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

Phases

Unknown

Study type

Observational

Source

ClinicalTrials.gov

Registry ID

NCT03769948

Enrollment

500

Registered

2018-12-10

Start date

2022-02-28

Completion date

2023-07-31

Last updated

2020-09-18

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Diabetic Retinopathy

Brief 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.

Interventions

OTHERrisk 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

Study design

Observational model

COHORT

Time perspective

RETROSPECTIVE

Eligibility

Sex/Gender

ALL

Inclusion criteria

For diabetic patients with DR: * With 250.xx diabetes and 362.0x DR ICD-9 codes * All variables are complete within the observation window For diabetic patients without DR: * With 250.xx diabetes ICD-9 codes * Without 362.0x DR ICD-9 codes * All variables are complete within the observation window

Design outcomes

Primary

Measure	Time frame	Description
Diabetic retinopathy indicator (yes/no)	March, 2019	Diabetic patients with 362.0x ICD-9 codes are classified as DR patient

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026