Some Prediction Models in the Study of Diabetic Retinopathy among known Type II Diabetes Mellitus Patients in a Southern Part of India: Various Statistical Models Approach

Abstract

Background: Diabetic Mellitus is a chronic disease and metabolic disorder. DM affects about 180 million people in the presently and it is a public health problem in worldwide. To find out the risk factors and how much its influence, to identify the risk factors that influencing, to identify the presence of DR and its progression by forming mathematical equations using which was found possible with some variables and to find several stages of DR and its progression. Methods: In this study, adult population (age ≥ 18) only was taken into account for data analysis. Some structured questionnaires were used for data collection. We have done some hospital based retrospective studies among known T2DM patients. The continuous variables were expressed as mean and standard deviation and categorial variables as frequency and proportions. We have used, various prediction statistical models. Results: By multiple regression analysis, found the influencing factors in the progression of DR, predicted the probability of a T2DM patient to develop DR and found the probability of DR among diabetes up to a given period of time and using by Markov Chain Analysis found the TPM and the absorbing state in a T2DM patient and to identify as having complete vision loss. Conclusions: Statistical models were revealed that found the influenced factors and risk ratio has been computed, Number of years of DM, and progression and transition of DR which predict the chance to develop DR in a known T2DM patient. Key Words: diabetic retinopathy, duration of diabetes, hypertension, family history, various multiple logistic regression models, risk ratio