Diabetic Retinopathy
Conditions
Brief summary
All OCTA data and biochemical indexes of diabetic patients were acquired. A prediction model of diabetic retinopathy was built, and the random forest method was used to identify sensitive indicators.
Detailed description
Diabetic patients at the Department of Ophthalmology of the Seventh Affiliated Hospital of Sun Yat-sen University were selected as research participants. All OCTA data and biochemical indexes were acquired. A prediction model of diabetic retinopathy was built, and the random forest method was used to identify sensitive indicators.
Interventions
DIAGNOSTIC_TESTimaging
imaging
Sponsors
Mingzhe Cao
Study design
Observational model
CASE_CONTROL
Time perspective
CROSS_SECTIONAL
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* Clinical diagnosis of diabetes
Exclusion criteria
* various other types of retinal and choroidal disease; * history of any intraocular surgery or treatment (including intravitreal injection, retinal photocoagulation etc. * with severe refractive medium opacity that could affect fundus examination.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| fasting blood glucose (FBG) | the time of the patient's first 1 day visit | biochemical indexes |
| glycosylated hemoglobin (HbAlc) | the time of the patient's first 1 day visit | biochemical indexes |
| OCTA data | the time of the patient's first 1 day visit | An image of the 3mm×3mm and 6 mm×6 mm macular areas detected by OCTA were captured. Quantitative analysis of vascular density and perfusion density of superficial capillary plexus in the macular area were automatically calculated using built-in software on the device. |
Countries
China
Contacts
Primary ContactMingzhe Cao, Dr.
Outcome results
None listed