Weiwei Zheng1. 1. Department of Emergency, Peking University People's Hospital, 11 Xizhimen South Street, Beijing 100044, China. mm25.52mm@163.com
Abstract
OBJECTIVE: To investigate factors related to diabetic retinopathy (DR). METHOD: Clinical data of 603 Chinese diabetic patients were analyzed retrospectively. On the basis of its severity, DR was graded as non-diabetic retinopathy (NDR), non proliferative diabetic retinopathy (NPDR) and proliferative diabetic retinopathy (PDR). Factor analysis was conducted and factor scores were used as independent variables in both Logistic and Ordinal regression models to identify the predictors of the development and/or progression of DR. RESULT: After factor analysis, 21 original variables were finally reduced to eight unique factors, representing obesity, glycemic, C peptide, lipids, time, renal, blood pressure and metabolic factors. Logistic regression revealed that female (OR = 2.208, 95%CI 1.328-3.671), comorbidity of peripheral atherosclerosis (PA) (OR = 2.690, 95%CI 1.000-7.238), time factor (OR = 1.838, 95%CI 1.421-2.377) and renal factor (OR = 2.444, 95%CI 1.757-3.400) were positively associated with DR, while C peptide factor (OR = 0.469, 95%CI 0.365-0.604) was negatively associated with DR. Besides another negatively related obesity factor (OR = 0.777), Ordinal regression revealed similarly related factors, but ruled out the influence of gender and PA. CONCLUSION: Female, macrovascular complications, time and renal factors are predictors of DR, while C peptide factor is negatively associated with the development and/or progression of DR.
OBJECTIVE: To investigate factors related to diabetic retinopathy (DR). METHOD: Clinical data of 603 Chinese diabeticpatients were analyzed retrospectively. On the basis of its severity, DR was graded as non-diabetic retinopathy (NDR), non proliferative diabetic retinopathy (NPDR) and proliferative diabetic retinopathy (PDR). Factor analysis was conducted and factor scores were used as independent variables in both Logistic and Ordinal regression models to identify the predictors of the development and/or progression of DR. RESULT: After factor analysis, 21 original variables were finally reduced to eight unique factors, representing obesity, glycemic, C peptide, lipids, time, renal, blood pressure and metabolic factors. Logistic regression revealed that female (OR = 2.208, 95%CI 1.328-3.671), comorbidity of peripheral atherosclerosis (PA) (OR = 2.690, 95%CI 1.000-7.238), time factor (OR = 1.838, 95%CI 1.421-2.377) and renal factor (OR = 2.444, 95%CI 1.757-3.400) were positively associated with DR, while C peptide factor (OR = 0.469, 95%CI 0.365-0.604) was negatively associated with DR. Besides another negatively related obesity factor (OR = 0.777), Ordinal regression revealed similarly related factors, but ruled out the influence of gender and PA. CONCLUSION: Female, macrovascular complications, time and renal factors are predictors of DR, while C peptide factor is negatively associated with the development and/or progression of DR.