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      Postprandial Blood Glucose Outweighs Fasting Blood Glucose and HbA1c in screening Coronary Heart Disease

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          Abstract

          The objective of the present study is to assess the performance of fasting blood glucose (FBG), postprandial blood glucose (PBG), and glycated hemoglobin (HbA1c) as screening for coronary heart disease (CHD) in an inpatient population undergoing coronary angiography. 1852 consecutive patients scheduled for coronary angiography were classified into Normal Glucose Tolerance (NGT), Impaired Glucose Regulation (IGR), and diabetes, based on FBG, PBG, and HbA1c. Correlations of Gensini score with glucose metabolism and insulin resistance were analyzed. The associations between glycemic variables and Gensini score or the presence of CHD were analyzed by multiple linear regression and logistic regression, respectively. CHD was diagnosed in 488, 622, and 414 patients with NGT, IGR, and diabetes, respectively. Gensini score was positively correlated with FBG (r = 0.09, p < 0.01), PBG (r = 0.20, p < 0.01), and HbA1c (r = 0.19, p < 0.01). Gensini score was not correlated with fasting insulin (r = −0.081, p = 0.36), post-prandial insulin (r = −0.02, p = 0.61), or HOMAIR (r = −0.0059, p = 0.13). When FBG, PBG and HbA1c were pooled altogether, only PBG persisted in its association with Gensini score and the prevalence of CHD. The severity of CHD was associated with glucose rather than insulin resistance in this Chinese population. PBG was optimally correlated with the presence and severity of CHD.

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          Contributions of fasting and postprandial plasma glucose increments to the overall diurnal hyperglycemia of type 2 diabetic patients: variations with increasing levels of HbA(1c).

          The exact contributions of postprandial and fasting glucose increments to overall hyperglycemia remain controversial. The discrepancies between the data published previously might be caused by the interference of several factors. To test the effect of overall glycemic control itself, we analyzed the diurnal glycemic profiles of type 2 diabetic patients investigated at different levels of HbA(1c). In 290 non-insulin- and non-acarbose-using patients with type 2 diabetes, plasma glucose (PG) concentrations were determined at fasting (8:00 A.M.) and during postprandial and postabsorptive periods (at 11:00 A.M., 2:00 P.M., and 5:00 P.M.). The areas under the curve above fasting PG concentrations (AUC(1)) and >6.1 mmol/l (AUC(2)) were calculated for further evaluation of the relative contributions of postprandial (AUC(1)/AUC(2), %) and fasting [(AUC(2) - AUC(1))/AUC(2), %] PG increments to the overall diurnal hyperglycemia. The data were compared over quintiles of HbA(1c). The relative contribution of postprandial glucose decreased progressively from the lowest (69.7%) to the highest quintile of HbA(1c) (30.5%, P < 0.001), whereas the relative contribution of fasting glucose increased gradually with increasing levels of HbA(1c): 30.3% in the lowest vs. 69.5% in the highest quintile (P < 0.001). The relative contribution of postprandial glucose excursions is predominant in fairly controlled patients, whereas the contribution of fasting hyperglycemia increases gradually with diabetes worsening. These results could therefore provide a unifying explanation for the discrepancies as observed in previous studies.
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            Glucose tolerance and cardiovascular mortality: comparison of fasting and 2-hour diagnostic criteria.

            (2001)
            New diagnostic criteria for diabetes based on fasting blood glucose (FBG) level were approved by the American Diabetes Association. The impact of using FBG only has not been evaluated thoroughly. The fasting and the 2-hour glucose (2h-BG) criteria were compared with regard to the prediction of mortality. Existing baseline data on glucose level at fasting and 2 hours after a 75-g oral glucose tolerance test from 10 prospective European cohort studies including 15 388 men and 7126 women aged 30 to 89 years, with a median follow-up of 8.8 years, were analyzed. Hazards ratios for death from all causes, cardiovascular disease, coronary heart disease, and stroke were estimated. Multivariate Cox regression analyses showed that the inclusion of FBG did not add significant information on the prediction of 2h-BG alone (P>.10 for various causes), whereas the addition of 2h-BG to FBG criteria significantly improved the prediction (P<.001 for all causes and P<.005 for cardiovascular disease). In a model including FBG and 2h-BG simultaneously, hazards ratios (95% confidence intervals) in subjects with diabetes on 2h-BG were 1.73 (1.45-2.06) for all causes, 1.40 (1.02-1.92) for cardiovascular disease, 1.56 (1.03-2.36) for coronary heart disease, and 1.29 (0.66-2.54) for stroke mortality, compared with the normal 2h-BG group. Compared with the normal FBG group, the corresponding hazards ratios in subjects with diabetes on FBG were 1.21 (1.01-1.44), 1.20 (0.88-1.64), 1.09 (0.71-1.67), and 1.64 (0.88-3.07), respectively. The largest number of excess deaths was observed in subjects who had impaired glucose tolerance but normal FBG levels. The 2h-BG is a better predictor of deaths from all causes and cardiovascular disease than is FBG.
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              Hyperinsulinemia as an independent risk factor for ischemic heart disease.

              Prospective studies suggest that hyperinsulinemia may be an important risk factor for ischemic heart disease. However, it has not been determined whether plasma insulin levels are independently related to ischemic heart disease after adjustment for other risk factors, including plasma lipoprotein levels. In 1985 we collected blood samples from 2103 men from suburbs of Quebec City, Canada, who were 45 to 76 years of age and who did not have ischemic heart disease. A first ischemic event (angina pectoris, acute myocardial infarction or death from coronary heart disease) occurred in 114 men (case patients) between 1985 and 1990. Each case patient was matched for age, body-mass index, smoking habits, and alcohol consumption with a control selected from among the 1989 men who remained free of ischemic heart disease during follow-up. After excluding men with diabetes, we compared fasting plasma insulin and lipoprotein concentrations at base line in 91 case patients and 105 controls. Fasting insulin concentrations at base line were 18 percent higher in the case patients than in the controls (P<0.001). Logistic-regression analysis showed that the insulin concentration remained associated with ischemic heart disease (odds ratio for ischemic heart disease with each increase of 1 SD in the insulin concentration, 1.7; 95 percent confidence interval, 1.3 to 2.4) after adjustment for systolic blood pressure, use of medications, and family history of ischemic heart disease. Further adjustment by multivariate analysis for plasma triglyceride, apolipoprotein B, low-density lipoprotein cholesterol, and high-density lipoprotein cholesterol concentrations did not significantly diminish the association between the insulin concentration and the risk of ischemic heart disease (odds ratio, 1.6; 95 percent confidence interval, 1.1 to 2.3). High fasting insulin concentrations appear to be an independent predictor of ischemic heart disease in men.
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                Author and article information

                Contributors
                zhongshan_endo@126.com
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                27 October 2017
                27 October 2017
                2017
                : 7
                : 14212
                Affiliations
                [1 ]Department of Endocrinology and Metabolism, ZhongShan Hospital, Fudan University, Shanghai, China
                [2 ]Department of Laboratory Medicine, ZhongShan Hospital, Fudan University, Shanghai, China
                Article
                14152
                10.1038/s41598-017-14152-y
                5660170
                29079813
                262d653e-7088-4233-8dab-f66898ba0f95
                © The Author(s) 2017

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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                : 18 May 2017
                : 5 October 2017
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