Predictors and generation of risk equations for albuminuria progression in type 2 diabetes

Diabetes is the most common cause of end-stage renal disease and is associated with increased mortality. Although only a proportion of type 2 diabetic subjects develop albuminuria or progress, it is not currently possible to identify those patients who will develop this complication or who will progress.

The aim of the study was to identify baseline risk factors for the development and progression of albuminuria in a cohort with type 2 diabetes and use this data to generate risk equations.

Type 2 diabetic subjects who had albumin-creatinine ratio (ACR) measurement in 2007 - 2008 were recruited and followed-up for 8 years.

260 patients were included in the study. Of all the normoalbuminuric and microalbuminuric patients, 24.3% progressed. Baseline HbA1c, white cell count (WCC), smoking, and duration of diabetes were associated with progression of albuminuria stage in univariate analysis. Duration of diabetes (p = 0.034) was independently associated with progression in binary logistic regression. Baseline HbA1c (p = 0.002), age (p = 0.01), serum creatinine (p = 0.02), serum potassium (p = 0.04), serum urea (p = 0.0004), WCC (p = 0.02), serum triglycerides (p = 0.02), systolic blood pressure (p = 0.02), and duration of diabetes (p = 0.003) were positively correlated with percentage change (% change) in ACR, whilst baseline estimated glomerular filtration rate (eGFR) (p = 0.03), serum sodium (p = 0.04), hemoglobin (p = 0.0006), and hematocrit (p = 0.0002) were negatively correlated in Spearman correlation. Duration of diabetes (p = 0.025) and baseline HbA1c (p = 0.02) were independently associated with % change in ACR in multivariate analysis. Based on these results, novel risk equations were generated.

We have identified baseline characteristics associated with progression of renal disease in type 2 diabetic subjects and generated equations to estimate the risk of progression. If validated in other populations, these equations might be useful in predicting risk of progression in clinical practice.