NCT03769948

Clinical Decision Support Algorithm to Predict Diabetic Retinopathy

Validating a Clinical Decision Support Algorithm Developed With Demographic, Co-morbidity, and Lab Data to Diagnose, Stage, Prevent, and Monitor a Patient's Diabetic Retinopathy

• Status: Unknown
• Phase: —
• Study type: Observational
• Enrollment: 500 (estimated)
• Sponsor: Oklahoma State University Center for Health Sciences · Academic / Other
• Sex: All
• Age: —
• Healthy volunteers: —

Summary

Diabetic retinopathy (DR), a complication of diabetes, is a leading cause of blindness among working-aged adults globally. In its early stages, DR is symptomless, and can only be detected by an annual eye exam. Once the disease has progressed to the point where vision loss has occurred, the damage is irreversible. Consequently, early detection is quintessential in treating DR. Two barriers to early detection are poor patient compliance with the annual exam and lack of access to specialists in rural areas. This research is focused on developing and validating new, cost-effective predictive technologies that can improve early screening of DR. Our overall objective is to develop and implement an entire suite of tools to detect diabetes complications in order to augment care for underserved rural populations in the US and internationally.

Conditions

• Diabetic Retinopathy

Interventions

Type	Name	Description
OTHER	risk factors for diabetic retinopathy	Demographic variables: gender, race, marital status, urban rural status. Co-morbidity variable: neuropathy, nephropathy, peripheral circulatory, ketoacidosis, hyperosmolarity Lab tests variables: alanine aminotransferase (ALT), albumin serum, anion gap, aspartate aminotransferase, blood urea nitrogen, calcium serum, chloride serum, creatinine serum, glucose serum plasma, hematocrit, hemoglobin, mean corpuscular hemoglobin concentration (MCHC), mean platelet volume (MPV), potassium serum, protein total serum, red blood cell (RBC) count, sodium serum, white blood cell (WBC) count

Timeline

• Start date: 2022-02-01
• Primary completion: 2022-08-01
• Completion: 2023-07-01
• First posted: 2018-12-10
• Last updated: 2020-09-18