Background: Diabetic kidney disease (DKD) is the leading cause of end-stage renal disease in the Western world. Early and accurate identification of DKD offers the best chance of slowing the progression of kidney disease. An important method for evaluating risk of progressive DKD is abnormal albumin excretion rate (AER). Due to the high variability in AER, most guidelines recommend the use of more than or equal to two out of three AER measurements within a 3- to 6-month period to categorise AER. There are recognised limitations of using AER as a marker of DKD because one quarter of patients with type 2 diabetes may develop kidney disease without an increase in albuminuria and spontaneous regression of albuminuria occurs frequently. Nevertheless, it is important to investigate the long-term intra-individual variability of AER in participants with type 2 diabetes.
Methods: Consecutive AER measurements (median 19 per subject) were performed in 497 participants with type 2 diabetes from 1999 to 2012 (mean follow-up 7.9 ± 3 years). Baseline clinical characteristics were collected to determine associations with AER variability. Participants were categorised as having normo-, micro- or macroalbuminuria according to their initial three AER measurements. Participants were then categorised into four patterns of AER trajectories: persistent, intermittent, progressing and regressing. Coefficients of variation were used to measure intra-individual AER variability.
Results: The median coefficient of variation of AER was 53.3%, 76.0% and 67.0% for subjects with normo-, micro- or macroalbuminuria at baseline. The coefficient of variation of AER was 37.7%, 66% and 94.8% for subjects with persistent, intermittent and progressing normoalbuminuria; 43%, 70.6%, 86.1% and 82.3% for subjects with persistent, intermittent, progressing and regressing microalbuminuria; and 55.2%, 67% and 82.4% for subjects with persistent, intermittent and regressing macroalbuminuria, respectively.
Conclusion: High long-term variability of AER suggests that two out of three AER measurements may not always be adequate for the optimal categorisation and prediction of AER.