Association of hemoglobin glycation index with outcomes of acute ischemic stroke in type 2 diabetic patients

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.

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.

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.

Michaelis-Menten kinetic modeling of hemoglobin A1c status facilitates personalized glycemic control

INTRODUCTION

Discrepancy between measured HbA1c and HbA1c calculated from plasma glucose is associated with higher risk for diabetic complications. However, quantification of this difference is inaccurate due to the imperfect linear conversion models. We propose to introduce a mathematical formula that correlates with the observational data and supports individualized glycemic control.

METHODS

We analysed 175,437 simultaneous plasma glucose and HbA1c records stored in our laboratory database. Employing the Michaelis-Menten (MM) equation, we compared the calculated HbA1c levels to the measured HbA1c levels. Data from patients with multiple records were used to establish the patients' glycemic status and to assess the predictive power of our MM model.

RESULTS

HbA1c levels calculated with the MM equation closely matched the population's average HbA1c levels. The Michaelis constant (Km) had a negative correlation with HbA1c (r2 = 0.403). Using personalized Km values in the MM equation, 85.1% of HbA1c predictions were within 20% error (ADAG calculation: 78.4%). MM prediction also performed better in predicting pathologic HbA1c levels (0.904 AUC vs. 0.849 AUC for ADAG).

CONCLUSION

MM equation is an improvement over linear models and could be readily employed in routine diabetes management. Km is a reliable and quantifiable marker to characterize variations in glucose tolerance.

Correlation Between Hemoglobin Glycation Index Measured by Continuous Glucose Monitoring With Complications in Type 1 Diabetes

OBJECTIVE

HbA1C is the "gold standard" parameter to evaluate glycemic control in diabetes; however, its correlation with mean glucose is not always perfect. The objective of this study was to correlate continuous glucose monitoring (CGM)-derived hemoglobin glycation index (HGI) with microvascular complications.

METHODS

We conducted a cross-sectional study including permanent users of CGM with type 1 diabetes mellitus or latent autoimmune diabetes of the adult. HGI was estimated, and presence of microvascular complications was compared in subgroups with high or low HGI. A logistic regression analysis to assess the contribution of high HGI to chronic kidney disease (CKD) was performed.

RESULTS

In total, 52 participants who were aged 39.7 ± 14.7 years, with 73.1% women and 15.5 years (IQR, 7.5-29 years) since diagnosis, were included; 32.7% recorded diabetic retinopathy, 25% CKD, and 19.2% neuropathy. The median HbA1C was 7.6% (60 mmol/mol) and glucose management indicator (GMI) 7.0% (53 mmol/mol). The average HGI was 0.55% ± 0.66%. The measured HbA1C was higher in the group with high HGI (8.1% [65 mmol/mol] vs 6.9% [52 mmol/mol]; P < .001), whereas GMI (7.0% [53 mmol/mol] vs 7.0% [53 mmol/mol]; P = .495) and mean glucose were similar in both groups (153 mg/dL vs 153 mg/dL; P = .564). In the high HGI group, higher occurrence of CKD (P = .016) and neuropathy were observed (P = .025). High HGI was associated with increased risk of CKD (odds ratio [OR]: 5.05; 95% CI: 1.02-24.8; P = .04) after adjusting for time since diagnosis (OR: 1.09; 95% CI: 1.02-1.16; P = .008).

CONCLUSION

High HGI measured by CGM may be a useful marker for increased risk of microvascular diabetic complications.

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.

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.

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.

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.

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.

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.

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.

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.