None listed
Conditions
Interventions
Intervention1: NIL: NIL
Intervention2: Nil: Nil
Sponsors
Translational AI for Networked Universal Healthcare
Eligibility
Inclusion criteria
Inclusion criteria: Participants fulfilling all the following will be eligible. Adults aged older than or equal to 18 years. Patients awaiting general medicine consultations as part of routine outpatient care or initial clinical assessment. Ability to understand the study information shared and provide written informed consent. Willingness to permit use of anonymized fundus images and limited clinical data for research Individuals with known or suspected risk factors for retinal or optic nerve disease, including but not limited to: Cardio vascular disease, Type 2 Diabetes, Chronic kidney disease, Liver disease. Ability to cooperate with non-invasive retinal fundus image acquisition.
Exclusion criteria
Exclusion criteria: Participants meeting any of the following will be excluded:Inability or unwillingness to provide written informed consent. Active ocular or periocular infection or inflammation interfering with safe imaging. Recent intraocular or periocular surgery, intravitreal injection, or retinal laser procedure, as judged by the investigator. Conditions preventing acquisition of gradable ophthalmic images. Any medical or ocular condition rendering participation unsafe or impractical Concurrent enrolment in another interventional ophthalmic study that may affect data interpretation.
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| Statistical association between imaging-derived microvascular features and systemic physiological and laboratory parameters for detection of cardiovascular disease, type 2 diabetes, chronic kidney disease and liver disease using retinal and conjunctival imaging biomarkers. Statistical association between ophthalmic microvascular parameters , systemic physiological and laboratory variables. Strength and significance of correlations across predefined biomarker categories relevant to systemic disease risk.Timepoint: 1 year | — |
Secondary
| Measure | Time frame |
|---|---|
| Development of continuous imaging-derived risk metrics and evaluation of their distribution across systemic parameter ranges. Establishment of normative reference ranges for retinal and conjunctival vascular parameters. Reproducibility of imaging measurements and inter operator variability across participating centres. Dataset diversity in terms of geography, ethnicity, disease spectrum and imaging conditions and its impact on model generalisability. Development and evaluation of referral prioritisation frameworks based on imaging and inferred risk profilesTimepoint: 6 months after benchmarking | — |
Countries
India
Contacts
Public ContactBhaskara Rao Chintada
TANUH AI Center of Excellence in Healthcare
Outcome results
None listed