Predicting Diabetic Retinopathy From Risk Factor Data and Digital Retinal Images

Sponsor
Charles Drew University of Medicine and Science (Other)
Overall Status
Completed
CT.gov ID
NCT03694145
Collaborator
National Library of Medicine (NLM) (NIH), Los Angeles County Department of Public Health (Other), University of California, Los Angeles (Other)
300
3
31.4
100
3.2

Study Details

Study Description

Brief Summary

The objective of this study is to compare the results of a deep learning approach to diabetic retinopathy assessment with results from (1) an in-person examination with an ophthalmologist, and (2) the assessments of optometrists involved in a teleretinal screening program.

Condition or Disease Intervention/Treatment Phase
  • Other: In-Person Eye Examination

Detailed Description

This study represents the third aim of a grant with five aims. The study will compare and evaluate the predictive accuracy of: (a) machine learning models developed to grade diabetic retinopathy and assess the presence or absence of diabetic macular edema and (b) the assessments of optometrist readers, both from digital retinal images, against standard of care dilated retinal examinations by board-certified ophthalmologists and/or retinal-specialty fellows for 300 diabetic patients utilizing a Los Angeles County reading center.

For the study, the investigators will recruit 300-500 eligible diabetic patients for in-person eye examinations performed by board certified ophthalmologists and/or retinal-specialty fellows at Los Angeles County reading centers. The study will take place over the course of two visits: a teleretinal screening and an in-person eye examination.

The in-person dilated eye examinations that the study participants will participate in and be compensated for follow the usual standard of care that patients receive in a setting that does not utilize teleretinal screening. Yearly dilated eye examinations are standard of care for all persons with diabetes.

Study Design

Study Type:
Observational
Actual Enrollment :
300 participants
Observational Model:
Other
Time Perspective:
Prospective
Official Title:
Predicting Diabetic Retinopathy From Risk Factor Data and Digital Retinal Images
Actual Study Start Date :
Oct 25, 2018
Actual Primary Completion Date :
Jun 8, 2021
Actual Study Completion Date :
Jun 8, 2021

Arms and Interventions

Arm Intervention/Treatment
Diabetic patients w. risk of retinopathy

The 300-500 patients to be enrolled for the study are diabetic patients normally seen by the Los Angeles County Department of Health Services (LACDHS) Teleretinal Diabetic Retinopathy Screening Program and Reading Center. In addition to receiving their recommended LACDHS annual teleretinal screening, for the study, participants will receive an additional in-person eye examination.

Other: In-Person Eye Examination
Dilated in-person eye examination by a board-certified ophthalmologist or retinal fellow.

Outcome Measures

Primary Outcome Measures

  1. Proportion of patients accurately diagnosed with retinopathy [9/2021]

    Proportion of patients accurately diagnosed with retinopathy using machine learning versus proportion accurately diagnosed by teleretinal screening optometrists with in-person eye examinations by ophthalmologists used as a gold standard.

Eligibility Criteria

Criteria

Ages Eligible for Study:
18 Years and Older
Sexes Eligible for Study:
All
Accepts Healthy Volunteers:
No
Inclusion Criteria:
  • Patients diagnosed with Type I or Type II Diabetes

  • Patients who are over the age of 18 years

  • Patients who have not previously been seen in the current year by the LACDHS Teleretinal Diabetic Retinopathy Screening Program and Reading Center

  • Patients whose teleretinal screening exam images yield readable results

Exclusion Criteria:
  • Patients under the age of 18 years

  • Patients with gestational diabetes

  • Patients who have previously been seen in the current year by LACDHS's Teleretinal Diabetic Retinopathy Screening Program and Reading Center

  • Patients whose teleretinal screening exam images do not yield readable results, as gradable images are needed for later comparison against ophthalmologist reads.

  • Previously eligible patients who do not return for an in-person eye exam within 3 months of receiving a teleretinal screening (In order for the results of the teleretinal screening and in-person eye examinations to yield similar information, patients who do not return for their in-person eye exam within 3 months of their teleretinal screening will not be able to remain in the study. This is because significant eye changes not documented by the teleretinal screening may occur after a 3-month period).

Contacts and Locations

Locations

Site City State Country Postal Code
1 Los Angeles Department of Public Health Los Angeles California United States 90012
2 University of California - Los Angeles Los Angeles California United States 90024
3 Charles R. Drew University of Medicine and Science Los Angeles California United States 90059

Sponsors and Collaborators

  • Charles Drew University of Medicine and Science
  • National Library of Medicine (NLM)
  • Los Angeles County Department of Public Health
  • University of California, Los Angeles

Investigators

  • Principal Investigator: Omolola Ogunyemi, PhD, Charles Drew University of Medicine and Science

Study Documents (Full-Text)

None provided.

More Information

Publications

None provided.
Responsible Party:
Charles Drew University of Medicine and Science
ClinicalTrials.gov Identifier:
NCT03694145
Other Study ID Numbers:
  • 1218589-3
  • R01LM012309
First Posted:
Oct 3, 2018
Last Update Posted:
Jun 29, 2021
Last Verified:
Jun 1, 2021
Individual Participant Data (IPD) Sharing Statement:
No
Plan to Share IPD:
No
Studies a U.S. FDA-regulated Drug Product:
No
Studies a U.S. FDA-regulated Device Product:
No
Additional relevant MeSH terms:

Study Results

No Results Posted as of Jun 29, 2021