Hemoglobin Glycation Index Is Associated With Cardiovascular Diseases in People With Impaired Glucose Metabolism

Association between the haemoglobin glycation index (HGI) and clinical outcomes in patients with acute decompensated heart failure

BACKGROUND

A growing number of studies show that people with similar blood glucose levels have different levels of glycosylated haemoglobin (HbA1c), and relying only on HbA1c may lead to clinical decision-making errors. The haemoglobin glycation index (HGI) quantifies the difference in HbA1c among individuals and is strongly linked to the risk of cardiovascular disease. However, the connection between this phenomenon and the poor outcomes of patients with acute decompensated heart failure (ADHF) is currently unknown.

PATIENTS AND METHODS

This retrospective, single-centre-based cohort study included 1531 hospitalized patients with ADHF from September 2010 to January 2020. The HGI is calculated from the difference between the observed and predicted HbA1c values [predicted HbA1c = 0.024 × fasting plasma glucose (FPG) (mg/dL)+3.1]. The endpoints examined in the study included all-cause death, cardiovascular (CV) death, and major adverse cardiac events (MACE). We fitted multivariable-adjusted Cox proportional hazard models to investigate the association between the HGI and clinical outcomes.

RESULTS

During the five-year follow-up, 427 (27.9%) patients died from all causes, 232 (15.6%) from CV death, and 848 (55.4%) from MACE. The restricted cubic spline analysis also showed that the cumulative risk of all-cause and CV deaths decreased linearly with increasing HGI. According to multivariate Cox proportional hazard models, the highest tertile of the HGI was associated with a lower incidence of all-cause and cardiovascular deaths [all-cause death, adjusted hazard ratio (HR): 0.720, 95% confidence interval (CI): 0.563-0.921, p = 0.009; CV death, adjusted HR: 0.619, 95% CI: 0.445-0.861, p = 0.004]. A 1% increase in the HGI was associated with a 12.5% reduction in the risk of all-cause death and a 20.8% reduction in the risk of CV death.

CONCLUSIONS

A high HGI was directly associated with a reduction in all-cause and CV deaths but was not associated with MACE. These findings may be helpful in the management of patients with ADHF.

Hemoglobin glycation index and cardiovascular outcomes in patients with diabetes and coronary artery disease: insights from a large cohort study

BACKGROUND/OBJECTIVES

The hemoglobin glycation index (HGI) has been demonstrated to serve as a substitute for the individual bias in glycosylated hemoglobin A1c (HbA1c). Our objective was to assess the correlation between HGI and cardiovascular (CV) outcomes in patients with diabetes and coronary artery disease (CAD).

SUBJECTS/METHODS

We sequentially recruited 11921 patients with diabetes and CAD at Fuwai Hospital. The patients were categorized into five groups based on their HGI quintiles, ranging from Q1 to Q5. The primary endpoint was the occurrence of major adverse cardiac events (MACEs), which included CV death and nonfatal myocardial infarction.

RESULTS

During the median 3-year follow-up, 327 (2.7%) MACEs were observed. A U-shaped relationship between HGI and 3-year MACEs was demonstrated by restricted cubic spline (RCS) after multivariable adjustment (nonlinear P = 0.014). The Kaplan-Meier curves demonstrated that the Q2 group had the lowest risk of MACE (P = 0.006). When comparing the HGI Q2 group, multivariable Cox regression models showed that both low (Q1) and high (Q4 or Q5) HGI were linked to a higher risk of MACEs (all P < 0.05). Patients with a low HGI (Q1) had a significantly increased risk of all-cause and CV death, with a 1.70-fold increase in both cases (both P < 0.05).

CONCLUSIONS

In individuals with diabetes and established CAD, HGI levels were found to have a U-shaped relationship with the occurrence of MACEs over a period of three years. Significantly, those with low HGI had an increased risk of CV death.

Risk analysis of the association between different hemoglobin glycation index and poor prognosis in critical patients with coronary heart disease-A study based on the MIMIC-IV database

BACKGROUND

The hemoglobin glycation index (HGI) is the difference between the observed and predicted values of glycosylated hemoglobin (HbA1c), which is closely associated with a variety of poor prognoses. However, there are still no studies on the correlation between HGI and poor prognosis in patients with critical coronary artery disease. The purpose of this study was to analyze the correlation between HGI and all-cause mortality in patients with critical coronary artery disease using the MIMIC-IV database.

METHODS

The HGI was calculated by constructing a linear regression equation between HbA1c and fasting plasma glucose (FPG). A Kaplan‒Meier survival analysis model was constructed based on the HGI quartiles to clarify the differences in all-cause mortality rates between groups, and the log-rank test was used to assess the differences between groups. The hazard ratio (HR) of HGI as a risk factor for outcome events was assessed using the Cox proportional risk model and restricted cubic spline (RCS), with the Q2 group serving as the reference group.

RESULTS

A total of 5260 patients were included in this study. The 30-day mortality rate of the patients was 4.94% and the mortality rate within 365 days was 13.12%. A low HGI was significantly associated with 30-day mortality (HR, 1.96; 95% CI, (1.38, 2.78); P < 0.001) and 365-day mortality (HR, 1.48; 95% CI, (1.19, 1.85); P < 0.001) in patients with critical coronary artery disease in the completely adjusted Cox proportional risk model. In addition, high levels of HGI were associated with 365-day mortality (HR, 1.31; 95% CI, (1.02, 1.69); P < 0.05). RCS analysis revealed a U-shaped relationship between HGI and outcome events. According to the stratified analysis, the interaction test revealed that the correlation between HGI and outcome events remained stable.

CONCLUSION

There was a significant correlation between HGI and all-cause mortality in patients with critical coronary artery disease, particularly in those with low HGI. HGI can be used as a potential indicator for assessing the short- and long-term risk of mortality in such patients.

Hemoglobin Glycation Index: A Novel Risk Factor for Incident Chronic Kidney Disease in an Apparently Healthy Population

CONTEXT

Chronic kidney disease (CKD) is a worldwide health problem. Recent literature has shown an association of hemoglobin glycation index (HGI) and CKD in patients with dysglycemia.

OBJECTIVE

The aim of this study was to reveal the impact of HGI as a predictor for incident CKD in the general population.

METHODS

CKD was defined as dipstick proteinuria or estimated glomerular rate (eGFR) < 60 mL/min/1.73 m2. Impact of HGI on incident CKD was assessed using the data from CKD-free health examinees (N = 23 467, 4.1% with diabetes) followed for a mean of 5.1 years: Cox proportional hazards model was employed with multivariate adjustment for age, systolic blood pressure, eGFR, fasting plasma glucose, body mass index, log[alanine aminotransferase], log[triglycerides], high-density lipoprotein cholesterol, platelet counts, smoking, and sex. Elevated level of HGI in subjects with CKD was ascertained after propensity score matching of another group of health examinees (N = 2580, 7.6% with diabetes).

RESULTS

In the former group, CKD developed in 2540 subjects and HGI was the second most robust predictor for CKD, following low eGFR. With adjustment for the 11 covariates, the hazard ratio of HGI (95% CI) for CKD was 1.293 (1.238 to 1.349) (P < .0001). The population attributable risk of HGI for CKD was 4.2%. In the latter group, among 708 subjects matched 1:1 for 9 covariates, HGI was significantly elevated in subjects with CKD (median [interquartile range] -0.208 [-0.504 to -0.156] vs -0.284 [-0.582 to 0.052], P = .03).

CONCLUSION

HGI was a novel risk factor for CKD in the general population.

Association between hemoglobin glycation index and non-alcoholic fatty liver disease in the patients with type 2 diabetes mellitus

AIMS/INTRODUCTION

The hemoglobin glycation index (HGI) represent the disparity between actual glycated hemoglobin measurements and predicted HbA1c. It serves as a proxy for the degree of non-enzymatic glycation of hemoglobin, which has been found to be positively correlated with diabetic comorbidities. In this study, we investigated the relationship between HGI and non-alcoholic fatty liver disease (NAFLD), along with other relevant biological markers in patients with diabetes.

MATERIALS AND METHODS

This cross-sectional study consisted of 3,191 adults diagnosed with type 2 diabetes mellitus. We calculated the predicted glycated hemoglobin levels based on fasting blood glucose levels. Multivariate binary logistic regression analysis was conducted to examine the correlation between the HGI and NAFLD. Hepatic steatosis was diagnosed using ultrasonography.

RESULTS

Among all participants, 1,784 (55.91%) were diagnosed with NAFLD. Participants with confirmed NAFLD showed elevated body mass index, diastolic blood pressure, liver enzyme, total cholesterol, triglyceride, low-density lipoprotein and uric acid levels compared with those without NAFLD. In the unadjusted model, participants in the last tertile of HGI were 1.40-fold more likely to develop NAFLD than those in the first tertile (95% confidence interval 1.18-1.66; P < 0.001). In the fully adjusted model, those in the last tertile of HGI had a 39% increased risk of liver steatosis compared with confidence interval in the first tertile of HGI (95% confidence interval 1.12-1.74; P < 0.001).

CONCLUSIONS

A higher HGI suggests an elevated risk of developing NAFLD in patients with type 2 diabetes.

Association between hemoglobin glycation index and 5-year major adverse cardiovascular events: the REACTION cohort study

BACKGROUND

The hemoglobin glycation index (HGI) was developed to quantify glucose metabolism and individual differences and proved to be a robust measure of individual glycosylated hemoglobin (HbA1c) bias. Here, we aimed to explore the relationship between different HGIs and the risk of 5-year major adverse cardiovascular events (MACEs) by performing a large multicenter cohort study in China.

METHODS

A total of 9791 subjects from the Risk Evaluation of Cancers in Chinese Diabetic Individuals: a Longitudinal Study (the REACTION study) were divided into five subgroups (Q1-Q5) with the HGI quantiles (≤5th, >5th and ≤33.3th, >33.3th and ≤66.7th, >66.7th and ≤95th, and >95th percentile). A multivariate logistic regression model constructed by the restricted cubic spline method was used to evaluate the relationship between the HGI and the 5-year MACE risk. Subgroup analysis between the HGI and covariates were explored to detect differences among the five subgroups.

RESULTS

The total 5-year MACE rate in the nationwide cohort was 6.87% (673/9791). Restricted cubic spline analysis suggested a U-shaped correlation between the HGI values and MACE risk after adjustment for cardiovascular risk factors ( χ2 = 29.5, P <0.001). After adjustment for potential confounders, subjects with HGIs ≤-0.75 or >0.82 showed odds ratios (ORs) for MACE of 1.471 (95% confidence interval [CI], 1.027-2.069) and 2.222 (95% CI, 1.641-3.026) compared to subjects with HGIs of >-0.75 and ≤-0.20. In the subgroup with non-coronary heart disease, the risk of MACE was significantly higher in subjects with HGIs ≤-0.75 (OR, 1.540 [1.039-2.234]; P = 0.027) and >0.82 (OR, 2.022 [1.392-2.890]; P <0.001) compared to those with HGIs of ≤-0.75 or >0.82 after adjustment for potential confounders.

CONCLUSIONS

We found a U-shaped correlation between the HGI values and the risk of 5-year MACE. Both low and high HGIs were associated with an increased risk of MACE. Therefore, the HGI may predict the 5-year MACE risk.

The Association Between Hemoglobin Glycation Index and Carotid Artery Plaque in Patients With Coronary Heart Disease

This study aimed to examine the association between the hemoglobin glycation index (HGI) and carotid artery plaque (CAP) in patients with coronary heart disease (CHD). We conducted a cross-sectional analysis of 10,778 patients with CHD. The participants were divided into three groups by HGI tertiles (T1 HGI<-0.44, T2 -0.44 ≤ HGI ≤ 0.15, T3 HGI>0.15). The presence of CAP was used to diagnose by carotid ultrasonography. Logistic regression analysis was used to analyze the association between the HGI and CAP. The association between HGI and CAP was also assessed according to sex, age, smoking status, and drinking status. We further assessed the association between HGI and the ultrasound characteristics of CAP. The baseline analysis showed substantial differences in relevant parameters between the three groups of patients with CHD according to the tertiles of the HGI. Multivariate logistic regression analysis showed that HGI was significantly associated with CAP (odds ratio [OR] 1.32; 95% confidence interval [CI] 1.26-1.39). The association between HGI and CAP exists among different sex, age, smoking, and drinking status. Furthermore, there was a significant and positive association between HGI and all four different echogenicities of the CAP.

Cardiovascular and metabolic health is associated with functional brain connectivity in middle-aged and older adults: Results from the Human Connectome Project-Aging study

Several cardiovascular and metabolic indicators, such as cholesterol and blood pressure have been associated with altered neural and cognitive health as well as increased risk of dementia and Alzheimer's disease in later life. In this cross-sectional study, we examined how an aggregate index of cardiovascular and metabolic risk factor measures was associated with correlation-based estimates of resting-state functional connectivity (FC) across a broad adult age-span (36-90+ years) from 930 volunteers in the Human Connectome Project Aging (HCP-A). Increased (i.e., worse) aggregate cardiometabolic scores were associated with reduced FC globally, with especially strong effects in insular, medial frontal, medial parietal, and superior temporal regions. Additionally, at the network-level, FC between core brain networks, such as default-mode and cingulo-opercular, as well as dorsal attention networks, showed strong effects of cardiometabolic risk. These findings highlight the lifespan impact of cardiovascular and metabolic health on whole-brain functional integrity and how these conditions may disrupt higher-order network integrity.

Association of hemoglobin glycation index with prognosis of coronary artery disease after percutaneous coronary intervention: A retrospective cohort study

AIMS

To analyze the association between hemoglobin glycation index (HGI) and the long-term prognosis of patients with coronary artery disease (CAD) after percutaneous coronary intervention (PCI).

METHODS

Predicted glycated hemoglobin (HbA1c) level was calculated using an established formula and HGI represented the difference between laboratory measured HbA1c and predicted HbA1c. A total of 1780 patients were stratified into three subgroups (HGI < -0.4, -0.4 ≦ HGI < 0.12 and HGI ≧ 0.12). The primary endpoints included all-cause mortality (ACM) and cardiac mortality (CM). The secondary endpoints were major adverse cardiac events (MACEs) and major adverse cardiac and cerebrovascular events (MACCEs).

RESULTS

ACM occurred in 54 patients: 22 (3.7) in the low-HGI subgroup, 8 (1.3) in the moderate-HGI subgroup and 24 (4.1) in the high-HGI subgroup (p = .012). After adjusting for the traditional clinical prognostic factors, multivariate Cox regression analysis showed that patients in both the low and high HGI subgroups had significantly increased risk of ACM as compared with patients in the moderate HGI subgroup (hazard ratio [HR] = 4.979, 95% confidence interval [CI]: 1.865-13.297, p = .001 and HR = 2.918, 95% CI: 1.075-7.922, p = .036). However, we did not find significant differences in the incidence of CM, MACEs and MACCEs.

CONCLUSION

HGI can predicts risk for long-term mortality in patients undergoing PCI. This index could be helpful for the effective clinical management of the CAD population.

Intensified glycemic control by HbA1c for patients with coronary heart disease and Type 2 diabetes: a review of findings and conclusions

The occurrence and development of coronary heart disease (CHD) are closely linked to fluctuations in blood glucose levels. While the efficacy of intensified treatment guided by HbA1c levels remains uncertain for individuals with diabetes and CHD, this review summarizes the findings and conclusions regarding HbA1c in the context of CHD. Our review showed a curvilinear correlation between regulated level of HbA1c and therapeutic effectiveness of intensified glycemic control among patients with type 2 diabetes and coronary heart disease. It is necessary to optimize the dynamic monitoring indicators of HbA1c, combine genetic profiles, haptoglobin phenotypes for example and select more suitable hypoglycemic drugs to establish more appropriate glucose-controlling guideline for patients with CHD at different stage of diabetes.

Associations of apolipoproteinA1, high density lipoprotein cholesterol with hemoglobin glycation index and triglyceride-glucose index in Chinese adults with coronary artery disease

AIMS

Scarce data explored the associations of apolipoproteins with hemoglobin glycation index (HGI) and triglyceride-glucose (TyG) index. This study determined associations of serum apolipoproteinA1 (ApoA1) and high density lipoprotein cholesterol (HDL-C) with HGI and TyG index in coronary artery disease (CAD) patients.

METHODS

A total of 10,803 CAD patients were included in this cross-sectional pilot study. Serum concentrations of ApoA1 and HDL-C were measured. Analyses of covariance were used to compare the mean differences in glucose metabolism indices (e.g., HGI, TyG index, hemoglobin glycation [HbA1c], fasting blood glucose [FBG]) among the quartiles of ApoA1, HDL-C and HDL-C/ApoA1 ratio.

RESULTS

In multivariate analysis, higher ApoA1, HDL-C and HDL-C/ApoA1 ratio were associated with significantly lower HGI (Quartile [Q]4 vs. Q1: -0.032 % vs. 0.017 % for ApoA1; -0.072 % vs. 0.079 % for HDL-C; -0.083 % vs. 0.085 % for HDL-C/ApoA1 ratio). Intermediate ApoA1 level was inversely associated with TyG index (Q2 vs. Q1: 296.278 vs. 306.794). The mean TyG index were significantly decreased with increased HDL-C and HDL-C/ApoA1 ratio (Q4 vs. Q1: 298.584 vs. 309.221 for HDL-C; 300.405 vs. 315.218 for HDL-C/ApoA1 ratio). Moreover, the inverse associations of ApoA1, HDL-C and HDL-C/ApoA1 ratio with HbA1c and FBG also were observed. In path analysis, the associations of HDL-C and HDL-C/ApoA1 ratio with TyG index were mediated by obesity.

CONCLUSION

This study provided further support for the hypoglycemic effects of ApoA1 and HDL-C in patients with CAD. Replication of these findings is warranted in further longitudinal studies in different populations.

The influence of shorter red blood cell lifespan on the rate of HbA1c target achieved in type 2 diabetes patients with a HbA1c detection value lower than 7

BACKGROUND

Variations in the red blood cell (RBC) lifespan can affect glycosylated hemoglobin (HbA1c) test values, but there is still a lack of evidence regarding how and to what degree the RBC lifespan influences HbA1c in the type 2 diabetes mellitus (T2DM) population owing to the restriction of traditional RBC lifespan-detection means. This study aimed to investigate the influence of RBC lifespan variation on HbA1c values in T2DM patients with a HbA1c detection value lower than 7%.

METHODS

Patients with HbA1c <7% were divided into two groups: RBC lifespan <90 days and RBC lifespan ≥90 days. We collected blood glucose levels at seven time points for three consecutive months, assessed the HbA1c and glycosylated albumin levels, and calculated the hemoglobin glycation index (HGI) for each patient.

RESULTS

There were no statistical differences in the HbA1c value between two groups, but the estimated glycosylated hemoglobin (eHbA1c) was significantly higher in patients with an RBC lifespan <90 days. The proportion of the eHbA1c ≥7% in the group with an RBC lifespan <90 days was significantly higher than the other group (33.87% vs. 12.50%, p < .01). Pearson analysis showed a significant negative correlation between RBC lifespan and the HGI in patients with T2DM (r = -0.348, p < .01).

CONCLUSION

A reduced RBC lifespan in T2DM patients caused a noticeable underestimate of the blood glucose levels as presented by HbA1c detection value.

Dietary patterns, oxidative Stress, inflammation and biological variation in hemoglobin A1c: Association and Mediation analysis in a rural community in north China

OBJECTIVE

The aim is to assess the relationship between the hemoglobin glycation index(HGI) and dietary patterns, and investigates whether inflammation and oxidative stress mediate the relationship.

METHODS

Cross-sectional data were collected from 453 dwellers in a Chinese rural community. Diet was assessed using 24 h food recalls. Based on the energy intake ratio from three macronutrients, dietary patterns were identified by cluster analysis. The HGI was defined as the observed HbA1c minus predicted HbA1c. Indicators of inflammation and oxidative stress were assessed.

RESULT

3 dietary patterns were clustered, namely "fat(n = 100)", "balance(n = 186)" and "carbohydrate(n = 167)". The fat dietary patterns had lower HGI than the other two dietary patterns. TNFα was higher in the carbohydrate dietary pattern. Linear regression analysis suggested that the carbohydrate dietary pattern was correlated with higher HGI levels(β = 0.204,95 %CI(0.071,0.338)), compared with the fat dietary pattern. The relationship disappeared after accounting for biomarkers of inflammation and oxidative stress. Mediation analyses indicated that TNFα might explain for 19.15 % effects of the carbohydrate dietary pattern on HGI, compared with the fat dietary pattern.

CONCLUSION

The carbohydrate dietary pattern had positive associations with HGI and TNFα. TNFα partly mediated the relationship between dietary patterns and HGI.

The hemoglobin glycation index predicts the risk of adverse cardiovascular events in coronary heart disease patients with type 2 diabetes mellitus

Background

Previous studies have shown that the hemoglobin glycation index (HGI) can be used as a predictor of diabetic complications. However, limited information is currently available to indicate the correlation between HGI and comorbidity of coronary heart disease (CHD) and diabetes. This study aimed to evaluate the potential of HGI to predict major adverse cardiovascular events (MACEs) in CHD patients with type 2 diabetes mellitus (T2DM) undergoing percutaneous coronary intervention (PCI).

Materials and methods

A total of 918 CHD patients with T2DM were enrolled in a 3-year retrospective cohort study, from December 2017 to December 2020 at the First Affiliated Hospital of Zhengzhou University. Data including fasting blood glucose (FPG/FBG) and glycated hemoglobin A1c (HbA1c) were collected. HGI was calculated as actual measured HbA1c minus predicted HbA1c. Three groups were further divided based on the levels of HGI, including low, medium, and high levels.

Result

Kaplan Meier analysis indicated that elevated HGI was strongly associated with the occurence of MACE (log-rank P < 0.001). Multivariate Cox regression analysis revealed that elevated HGI was an independent risk factor for incident MACE in CHD patients with T2DM [adjusted hazard ratio (HR): 1.473; 95% confidence interval (CI): 1.365-1.589, P < 0.001].

Conclusions

Hemoglobin glycation index is an independent predictor of MACE events in CHD patients with T2DM. High HGI indicates a higher risk of MACE occurrence.

Association of haemoglobin glycation index with outcomes in patients with acute coronary syndrome: results from an observational cohort study in China

BACKGROUND

The hemoglobin glycation index (HGI) is the difference between measured and estimated glycation of hemoglobin. However, there is limited evidence to investigate the HGI and the clinical outcomes of acute coronary syndrome patients. This study aimed to evaluate the association between HGI and the clinical outcomes of acute coronary syndrome (ACS) in a China cohort.

METHOD

This single-center retrospective study was carried out in the Cardiovascular Center of Beijing Friendship Hospital, a total of 11004 consecutive patients with ACS from Dec 2012-Dec 2020 were enrolled in this study. Patients were divided into quintiles according to their HGI levels. The incidence of major adverse cardiac and cerebrovascular events (MACCEs) was recorded.

RESULT

HGI were divided into five quintiles quintiles: -0.906 (-7.188, -0.663), -0.491 (-0.663, -0.343), -0.196 (-0.342, -0.039), 0.170 (-0.039, 0.485), and 1.156 (0.485, 7.875), respectively. Competing risk regression revealed that HGI was positively related to all-cause death, CV death, and composite MACCEs. Multivariate Cox proportional hazards regression analysis indicated that hypertension (HR:1.109, P = 0.013), previous stroke (HR:1.208, P < 0.001), past PCI (HR: 1.268, P < 0.001), age (HR: 1.011, P < 0.001), BMI (HR: 0.987, P = 0.012), heart rate (HR: 1.004, P = 0.001), NSTEMI (HR: 1.205, P < 0.001), WBC (HR: 1.020, P = 0.008), eGFR (HR: 0.993, P < 0.001), HDL-C (HR: 0.809, P = 0.002), LVEF (HR:0.240, P < 0.001), LM/three-vessel or proximal LAD involved (HR: 1.208 P < 0.001; HR:0.914, P = 0.019, respectively), and antiplatelet agents during hospitalization (HR:0.806, P = 0.020) independently predicted the incidence of MACCEs in ACS patients. Restricted cubic spline indicated a U-shaped association between the HGI and risk of MACCEs.

CONCLUSION

Both low HGI and high HGI was associated with an increased risk of adverse outcomes in patients with acute coronary syndrome, compared with moderate HGI.

The Value of Hemoglobin Glycation Index-Diabetes Mellitus System in Evaluating and Predicting Incident Stroke in the Chinese Population

We aimed to clarify the effect of the hemoglobin glycation index (HGI)–diabetes mellitus (DM) system in evaluating the risk of incident stroke. We followed up on 2934 subjects in rural regions of Northeast China, established Cox proportional hazards models to evaluate the effects of the HGI–DM system in describing stroke risk, and further conducted a discrimination analysis to confirm the improvement in HGI based on the traditional stroke risk model. After a median of 4.23 years of follow-up, 79 subjects developed stroke or related death. DM-high HGI condition significantly elevated the risk of incident stroke (hazard ratio (HR): 2.655, 95% confidence interval (CI): 1.251–5.636). In addition, higher HGI levels elevated the risk of stroke, even if the patients did not have DM (HR: 1.701, 95% CI: 1.136–2.792), but DM failed to bring an extra risk of incident stroke to patients with lower HGI levels (HR: 1.138, 95% CI: 0.337–3.847). The discrimination analysis indicated that the integrated discrimination index (IDI) of the HGI model was 0.012 (95% CI: 0.007–0.015) and that the net reclassification index (NRI) was 0.036 (95% CI: 0.0198–0.0522). These results indicated HGI was associated with the onset of stroke, and high HGI indicated an aggravated trend in glycemic status and increased risk of incident stroke. The HGI–DM system enabled us to identify the different glucose statuses of patients, to conduct suitable treatment strategies, as well as to improve the predictability of incident stroke based on the traditional model.

Association of hemoglobin glycation index with cardiovascular risk factors in non-diabetic adults: A cross-sectional study

BACKGROUND AND AIMS

The study aimed to explore the association of hemoglobin glycation index (HGI) with cardiovascular risk factors in non-diabetic adults.

METHODS

This cross-sectional study included 200 adults of 20-60 years of age. Predicted glycated hemoglobin (HbA1c) was calculated from linear regression equation. HGI was calculated using the formula HGI = measured HbA1c- predicted HbA1c. The study subjects were classified into three groups based on their HGI tertiles. Cardiovascular risk factors were compared between the groups and Pearson correlation test was done to correlate HGI with cardiovascular risk factors.

RESULTS

Serum total cholesterol, triglyceride, low density lipoprotein cholesterol (LDL-C) and very low density lipoprotein cholesterol (VLDL-C) showed significant increase with increase in HGI in non diabetic individuals. High HGI group had significantly high serum total cholesterol, triglyceride, LDL-C and VLDL-C compared to low HGI group. Serum total cholesterol, triglyceride, LDL-C and VLDL-C showed a statistically significant positive correlation with HGI.

CONCLUSION

We have found a statistically significant correlation of HGI with serum lipid profile, a significant cardiovascular risk factor in non-diabetic individuals. HGI, a simple derivative of HbA1c and fasting plasma glucose may be used to identify cardiovascular risk in non-diabetic individuals. Further prospective studies are required in larger sample size to confirm the clinical implications of HGI.

Variation in the hemoglobin glycation index

A high hemoglobin glycation index (HGI) has been repeatedly associated with greater risk for hypoglycemia in people with diabetes and greater risk for chronic vascular disease in people with or without diabetes. This review explores how different sources of analytical and biological variation in HbA1c and blood glucose individually and collectively affect the clinical information value of HGI. We conclude that HGI is a complex quantitative trait that is a clinically practical biomarker of risk for both hypoglycemia and chronic vascular disease.

Potential misclassification of diabetes and prediabetes in the U.S.: Mismatched HbA1c and glucose in NHANES 2005-2016

AIMS

To assess the prevalence and clinical implications of "mismatches" between HbA1c and glucose levels in the United States across the life course.

METHODS

Participants ages 12-79 years from U.S. National Health and Nutrition Examination Survey (NHANES) 2005-2016 without known diagnosis of diabetes and who had a 75 g oral glucose tolerance test were included. Previously undiagnosed diabetes (DM), prediabetes, and normal glucose metabolism (NGM) were defined using American Diabetes Association cut-points. Mismatches were defined by the hemoglobin glycation index (HGI).

RESULTS

In 10,361 participants, 5% and 41% had diabetes and prediabetes, respectively, by fasting or 2-hour glucose criteria. By HbA1c criteria, the high HGI tertile consisted of mostly abnormal classification (3% DM, 52% prediabetes) and the low HGI tertile contained mostly normal classification (78% NGM). Across all ages, 15% (weighted: 30 million individuals) had clinically significant mismatches of HGI magnitude ≥+0.5% (i.e., high mismatch) or ≤-0.5% (low mismatch). Mismatch was most common in older adults and non-Hispanic Black participants.

CONCLUSIONS

Mismatches of clinically significant magnitude could lead to HbA1c-related misdiagnosis or inappropriate management in up to 30 million Americans. Older adults, non-Hispanic Black individuals, and others with high mismatches may benefit from complementing HbA1c with additional diagnostic and management strategies.

Hemoglobin glycation index predicts renal function deterioration in patients with type 2 diabetes and a low risk of chronic kidney disease

AIMS

Hemoglobin glycation index (HGI) is used to describe the difference between estimated and measured glycated hemoglobin (HbA_1c). We aimed to study whether HGI can predict renal function deterioration in patients with type 2 diabetes and a low risk of chronic kidney disease (CKD).

METHODS

This retrospective cohort study enrolled 780 patients with type 2 diabetes and a low CKD risk according to the criteria of kidney disease: improving global outcomes. Participants were divided into two subgroups according to the baseline HGI calculated by fasting blood glucose and HbA_1c. Multivariate Cox proportional hazard models were used to evaluate the hazard ratios of the study endpoints. Longitudinal data was analyzed using generalized estimating equation (GEE).

RESULTS

The participants were followed for a median of 7.3 years. A high HGI predicted rapid renal function decline without or with a resultant eGFR < 60 ml/min/1.73 m², but not onset of macroalbuminuria. The longitudinal GEE model demonstrated a negative association between HGI and the predicted eGFR changes in both the 1-year and 3-year intervals.

CONCLUSIONS

HGI independently predicted renal function deterioration in patients with type 2 diabetes and a low CKD risk. Further investigations are warranted to elucidate its potential clinical impact.

Association between hemoglobin glycation index and subclinical myocardial injury in the general population free from cardiovascular disease

BACKGROUND AND AIMS

The relationship between hemoglobin glycation index (HGI) and the diagnosis and prognosis of cardiovascular disease (CVD) has been verified by previous studies. However, it remains unknown whether HGI has a predictive effect on subclinical myocardial injury (SC-MI). The purpose of the present study was to explore the relationship between HGI and SC-MI in the general population free from CVD.

METHODS AND RESULTS

The present study included 6009 participants free of CVD from the third National Health and Nutrition Examination Survey. Binary Logistic regression analysis was used to tested the association between HGI and SC-MI. As results, the HGI was significantly higher in participants with SC-MI compared with those without, and the HGI was positively correlated with SC-MI and other metabolic disorder parameters. Each 1-unit increase of HGI and glycated hemoglobin A1c (HbA1c) was independently associated with higher risk of SC-MI (P < 0.05), while fasting plasma glucose (FPG) was no longer a predictive indicator of SC-MI with the increase of confounding factors [OR (95% CI): 1.001 (0.999-1.003), P = 0.305]. And in the subgroup analysis, HGI, only in participants without diabetes, was independently associated with higher risk of SC-MI, while HbA1c and FPG had no independent predictive role in both diabetic and non-diabetic participants.

CONCLUSIONS

HGI was a significant predictor of SC-MI in the general population free from CVD.

High Hemoglobin Glycation Index Is Associated With Telomere Attrition Independent of HbA1c, Mediated by TNFα

CONTEXT

The hemoglobin glycation index (HGI) is correlated with metabolic diseases and inflammation. Whether the HGI is associated with the aging process and how inflammation and oxidative stress affect the relationship remain unclear.

OBJECTIVE

We aimed to analyze links between the HGI and aging biomarkers, and to explore a potential role of inflammation and oxidative stress in the correlations.

METHODS

A cross-sectional study of 434 subjects with different glucose intolerances in a rural community was enrolled. The HGI was calculated as the difference between the measured and predicted hemoglobin A1c (HbA1c). The population was categorized into tertiles of the HGI. Telomere length (LTL) and mitochondrial DNA copy number (mtDNAcn) determined by polymerase chain reaction assay. Tumor necrosis factor (TNF) α and interleukin (IL) 6, 8-oxo-2'-deoxyguanosine (8-oxo-dG), superoxide dismutase (SOD) activities, and glutathione reductase (GR) were measured.

RESULTS

Participants in the high HGI group were older and reported a shorter LTL, higher levels of TNFα, SOD activities, and HbA1c. Correlation analyses demonstrated that HGI was correlated with LTL (r = -0.25, P < .001) and TNFα (r = 0.19, P < .001) regardless of HbA1c levels. No relationship was found between HGI and mtDNAcn. HGI (β = -0.238, 95% CI -0.430, -0.046, P = .015) and TNFα (β = -0.02, 95% CI -0.030, -0.014, P < .001) were proved to be correlated with LTL independently, using multiple linear regression analysis. Ordinal logistic regression models showed that compared with subjects the high HGI group, the possibilities of a higher-level LTL was 5.29-fold in the low HGI group (OR 5.29, 95% CI (2.45, 11.41), P < .001), 2.41-fold in the moderate HGI group (OR 2.41, 95% CI 1.35, 4.30, P = .003) after controlling for confounding variables. Mediation analyses indicated that TNFα accounted for 30.39% of the effects of the HGI on LTL.

CONCLUSION

HGI was negatively related to telomere attrition, independent of HbA1c. TNFα acted as a mediator of the relationship between HGI and LTL.

Hemoglobin glycation index, calculated from a single fasting glucose value, as a prediction tool for severe hypoglycemia and major adverse cardiovascular events in DEVOTE

INTRODUCTION

Hemoglobin glycation index (HGI) is the difference between observed and predicted glycated hemoglobin A1c (HbA1c), derived from mean or fasting plasma glucose (FPG). In this secondary, exploratory analysis of data from DEVOTE, we examined: whether insulin initiation/titration affected the HGI; the relationship between baseline HGI tertile and cardiovascular and hypoglycemia risk; and the relative strengths of HGI and HbA1c in predicting these risks.

RESEARCH DESIGN AND METHODS

In DEVOTE, a randomized, double-blind, cardiovascular outcomes trial, people with type 2 diabetes received once per day insulin degludec or insulin glargine 100 units/mL. The primary outcome was time to first occurrence of a major adverse cardiovascular event (MACE), comprising cardiovascular death, myocardial infarction or stroke; severe hypoglycemia was a secondary outcome. In these analyses, predicted HbA1c was calculated using a linear regression equation based on DEVOTE data (HbA1c=0.01313 FPG (mg/dL) (single value)+6.17514), and the population data were grouped into HGI tertiles based on the calculated HGI values. The distributions of time to first event were compared using Kaplan-Meier curves; HRs and 95% CIs were determined by Cox regression models comparing risk of MACE and severe hypoglycemia between tertiles.

RESULTS

Changes in HGI were observed at 12 months after insulin initiation and stabilized by 24 months for the whole cohort and insulin-naive patients. There were significant differences in MACE risk between baseline HGI tertiles; participants with high HGI were at highest risk (low vs high, HR: 0.73 (0.61 to 0.87)95% CI; moderate vs high, HR: 0.67 (0.56 to 0.81)95% CI; p<0.0001). No significant differences between HGI tertiles were observed in the risk of severe hypoglycemia (p=0.0911). With HbA1c included within the model, HGI no longer significantly predicted MACE.

CONCLUSIONS

High HGI was associated with a higher risk of MACE; this finding is of uncertain significance given the association of HGI with insulin initiation and HbA1c.

TRIAL REGISTRATION NUMBER

NCT01959529.

Effects of the hemoglobin glycation index on hyperglycemia diagnosis: Results from the REACTION study

AIMS

This study aimed to assess the effects of the hemoglobin glycation index (HGI) on hyperglycemia diagnosis and summarize the general characteristics of patients with a high-HGI phenotype.

METHODS

The fasting plasma glucose and glycated hemoglobin (HbA1c) levels of participants (n = 47,648) were used to estimate a linear regression equation and determine the baseline HGI. Overall, 42,317 participants without a history of diabetes were included in the final analysis. The participants were divided into three groups according to the tertiles (low, moderate, and high) of baseline HGI. Proportions and variables were compared among the three HGI groups. A multivariate ordered logistic regression model was used to explore associations between related variables and the high-HGI phenotype.

RESULTS

Regression analysis indicated that the high-HGI phenotype was positively associated with female sex, advanced age, obesity, increased low-density lipoprotein and triglyceride levels, decreased high-density lipoprotein cholesterol, and postprandial glycemic excursion levels (all P < 0.05). The prevalence of hyperglycemia increased from the low- to the high-HGI groups when using HbA1c for diagnosis.

CONCLUSIONS

Individuals with high HGI have similar clinical characteristics. Measuring HbA1c alone for diagnosis could lead to inappropriate diabetes management decisions in people with low or high HGI.

Standardizing the haemoglobin glycation index

Aims

A high haemoglobin glycation index (HGI) is associated with greater risk for hypoglycaemia and chronic vascular disease. Standardizing how the HGI is calculated would normalize results between research studies and hospital laboratories and facilitate the clinical use of HGI for assessing risk.

Methods

The HGI is the difference between an observed HbA1c and a predicted HbA1c obtained by inserting fasting plasma glucose (FPG) into a regression equation describing the linear relationship between FPG and HbA1c in a reference population. We used data from the 2005–2016 U.S. National Health and Nutrition Examination Survey (NHANES) to identify a reference population of 18,675 diabetes treatment–naïve adults without self‐reported diabetes. The reference population regression equation (predicted HbA1c = 0.024 FPG + 3.1) was then used to calculate the HGI and divide participants into low (<−0.150), moderate (−0.150 to <0.150) and high (≥0.150) HGI subgroups. Diabetes status was classified by OGTTs.

Results

As previously reported in multiple studies, a high HGI was associated with black race independent of diabetes status, and with older age, higher BMI and higher CRP in normal and prediabetic but not diabetic participants. The mean HGI was 0.6% higher in self‐reported diabetic adults. The HGI was not associated with plasma insulin, HOMA‐IR or 2 h OGTT in participants classified as normal, prediabetic or diabetic.

Conclusions

The regression equation derived from this demographically diverse diabetes treatment–naïve adult NHANES reference population is suitable for standardizing how the HGI is calculated for both clinical use and in research to mechanistically explain population variation in the HGI and why a high HGI is associated with greater risk for chronic vascular disease.

Personal Glycation Factors and Calculated Hemoglobin A1c for Diabetes Management: Real-World Data from the Diabetes Prospective Follow-up (DPV) Registry

Background: Glycated hemoglobin A1c (HbA1c) is a key biomarker in the glycemic management of individuals with diabetes, but the relationship with glucose levels can be variable. A recent kinetic model has described a calculated HbA1c (cHbA1c) that is individual specific. Our aim was to validate the routine clinical use of this glucose metric in younger individuals with diabetes under real-life settings. Materials and Methods: We retrieved HbA1c and glucose data from the German-Austrian-Swiss-Luxembourgian diabetes follow-up (DPV) registry, which covers pediatric individuals with type 1 diabetes (T1D). The new glycemic measure, cHbA1c, uses two individual parameters identified by data sections that contain continuous glucose data between two laboratory HbA1c measurements. The cHbA1c was prospectively validated using longitudinal HbA1c data. Results: Continuous glucose monitoring data from 352 T1D individuals in 13 clinics were analyzed together with HbA1c that ranged between 4.9% and 10.6%. In the prospective analysis, absolute deviations of estimated HbA1c (eHbA1c), glucose management indicator (GMI), and cHbA1c compared with laboratory HbA1c were (median [interquartile range]): 1.01 (0.50, 1.75), 0.46 (0.21, 084) and 0.26 (0.12, 0.46), giving an average bias of 0.6, 0.4 and 0.0, respectively, in National Glycohemoglobin Standardization Program (NGSP) % unit. For eHbA1c and GMI only 25% and 54% of subjects were within ±0.5% of laboratory HbA1c values, whereas 82% of cHbA1c were within ±0.5% of laboratory HbA1c results. Conclusions: Our data show the superior performance of cHbA1c compared with eHbA1c and GMI at reflecting laboratory HbA1c. These data indicate that cHbA1c can be potentially used instead in laboratory HbA1c, at least in younger individuals with T1D.

Association Between Hemoglobin Glycation Index and Risk of Cardiovascular Disease and All Cause Mortality in Type 2 Diabetic Patients: A Meta-Analysis

Background: The hemoglobin glycation index (HGI) has been proposed as a marker to quantify inter-individual variation in hemoglobin glycosylation. However, whether HGI is associated with an increased risk of diabetic complications independent of glycated hemoglobin (HbA1c) remains unclear. This meta-analysis aimed to determine the association between HGI and the risk of all cause mortality and composite cardiovascular disease (CVD).

Methods: PubMed, and EMBASE databases were searched for related studies up to March 31, 2021. Observational studies reported associations between HGI levels and composite CVD and all cause mortality were included for meta-analysis. A random effect model was used to calculate the hazard ratios (HRs) and 95% confidence intervals (CI) for higher HGI.

Results: A total of five studies, comprising 22,035 patients with type two diabetes mellitus were included for analysis. The median follow-up duration was 5.0 years. After adjusted for multiple conventional cardiovascular risk factors, an increased level of HGI was associated with a higher risk of composite CVD (per 1 SD increment: HR = 1.14, 95% CI = 1.04–1.26) and all cause mortality (per 1 SD increment: HR = 1.18, 95% CI = 1.05–1.32). However, when further adjusted for HbA1c, the association between HGI and risk of composite CVD (per 1 SD increment of HGI: HR = 1.01, 95% CI = 0.93–1.10) and all cause mortality (per 1 SD increment of HGI: HR = 1.03, 95% CI = 0.96–1.10) became insignificant.

Conclusions: High HGI was associated with an increased risk of composite CVD and all cause mortality after adjustment for multiple conventional cardiovascular risk factors. However, the association was mainly mediating by the level of HbA1c.

Integrated Strategy for Discovery and Validation of Glycated Candidate Biomarkers for Hemodialysis Patients with Cardiovascular Complications

Glycation plays a pathogenic role in many age-related degenerative pathological conditions, such as diabetes, end-stage renal diseases, and cardiovascular diseases. Mass spectrometry-based qualitative and quantitative analysis methods have been greatly developed and contribute to our understanding of protein glycation. However, it is still challenging to sensitively and accurately quantify endogenous glycated proteome in biological samples. Herein, we proposed an integrated and robust quantitative strategy for comprehensive profiling of early-stage glycated proteome. In this strategy, a filter-assisted sample preparation method was applied to reduce sample loss and improve reproducibility of sample preparation, contributing to high-throughput analysis and accurate quantification of endogenous glycated proteins with low abundance. Standard glycated peptides were spiked and performed the subsequent process together with complex samples both in label-free quantification and multiple reaction monitoring (MRM) analysis, contributing to the improvement of quantitative accuracy. In parallel, a novel approach was developed for the synthesis of heavy isotope-labeled glycated peptides used in MRM analysis. By this way, a total of 1128 endogenous glycated peptides corresponding to 203 serum proteins were identified from 60 runs of 10 pairs of hemodialysis patients with and without cardiovascular complications, and 234 glycated peptides corresponding to 63 proteins existed in >70% runs, among which 17 peptides were discovered to be differentially glycated (P < 0.05, fold-change > 1.5 or <0.67). Furthermore, we validated the glycation difference of four target peptides in 46 serum samples using MRM analysis, which were consistent with our results of label-free quantification.

Postchallenge glucose increment was associated with hemoglobin glycation index in subjects with no history of diabetes

We investigated the association between postchallenge glucose increment and hemoglobin glycation index (HGI), the difference between observed and predicted glycated hemoglobin (HbA1c), in subjects with no history of diabetes. We enrolled 1381 subjects who attended our outpatient clinic for an oral glucose tolerance test (OGTT) to screen for diabetes. HGI was defined as observed HbA1c minus predicted HbA1c. The predicted HbA1c was calculated by entering fasting plasma glucose (FPG) level into an equation [HbA1c(%)=FPG(mg/dL)*0.029+2.9686] determined from an HbA1c versus FPG regression analysis using data from an independent cohort of 2734 subjects with no history of diabetes. The association between 2-hour glucose increment and HGI was analyzed using linear regression analyses with adjustment of relevant parameters. Overall, the proportions of subjects with normal glucose tolerance, pre-diabetes, and newly diagnosed diabetes were 42.3%, 41.3%, and 16.4%, respectively. Compared with subjects who had an HGI≤0, subjects with an HGI>0 had a lower FPG (95.0±13.3 vs 98.5±15.3 mg/dL, p<0.001) but a higher 2-hour plasma glucose (151.1±52.8 vs 144.6±51.4 mg/dL, p=0.027) and 2-hour glucose increment (56.1±46.1 vs 46.1±45.0 mg/dL, p<0.001). The 2-hour glucose increment after an OGTT was independently associated with HGI (β coefficient 0.003, 95% CI 0.002 to 0.003, p<0.001). Our findings suggested that postchallenge glucose increment was independently associated with HGI in subjects with no history of diabetes.

Hemoglobin glycation index is associated with incident chronic kidney disease in subjects with impaired glucose metabolism: A 10-year longitudinal cohort study

AIM

We investigated the associations between hemoglobin glycation index (HGI) and incident chronic kidney disease (CKD) in treatment-naïve subjects with prediabetes or diabetes.

METHODS

We conducted a prospective cohort study comprising 2187 subjects with prediabetes or diabetes. HGI was calculated as the difference between the measured and predicted values of HbA1c using the linear relationship between HbA1c level and fasting plasma glucose levels. Incident CKD was considered if eGFR decreased to <60 mL/min/1.73 m² and by >25% from the baseline value during follow up. The hazard ratios (HRs) for incident CKD were calculated using Cox proportional hazards regression models.

RESULTS

The overall prevalence of CKD was 15.3% (n = 335) during the 10-year follow-up period. The prevalence of CKD increased significantly from the low to the high HGI groups. In the multivariate analysis, the highest HGI group showed the highest adjusted HR for incident CKD (HR, 1.57; 95% confidence interval, 1.06-2.34), and this remained significant even after adjusting for the HbA1c level.

CONCLUSIONS

High HGI was associated with an increased risk of incident CKD among treatment-naïve subjects with prediabetes or diabetes, suggesting that HGI may be used to predict CKD in these patients regardless of HbA1c levels.

The Relationship Between Hemoglobin Glycation Variation Index and Vitamin D in Type 2 Diabetes Mellitus

OBJECTIVE

This study aimed to investigate the relationship between hemoglobin glycation variation index (HGI) and vitamin D in patients with type 2 diabetes mellitus (T2DM).

MATERIALS AND METHODS

This is a cross-sectional study that recruited 347 patients with T2DM. The subjects were divided into no vitamin D deficiency group (25(OH)D ≥20 ng/mL) and vitamin D deficiency group (25(OH)D < 20 ng/mL). HGI was calculated as the difference between the measured and predicted values of HbA1c using the linear relationship between HbA1c level and fasting plasma glucose levels. All study participants were divided into high HGI and low HGI groups using the median of HGI as the boundary. At last, the subjects were divided into male group and female group, and these groups were further subdivided into vitamin D deficiency group and no vitamin D deficiency group.

RESULTS

The levels of HGI were significantly higher in the vitamin D deficiency group compared with the no vitamin D deficiency group for all patients. The same was true for female patients but not for male patients. The prevalence of vitamin D deficiency in the high HGI group was higher than that in the low HGI group. The high HGI group had lower vitamin D levels compared to the low HGI group. Compared to the male group, the female group had lower vitamin D levels but higher HGI levels. A negative correlation existed between 25(OH) D and HGI in all subjects, as well as in the female-only subgroups. In the male-only subgroups, there was no correlation between them, and this positive correlation still existed after adjusting for other factors in multilinear regression analysis.

CONCLUSION

Our study showed for the first time that HGI is inversely associated with vitamin D in all patients with T2DM, and the correlation was also found in female patients, but not in male patients.

Association of hemoglobin glycation index and its interaction with obesity/family history of hypertension on hypertension risk: a community-based cross-sectional survey

Background

Hemoglobin glycation index (HGI) is considered to be a convenient measurable indicator to assess the inter-individual variation of HbA1c. In the present study, we tested the relationship between HGI and risk of hypertension, and further explored the possible interacting influences of HGI with other such factors on hypertension risk among Chinese individuals.

Methods

The eligible subjects were chosen from a community-based cross-sectional survey in China. We collected relevant data and clinical indicators for each participant. HGI was calculated as “measured HbA1c-predicted HbA1c” and divided into four categories according to quartile. The following indicators were used to assess interactive effects: (1) relative excess risk due to interaction (RERI); (2) attributable proportion due to interaction (AP); and (3) synergy index (SI). Statistical analysis was performed using R software.

Results

Specifically, 1777 eligible participants were selected in this cross-sectional survey. There were 433 subjects who were identified to have hypertension (24.4%). A significant increase in the prevalence of hypertension from Q1 to Q4 of HGI was observed (p < 0.001). Multivariable logistic model demonstrated that subjects at the highest HGI group had a substantially increased risk of being hypertensive than subjects in the first quartile of HGI, as indicated by the OR value of 1.87 (95% CI 1.26–2.78). Moreover, a significant interaction between family history of hypertension and HGI on hypertension risk was detected (RERI: 1.36, 95% CI 0.11–2.63; AP: 0.43, 95% CI 0.17–0.69; and SI:2.68, 95% CI 1.10–6.48). The interactive effect between HGI and abdominal obesity was also found to be significant, as estimated by the value of RERI (1.04, 95% CI 0.24–1.85), AP (0.33, 95% CI 0.11–0.56) and SI (1.96, 95% CI 1.01–3.79). However, in the analysis of the interaction between HGI and general obesity, only the AP value (0.28, 95% CI 0.01–0.54) was observed to be significant.

Conclusion

High HGI was independently associated with the risk of hypertension. Moreover, HGI significantly shared interactions with obesity and family history of hypertension that influenced the risk of hypertension.

Prediabetes Deserves More Attention: A Review

Evidence increasingly demonstrates that prediabetes is a toxic state, as well as a risk factor for diabetes, and is associated with pathophysiological changes in several tissues and organs. Unfortunately, use of available evidence-based treatments for prediabetes is low. This review seeks to explain why prediabetes must be viewed and treated as a serious pathological entity in its own right. It offers an overview of the pathophysiology and complications of prediabetes and describes how this condition can be reversed if all treatment avenues are deployed early in its course.

Hemoglobin glycation index in relationship to the risk of cardiovascular complication in patients with type 2 diabetes: A systematic review and meta-analysis

AIM

To estimate the association of hemoglobin glycation index (HGI) level with total mortality and cardiovascular complication risk among patients with T2DM.

METHODS

Literatures evaluating the associations of HGI with the risk of cardiovascular outcomes and total mortality in patients with T2DM were systematically searched by using the PubMed and Embase databases from January 2002 to April 2019. Fixed-effects model and random-effects model meta-analyses were used to calculate pooled adjusted hazard ratios (HRs).

RESULTS

Six prospective cohort studies and one nest case-control study (comprising n = 37,280) were included in this systematic review. T2DM patients with high HGI level had significant high HRs (95% confidence interval, 95% CI) for cardiovascular complication [1.25 (1.16, 1.36)] and total mortality [1.26 (1.14, 1.39)] compared to intermediate HGI level. For every 1-unit increment in HGI, the average HR (95% CI) were 1.20 (1.00, 1.41) for cardiovascular complication and 1.13 (1.06, 1.19) for total mortality.

CONCLUSIONS

The findings suggested that a rising HGI level was associated with the increased risk for cardiovascular complication and total mortality among patients with T2DM.

High hemoglobin glycation index is associated with increased systemic arterial stiffness independent of hyperglycemia in real-world Japanese population: A cross-sectional study

AIMS

To investigate the association of metabolic parameters including hemoglobin glycation index (HGI, observed HbA1c - predicted HbA1c) with systemic arterial stiffness assessed by cardio-ankle vascular index (CAVI).

SUBJECTS

We analyzed the cross-sectional data from 22,696 subjects (mean age 48.0 years, mean FPG 88 mg/dL, mean HbA1c 5.5%) with or without past history of metabolic disorders including diabetes.

RESULTS

Men had higher body mass index (BMI), CAVI, blood pressure (BP), FPG, HbA1c, total cholesterol and triglyceride; and lower age, HGI and HDL-cholesterol. After stratifying subjects into HGI quartiles, the highest quartile (Q4) group showed higher age, female ratio, and frequencies of obesity, hypertension, diabetes, and dyslipidemia. Furthermore, bivariate logistic regression model revealed that the Q4 of HGI was a significant predictor of high CAVI (⩾9.0) independent of the presence of diabetes.

CONCLUSION

High HGI is associated with systemic arterial stiffening independent of hyperglycemia. This index is therefore expected to be not only a predictor of hypoglycemia, but also a therapeutic guide for atherosclerosis.

Comprehensive Isotopic Targeted Mass Spectrometry: Reliable Metabolic Flux Analysis with Broad Coverage

Metabolic flux analysis (MFA) is highly relevant to understanding metabolic mechanisms of various biological processes. While the pace of methodology development in MFA has been rapid, a major challenge the field continues to witness is limited metabolite coverage, often restricted to a small to moderate number of well-known compounds. In addition, isotopic peaks from an enriched metabolite tend to have low abundances, which makes liquid chromatography tandem mass spectrometry (LC-MS/MS) highly useful in MFA due to its high sensitivity and specificity. Previously we have built large-scale LC-MS/MS approaches that can be routinely used for measurement of up to ∼1,900 metabolite/feature levels [Gu et al. Anal. Chem. 2015, 87, 12355-12362. Shi et al. Anal. Chem. 2019, 91, 13737-13745.]. In this study, we aim to expand our previous studies focused on metabolite level measurements to flux analysis and establish a novel comprehensive isotopic targeted mass spectrometry (CIT-MS) method for reliable MFA analysis with broad coverage. As a proof-of-principle, we have applied CIT-MS to compare the steady-state enrichment of metabolites between Myc(oncogene)-On and Myc-Off Tet21N human neuroblastoma cells cultured with U-13C6-glucose medium. CIT-MS is operationalized using multiple reaction monitoring (MRM) mode and is able to perform MFA of 310 identified metabolites (142 reliably detected, 46 kinetically profiled) selected from >35 metabolic pathways of strong biological significance. Further, we developed a novel concept of relative flux, which eliminates the requirement of absolute quantitation in traditional MFA and thus enables comparative MFA under the pseudosteady state. As a result, CIT-MS was shown to possess the advantages of broad coverage, easy implementation, fast throughput, and more importantly, high fidelity and accuracy in MFA. In principle, CIT-MS can be easily adapted to track the flux of other labeled tracers (such as 15N-tracers) in any metabolite detectable by LC-MS/MS and in various biological models (such as mice). Therefore, CIT-MS has great potential to bring new insights to both basic and clinical metabolism research.

Applications and pitfalls of hemoglobin A1C and alternative methods of glycemic monitoring

INTRODUCTION

Intensive glycemic control minimizes the risks of microvascular complications in diabetes. A1C is a convenient estimate of mean blood glucose, but is not the only marker available. The practical use and limitations of alternative markers and continuous glucose monitors are the focus of this review.

METHODS

PubMed and the Cochrane Library were searched for studies concerning applications or limitations of A1C, fructosamine, glycated albumin, 1,5-anhydroglucitol, skin autofluorescence, and continuous glucose monitoring. Papers reporting on strengths, limitations, or comparisons of these methods were reviewed for inclusion.

RESULTS

A1C reflects three months of glycemic control and is not an ideal marker in all patient populations. Fructosamine and glycated albumin reflect mean blood glucose over three weeks. 1,5-Anhydroglucitol can measure hyperglycemic excursions in days to weeks. Continuous glucose monitors provide immediate feedback for timely intervention to reduce glycemic excursions and can assess glycemic variability. Current barriers to continuous glucose monitor use include inexperience, cost, discomfort, and medication interference.

CONCLUSIONS

Many promising alternative glycemic markers exist. The main limitations for all alternative methods of glycemic monitoring are a lack of standardization for clinically useful cut-offs or guidelines, and a lack of long-term data on their association with complications, particularly in varied patient populations.

Relationships between Thigh and Waist Circumference, Hemoglobin Glycation Index, and Carotid Plaque in Patients with Type 2 Diabetes

BACKGROUND

This study investigated the relationships of thigh and waist circumference with the hemoglobin glycation index (HGI) and carotid atherosclerosis in patients with type 2 diabetes.

METHODS

This observational study included 3,075 Korean patients with type 2 diabetes, in whom anthropometric measurements and carotid ultrasonography were conducted. HGI was defined as the measured hemoglobin A1c (HbA1c) level minus the predicted HbA1c level, which was calculated using the linear relationship between HbA1c and fasting plasma glucose levels. Carotid atherosclerosis was defined as a clearly isolated focal plaque or focal wall thickening &gt;50% of the surrounding intima-media thickness.

RESULTS

The frequency of a positive HGI decreased with increasing thigh circumference in men and increased with increasing waist circumference in women after adjusting for potential confounding variables. Thigh and waist circumference had a combined augmentative effect on the likelihood of positive HGI, which was dramatically higher in patients in higher waist-to-thigh ratio quartiles (adjusted odds ratios for the highest compared to the lowest quartile: 1.595 in men and 1.570 in women). Additionally, the larger the thigh circumference, the lower the risk of carotid atherosclerosis, although in women, this relationship lacked significance after adjustment for potential confounders.

CONCLUSION

HGI was associated with thigh circumference in men and waist circumference in women. In addition, the combination of low thigh circumference and high waist circumference was strongly associated with a higher HGI in Korean patients with type 2 diabetes. In particular, thigh circumference was associated with carotid atherosclerosis in men. However, further longitudinal studies are warranted.

Consistency of the Glycation Gap with the Hemoglobin Glycation Index Derived from a Continuous Glucose Monitoring System

BACKGROUND

Discordances between glycated hemoglobin (HbA1c) levels and glycemic control are common in clinical practice. We aimed to investigate the consistency of the glycation gap with the hemoglobin glycation index (HGI).

METHODS

From 2016 to 2019, 36 patients with type 2 diabetes were enrolled. HbA1c, glycated albumin (GA), and fasting blood glucose levels were simultaneously measured and 72-hour continuous glucose monitoring (CGM) was performed on the same day. Repeated tests were performed at baseline and 1 month later, without changing patients' diabetes management. The HGI was calculated as the difference between the measured HbA1c and the predicted HbA1c that was derived from CGM. The glycation gap was calculated as the difference between the measured and GA-based predicted HbA1c levels.

RESULTS

Strong correlations were found between the mean blood glucose (MBG)-based HGI and the prebreakfast glucose-based HGI (r=0.867, P&lt;0.001) and between the glycation gap and the MBG-based HGI (r=0.810, P&lt;0.001). A close correlation was found between the MBG-based HGI at baseline and that after 1 month (r=0.729, P&lt;0.001), with a y-intercept of 0 and a positive slope.

CONCLUSION

The HGI and glycation gap were highly reproducible, and the magnitudes of repeated determinations were closely correlated. Patients with similar mean glucose levels may have significantly different HbA1c levels.

Impact of mismatches in HbA1c vs glucose values on the diagnostic classification of diabetes and prediabetes

AIMS

To determine whether HbA_1c mismatches (HbA_1c levels that are higher or lower than expected for the average glucose levels in different individuals) could lead to errors if diagnostic classification is based only on HbA_1c levels.

METHODS

In a cross-sectional study, 3106 participants without known diabetes underwent a 75-g oral glucose tolerance test (fasting glucose and 2-h glucose) and a 50-g glucose challenge test (1-h glucose) on separate days. They were classified by oral glucose tolerance test results as having: normal glucose metabolism; prediabetes; or diabetes. Predicted HbA_1c was determined from the linear regression modelling the relationship between observed HbA_1c and average glucose (mean of fasting glucose and 2-h glucose from the oral glucose tolerance test, and 1-h glucose from the glucose challenge test) within oral glucose tolerance test groups. The haemoglobin glycation index was calculated as [observed - predicted HbA_1c ], and divided into low, intermediate and high haemoglobin glycation index mismatch tertiles.

RESULTS

Those participants with higher mismatches were more likely to be black, to be men, to be older, and to have higher BMI (all P<0.001). Using oral glucose tolerance test criteria, the distribution of normal glucose metabolism, prediabetes and diabetes was similar across mismatch tertiles; however, using HbA_1c criteria, the participants with low mismatches were classified as 97% normal glucose metabolism, 3% prediabetes and 0% diabetes, i.e. mostly normal, while those with high mismatches were classified as 13% normal glucose metabolism, 77% prediabetes and 10% diabetes, i.e. mostly abnormal (P<0.001).

CONCLUSIONS

Measuring only HbA_1c could lead to under-diagnosis in people with low mismatches and over-diagnosis in those with high mismatches. Additional oral glucose tolerance tests and/or fasting glucose testing to complement HbA_1c in diagnostic classification should be performed in most individuals.

Implications of the Hemoglobin Glycation Index on the Diagnosis of Prediabetes and Diabetes

OBJECTIVE

Fasting plasma glucose (FPG), 2-hour plasma glucose (2hPG) from a 75-g oral glucose tolerance test (OGTT) and glycated hemoglobin (HbA1c) can lead to different results when diagnosing prediabetes and diabetes. The Hemoglobin Glycation Index (HGI) quantifies the interindividual variation in glycation resulting in discrepancies between FPG and HbA1c. We used data from the Vitamin D and Type 2 Diabetes (D2d) study to calculate HGI, to identify HGI-associated variables, and to determine how HGI affects prediabetes and diabetes diagnosis.

MEASUREMENTS

A linear regression equation [HbA1c (%) = 0.0164 × FPG (mg/dL) + 4.2] was derived using the screening cohort (n = 6829) and applied to calculate predicted HbA1c. This was subtracted from the observed HbA1c to determine HGI in the baseline cohort with 2hPG data (n = 3945). Baseline variables plus prediabetes and diabetes diagnosis by FPG, HbA1c, and 2hPG were compared among low, moderate, and high HGI subgroups.

RESULTS

The proportion of women and Black/African American individuals increased from low to high HGI subgroups. Mean FPG decreased and mean HbA1c increased from low to high HGI subgroups, consistent with the HGI calculation; however, mean 2hPG was not significantly different among HGI subgroups.

CONCLUSIONS

High HGI was associated with Black race and female sex as reported previously. The observation that 2hPG was not different across HGI subgroups suggests that variation in postprandial glucose is not a significant source of population variation in HGI. Exclusive use of HbA1c for diagnosis will classify more Black individuals and women as having prediabetes compared with using FPG or 2hPG.

Favorable Glycemic Control with Once-Daily Insulin Degludec/Insulin Aspart after Changing from Basal Insulin in Adults with Type 2 Diabetes

BACKGROUND

Conflicting results have been reported on the efficacy of insulin degludec/insulin aspart (IDegAsp) compared to basal insulin in type 2 diabetes. We investigated the effects of changing basal insulin to IDegAsp on glycemic control and sought to identify factors related to those effects.

METHODS

In this retrospective study of patients from three referral hospitals, patients with type 2 diabetes using basal insulin with hemoglobin A1c (HbA1c) levels less than 11.0% were enrolled. Basal insulin was replaced with IDegAsp, and data were analyzed from 3 months before to 3 months after the replacement.

RESULTS

Eighty patients were recruited (52.5% male; mean age, 67.0±9.8 years; mean duration of diabetes, 18.9±8.5 years; mean HbA1c, 8.7%±1.0%). HbA1c levels increased during 3 months of basal insulin use, but significantly decreased after changing to IDegAsp (8.28%±1.10%, P=0.0001). The reduction was significant at 6 months in 35 patients whose longer-term data were available. Patients with a measured fasting plasma glucose (m-FPG) lower than their predicted FPG (p-FPG) by regression from HbA1c showed a significant HbA1c reduction caused by the change to IDegAsp, even without a significantly increased insulin dose. However, patients whose m-FPG was higher than their p-FPG did not experience a significant HbA1c reduction, despite a significantly increased insulin dose. Furthermore, the HbA1c reduction caused by IDegAsp was significant in patients with low fasting C-peptide levels and high insulin doses.

CONCLUSION

We observed a significant glucose-lowering effect by replacing basal insulin with IDegAsp, especially in patients with a lower m-FPG than p-FPG.

An elevated glycemic gap predicts adverse outcomes in diabetic patients with necrotizing fasciitis

Background

Diabetes is the most common comorbidity of necrotizing fasciitis (NF), but the effect of stress-induced hyperglycemia (SIH) on diabetic patients with NF has never been investigated. The aim of this study was to assess whether SIH, as determined by the glycemic gap between admission glucose levels and A_1C-derived average glucose levels, predicts adverse outcomes in diabetic patients hospitalized with NF.

Methods

We retrospectively reviewed the glycemic gap and clinical outcomes in 252 diabetic patients hospitalized due to NF from 2011 to 2018 in a single medical center in Taiwan. A receiver operating characteristic (ROC) curve was used to analyze the optimal cutoff values for predicting adverse outcomes. Univariate and multivariate logistic regression analyses were employed to identify significant predictors of adverse outcomes.

Results

In total, 194 diabetic NF patients were enrolled. Compared with patients without adverse outcomes, patients with adverse outcomes had significantly higher glycemic gaps, Acute Physiology and Chronic Health Evaluation (APACHE) II scores and C-reactive protein (CRP) levels; lower albumin and hemoglobin levels; greater incidence of limb loss; and longer hospital and intensive care unit stays. The glycemic gap positively correlates with the laboratory risk indicator for NF scores, APACHE II scores and CRP levels. A glycemic gap of 146 mg/dL was the optimal cutoff value for predicting adverse outcomes using the ROC curve. Compared with patients with glycemic gaps ≤146 mg/dL, those with glycemic gaps >146 mg/dL had higher APACHE II scores and incidence rates of adverse outcomes, especially bacteremia and acute kidney injury. Multivariate analysis revealed that a glycemic gap >146 mg/dL and APACHE II score >15 were independent predictors of adverse outcomes, while the presence of hyperglycemia at admission was not.

Conclusions

An elevated glycemic gap was significantly independently associated with adverse outcomes in diabetic NF patients. Further prospective studies are warranted to validate the role of the glycemic gap in NF patients with diabetes.

Potential Clinical Error Arising From Use of HbA1c in Diabetes: Effects of the Glycation Gap

The glycation gap (GGap) and the similar hemoglobin glycation index (HGI) define consistent differences between glycated hemoglobin and actual glycemia derived from fructosamine or mean blood glucose, respectively. Such a disparity may be found in a substantial proportion of people with diabetes, being >1 U of glycated HbA1c% or 7.2 mmol/mol in almost 40% of estimations. In this review we define these indices and explain how they can be calculated and that they are not spurious, being consistent in individuals over time. We evaluate the evidence that GGap and HGI are associated with variation in risk of complications and mortality and demonstrate the potential for clinical error in the unquestioning use of HbA1c. We explore the underlying etiology of the variation of HbA1c from mean glucose in blood plasma, including the potential role of enzymatic deglycation of hemoglobin by fructosamine-3-kinase. We conclude that measurement of GGap and HGI are important to diabetes clinicians and their patients in individualization of therapy and the avoidance of harm arising from consequent inappropriate assessment of glycemia and use of therapies.

The haemoglobin glycation index is associated with nonalcoholic fatty liver disease in healthy subjects

OBJECTIVES

The hemoglobin glycation index (HGI) quantifies interindividual variations in glycated hemoglobin (HbA1c) and is associated with diabetic complications and metabolic diseases. However, information on the association between HGI and non-alcoholic fatty liver disease (NAFLD) in healthy subjects is limited, particularly in Asian populations. This study aimed to investigate the association between HGI and NAFLD in a healthy Korean cohort.

DESIGN

Subjects were stratified in quartiles according to their HGI level. NAFLD was diagnosed by hepatic ultrasonography, hepatic steatosis index and fatty liver index. Multiple logistic regression analysis was performed to evaluate the association between HGI quartiles and the risk of NAFLD.

PATIENTS

Data from subjects without diabetes who underwent liver ultrasonography during routine health examinations were retrospectively reviewed.

RESULTS

Data from 14 465 subjects were included in the analysis. The prevalence of NAFLD increased significantly with each HGI quartile (24.8%, 29.7%, 32.6% and 40.6% in quartiles 1-4, respectively; P < 0.001). In comparison with the lowest HGI quartile group, the highest quartile exhibited worse metabolic parameters, including body weight, waist circumference, body mass index and lipid profiles. Multiple logistic regression analysis adjusted for multiple factors showed that the odds ratio of having NAFLD was 1.564 (95% CI: 1.350-1.813, P < 0.001) in the highest HGI quartile.

CONCLUSIONS

Elevated HGI levels are independently associated with NAFLD in a healthy Asian population.

Association between hemoglobin glycation index and cardiometabolic risk factors in Korean pediatric nondiabetic population

PURPOSE

The hemoglobin glycation index (HGI) represents the degree of nonenzymatic glycation and has been positively associated with cardiometabolic risk factors (CMRFs) and cardiovascular disease in adults. This study aimed to investigate the association between HGI, components of metabolic syndrome (MS), and alanine aminotransferase (ALT) in a pediatric nondiabetic population.

METHODS

Data from 3,885 subjects aged 10-18 years from the Korea National Health and Nutrition Examination Survey (2011-2016) were included. HGI was defined as subtraction of predicted glycated hemoglobin (HbA1c) from measured HbA1c. Participants were divided into 3 groups according to HGI tertile. Components of MS (abdominal obesity, fasting glucose, triglycerides, high-density lipoprotein cholesterol, and blood pressure), and proportion of MS, CMRF clustering (≥2 of MS components), and elevated ALT were compared among the groups.

RESULTS

Body mass index (BMI) z-score, obesity, total cholesterol, ALT, abdominal obesity, elevated triglycerides, and CMRF clustering showed increasing HGI trends from lower-to-higher tertiles. Multiple logistic regression analysis showed the upper HGI tertile was associated with elevated triglycerides (odds ratio, 1.65; 95% confidence interval, 1.18-2.30). Multiple linear regression analysis showed HGI level was significantly associated with BMI z-score, HbA1c, triglycerides, and ALT. When stratified by sex, age group, and BMI category, overweight/obese subjects showed linear HGI trends for presence of CMRF clustering and ALT elevation.

CONCLUSION

HGI was associated with CMRFs in a Korean pediatric population. High HGI might be an independent risk factor for CMRF clustering and ALT elevation in overweight/obese youth. Further studies are required to establish the clinical relevance of HGI for cardiometabolic health in youth.

Triglyceride glucose and haemoglobin glycation index for predicting outcomes in diabetes patients with new-onset, stable coronary artery disease: a nested case-control study

AIM

Previous studies have shown that both triglyceride glucose (TyG) and haemoglobin glycation indexes (HGI) are predictors of cardiovascular risk. However, the prognostic value of TyG index and HGI in patients with type 2 diabetes mellitus (T2DM) and stable coronary artery disease (CAD) is not determined.

METHODS

We conducted a nested case-control study among 1282 T2DM patients with stable CAD. Patients were followed up for 3846 person-years. A total of 160 patients with events (12.5%) were identified and matched individually on age, gender, previous use of lipid lowering agents and duration of follow-up with 640 controls.

RESULTS

In Kaplan-Meier analysis, the upper tertiles of TyG index and HGI had a significant lower event-free survival (p = .002; p = .036, respectively). Of the note, both TyG index and HGI were associated with increased risk of MACCEs after adjusting for confounding risk factors [adjusted HR (95% CI): 1.693 (1.238-2.316); 1.215 (1.046-1.411), respectively]. Moreover, adding TyG index to the Cox model increased the C-statistic to 0.638 (95%CI: 0.595-0.683, p = .002) while the C-statistic was not statistically improved when HGI was included (p = .240).

CONCLUSIONS

Both TyG index and HGI could predict cardiovascular outcomes in T2DM patients with new-onset, stable CAD while TyG index might be better. Key messages Both TyG and HGI are predictors of cardiovascular risk. The prognostic value of TyG index and HGI in T2DM patients with stable coronary artery disease is not determined. Our study firstly indicates that TyG index might have better prognostic value than HGI in T2DM patients with new-onset, stable CAD.

Hemoglobin glycation index predicts cardiovascular disease in people with type 2 diabetes mellitus: A 10-year longitudinal cohort study

BACKGROUND AND AIMS

Previous studies have suggested that the hemoglobin glycation index (HGI) can be used as a predictor of diabetes-related complications. We examined the prognostic significance of a high HGI for cardiovascular disease (CVD) in an ongoing hospital-based cohort.

METHODS

From March 2003 to December 2004, 1302 consecutive patients with type 2 diabetes and without a prior history of CVD were enrolled. CVD was defined as the occurrence of coronary artery disease or ischemic stroke. The HGI was calculated as the measured glycated hemoglobin (HbA1c) minus predicted HbA1c. Predicted HbA1c were calculated for 1302 participants by inserting fasting blood glucose (FBG) into the equation, Predicted HbA1c level = 0.02106 × FBG [mg/dL] + 4.973. Cox proportional hazards models were used to identify the associations between the HGI and CVD after adjusting for confounding variables.

RESULTS

During 11.1 years of follow-up, 225 participants (17.2%) were newly diagnosed with CVD. The baseline HGI was significantly higher in subjects with incident CVD than in those without CVD, although the baseline FBG levels did not differ according to the occurrence of CVD. Compared with patients without CVD, those with CVD were older, had a longer duration of diabetes and hypertension, and used more insulin at baseline. A Cox hazard regression analysis revealed that the development of CVD was significantly associated with baseline HGI (hazard ratio [HR], 1.94; 95% confidence interval [CI], 1.31-2.87; p < 0.001, comparing the highest and lowest quartiles of HGI). This relationship was unchanged after additional adjustment for baseline HbA1c level (HR, 1.74; 95% CI, 1.08-2.81). The HRs of HbA1c in relation to outcomes were similar to or lower than those seen for HGI. After adjustment for HGI, the effect of the highest HbA1c on incident CVD disappeared.

CONCLUSIONS

High HGI was independently associated with incident CVD in patients with type 2 diabetes. Patients with high HGI at baseline had a higher inherent risk for CVD.

Role of Ligands of Receptor for Advanced Glycation End Products (RAGE) in Peripheral Artery Disease

Atherosclerotic cardiovascular disease, including peripheral artery disease (PAD), is more common and severe in diabetic patients compared with nondiabetic individuals. Indeed, diabetes is associated with the increased risk of limb amputation and all-cause mortality in patients with symptomatic PAD. Proteins and lipids are nonenzymatically modified by sugars, resulting in the formation and accumulation of advanced glycation end products (AGEs), whose process is accelerated under diabetic conditions, especially patients with a long duration of diabetes. Accumulating evidence shows that nonenzymatic modification by sugars alters the structural integrity of collagens and lipoproteins in large vessels, thereby being involved in vascular stiffness and atherosclerotic plaque instability. Furthermore, engagement of receptor for AGEs (RAGE) with its ligands, such as AGEs, high mobility group box 1, and S100A proteins evokes inflammatory and thrombotic reactions, thus playing a central role in the development and progression of atherosclerotic cardiovascular disease. In this article, we review the pathophysiological role of RAGE ligands in PAD and discuss the clinical utility of measurement of plasma, serum, or tissue RAGE ligands for assessment of the severity and prognosis of PAD. This review suggests that RAGE ligands may be a novel biomarker and also a therapeutic target of PAD, especially in patients with diabetes.

Limited benefit of haemoglobin glycation index as risk factor for cardiovascular disease in type 2 diabetes patients

BACKGROUND

The haemoglobin glycation index (HGI) has been proposed as a marker of interindividual differences in haemoglobin glycosylation. Previous studies have shown a relationship between high HGI and risk of cardiovascular disease (CVD) in patients with diabetes. However, no studies have investigated the role of previous CVD in this association.

METHODS

The study cohort comprised patients with type 2 diabetes mellitus (T2DM; n=1910) included in the Second Manifestations of Arterial Disease (SMART) study. The relationship between either HGI or HbA_1c and a composite of cardiovascular events as the primary outcome, and mortality, cardiovascular mortality, myocardial infarction and stroke as secondary outcomes, was investigated using Cox proportional-hazards models. Similar analyses were performed after stratification according to previous CVD.

RESULTS

A 1-unit higher HGI was associated with a 29% greater risk of a composite of cardiovascular events (HR: 1.29, 95% CI: 1.06-1.57) in patients without previous CVD, whereas no such relationship was seen in patients with previous CVD (HR: 0.96, 95% CI: 0.86-1.08). The direction and magnitude of the hazard ratios (HRs) of HGI and HbA_1c in relation to outcomes were similar. Additional adjustment for HbA_1c in the association between HGI and outcomes lowered the HRs.

CONCLUSION

Similar to HbA_1c, higher HGI is related to higher risk of cardiovascular events in patients with T2DM without CVD. As HbA_1c has proved to be a comparable risk factor, and obtaining and interpreting the HGI is complicated, any additional benefit of applying the HGI in clinical settings is likely to be limited.