Clinical trial NCT06552247: Glaucoma Algorithm Validation Study in African Population - the MAGIC Study
Official title: Validation Study of an Artificial Algorithm for Glaucoma Detection in an African Population
Study type: INTERVENTIONAL
Overall status: NOT_YET_RECRUITING
Phase: NA
Conditions: Glaucoma
Diabetic Retinopathy
Keywords: Artificial Intelligence
Validation
Screening
Lead sponsor: Centro Hospitalar Universitário Lisboa Norte
Sponsor class: OTHER
Collaborators: name: Dr. Agarwal's Eye Hospital
First posted: 2024-08-13
Enrollment: 100
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Allocation: NA
Intervention model: SINGLE_GROUP
Intervention model description: Single arm. Consecutive patients in a general ophthalmology consultation will be offered intervention
Primary purpose: DIAGNOSTIC

Brief summary: Artificial Intelligence (AI) algorithms require validation in a variety of populations to ensure widespread clinical applicability. In Ophthalmology, AI algorithms are reaching maturity in diagnosis such as diabetic retinopathy and glaucoma. Higher-at-risk subjects of African descent are nevertheless usually under-represented in training datasets and therefore unclear about representativity.

A small scale validation study in consecutive patients in a large Eyesore unit in Mozambique will be performed to determine the diagnostic ability of these AI softwares in this population

Detailed description: Artificial Intelligence (AI) algorithm's are the next frontier in medical management, usually meant to improve diagnostic capabilities and to optimize the existing resources. They are particularly relevant in settings where there is a lack of specialised Human Resources such as physicians.

Ensuring these algorithms can be used in a wide population is therefore crucial to clinical implementation. Validation studies in specific segments of populations are needed to ensure all patients are represented and the results are therefore reliable. Higher-at-risk subjects of African descent are nevertheless usually under-represented in training datasets and therefore unclear about representativity.

A pilot study for validation of an AI algorithm for Glaucoma and Diabetic Retinopathy will be done for the MONA G-RISK® and diabetic retinopathy. Consecutive patients from a large Eye Unit in Mozambique's capital will be screened using these AI algorithms and validated using clinical standard as ground truth.

Eligibility criteria: Inclusion Criteria:

* subjects age above 18 years old presenting at the Eye Unit
* willingness to sign an informed consent for the screening process

Exclusion Criteria:

* none
* Poor quality in screening image will be included in the intention to treat analysis, but excluded from the diagnostic comparator outcome.
* Patients with a known glaucoma diagnosis will not be excluded from the screening

Primary outcomes:
measure: Diagnostic agreement between referring decision and reading center decision
timeFrame: Duration of the study - 3 weeks
Secondary outcomes:
measure: Level of agreement (in %) between AI-risk score and human-based assessment of disease severity
timeFrame: After the study - 6 months
Other outcomes:
Locations:
Study officials:
affiliation: ULS Santa Maria
name: Joana Ferreira, MD, PhD
role: STUDY_DIRECTOR
affiliation: Dr. Agarwal Eye Hospital
name: Amelia Buque, MD
role: STUDY_DIRECTOR
References: