Little is known about the associations of magnesium (Mg) and calcium (Ca) with hemoglobin glycation index (HGI) and triglyceride-glucose index (TyG) in adults. In this study, we examined the associations of serum Mg and Ca with HGI and TyG in adults with coronary artery disease (CAD). This hospital-based cross-sectional study included 10757 CAD patients with a mean age of 61.6 years. Serum concentrations of Mg and Ca were measured in clinical laboratory. Overall, serum Mg and Ca were inversely associated with HGI and TyG. In multivariable analyses, Mg and Ca were inversely associated with HGI (MgQ4 vs. Q3: -0.601 vs. -0.528; CaQ4 vs. Q1: -0.769 vs. -0.645). In terms of TyG, inverse associations of serum Mg and Ca with TyG were observed. The corresponding TyG values were 9.054 (vs. 9.099) for Mg and 9.068 (vs. 9.171) for Ca in the fourth quartile compared with the first quartile. Moreover, Mg, Ca or Mg/Ca ratio were also inversely associated with HbA1c and FBG. In path analysis, no mediating effects of obesity on \"serum Mg (or Ca)- HGI (or TyG)\" associations were observed. Generally, our study identified the inverse associations of the serum Mg and Ca levels with HGI and TyG in adults with CAD. Large sample longitudinal study, and particularly randomized controlled trials, are warranted to validate our findings and overcome the limitations of cross-sectional studies.

The proposed glucosylamine oxidation pathway (GOP) is a two-step, intraerythrocyte, thermodynamically favorable nonenzymatic reaction that first binds glucose to the N-terminal valine of beta globin (βVal1) to form a closed-chain glucosylamine that can spontaneously reduce oxidized vitamin C to its antioxidant form. This review summarizes analytical, biochemical and clinical research supporting the existence of the GOP and the surprising hypothesis that βVal1 glucosylamine is a reducing agent that works cooperatively with reduced glutathione to dynamically regulate vitamin C recycling during naturally occurring periods of transiently or chronically elevated blood glucose and oxidant production. Rationale for the existence of the GOP is presented from the perspective of the hemoglobin glycation index, a clinically practical biomarker of risk for chronic vascular disease that we propose is mechanistically explained by person-to-person variation in GOP activity.

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.
CONCLUSIONS: 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.

BACKGROUND: The 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.
METHODS: Data 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.
RESULTS: In 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.
CONCLUSIONS: This 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.

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.

BACKGROUND: 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).
CONCLUSIONS: 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.

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).
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).
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.
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.

OBJECTIVE: 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.
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.

The data for the effect of dietary magnesium (Mg) on hemoglobin glycation index (HGI) is limited. Thus, this study aimed to examine the relationship between dietary Mg and HGI in the general population. Our research used data from the National Health and Nutrition Examination Survey from 2001 to 2002. The dietary intake of Mg was assessed by two 24-h dietary recalls. The predicted HbA1c was calculated based on fasting plasma glucose. Logistic regression and restricted cubic spline models were applied to assess the relationship between dietary Mg intake and HGI. We found a significant inverse association between dietary Mg intake and HGI (β =  - 0.00016, 95%CI: - 0.0003, - 0.00003, P = 0.019). Dose-response analyses revealed that HGI decreased with increasing intakes of Mg when reached the point above 412 mg/day. There was a linear dose-response relationship between dietary Mg intake and HGI in diabetic subjects, and there was an L-shape dose-response relationship in non-diabetic individuals. Increasing the intake of Mg might help lower the risk associated with high HGI. Further prospective studies are requested before dietary recommendations.

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.
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.
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.
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.