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.
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.
Study Type
OBSERVATIONAL
Enrollment
200
imaging
The Seventh Affiliated Hospital, Sun Yat-sen University
Shenzhen, Guangdong, China
RECRUITINGfasting blood glucose (FBG)
biochemical indexes
Time frame: the time of the patient's first 1 day visit
glycosylated hemoglobin (HbAlc)
biochemical indexes
Time frame: the time of the patient's first 1 day visit
OCTA data
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.
Time frame: the time of the patient's first 1 day visit
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