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Relationship between hemoglobin glycation index and extent of coronary heart disease in individuals with type 2 diabetes mellitus: a cross-sectional study.

ABSTRACT: Individuals with type 2 diabetes (T2D) are at an increased risk of coronary heart disease (CHD). Diabetic complications have recently been associated with a measure of glucose metabolism known as the hemoglobin glycation index (HGI). Currently there is insufficient information regarding a potential link between HGI and cardiovascular disease. This study aimed to investigate the relationship between HGI and extent of CHD in individuals with T2D.This cross-sectional study screened individuals visiting the endocrinology clinic between June 2012 and May 2016 for eligibility. Enrollment criteria included individuals above 21 years of age with T2D diagnosed in the preceding ten years. Candidates with hemoglobin disorders, pregnancy, and existing coronary artery disease were excluded. Fasting plasma glucose (FPG) and glycated hemoglobin A1c (HbA1c) were sampled three months prior to angiography. The regression equation of predicted HbA1c = 0.008 × FPG + 6.28 described the linear relationship between these variables. HGI was calculated as the difference between the measured HbA1c and predicted HbA1c. Participants were classified into two groups according to the presence of supranormal (?0) or subnormal HGI (<0).Among 423 participants, people with supranormal HGI harbored an increased prevalence of multiple vessel disease relative to those with subnormal HGI (Odds ratio (OR): 3.9, 95% CI [2.64-5.98], P < 0.001). Moreover, individuals with supranormal HGI more frequently demonstrated lesions involving the left anterior descending artery (OR: 3.0, 95% CI [1.97-4.66], P < 0.001). The intergroup difference in mean HbA1c was statistically nonsignificant (7.5 ± 1.0% versus 7.4 ± 1.1%, P = 0.80).This study demonstrated that HGI correlated with the extent of CHD in individuals with T2D. People with supranormal HGI harbored a higher prevalence of extensive cardiovascular disease compared to those with subnormal HGI. The relationship between HGI and extent of CHD enables cardiovascular risk stratification in at risk individuals. Overall, HGI provides useful information concerning cardiovascular risk in clinical practice.

SUBMITTER: Cheng PC

PROVIDER: S-EPMC5632534 | biostudies-other | 2017

REPOSITORIES: biostudies-other

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Relationship between hemoglobin glycation index and extent of coronary heart disease in individuals with type 2 diabetes mellitus: a cross-sectional study.

Cheng Po Chung PC Hsu Shang Ren SR Cheng Yun Chung YC Liu Yu Hsiu YH

PeerJ 20171005

<h4>Background</h4>Individuals with type 2 diabetes (T2D) are at an increased risk of coronary heart disease (CHD). Diabetic complications have recently been associated with a measure of glucose metabolism known as the hemoglobin glycation index (HGI). Currently there is insufficient information regarding a potential link between HGI and cardiovascular disease. This study aimed to investigate the relationship between HGI and extent of CHD in individuals with T2D.<h4>Methods</h4>This cross-sectio ...[more]

PMID: 29018613

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Project description:BackgroundThe 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.MethodsThe 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.ResultsA 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.ConclusionThere 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.

Project description:BackgroundThe Triglyceride glucose-body mass index (TyG-BMI) and hemoglobin glycation index (HGI) are well-established surrogate markers for insulin resistance. Nevertheless, the extent to which these markers offer additive predictive value for heart failure (HF) prevalence in hypertensive populations, and their predictive utility across various diabetic statuses, remains to be clarified. Consequently, this study aimed to explore the independent and synergistic effects of TyG-BMI and HGI on HF risk among individuals with different diabetic statuses.MethodsData from the study population (n = 9847) were obtained from the National Health and Nutrition Examination Survey (NHANES). Multivariable logistic regression models were employed to estimate odds ratios (ORs) and 95% confidence intervals (CIs) to assess the combined associations between TyG-BMI and HGI and the prevalence of HF across various diabetic statuses.ResultsIn the total population, compared to the reference group (low TyG-BMI and low HGI), the OR (95% CI) for HF prevalence was 1.30 (1.04, 1.64) for the combination of low TyG-BMI and high HGI, 2.40 (1.76, 3.29) for high TyG-BMI and low HGI, and 3.47 (2.41, 4.99) for high TyG-BMI and high HGI. Interestingly, among normoglycemic individuals, higher TyG-BMI and HGI did not significantly increase the prevalence of HF. Conversely, in the prediabetic population, the OR (95%CI) for HF prevalence was 2.42 (1.69, 3.48) for the combination of high TyG-BMI and low HGI, and 4.30 (2.45, 7.54) for high TyG-BMI and high HGI. Similarly, in the diabetic population, the OR (95%CI) for HF prevalence was 2.22 (1.43, 3.45) for low TyG-BMI and high HGI, 4.04 (2.43, 6.73) for high TyG-BMI and low HGI, and 4.13 (2.25, 7.59) for high TyG-BMI and high HGI, compared to low TyG-BMI and low HGI.ConclusionThis study reveals that elevated TyG-BMI and HGI levels exert a synergistic impact on the prevalence of HF in hypertensive adults, especially in those with prediabetes and diabetes. Additionally, the presence of prediabetes and diabetes may amplify the detrimental combined effect of TyG-BMI and HGI on HF prevalence.

Project description:Background: Glycosylated hemoglobin (HbA1c) variability is a risk factor for cardiovascular complications in patients with Type 2 diabetes mellitus (T2DM), but its relationship with the severity of coronary artery disease (CAD) is unclear. Methods: Patients with T2DM who underwent coronary angiography due to angina were enrolled. HbA1c variability was expressed as coefficient of variation (CV), standard deviation (SD), variability independent of mean (VIM), and time in range (TIR). The severity of CAD was expressed by the number of involved vessels and Gensini score. Multivariate regression models were constructed to test the relationship between HbA1c variability, number of involved vessels, and the Gensini score, followed by linear regression analysis. Results: A total of 147 patients were included. In multivariate analysis, VIM-HbA1c (OR = 2.604; IQR: 1.15, 5.90; r = 0.026) and HbA1cTIR (OR = 0.13; IQR: 0.04, 0.41; r < 0.001) were independent risk factors for the number of involved vessels. After adjustment, HbA1cTIR (OR = 0.01; IQR: 0.002, 0.04; r < 0.001), SD-HbA1c (OR = 4.12, IQR: 1.64, 10.35; r = 0.001), CV-HbA1c (OR = 1.41, IQR: 1.04, 1.92; r = 0.007), and VIM-HbA1c (OR = 3.26; IQR: 1.43, 7.47; r = 0.003) were independent risk factors for the Gensini score. In the linear analysis, the Gensini score was negatively correlated with HbA1cTIR (β = -0.629; r < 0.001) and positively correlated with SD-HbA1c (β = 0.271; r = 0.001) and CV-HbA1c (β = 0.176; r = 0.033). After subgroup analysis, HbA1cTIR was a risk factor for the number of involved vessels. The Gensini score was negatively correlated with HbA1cTIR and positively correlated with SD-HbA1c at subgroups of subjects with a mean HbA1c ≤ 7%. Conclusions: Our analysis indicates that HbA1c variability, especially HbA1cTIR, plays a role for the severity of CAD in patients with T2DM. HbA1c variability may provide additional information and require management even at the glycemic target. Translational Aspects: Studies have shown that HbA1c variability is related to cardiovascular complications. Further, we explore the correlation between HbA1c variability and the severity of CAD. HbA1c variability is a risk factor for coronary stenosis in T2DM. It may be a potential indicator reflecting glycemic control for the prevention and treatment of cardiovascular complications.

Dataset Information

Relationship between hemoglobin glycation index and extent of coronary heart disease in individuals with type 2 diabetes mellitus: a cross-sectional study.

Publications

Relationship between hemoglobin glycation index and extent of coronary heart disease in individuals with type 2 diabetes mellitus: a cross-sectional study.

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