Predictors Associated with Type 2 Diabetes Mellitus Complications over Time: A Literature Review

Abstract

Early detection of type 2 diabetes mellitus (T2DM) complications is essential to prevent disability and death. Risk prediction models are tools to estimate the probability that an individual with specific risk factors will develop a future condition within a certain time period. A predictive model that incorporates time to quantify the risk of T2DM complications such as cardiovascular diseases (CVD) event is still lacking. Well-established and validated predictive models of T2DM complications are vital to stratify patients based on their risks; thus, individualization therapy could be optimized. New approaches (e.g., the parametric approach) are needed in developing predictive models of T2DM complications by incorporating new and time-varying predictors that may improve the existing models’ predictive ability. This review aimed (1) to summarize the reported predictors for the five main complications of T2DM, which include cardiovascular diseases, ischemic stroke, diabetic nephropathy, diabetic neuropathy, and diabetic retinopathy, and (2) to highlight the persistent need for future risk score models as screening tools for the early prevention of T2DM complications.