pittsburgh, Pennsylvania, United States
Participants and Setting This will be a 12-month, within-subject design, single center study of 300 children 6 to 24 months of age presenting to their primary care providers at Children's Community Pediatrics offices with upper respiratory symptoms. Exclusion criteria are children with tympanostomy tubes or purulent otorrhea, absence of upper respiratory symptoms, or who are currently taking antimicrobials.
Design and Outcomes
Using a double blind, within-subject design, each child's ear will be assessed by the AI app and a standard clinical exam. The primary outcome measure will be antimicrobial prescription rates derived from 150 paired images that each have an AI app and clinician diagnosis. We will secondarily assess acute otitis media (AOM) diagnosis rates. If the AI app diagnoses AOM it will always prescribe an antimicrobial. Secondary outcomes are described below:
Sample Size Calculation Using paired observations (AI app vs clinician antimicrobial prescription recommendations), an estimated 300 children 6 to 24 months of age presenting to primary care practices with upper respiratory symptoms will need to be enrolled to derive 150 paired interpretable images to detect a 10% difference in AOM diagnosis and subsequent antimicrobial prescription rates between the AI app and clinicians, assuming a power of 80% and two-sided p-value <0.05. This assumes 15% of children in the target population will truly have AOM, and clinicians will diagnose and treat AOM at a 10% higher rate (25%) compared to the AI app. If clinicians reconcile and follow the app diagnosis and treatment recommendations, this will equate to a 40% reduced/avoidable antimicrobial prescription rate. This estimate accounts for two ears per child and estimates 50% of images will be uninterpretable by the app, and 50% of clinician exams will not result in a diagnosis.
Statistical analysis All analyses will be conducted by a statistician in the General Academic Pediatrics Division, Department of Pediatrics.
The primary outcome of antimicrobial prescription rates will be assessed by the McNemar's Test. Differences in secondary outcomes will be assessed by generalized estimating equation (symptom score) and chi square test (antimicrobial side effects and recurrent AOM).
Descriptive outcomes (uninterpretable images, clinician ability to make a diagnosis, AOM diagnosis, antimicrobial prescriptions) will be reported as rates (%).
Study Procedures:
Screening: Office schedules will be screened to identify children in the eligible age group who are presenting with upper respiratory symptoms.
Consent: Once age-eligible children have checked in to the office their parents will be approached by research personnel to assess their interest in the study and eligibility. Informed consent will be obtained after rooming.
Study Procedures:
The duration of the study procedures, not including standard clinical care, will be about 10 minutes. After consent, each participating child will have two ear exams.
Data will be recorded in an electronic database.
Demographic Information:
Research staff will obtain demographic information after the study procedures (duration: 60 seconds).
Follow-up:
All participants will be followed for 10 days to assess symptom resolution and side effects of antimicrobial use. AOM symptoms will be monitored daily for 10 days using a validated symptom scale entered once every evening (duration: 60 seconds), whether on antimicrobial therapy or not, by parents in electronic diaries which have used by our team in many other studies. If any participant increases their symptoms score by >20% at any time, they will be contacted and offered a visit. Rates of protocol-defined diarrhea and diaper rash which are the most common side effects of antimicrobial use in this age group will also be assessed. Finally, AOM recurrences will be monitored by reviewing the electronic medical record for 3 months following enrollment.
Duration:
Healthy volunteers accepted: No
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Exclusion criteria
The clinician will examine the child's ear with a standard otoscope and give a clinical diagnosis and decision to treat with antibiotics.
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
Time frame: Day 1
The rate of antimicrobial prescriptions will be compared between standard care and AI app groups.
Time frame: Day 1
The rate of diagnosis of acute otitis media will be compared between standard clinical examination and the AI app
Time frame: Day 1
The rate of AI app and clinician interpretable images among enrolled participants
Time frame: From enrollment to 11 days after enrollment
A validated and reliable 10-item scale for measuring AOM symptom burden. Responses for each item are scored 0-5 and the total score minimum is 0 and maximum is 50. Higher values represent more severe symptoms.
Time frame: From enrollment to 3 months from enrollment
All participants with paired clinician and AI app images in the same ear will be followed for 3 months to assess recurrences of AOM. This will be determined from diagnostic codes entered into the electronic medical record. A new AOM diagnosis must be at least 14 days after the previous diagnosis. AOM recurrences will be expressed as total counts among participants and total counts among ears.
Contact information is provided by the study sponsor or research team.
Nader Shaikh, MD, MPH
CONTACT
Timothy R Shope, MD, MPH
CONTACT
Timothy Shope
Other
Intelligent Medical Assessment for Guiding Ear Infection Treatment
Acronym: IMAGE
OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.
View the official ClinicalTrials.gov record (opens in a new tab)This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.
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