Objective To expolre the factors which affect the size of diabetic,macular fobeal avascss scular zone(FAZ). Methods Making ten years of duration of diabetes a limit,79 nonproliferative and early proliferative diabetic patients were divided into 2 groups.Diabetic retinopathy severity level was diveided into 4 stages,and the macular edema was subdivided into focal、diffuse and cystoid according to fluorescein leakage of foveomacular region.All patients were measured FAZ with Heidelberg scanning laser fluoresceion angiography system and then compaired the size of FAZ of patients with different duration of diabetes、diabetic retinopathy severity level and macular edema status.The results were performed analysis of variance and t test. ResultsThe study shown the size of FAZ was not directly related to the duration of diabetes(t=1.3854,Pgt;0.1);There were significant differences about the size of FAZ of patients with different diabetic retinopathy severity level(F=7.6251,P＜0.01)and macular edema status(F=5.4369,P＜0.01)． Conclusion The size of FAZ was significantly increased in diabetic patients.It was enlarged with the development of diabetic retinopathy severity level,but it was not related to duration of diabetes. (Chin J Ocul Fundus Dis,2000,16:155-156)
Objective To investigate the early influences of laser photocoagulation on macular retinal thickness in diabetic retinopathy(DR). Methods Optic coherence tomography examination was performed in 30 eyes with DR(phase Ⅲ~Ⅳ) before, and on the 3rd day and the 7th day after photocoagulation respectively. The thickness of neuroretina and pigment epithelium were measured in the areas of fovea macula and 750 μm from fovea macula. Results Three days after photocoagulation, significant thickening of neuroretina was observed in the fovea macula, which is positively related with age, fasting blood sugar and duration of DR. There was no significant changes in the thickness of pigment epithelium in macula and in the thickness of neuroretina 750 μm from fovea macula. Conclusion Significant thickening of neuroretina in fovea macula in DR early after photocoagulation reveals progressed macular edema induced by photocoagulation which is positively related with age, fasting blood sugar and duration of DR. (Chin J Ocul Fundus Dis, 2002, 18: 31-33)
ObjectiveTo explore the morbidity rate and risk factors of proliferative diabetic retinopathy (PDR) in type 2 diabetes.MethodsThe clinical data of patients, with PDR in 2739 consecutive cases of type 2 diabetes diagnosed in this hospital from 1994 to 2001 were analyed retospectively. The diagnosis of diabetic retinopathy (DR) was confirmed by ophthalmoscopy and fundus fluorescein angiography (FFA). Blood pressure, fasting and postprandial blood sugar, glycosylated haemoglobin（HbA1c）, total serum cholesterol, triglyceride, creatinine, and albumin excretion rate were measured.ResultsThe morbidity rate of type 2 DR was 27.8%（761/2739）, and the morbidity rate of PDR was 4.2%（114/2 739） occupying 15% of the patients with DR. The duration, fasting blood sugar, glycosylated haemoglobin, blood pressure and albumin excretion rate were much higher than those in the control（P＜0.01, glycosylated haemoglobin P＜0.05）. The independent risk factors of PDR were duration of the disease （r=0.15, P＜0.01） and albumin excretion rate （r=0.08, P＜0.05）. The risk factors of PDR were albumin excretion rate and fasting blood sugar (r=0.13, P＜0.05) in patients with longer duration(≥5 years). The morbidity rate of PDR was 2.3%, 5.9% and 12.4% in patients with duration less than 5 years, 5 to 10 years and over 10 years groups, respectively. The morbidity of PDR of the patients in normal albuminuria, microalbuminuria and overt albuminuria group was 2.1%、5.3% and 18.8% respectively.ConclusionsType 2 diabetes accompanied with PDR is relative to the duration of the diabetes, albumin excretion rate, fasting blood sugar, blood pressure, and glycosylated haemoglobin, in which the duration of the disease, albuminuria and fasting blood sugar are the risk factors of occurance of PDR. (Chin J Ocul Fundus Dis, 2003,19:338-340)
Objective To determine the affected factors of intraorbital hemodynamic results in diabetic retinopathy (DR) and the risk factors related to the occurrence of DR. Methods Posterior ciliary artery (PCA), central retinal artery (CRA), central retinal vein (CRV), and vortex vein (VV) of 68 patients with DR were measured by color Doppler flow image (CDFI). Thirty-one hemodynamic parameters, including systolic velocity, diastolic velocity, mean velocity, resistive index, pulsatility index and accelerative velocity of ophthalmic artery (OA), and other variates (blood pressure, blood sugar, gender, age, duration of the disease, and so on) were collected and clustered in a principal components analys is following a forward, stepwise logistic regression on these components. Results Nine principal components were extracted from 37 original variates, reflecting the velocity of OA, velocity of PCA, resistance of OA, velocity of CRA,resistance of CRA, resistance of PCA, time-related factor, venous drainage factor and gender factor, respectively. In the result of logistic regression, resistance of OA, velocity of CRA, resistance of PCA, time-related factor, and venous drainage factor were the risk factors related to DR. Conclusion The first risk factor affecting DR is time, and intraorbital hemodynamic abnormity influencing the development of diabetic retinopathy may be the increase of resistance of OA, decrease of velocity of CRA, decrease of resistance of PCA, and increase of venous drainage. (Chin J Ocul Fundus Dis，2004，20：98-100)
Objective To investigate the early effects of intervention with tanakan on retinal function in diabetic retinopathy(DR) after laser photocoagulation. Methods Prospective random controlled study was performed on 60 Patients (60 eyes) from 23 to 69 years old with DR(phase Ⅲ～Ⅳ). The multifocal electroretinograms (MERG) were tested with VERIS Ⅳ before, the 3rd day and the 7th day after photocoagulation. Results No significant differences were found in the latencies and response densities of N1,P1 and N2 between the two groups before photocoagulation. Compared with that before photocoagulation, three days after photocoagulation the latencies in tanakan group had no significant change. The response densities of N1,P1 and N2 reduced and the changes were much smaller than that in control. Three days after photocoagulation, the response densities of P1 and N2 in the central macula 5°area were much higher and the latencies of P1 and N2 were significantly shorter than that in control group. There were no significant differences in the response densities in the 7th day and the differences in the latencies between two groups still existed. Conclusion Tanakan may be effective in preventing the retina from damage of retinal photocoagulation in some degree in DR. (Chin J Ocul Fundus Dis, 2002, 18: 208-211)
ObjectiveTo compare the consistency of artificial analysis and artificial intelligence analysis in the identification of fundus lesions in diabetic patients.MethodsA retrospective study. From May 2018 to May 2019, 1053 consecutive diabetic patients (2106 eyes) of the endocrinology department of the First Affiliated Hospital of Zhengzhou University were included in the study. Among them, 888 patients were males and 165 were females. They were 20-70 years old, with an average age of 53 years old. All patients were performed fundus imaging on diabetic Inspection by useing Japanese Kowa non-mydriatic fundus cameras. The artificial intelligence analysis of Shanggong's ophthalmology cloud network screening platform automatically detected diabetic retinopathy (DR) such as exudation, bleeding, and microaneurysms, and automatically classifies the image detection results according to the DR international staging standard. Manual analysis was performed by two attending physicians and reviewed by the chief physician to ensure the accuracy of manual analysis. When differences appeared between the analysis results of the two analysis methods, the manual analysis results shall be used as the standard. Consistency rate were calculated and compared. Consistency rate = (number of eyes with the same diagnosis result/total number of effective eyes collected) × 100%. Kappa consistency test was performed on the results of manual analysis and artificial intelligence analysis, 0.0≤κ＜0.2 was a very poor degree of consistency, 0.2≤κ＜0.4 meant poor consistency, 0.4≤κ＜0.6 meant medium consistency, and 0.6≤κ＜1.0 meant good consistency.ResultsAmong the 2106 eyes, 64 eyes were excluded that cannot be identified by artificial intelligence due to serious illness, 2042 eyes were finally included in the analysis. The results of artificial analysis and artificial intelligence analysis were completely consistent with 1835 eyes, accounting for 89.86%. There were differences in analysis of 207 eyes, accounting for 10.14%. The main differences between the two are as follows: (1) Artificial intelligence analysis points Bleeding, oozing, and manual analysis of 96 eyes (96/2042, 4.70%); (2) Artificial intelligence analysis of drusen, and manual analysis of 71 eyes (71/2042, 3.48%); (3) Artificial intelligence analyzes normal or vitreous degeneration, while manual analysis of punctate exudation or hemorrhage or microaneurysms in 40 eyes (40/2042, 1.95%). The diagnostic rates for non-DR were 23.2% and 20.2%, respectively. The diagnostic rates for non-DR were 76.8% and 79.8%, respectively. The accuracy of artificial intelligence interpretation is 87.8%. The results of the Kappa consistency test showed that the diagnostic results of manual analysis and artificial intelligence analysis were moderately consistent (κ=0.576, P＜0.01).ConclusionsManual analysis and artificial intelligence analysis showed moderate consistency in the diagnosis of fundus lesions in diabetic patients. The accuracy of artificial intelligence interpretation is 87.8%.