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Journal Article
Research Support, Non-U.S. Gov't
Macrovascular risk and diagnostic criteria for type 2 diabetes: implications for the use of FPG and HbA(1c) for cost-effective screening.
Diabetes Care 2003 Februrary
OBJECTIVE: The use of fasting plasma glucose (FPG) level > or =7.0 mmol/l leads to underdiagnosis of type 2 diabetes compared with the oral glucose tolerance test (OGTT). The OGTT is of limited use for population screening. Most of the increase in cardiovascular risk in relation to increasing blood glucose occurs before the threshold at which the diagnosis of type 2 diabetes is made. The aim of this study was to evaluate the use of HbA(1c) and FPG as predictors of type 2 diabetes and cardiovascular risk and, accordingly, to develop a rational approach to screening for abnormalities of glucose tolerance.
RESEARCH DESIGN AND METHODS: OGTT and measurement of HbA(1c) and FPG levels were performed in 505 subjects screened for type 2 diabetes. Anthropomorphic measurements were obtained. A cardiovascular risk factor questionnaire was completed.
RESULTS: The subjects were aged 19-88 years (mean 53.8). The incidence of type 2 diabetes was 10.4% based on the OGTT and 4% based on an FPG level > or =7.0 mmol/l. Using high-performance liquid chromatography (HPLC), HbA(1c) of <4.7 and > or =6.2% predicted with certainty the absence or presence of type 2 diabetes as defined by the OGTT. The corresponding cutoffs were <5.0 and > or =6.8% for HbA(1c) (DCA2000 HPLC device; Bayer Diagnostics, Mulgrave, Australia) and <4.7 and > or =6.4 mmol/l for FPG. However, 75-85% of subjects in each case had intermediate values, which were therefore nondiagnostic. Cardiovascular risk increased at least 2.2 times at an HbA(1c) level > or =6.2% (by HPLC), 1.8-2.2 times at an HbA(1c) level of 5.6-6.1% (by HPLC), 2 times at an FPG level > or =6.4 mmol/l, and 1.7-1.9 times at an FPG level of 5.6-6.3 mmol/l.
CONCLUSIONS: Measurement of FPG and HbA(1c) levels will diagnose or exclude type 2 diabetes with certainty in a minority (15%) of people. There is a continuous relationship between FPG and HbA(1c) and cardiovascular risk. Accordingly, we propose that there is a rational basis for using either FPG and HbA(1c) for purposes of screening and assigning risk. Individuals with an HbA(1c) level of 5.6-6.1% and an FPG level of 5.6-6.3 mmol/l are at greatest risk for cardiovascular disease and should be targeted for further evaluation. An algorithm outlining a cost-effective approach is presented.
RESEARCH DESIGN AND METHODS: OGTT and measurement of HbA(1c) and FPG levels were performed in 505 subjects screened for type 2 diabetes. Anthropomorphic measurements were obtained. A cardiovascular risk factor questionnaire was completed.
RESULTS: The subjects were aged 19-88 years (mean 53.8). The incidence of type 2 diabetes was 10.4% based on the OGTT and 4% based on an FPG level > or =7.0 mmol/l. Using high-performance liquid chromatography (HPLC), HbA(1c) of <4.7 and > or =6.2% predicted with certainty the absence or presence of type 2 diabetes as defined by the OGTT. The corresponding cutoffs were <5.0 and > or =6.8% for HbA(1c) (DCA2000 HPLC device; Bayer Diagnostics, Mulgrave, Australia) and <4.7 and > or =6.4 mmol/l for FPG. However, 75-85% of subjects in each case had intermediate values, which were therefore nondiagnostic. Cardiovascular risk increased at least 2.2 times at an HbA(1c) level > or =6.2% (by HPLC), 1.8-2.2 times at an HbA(1c) level of 5.6-6.1% (by HPLC), 2 times at an FPG level > or =6.4 mmol/l, and 1.7-1.9 times at an FPG level of 5.6-6.3 mmol/l.
CONCLUSIONS: Measurement of FPG and HbA(1c) levels will diagnose or exclude type 2 diabetes with certainty in a minority (15%) of people. There is a continuous relationship between FPG and HbA(1c) and cardiovascular risk. Accordingly, we propose that there is a rational basis for using either FPG and HbA(1c) for purposes of screening and assigning risk. Individuals with an HbA(1c) level of 5.6-6.1% and an FPG level of 5.6-6.3 mmol/l are at greatest risk for cardiovascular disease and should be targeted for further evaluation. An algorithm outlining a cost-effective approach is presented.
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