Hemoglobin Glycation Index Is Associated With Cardiovascular Diseases in People With Impaired Glucose Metabolism.
ABSTRACT: Context:There is a substantial interindividual variation in the association between glycated hemoglobin (HbA1c) and plasma glucose concentrations. Its impact on cardiovascular disease (CVD) has not been comprehensively evaluated. Objective:We examined associations between interindividual variations in HbA1c, which was estimated as the hemoglobin glycation index (HGI), and CVD. Design, Setting, and Participants:We performed a cross-sectional analysis with 1248 treatment-naïve subjects with prediabetes or diabetes. The HGI was defined as the measured HbA1c minus predicted HbA1c, which was calculated from the linear relationship between HbA1c and fasting plasma glucose levels. Main Outcome Measures:The prevalence of composite and individual CVDs including coronary artery disease (CAD), stroke, and peripheral artery disease (PAD). Results:The overall prevalence of composite CVD was 10.3% and individual prevalences of CAD, stroke, and PAD were 5.7%, 5.1%, and 1.3%, respectively. All prevalences significantly increased from the first to third tertile of HGI. In multivariate analysis, the highest HGI tertile was independently associated with composite CVD [odds ratio (95% confidence interval): 2.81 (1.59-4.98)], and individual CAD [2.30 (1.12-4.73)], stroke [3.40 (1.50-7.73)], and PAD [6.37 (1.18-34.33)] after adjustment for other CVD risk factors including HbA1c levels. Two consecutive measurements of HGI obtained on different days showed good correlation (r = 0.651, P < 0.001) and high concordance rate in the tertile classification (69.1%). Conclusions:High HGI was independently associated with overall and individual CVDs. This result suggests that discrepancy between HbA1c and fasting glucose levels can reflect vascular health in subjects with impaired glucose metabolism.
Project description:Importance:The effect of polyvascular disease on cardiovascular outcomes in the background of peripheral artery disease (PAD) is unclear. Objective:To determine the risk of ischemic events (both cardiac and limb) among patients with PAD and polyvascular disease. Design, Setting, and Participants:In this post hoc secondary analysis of the international Examining Use of Ticagrelor in Peripheral Artery Disease (EUCLID) trial, outcomes were compared among 13?885 enrolled patients with PAD alone, PAD + coronary artery disease (CAD), PAD + cerebrovascular disease (CVD), and PAD + CAD + CVD. Adjusted Cox proportional hazards regression models were implemented to determine the risk associated with polyvascular disease and outcomes, and intention-to-treat analysis was performed. The EUCLID trial was conducted from December 31, 2012, to March 7, 2014; the present post hoc analysis was performed from June 1, 2017, to February 5, 2018. Interventions:EUCLID evaluated ticagrelor vs clopidogrel in preventing major adverse cardiac events (cardiovascular death, myocardial infarction [MI], or ischemic stroke) and major bleeding in patients with PAD. Main Outcomes and Measures:The primary end point was a composite of cardiovascular death, MI, or ischemic stroke. Key secondary end points included the individual components of the primary end point and acute limb ischemia leading to hospitalization, major amputation, and lower-extremity revascularization. The primary end point of Thrombolysis in Myocardial Infarction (TIMI) major bleeding was also evaluated. Results:The EUCLID trial randomized 13?885 patients with a median age of 66 years (interquartile range, 60-73 years), of whom 3888 (28.0%) were women. At baseline, 7804 patients (56.2%) had PAD alone; 2639 (19.0%) had PAD + CAD; 2049 (14.8%) had PAD + CVD; and 1393 (10.0%) had PAD + CAD + CVD. Compared with patients with isolated PAD, the adjusted hazard ratios (aHRs) for major adverse cardiac events were 1.34 (95% CI, 1.15-1.57; P?<?.001) for PAD + CVD, 1.65 (95% CI, 1.43-1.91; P?<?.001) for PAD + CAD, and 1.99 (95% CI, 1.69-2.34; P?<?.001) for PAD + CAD + CVD. The aHRs for lower-extremity revascularization were 1.17 (95% CI, 1.03-1.34; P?=?.01) for PAD + CAD, 1.17 (95% CI, 1.02-1.35; P?=?.02) for PAD + CVD, and 1.34 (95% CI, 1.15-1.57; P?<?.001) for PAD + CAD + CVD. Polyvascular disease was not associated with an increased risk of acute limb ischemia (aHR for PAD + CVD, 0.91; 95% CI, 0.62-1.34, P?=?.63; PAD + CAD, 0.93; 95% CI, 0.64-1.34, P?=?.69; and PAD + CAD + CVD, 0.98; 95% CI, 0.63-1.53, P?=?.93), major amputation (aHR for PAD + CVD, 0.83; 95% CI, 0.54-1.27, P?=?.40; PAD + CAD, 0.74; 95% CI, 0.47-1.16, P?=?.19; and PAD + CAD + CVD, 1.12; 95% CI, 0.69-1.80, P?=?.65), or TIMI major bleeding (PAD + CVD, 0.98; 0.66-1.44, P?=?.91; PAD + CAD, 1.04; 0.74-1.48, P?=?.81; and PAD + CAD + CVD, 0.96; 95% CI, 0.62-1.51, P?=?.88). Conclusions and Relevance:Compared with patients with PAD alone, the risk of major adverse cardiac events and lower-extremity revascularization increased with multiple vascular bed involvement. There was no clear increased risk of bleeding associated with polyvascular disease.
Project description:OBJECTIVE:This study tested the hypothesis that intensive treatment in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial disproportionately produced adverse outcomes in patients with diabetes with a high hemoglobin glycation index (HGI = observed HbA1c - predicted HbA1c). RESEARCH DESIGN AND METHODS:ACCORD was a randomized controlled trial of 10,251 patients with type 2 diabetes assigned to standard or intensive treatment with HbA1c goals of 7.0% to 7.9% (53 to 63 mmol/mol) and less than 6% (42 mmol/mol), respectively. In this ancillary study, a linear regression equation (HbA1c = 0.009 × fasting plasma glucose [FPG] [mg/dL] + 6.8) was derived from 1,000 randomly extracted participants at baseline. Baseline FPG values were used to calculate predicted HbA1c and HGI for the remaining 9,125 participants. Kaplan-Meier and Cox regression were used to assess the effects of intensive treatment on outcomes in patients with a low, moderate, or high HGI. RESULTS:Intensive treatment was associated with improved primary outcomes (composite of cardiovascular events) in the low (hazard ratio [HR] 0.75 [95% CI 0.59-0.95]) and moderate (HR 0.77 [95% CI 0.61-0.97]) HGI subgroups but not in the high HGI subgroup (HR 1.14 [95% CI 0.93-1.40]). Higher total mortality in intensively treated patients was confined to the high HGI subgroup (HR 1.41 [95% CI 1.10-1.80]). A high HGI was associated with a greater risk for hypoglycemia in the standard and intensive treatment groups. CONCLUSIONS:HGI calculated at baseline identified subpopulations in ACCORD with harms or benefits from intensive glycemic control. HbA1c is not a one-size-fits-all indicator of blood glucose control, and taking this into account when making management decisions could improve diabetes care.
Project description:BACKGROUND:Lower-extremity peripheral artery disease (LE-PAD) and coronary artery disease (CAD) are both pathologically rooted in atherosclerosis, and their shared clinical features regarding the exposure to cardiovascular risk factors have been emphasized. However, comparative data of the two cardiovascular diseases (CVDs) were so far lacking. The purpose of this study was to directly compare the clinical profile between cases undergoing endovascular therapy (EVT) for LE-PAD and those undergoing percutaneous coronary intervention (PCI). METHODS:Data were extracted from the nationwide procedural databases of EVT and PCI in Japan (J-EVT and J-PCI) between 2012 and 2017. A total of 1,121,359 cases (103,887 EVT cases for critical limb ischemia [CLI] or intermittent claudication and 1,017,472 PCI cases for acute coronary syndrome [ACS] or stable angina) were analyzed. Heterogeneity in clinical profile between CVDs was evaluated using the C statistic of the logistic regression model for which dependent variable was one CVD versus another, and explanatory variables were clinical profile. When two CVDs were completely discriminated from each other by the developed model, the C statistic (discrimination ability) of the model would be equal to 1, indicating that the two CVDs were completely different in clinical profile. On the other hand, when two CVDs were identical in clinical profile, the developed model would not discriminate them at all, with the C statistic equal to 0.5. RESULTS:Mean age was 73.5?±?9.3 years in LE-PAD patients versus 70.0?±?11.2 years in CAD patients (P?<?0.001). The prevalence of diabetes mellitus and end-stage renal disease was 1.96- and 6.39-times higher in LE-PAD patients than in CAD patients (both P?<?0.001). The higher prevalence was observed irrespective of age group. The exposure to other cardiovascular risk factors and the likelihood of cardiovascular risk clustering also varied between the diseases. The between-disease heterogeneity in patient profile was particularly evident between CLI and ACS, with the C statistic equal to 0.833 (95% CI 0.831-0.836). CONCLUSIONS:The current study, an analysis based on nationwide procedural databases, confirmed that patient profiles were not identical but rather considerably different between clinically significant LE-PAD and CAD warranting revascularization.
Project description:OBJECTIVE:Identifying patients who may experience decreased or increased mortality risk from intensive glycemic therapy for type 2 diabetes remains an important clinical challenge. We sought to identify characteristics of patients at high cardiovascular risk with decreased or increased mortality risk from glycemic therapy for type 2 diabetes using new methods to identify complex combinations of treatment effect modifiers. RESEARCH DESIGN AND METHODS:The machine learning method of gradient forest analysis was applied to understand the variation in all-cause mortality within the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial (N = 10,251), whose participants were 40-79 years old with type 2 diabetes, hemoglobin A1c (HbA1c) ≥7.5% (58 mmol/mol), cardiovascular disease (CVD) or multiple CVD risk factors, and randomized to target HbA1c <6.0% (42 mmol/mol; intensive) or 7.0-7.9% (53-63 mmol/mol; standard). Covariates included demographics, BMI, hemoglobin glycosylation index (HGI; observed minus expected HbA1c derived from prerandomization fasting plasma glucose), other biomarkers, history, and medications. RESULTS:The analysis identified four groups defined by age, BMI, and HGI with varied risk for mortality under intensive glycemic therapy. The lowest risk group (HGI <0.44, BMI <30 kg/m2, age <61 years) had an absolute mortality risk decrease of 2.3% attributable to intensive therapy (95% CI 0.2 to 4.5, P = 0.038; number needed to treat: 43), whereas the highest risk group (HGI ≥0.44) had an absolute mortality risk increase of 3.7% attributable to intensive therapy (95% CI 1.5 to 6.0; P < 0.001; number needed to harm: 27). CONCLUSIONS:Age, BMI, and HGI may help individualize prediction of the benefit and harm from intensive glycemic therapy.
Project description:AIMS/HYPOTHESIS:Previous studies have suggested that the haemoglobin glycation index (HGI) can be used as a predictor of diabetes-related complications in individuals with type 1 and type 2 diabetes. We investigated whether HGI was a predictor of adverse outcomes of intensive glucose lowering and of diabetes-related complications in general, using data from the Action in Diabetes and Vascular Disease: Preterax and Diamicron Modified Release Controlled Evaluation (ADVANCE) trial. METHODS:We studied participants in the ADVANCE trial with data available for baseline HbA1c and fasting plasma glucose (FPG) (n?=?11,083). HGI is the difference between observed HbA1c and HbA1c predicted from a simple linear regression of HbA1c on FPG. Using Cox regression, we investigated the association between HGI, both categorised and continuous, and adverse outcomes, considering treatment allocation (intensive or standard glucose control) and compared prediction of HGI and HbA1c. RESULTS:Intensive glucose control lowered mortality risk in individuals with high HGI only (HR 0.74 [95% CI 0.61, 0.91]; p?=?0.003), while there was no difference in the effect of intensive treatment on mortality in those with high HbA1c. Irrespective of treatment allocation, every SD increase in HGI was associated with a significant risk increase of 14-17% for macrovascular and microvascular disease and mortality. However, when adjusted for identical covariates, HbA1c was a stronger predictor of these outcomes than HGI. CONCLUSIONS/INTERPRETATION:HGI predicts risk for complications in ADVANCE participants, irrespective of treatment allocation, but no better than HbA1c. Individuals with high HGI have a lower risk for mortality when on intensive treatment. Given the discordant results and uncertain relevance beyond HbA1c, clinical use of HGI in type 2 diabetes cannot currently be recommended.
Project description:Individuals with type 2 diabetes (T2D) are at an increased risk of coronary heart disease (CHD). Diabetic complications have recently been associated with a measure of glucose metabolism known as the hemoglobin glycation index (HGI). Currently there is insufficient information regarding a potential link between HGI and cardiovascular disease. This study aimed to investigate the relationship between HGI and extent of CHD in individuals with T2D.This cross-sectional study screened individuals visiting the endocrinology clinic between June 2012 and May 2016 for eligibility. Enrollment criteria included individuals above 21 years of age with T2D diagnosed in the preceding ten years. Candidates with hemoglobin disorders, pregnancy, and existing coronary artery disease were excluded. Fasting plasma glucose (FPG) and glycated hemoglobin A1c (HbA1c) were sampled three months prior to angiography. The regression equation of predicted HbA1c = 0.008 × FPG + 6.28 described the linear relationship between these variables. HGI was calculated as the difference between the measured HbA1c and predicted HbA1c. Participants were classified into two groups according to the presence of supranormal (?0) or subnormal HGI (<0).Among 423 participants, people with supranormal HGI harbored an increased prevalence of multiple vessel disease relative to those with subnormal HGI (Odds ratio (OR): 3.9, 95% CI [2.64-5.98], P < 0.001). Moreover, individuals with supranormal HGI more frequently demonstrated lesions involving the left anterior descending artery (OR: 3.0, 95% CI [1.97-4.66], P < 0.001). The intergroup difference in mean HbA1c was statistically nonsignificant (7.5 ± 1.0% versus 7.4 ± 1.1%, P = 0.80).This study demonstrated that HGI correlated with the extent of CHD in individuals with T2D. People with supranormal HGI harbored a higher prevalence of extensive cardiovascular disease compared to those with subnormal HGI. The relationship between HGI and extent of CHD enables cardiovascular risk stratification in at risk individuals. Overall, HGI provides useful information concerning cardiovascular risk in clinical practice.
Project description:This study evaluate association between glycemic variability and adverse vascular events in nondiabetic middle-aged adults. From 10,020 Ansung-Ansan cohort, Korean Genome, and Epidemiology Study (KoGES) data. 6,462 nondiabetic adults aged <65 years was analyzed. The mean and coefficient of variation (CV) of all biannually recorded HbA1c, fasting blood glucose(FBG), and post 2?hr blood glucose (PBG) were calculated and divided into 3 groups based on tertile of CV at each measurement, respectively. Primary endpoint was composite of Macro (composite of Coronary artery disease, Myocardial infarction, Congestive heart failure or Stroke) and Microvascular event (Creatine Clearance <60?ml/min/1.73?m2). The participants (mean age: 50 years, 50% men) were followed for a median of 9.9 (9.1-10.0) years. The high HbA1c-CV tertile (odds ratio 1.30; 1.01-1.66) was independent risk factor for microvascular events. In contrast, high FBG-CV tertile (2.32; 1.30-4.12) and PBG-CV (1.85; 1.05-3.26) was for macrovascular events. In this 10-year prespective cohort study, higher HbA1c-CV tertile was associated with higher composite of macro- and microvascular events and independent risk factor in non-DM middle-aged participants. In addition, higher tertile of FBG-CV and PBG-CV were risk factors for macrovascular events.
Project description:<h4>Introduction</h4>A high hemoglobin glycation index (HGI) and glycated hemoglobin (HbA1c) level are associated with greater inflammatory status, and dipeptidyl peptidase-4 (DPP-4) inhibitors can suppress inflammation. We aimed to evaluate the relationship between HGI and the therapeutic effect of DPP-4 inhibitors.<h4>Methods</h4>This retrospective cohort study followed 468 patients with type 2 diabetes receiving DPP-4 inhibitor treatment for 1 year. Estimated HbA1c was calculated using a linear regression equation derived from another 2969 randomly extracted patients with type 2 diabetes based on fasting plasma glucose (FPG) level. The subjects were divided into two groups based on HGI (HGI = observed HbA1c - estimated HbA1c). Mixed model repeated measures were used to compare the treatment efficacy after 1 year in patients with a low (HGI<0, n = 199) and high HGI (HGI?0, n = 269).<h4>Results</h4>There were no significant group differences in mean changes of FPG after 1 year (-12.8 and -13.4 mg/dL in the low and high HGI groups, respectively). However, the patients with a high HGI had a significantly greater reduction in HbA1c from baseline compared to those with a low HGI (-1.9 versus -0.3% [-20.8 versus -3.3 mmol/mol]). Improvements in glycemic control were statistically significantly associated with the tested DPP-4 inhibitors in the high HGI group (-2.4, -1.4, -1.2 and -2.2% [-26.2, -15.3, -13.1 and -24.0 mmol/mol] for vildagliptin, linagliptin, saxagliptin and sitagliptin, respectively) but not in the low HGI group.<h4>Conclusions</h4>The HGI index derived from FPG and HbA1c may be able to identify who will have a better response to DPP-4 inhibitors.
Project description:BACKGROUND:This study investigated whether visit-to-visit fasting plasma glucose (FPG) variability, as measured by the coefficient of variation (CV), increased peripheral artery disease (PAD) risk. METHODS:Individuals with type 2 diabetes from the National Diabetes Care Management Program during the period 2002-2004, ??30 years of age, and free of PAD (n?=?30,932) were included and monitored until 2011. Cox proportional hazards regression models were implemented to analyze related determinants of PAD. RESULTS:A total of 894 incident cases of PAD were identified during an average 8.2 years of follow-up, resulting in a crude incidence rate of 3.53 per 1000 person-years. Both FPG-CV and HbA1c were significantly associated with PAD after multivariate adjustment, with corresponding hazard ratios of 1.24 [95% confidence interval (CI) 1.04-1.47] for FPG-CV in the third tertile and 1.50 (95% CI 1.10-2.04) for HbA1c???10%. The findings of the sensitivity analysis remained consistent after excluding potential confounders, demonstrating the consistency of the results. CONCLUSIONS:The associations between HbA1c, variability in FPG-CV, and PAD suggest a linked pathophysiological mechanism, suggesting the crucial role of glycemic variability in clinical management and therapeutic goals in preventing PAD in type 2 diabetes.
Project description:The prevalences of cardiovascular disease (CVD) and type 2 diabetes (T2D) have increased among the Navajo Native American community in recent decades. Oxidized low-density lipoprotein (oxLDL) is a novel CVD biomarker that has never been assessed in the Navajo population. We examined the relationship of oxLDL to conventional CVD and T2D risk factors and biomarkers in a cross-sectional population of Navajo participants. This cross-sectional study included 252 participants from 20 Navajo communities from the Diné Network for Environmental Health Project. Plasma samples were tested for oxLDL levels by a sandwich enzyme-linked immunosorbent assay. Univariate and multivariate analyses were used to determine the relationship of oxLDL and oxidized- to non-oxidized lipoprotein ratios to glycated hemoglobin (HbA1c), C-reactive protein (CRP), interleukin 6 (IL6) and demographic and health variables. Type 2 diabetes, hypertension and obesity are very prevalent in this Navajo population. HbA1c, CRP, body mass index (BMI), high-density lipoprotein, and triglycerides were at levels that may increase risk for CVD and T2D. Median oxLDL level was 47 (36.8-57) U/L. Correlational analysis showed that although oxLDL alone was not associated with HbA1c, oxLDL/HDL, oxLDL/LDL and CRP were significantly associated with HbA1c and glucose. OxLDL, oxLDL/HDL and oxLDL/LDL were significantly associated with CRP. Multivariate analysis showed that triglycerides were a common and strong predictor of oxLDL, oxLDL/HDL and oxLDL/LDL. OxLDL was trended with HbA1c and glucose but did not reach significance, however, HbA1c was an independent predictor of OxLDL/HDL. CRP trended with oxLDL/HDL and was a weak predictor of oxLDL/LDL. This Navajo subset appears to have oxLDL levels comparable to subjects without evidence of CVD reported in other studies. The high prevalence of T2D, hypertension and obesity along with abnormal levels of other biomarkers including HbA1c indicate that the Navajo population has a worsening CVD risk profile.