Glycaemic Control Impact on Renal Endpoints in Diabetic Patients on Haemodialysis
OBJECTIVE Hemoglobin A1c (HbA(1c)) has been widely used as a clinically important assessment tool for outcome analyses related to glycemic control. However, because of special conditions in dialysis patients, including the uremic milieu, there is no HbA(1c) blood glucose (BG) equation specific for patients on dialysis. In this study, we sought to develop HbA(1c)-BG equation models for hemodialysis patients. RESEARCH DESIGN AND METHODS We examined associations between HbA(1c) and random serum BG over time in a contemporary cohort of diabetic patients with hemodialysis treated in DaVita dialysis clinics. We identified 11,986 patients (63 ± 12 years old and 49% male) with 69,764 paired measurements of HbA(1c) and BG over the course of 5 years (2001-2006). Bootstrapping method was used to estimate average BG and corresponding HbA(1c) levels. The association was adjusted by patient factors using linear regression. RESULTS Linear regression analyses yielded the following three regression equations: BG = 59.2 + 29.4 × HbA(1c) - 20.8 × Alb (R(2) = 0.483); BG = 104.8 + 29.7 × HbA(1c) - 18.4 × Alb - 4.7 × Hb (R(2) = 0.486); and BG = 82.9 + 30.7 × HbA(1c) - 16.5 × Alb - 5.4 × Hb + 0.3 × age + race (R(2) = 0.491). All our models showed stronger association than previous equation models (R(2) = 0.468 in the Diabetes Control and Complications Trial and A1c-Derived Average Glucose equations). CONCLUSIONS The association between HbA(1c) and BG in hemodialysis patients is different than that of patients with normal kidney function. Our analysis suggests that equations including serum albumin or hemoglobin are better for hemodialysis patients.