Prediction factors and models for chronic kidney disease in type 2 diabetesmellitus: A review of the literature

Abstract

Diabetes mellitus (DM) has become a major chronic disease seriously affecting human health. Type 2 diabetes mellitus (T2DM) accounts for about 90% of DM patients, which is the largest type. Approximately 25–35% of T2DM patients develop kidney disease, which not only impacts the survival rate and quality of life but also, to the family and society, are of great economic burden. Early identification of high-risk T2DM patients with kidney disease is crucial for initiating targeted prevention and treatment measures in time to reduce or delay the occurrence and progression of diabetic kidney disease. Previous studies have identified a variety of clinical predictors for the progression of renal function in T2DM patients, including proteinuria, estimated glomerular filtration rate, blood glucose, blood pressure, serum uric acid, dyslipidemia, obesity, smoking, duration of DM, age, gender, race, family history of DM, and diabetic retinopathy. Clinical prediction models based on conventional clinical indicators are instrumental in evaluating the risk of kidney disease in T2DM patients, assisting in patient risk stratification. This article systematically reviews the clinical prediction factors and prediction models associated with the progression of renal function in T2DM patients, providing a comprehensive and current reference for improved clinical assessment of the risk of renal function progression.

Keywords

diabetes kidney disease / diabetic nephropathy / end-stage renal disease / prediction models / type 2 diabetes mellitus

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