Background: In view of the alarming increase in the number of people with diabetes mellitus (DM), a rising number of patients with diabetic kidney disease (DKD), end-stage renal disease (ESRD) and cardiovascular disease (CVD) is forecasted. It is therefore imperative to re-visit the natural history of DKD and to identify potential risk factors, which may enhance the progression of the disease and its complications.
Methods: The medical records of 270 Type 2 diabetic chronic kidney disease patients followed up at the Sheffield Kidney Institute between 2000 and 2008 were reviewed. Various socio-demographic, clinical and biochemical parameters (baseline and follow-up parameters) were retrospectively collected from the patients' database. Progression of DKD was evaluated by evaluation of the rate of decline of estimated glomerular filtration rate (eGFR) as calculated from the simplified Modification of Diet in Renal Disease formula [progressors: loss of glomerular filtration rate (GFR) >2 mL/min/1.73m(2)/year] as well as by the progression pattern based on the slope of GFR changes. Variables associated with progression in univariate analysis were examined by multivariate analysis to determine the factors independently associated with DKD progression.
Results: The majority of the study populations were males (66.7%) and Caucasians (88%). Ninety-four patients (34.8%) had progressive, whereas 176 (65.2%) had non-progressive DKD. The rate of eGFR decline in progressors was -3.57 ± 1.45 mL/min/1.73m(2)/year compared to -1.31 ± 0.23 mL/min/1.73m(2)/year in non-progressors. The following parameters discriminated progressors from non-progressors by univariate analysis: baseline-blood pressure (BP) parameters, eGFR and proteinuria as well as serum uric acid. We also observed that area under the curve for follow-up systolic blood pressure (SBP), glycosylated haemoglobin (HbA1c) and proteinuria were significantly higher among the progressors (P = 0.043, P = 0.02 and P = 0.001, respectively). Independent determinants of DKD progression in this study in an adjusted logistic regression model were baseline HbA1c [odds ratio (OR), 2.27; 95% confidence interval (CI), 1.14-4.54], baseline SBP (OR, 1.23; 95% CI, 1.06-1.41), baseline proteinuria (OR, 3.24; 95% CI, 2.1-5.38), baseline serum uric acid (OR, 1.16; 95% CI, 1.09-1.39) and vascular co-morbidities (OR, 1.61; 95% CI, 1.02-2.54). Percentage changes in the key parameters (BP, HbA1c and proteinuria) during the first year of the study did not affect the rate of eGFR decline.
Conclusions: Baseline HbA1c, SBP, proteinuria and serum uric acid together with the presence of vascular co-morbidities are strongly and independently associated with faster DKD progression. A further prospective observational study is currently undertaken to evaluate these findings and to determine the predictive value of other biochemical peptides and cellular markers on DKD outcome.