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Clinical Decision Support Algorithm to Predict Diabetic Retinopathy

The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been evaluated by the U.S. Federal Government. Know the risks and potential benefits of clinical studies and talk to your health care provider before participating. Read our disclaimer for details.
 
ClinicalTrials.gov Identifier: NCT03769948
Recruitment Status : Not yet recruiting
First Posted : December 10, 2018
Last Update Posted : September 18, 2020
Sponsor:
Collaborators:
Oklahoma State University
University of Oklahoma
Information provided by (Responsible Party):
William Paiva, Oklahoma State University

Tracking Information
First Submitted Date December 6, 2018
First Posted Date December 10, 2018
Last Update Posted Date September 18, 2020
Estimated Study Start Date February 2022
Estimated Primary Completion Date August 2022   (Final data collection date for primary outcome measure)
Current Primary Outcome Measures
 (submitted: December 6, 2018)
Diabetic retinopathy indicator (yes/no) [ Time Frame: March, 2019 ]
Diabetic patients with 362.0x ICD-9 codes are classified as DR patient
Original Primary Outcome Measures Same as current
Change History
Current Secondary Outcome Measures Not Provided
Original Secondary Outcome Measures Not Provided
Current Other Pre-specified Outcome Measures Not Provided
Original Other Pre-specified Outcome Measures Not Provided
 
Descriptive Information
Brief Title Clinical Decision Support Algorithm to Predict Diabetic Retinopathy
Official Title 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
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.
Detailed Description Not Provided
Study Type Observational
Study Design Observational Model: Cohort
Time Perspective: Retrospective
Target Follow-Up Duration Not Provided
Biospecimen Not Provided
Sampling Method Probability Sample
Study Population The cohort will be selected from diabetic patients that have Electronic Medical Records in Harold Hamm Diabetes Center.
Condition Diabetic Retinopathy
Intervention 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
Study Groups/Cohorts Not Provided
Publications * Not Provided

*   Includes publications given by the data provider as well as publications identified by ClinicalTrials.gov Identifier (NCT Number) in Medline.
 
Recruitment Information
Recruitment Status Not yet recruiting
Estimated Enrollment
 (submitted: December 6, 2018)
500
Original Estimated Enrollment Same as current
Estimated Study Completion Date July 2023
Estimated Primary Completion Date August 2022   (Final data collection date for primary outcome measure)
Eligibility Criteria

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
Sex/Gender
Sexes Eligible for Study: All
Ages Child, Adult, Older Adult
Accepts Healthy Volunteers Not Provided
Contacts
Listed Location Countries Not Provided
Removed Location Countries  
 
Administrative Information
NCT Number NCT03769948
Other Study ID Numbers HR-18-087
Has Data Monitoring Committee Not Provided
U.S. FDA-regulated Product
Studies a U.S. FDA-regulated Drug Product: No
Studies a U.S. FDA-regulated Device Product: No
IPD Sharing Statement Not Provided
Responsible Party William Paiva, Oklahoma State University
Study Sponsor Oklahoma State University Center for Health Sciences
Collaborators
  • Oklahoma State University
  • University of Oklahoma
Investigators Not Provided
PRS Account Oklahoma State University Center for Health Sciences
Verification Date September 2020