Clinical trial NCT04863391: Telemedicine in Age-Related Macular Degeneration
Official title: Pivotal Trial of an Automated AI-based System for Early Diagnosis and Prediction of Late Age Related Macular Degeneration in Primary Care Settings.
Study type: OBSERVATIONAL
Overall status: UNKNOWN
Conditions: Age Related Macular Degeneration
Lead sponsor: The New York Eye & Ear Infirmary
Sponsor class: OTHER
Collaborators: name: iHealthScreen Inc
First posted: 2021-04-28
Enrollment: 1000
Sex: ALL
Minimum age (years): 50
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Participants who fit the eligibility inclusion criteria and not the exclusion criteria.

Brief summary: This study seeks to evaluate a system for the automated early detection of Age-Related Macular Degeneration (AMD). AMD is a condition in which there is breakdown of the macula of the eye, the part of the retina that is responsible for sharp, central vision. We will take pictures of subjects' eyes using an automated camera. These photographs will be securely transmitted and and then analyzed by a computer program which has been developed in other studies. The outcome of the computer program analysis will be compared with human analysis of these same pictures. If the computer analysis is has good enough accuracy, then this computer system could be used for wide-scale screening for AMD.

Detailed description: iPredict,an AI and telemedicine based software which used individual's color fundus image for early diagnosis of AMD and predict if an individual is at risk of progression to late AMD. iPredict platform integrates the server-side programs (the image analysis and deep-learning modules for AMD severity screening and prediction) and local remote computer/mobile devices (for collecting patient data and images). DRS plus camera will be used in the doctor's office. The remote devices will upload images and data to the server to analyze and screen AMD automatically. The telemedicine platform has been developed for web-based platform. The automatic analysis will be performed on the server, and a report will be sent to the patient/remote devices with an individual's AMD stage as referable or non-referable AMD, and a risk prediction score of developing late AMD (within a minute), and further recommendations to visit a nearby ophthalmologist.

Eligibility criteria: Inclusion Criteria:

1. Subjects will be recruited if willing and able to comply with clinic visit and study-related procedures, and provide signed informed consent
2. Gender of Subjects: Both males and females will be invited to participate.
3. Age of Subjects: Patients will be over 50 years and older

Exclusion Criteria:

1. Unable to provide informed consent.
2. Other retinal degenerations and retinal vascular diseases such as diabetic retinopathy or macular edema, prior retinal surgery.

Primary outcomes:
measure: Sensitivity of identification of referable and non-referable AMD for early diagnosis of AMD
timeFrame: 2 years
measure: Specificity of identification of referable and non-referable AMD for early diagnosis of AMD using the iPredict's AI-based AMD screening software utilizing color fundus imaging.
timeFrame: 2 years
Secondary outcomes:
Other outcomes:
Locations:
city: New York
country: United States
facility: New York Eye and Ear Infirmary of Mount Sinai
state: New York
Study officials:
References: