Relationship between glycated haemoglobin and microvascular complications: is there a natural cut-off point for the diagnosis of diabetes?
This study was designed to determine whether the relationship of glycated haemoglobin to diabetic microvascular complications shows any natural thresholds that could be useful in diagnosing diabetes.We examined a population-based sample of 3,190 Malay adults aged 40-80 years in Singapore. The microvascular outcomes of interest were: (1) any retinopathy, defined from fundus photographs; (2) mild retinopathy, defined as in (1); (3) moderate retinopathy, defined as in (1); (4) chronic kidney disease, defined from estimated glomerular filtration rate; (5) micro- or macroalbuminuria, defined from urinary albumin to creatinine ratio; and (6) peripheral neuropathy, defined from neurothesiometer or monofilament sensory testing.Increasing HbA(1c) was associated with all microvascular complications. The optimal cut-off points for detecting mild and moderate retinopathy were 6.6% (87.0% sensitivity, 77.1% specificity and area under the receiver operating characteristics [ROC] curve 0.899) and 7.0% (82.9% sensitivity, 82.3% specificity and area under ROC curve 0.904). The prevalences of mild and moderate retinopathy were <1% below the optimal cut-off points. For other complications, the association with HbA(1c) was linear without evidence of a distinct threshold. Although ROC analysis for these other complications also suggested optimal cut-off points between 6.6% and 7.0%, the sensitivity at these cut-off points was considerably lower than for mild and moderate retinopathy, ranging from 31.8% to 66.5%.Higher levels of HbA(1c) were associated with microvascular complications. Our data support use of an HbA(1c) cut-off point of between 6.6 and 7.0% in diagnosing diabetes. Cut-off points in this range were best for the identification of individuals with mild and moderate retinopathy. Any retinopathy, chronic kidney disease, albuminuria and peripheral neuropathy are less well detected at these cut-off points.
Sabanayagam, C; Liew, G; Tai, ES; Shankar, A; Lim, SC; Subramaniam, T; Wong, TY
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