Variability in hemoglobin A1c predicts all-cause mortality in patients with type 2 diabetes
Journal
Journal of Diabetes and its Complications
Journal Volume
26
Journal Issue
4
Pages
296-300
Date Issued
2012
Author(s)
Abstract
Background: To evaluate the relationship between hemoglobin A1c variability and all-cause mortality in type 2 diabetic patients. Methods: This was a retrospective cohort study in type 2 diabetic patients followed for at least 2 years between 2003 and 2009. A1C variability was determined from the standard deviation or coefficient of variation of serial A1C values (A1CSD or A1CCV). Subjects were categorized into either the high or low A1C variability group according to their A1CCV median. Hazard ratios (HRs) of various factors for all-cause mortality were determined from Cox's proportional hazard models. Results: A total of 881 subjects (422 men, 459 women) were included and 73 (8.3%) died during follow-up. The follow-up period was 4.7 ± 2.3 years. All-cause mortality was higher in subjects with high A1CCV (11.0% vs. 5.4%, p = 0.002). In the Kaplan-Meier failure curve, subjects with higher A1CCV demonstrated a trend of higher mortality (p = 0.1). In multivariate Cox's proportional hazards models, A1C SD and A1CCV significantly predicted all-cause mortality with an HR of 1.987 (p = 0.02) and 1.062 (p = 0.013), respectively, after adjusting for age, gender, body mass index, duration of diabetes, mean systolic blood pressure, use of antihypertensives and statins, mean LDL-cholesterol, smoking status, chronic kidney disease, and mean A1C values (A1C MEAN). The ability of A1CSD and A1CCV to predict all-cause mortality was more evident in subjects with relatively low A1CMEAN. Conclusions: A1C variability is an important risk factor for all-cause mortality in type 2 diabetic patients. ? 2012 Elsevier Inc. All rights reserved.
SDGs
Other Subjects
antihypertensive agent; hemoglobin A1c; hydroxymethylglutaryl coenzyme A reductase inhibitor; low density lipoprotein cholesterol; adult; article; body mass; chronic kidney disease; cohort analysis; controlled study; correlation coefficient; diabetic patient; female; follow up; gender and sex; hazard ratio; human; Kaplan Meier method; major clinical study; male; mortality; non insulin dependent diabetes mellitus; prediction; priority journal; proportional hazards model; retrospective study; smoking cessation; survival prediction; systolic blood pressure; Aged; Cohort Studies; Diabetes Mellitus, Type 2; Female; Follow-Up Studies; Hemoglobin A, Glycosylated; Humans; Kaplan-Meier Estimate; Male; Middle Aged; Predictive Value of Tests; Proportional Hazards Models; Retrospective Studies; Risk Factors
Type
journal article