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A1C variability as an independent risk factor for microalbuminuria in young people with type 1 diabetes.

ABSTRACT: To assess the potential association between A1C variability (A1C-SD) and microalbuminuria in young people with type 1 diabetes.Serially collected samples for A1C measurement were available for 1,232 subjects with childhood-onset type 1 diabetes recruited to the Oxford Regional Prospective Study and the Nephropathy Family Study.The median (range) number of A1C assessments was 4 (2-16). Mean intrapersonal A1C was 9.5% and A1C-SD was 0.91. Mean A1C and A1C-SD values were higher in subjects with microalbuminuria (n = 227) than in those with normoalbuminuria (10.3 vs. 9.4%; 1.12 vs. 0.86, P < 0.001). In a Cox regression model, A1C-SD was independently associated with microalbuminuria (hazard ratio 1.31 [95% CI 1.01-1.35]).In the current study, A1C variability was an independent variable that added to the effect of A1C on the risk for microalbuminuria in youth with type 1 diabetes, a population highly vulnerable to vascular complications.

SUBMITTER: Marcovecchio ML

PROVIDER: S-EPMC3064014 | biostudies-literature | 2011 Apr

REPOSITORIES: biostudies-literature

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A1C variability as an independent risk factor for microalbuminuria in young people with type 1 diabetes.

Marcovecchio M Loredana ML Dalton R Neil RN Chiarelli Francesco F Dunger David B DB

Diabetes care 20110218 4

<h4>Objective</h4>To assess the potential association between A1C variability (A1C-SD) and microalbuminuria in young people with type 1 diabetes.<h4>Research design and methods</h4>Serially collected samples for A1C measurement were available for 1,232 subjects with childhood-onset type 1 diabetes recruited to the Oxford Regional Prospective Study and the Nephropathy Family Study.<h4>Results</h4>The median (range) number of A1C assessments was 4 (2-16). Mean intrapersonal A1C was 9.5% and A1C-SD ...[more]

PMID: 21335371

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Project description:ObjectivesMost type 2 diabetes simulation models utilise equations mapping out lifetime trajectories of risk factors [e.g. glycated haemoglobin (HbA1c)]. Existing equations, using historic data or assuming constant risk factors, frequently underestimate or overestimate complication rates. Updated risk factor time path equations are needed for simulation models to more accurately predict complication rates.Aims(1) Update United Kingdom Prospective Diabetes Study Outcomes Model (UKPDS-OM2) risk factor time path equations; (2) compare quality-adjusted life-years (QALYs) using original and updated equations; and (3) compare QALY gains for reference case simulations using different risk factor equations.MethodsUsing pooled contemporary data from two randomised trials EXSCEL and TECOS (n = 28,608), we estimated: dynamic panel models of seven continuous risk factors (high-density lipoprotein cholesterol, low density lipoprotein cholesterol, HbA1c, haemoglobin, heart rate, blood pressure and body mass index); two-step models of estimated glomerular filtration rate; and survival analyses of peripheral arterial disease, atrial fibrillation and albuminuria. UKPDS-OM2-derived lifetime QALYs were extrapolated over 70 years using historical and the new risk factor equations.ResultsAll new risk factor equation predictions were within 95% confidence intervals of observed values, displaying good agreement between observed and estimated values. Historical risk factor time path equations predicted trial participants would accrue 9.84 QALYs, increasing to 10.98 QALYs using contemporary equations.DiscussionIncorporating updated risk factor time path equations into diabetes simulation models could give more accurate predictions of long-term health, costs, QALYs and cost-effectiveness estimates, as well as a more precise understanding of the impact of diabetes on patients' health, expenditure and quality of life.Trial registrationClinicalTrials.gov NCT01144338 and NCT00790205.

Dataset Information

A1C variability as an independent risk factor for microalbuminuria in young people with type 1 diabetes.

Publications

A1C variability as an independent risk factor for microalbuminuria in young people with type 1 diabetes.

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