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Modeling Chronic Glycemic Exposure Variables as Correlates and Predictors of Microvascular Complications of Diabetes

¹ Department of Neurology, Mayo Clinic College of Medicine, Rochester, Minnesota
² Division of Endocrinology, Mayo Clinic College of Medicine, Rochester, Minnesota
³ Department of Ophthalmology, Mayo Clinic College of Medicine, Rochester, Minnesota
⁴ Department of Ophthalmology, University of Wisconsin Madison, Madison, Wisconsin
⁵ Division of Nephrology and Hypertension, Mayo Clinic College of Medicine, Rochester, Minnesota
⁶ Division of Epidemiology, Mayo Clinic College of Medicine, Rochester, Minnesota
⁷ Division of Biostatistics, Mayo Clinic College of Medicine, Rochester, Minnesota

Address correspondence and reprint requests to Peter J. Dyck, MD, Mayo Clinic College of Medicine, Department of Neurology, 200 First St. SW, Rochester, MN 55905. E-mail: dyck.peter{at}mayo.edu

OBJECTIVE—The degree to which chronic glycemic exposure (CGE) (fasting plasma glucose [FPG], HbA_1c [A1C], duration of diabetes, age at onset of diabetes, or combinations of these) is associated with or predicts the severity of microvessel complications is unsettled. Specifically, we test whether combinations of components correlate and predict complications better than individual components.

RESEARCH DESIGN AND METHODS—Correlations and predictions of CGE and complications were assessed in the Rochester Diabetic Neuropathy Study, a population-based, cross-sectional, and longitudinal epidemiologic survey of 504 patients with diabetes followed for up to 20 years.

RESULTS—In multivariate analysis, A1C and duration of diabetes (and to a lesser degree age at onset of diabetes but not FPG) were the main significant CGE risk covariates for complications. A derived glycemic exposure index (GE_i) correlated with and predicted complications better than did individual components. Composite or staged measures of polyneuropathy provided higher correlations and better predictions than did dichotomous measures of whether polyneuropathy was present or not. Generally, the mean GE_i was significantly higher with increasing stages of severity of complications.

CONCLUSIONS—A combination of A1C, duration of diabetes, and age at onset of diabetes (a mathematical index, GE_i) correlates significantly with complications and predicts later complications better than single components of CGE. Serial measures of A1C improved the correlations and predictions. For polyneuropathy, continuous or staged measurements performed better than dichotomous judgments. Even with intensive assessment of CGE and complications over long times, only about one-third of the variability of the severity of complications is explained, emphasizing the role of other putative risk covariates.

Abbreviations: CGE, chronic glycemic exposure • DCCT, Diabetes Control and Complications Trial • DSPN, diabetic sensory polyneuropathy • FPG, fasting plasma glucose • GE_i, glycemic exposure index • NIS, Neuropathy Impairment Score • NSC, Neuropathy Symptoms and Change • QST, quantitative sensation test • RDNS, Rochester Diabetic Neuropathy Study

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