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

The combined effect of handgrip strength and obesity phenotype on the risk of stroke in Chinese middle-aged and elderly: A cohort study

OBJECTIVE

The aim of this study was to investigate the combined effect of handgrip strength (HGS) and obesity phenotype on the risk of stroke in Chinese middle-aged and elderly people.

METHODS

The data was used from the China Health and Retirement Longitudinal Study (CHARLS). Middle-aged and older adults who participated in surveys between 2011 and 2018 were included in the study. They were divided into 4 different types of obesity phenotypes based on obesity and metabolic status: metabolically healthy non-overweight/obesity (MHNO), metabolically healthy overweight/obesity (MHO), metabolically abnormal non-overweight/obesity (MANO), and metabolically abnormal overweight/obesity (MAO). The HGS level was divided into low and high groups according to the median values. Cox proportional risk regression model was used to analyze the joint effect of HGS and obesity phenotype on the risk of stroke among participants.

RESULTS

A total of 7904 participants aged 58.89±9.08 years were included in this study. After adjusting for potential confounders, high HGS&MHO (HR=1.86, 95 % CI=1.12-3.09), high HGS&MANO (HR=2.01, 95 %CI=1.42-2.86), high HGS&MAO (HR=2.01, 95 % CI=1.37-2.93), low HGS&MHNO (HR=1.57, 95 % CI=1.00-2.46), low HGS&MHO (HR=2.09, 95 % CI=1.29-3.38), low HGS&MANO (HR=2.02, 95 % CI=1.35-3.03), and low HGS&MAO (HR=2.48, 95 % CI=1.72-3.58) group had significantly higher risks of stroke than the high HGS&MHNO group.

CONCLUSION

The coexistence of metabolically unhealthy and low HGS can synergistically increase the risk of stroke in Chinese middle-aged and elderly people.

Sex-specific associations between haemoglobin glycation index and the risk of cardiovascular and all-cause mortality in individuals with pre-diabetes and diabetes: A large prospective cohort study

AIM

The aim of this study was to investigate the relationship between the haemoglobin glycation index (HGI), and cardiovascular disease (CVD) and all-cause mortality in adults with pre-diabetes and diabetes.

METHODS

This study included 10 267 adults with pre-diabetes and diabetes from the National Health and Nutrition Examination Survey (NHANES) 1999-2018. Sex-differentiated relationships between HGI and mortality were elucidated using multivariate Cox proportional hazards models, restricted cubic splines and a two-piecewise Cox proportional hazards model.

RESULTS

During the median follow-up time of 103.5 months, a total of 535 CVD deaths and 1918 all-cause deaths were recorded. After multivariate adjustment, in males with pre-diabetes and diabetes, there was a U-shaped relationship between HGI and CVD mortality and all-cause mortality, with threshold points of -0.68 and -0.63, respectively. Before the threshold point, HGI was negatively associated with CVD mortality [hazard ratio (HR) 0.60; 95% confidence interval (CI) 0.41, 0.89] and all-cause mortality (HR 0.56; 95% CI 0.43, 0.74), and after the threshold point, HGI was positively associated with CVD mortality (HR 1.46; 95% CI 1.23, 1.73) and all-cause mortality (HR 1.40; 95% CI 1.23, 1.59). In contrast, HGI had an L-shaped relationship with all-cause mortality and no significant association with CVD mortality in females. To the left of the threshold points, the risk of all-cause mortality decreased (HR 0.50; 95% CI 0.35, 0.71) progressively with increasing HGI.

CONCLUSIONS

In the cohort study, HGI in pre-diabetic and diabetic populations was found to have a U-shaped association with CVD mortality and all-cause mortality in males and an L-shaped association with all-cause mortality only in females. Further prospective and mechanistic studies are warranted.

Precision prognostics for cardiovascular disease in Type 2 diabetes: a systematic review and meta-analysis

BACKGROUND

Precision medicine has the potential to improve cardiovascular disease (CVD) risk prediction in individuals with Type 2 diabetes (T2D).

METHODS

We conducted a systematic review and meta-analysis of longitudinal studies to identify potentially novel prognostic factors that may improve CVD risk prediction in T2D. Out of 9380 studies identified, 416 studies met inclusion criteria. Outcomes were reported for 321 biomarker studies, 48 genetic marker studies, and 47 risk score/model studies.

RESULTS

Out of all evaluated biomarkers, only 13 showed improvement in prediction performance. Results of pooled meta-analyses, non-pooled analyses, and assessments of improvement in prediction performance and risk of bias, yielded the highest predictive utility for N-terminal pro b-type natriuretic peptide (NT-proBNP) (high-evidence), troponin-T (TnT) (moderate-evidence), triglyceride-glucose (TyG) index (moderate-evidence), Genetic Risk Score for Coronary Heart Disease (GRS-CHD) (moderate-evidence); moderate predictive utility for coronary computed tomography angiography (low-evidence), single-photon emission computed tomography (low-evidence), pulse wave velocity (moderate-evidence); and low predictive utility for C-reactive protein (moderate-evidence), coronary artery calcium score (low-evidence), galectin-3 (low-evidence), troponin-I (low-evidence), carotid plaque (low-evidence), and growth differentiation factor-15 (low-evidence). Risk scores showed modest discrimination, with lower performance in populations different from the original development cohort.

CONCLUSIONS

Despite high interest in this topic, very few studies conducted rigorous analyses to demonstrate incremental predictive utility beyond established CVD risk factors for T2D. The most promising markers identified were NT-proBNP, TnT, TyG and GRS-CHD, with the highest strength of evidence for NT-proBNP. Further research is needed to determine their clinical utility in risk stratification and management of CVD in T2D.

Communal interaction of glycation and gut microbes in diabetes mellitus, Alzheimer's disease, and Parkinson's disease pathogenesis

Diabetes and its complications, Alzheimer's disease (AD), and Parkinson's disease (PD) are increasing gradually, reflecting a global threat vis-à-vis expressing the essentiality of a substantial paradigm shift in research and remedial actions. Protein glycation is influenced by several factors, like time, temperature, pH, metal ions, and the half-life of the protein. Surprisingly, most proteins associated with metabolic and neurodegenerative disorders are generally long-lived and hence susceptible to glycation. Remarkably, proteins linked with diabetes, AD, and PD share this characteristic. This modulates protein's structure, aggregation tendency, and toxicity, highlighting renovated attention. Gut microbes and microbial metabolites marked their importance in human health and diseases. Though many scientific shreds of evidence are proposed for possible change and dysbiosis in gut flora in these diseases, very little is known about the mechanisms. Screening and unfolding their functionality in metabolic and neurodegenerative disorders is essential in hunting the gut treasure. Therefore, it is imperative to evaluate the role of glycation as a common link in diabetes and neurodegenerative diseases, which helps to clarify if modulation of nonenzymatic glycation may act as a beneficial therapeutic strategy and gut microbes/metabolites may answer some of the crucial questions. This review briefly emphasizes the common functional attributes of glycation and gut microbes, the possible linkages, and discusses current treatment options and therapeutic challenges.

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.

Precision Prognostics for Cardiovascular Disease in Type 2 Diabetes: A Systematic Review and Meta-analysis

Background Precision medicine has the potential to improve cardiovascular disease (CVD) risk prediction in individuals with type 2 diabetes (T2D). Methods We conducted a systematic review and meta-analysis of longitudinal studies to identify potentially novel prognostic factors that may improve CVD risk prediction in T2D. Out of 9380 studies identified, 416 studies met inclusion criteria. Outcomes were reported for 321 biomarker studies, 48 genetic marker studies, and 47 risk score/model studies. Results Out of all evaluated biomarkers, only 13 showed improvement in prediction performance. Results of pooled meta-analyses, non-pooled analyses, and assessments of improvement in prediction performance and risk of bias, yielded the highest predictive utility for N-terminal pro b-type natriuretic peptide (NT-proBNP) (high-evidence), troponin-T (TnT) (moderate-evidence), triglyceride-glucose (TyG) index (moderate-evidence), Genetic Risk Score for Coronary Heart Disease (GRS-CHD) (moderate-evidence); moderate predictive utility for coronary computed tomography angiography (low-evidence), single-photon emission computed tomography (low-evidence), pulse wave velocity (moderate-evidence); and low predictive utility for C-reactive protein (moderate-evidence), coronary artery calcium score (low-evidence), galectin-3 (low-evidence), troponin-I (low-evidence), carotid plaque (low-evidence), and growth differentiation factor-15 (low-evidence). Risk scores showed modest discrimination, with lower performance in populations different from the original development cohort. Conclusions Despite high interest in this topic, very few studies conducted rigorous analyses to demonstrate incremental predictive utility beyond established CVD risk factors for T2D. The most promising markers identified were NT-proBNP, TnT, TyG and GRS-CHD, with the highest strength of evidence for NT-proBNP. Further research is needed to determine their clinical utility in risk stratification and management of CVD in T2D.

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.

Handgrip strength is associated with risks of new-onset stroke and heart disease: results from 3 prospective cohorts

BACKGROUND

Stroke and heart disease are two major contributors to the global disease burden. We aimed to evaluate and compare the roles of different handgrip strength (HGS) expressions in predicting stroke and heart disease in three nationally representative cohorts.

METHODS

This longitudinal study used data from the Health and Retirement Study (HRS), the Survey of Health, Ageing, and Retirement in Europe (SHARE), and the China Health and Retirement Longitudinal Study (CHARLS). The Cox proportional hazard model was applied to analyze the relationship between HGS and stroke and heart disease, and Harrell's C index was used to assess the predictive abilities of different HGS expressions.

RESULTS

A total of 4,407 participants suffered from stroke and 9,509 from heart disease during follow-up. Compared with the highest quartile, participants in the lowest quartile of dominant HGS, absolute HGS and relative HGS possessed a significantly higher risk of new-onset stroke in Europe, America, and China (all P < 0.05). After adding HGS to office-based risk factors, there were minimal or no differences in the increases of Harrell's C indexes among three HGS expressions. In contrast, the modest association between HGS and heart disease was only seen in SHARE and HRS, but not in CHARLS.

CONCLUSION

Our findings support that HGS can be used as an independent predictor of stroke in middle-aged and older European, American and Chinese populations, and the predictive ability of HGS may not depend on how it is expressed. The relationship between HGS and heart disease calls for further validation.

Gaps Remain for Achieving HbA1c Targets for People with Type 1 or Type 2 Diabetes Using Insulin: Results from NHANES 2009-2020

INTRODUCTION

Glycated hemoglobin A1c (HbA1c) is an important measure to assess glycemic control and predict diabetes complications. However, there is limited information on trends in HbA1c among people with diabetes (PwDs) who use insulin. The aim of this study was to describe trends in HbA1c among PwDs who use insulin by diabetes type and insulin regimen.

METHODS

A retrospective analysis was conducted using data from the National Health and Nutrition Examination Survey (NHANES, 2009-2020). PwDs were classified into three cohorts: type 1 diabetes mellitus (T1DM), type 2 diabetes mellitus using mealtime insulin (T2DM-MTI), and type 2 diabetes mellitus (T2DM) using basal-only insulin (T2DM basal-only). Trends in HbA1c over time were assessed using regression analysis after adjusting for age, gender, and race/ethnicity.

RESULTS

Mean HbA1c values aggregated over 2009-2020 were 8.0% (T1DM), 8.6% (T2DM-MTI), and 8.6% (T2DM basal-only). The American Diabetes Association-recommended target of HbA1c of < 7% was achieved by 25.2% of people in the T1DM and T2DM-MTI groups each and by 12.3% of people in the T2DM basal-only group. Over time, an upward trend was observed in the percentage of people achieving HbA1c < 7% in the T2DM basal-only group. The percentage of PwDs achieving individualized HbA1c targets was 27.0%, 12.4%, and 16.1% for the T1DM, T2DM-MTI, and T2DM basal-only groups, respectively.

CONCLUSIONS

Our study using NHANES data suggests that approximately 25% of PwDs achieve glycemic targets. This study highlights the need for improved therapies to better manage glycemic targets in PwDs.

Trajectory of glycated haemoglobin over time, using real-world data, in type 2 diabetes patients with obesity on a U-100 basal-bolus insulin regimen

AIMS

To identify patient clusters with poor glucose control among type 2 diabetes mellitus (T2DM) patients with obesity who are receiving basal-bolus insulin and to identify the potential therapeutic inertia factors associated with poor control.

METHODS

Glycated haemoglobin (HbA1c) trajectories across a 3-year period were structured at 6-month intervals for a retrospective cohort of T2DM patients with obesity on basal-bolus insulin from the Veterans' Health Administration database. Based on each patient's longitudinal HbA1c features, an unsupervised clustering procedure was used to determine the numbers of clusters and associated trajectory patterns. Multinomial logistic regression was used to examine the association between HbA1c trajectory clusters and patient characteristics/treatment patterns.

RESULTS

A total of 51 273 patients were included, of whom 11.2% were in a subgroup with persistent missingness of HbA1c values. For those with sufficient HbA1c observations, cluster analysis indicated six distinct HbA1c trajectories: stable low (35.8%); stable high (20.8%); descending low (10.5%); ascending low (10.2%); descending high (5.7%); and ascending high (5.7%). Being of Black ethnicity, not initiating noninsulin antihyperglycaemic agents (sodium-glucose cotransporter-2 inhibitors, glucagon-like peptide-1 receptor agonists or thiazolidinediones) or concentrated insulin, low adherence (measured by proportion of days covered), and reduced insulin prescription refills were factors associated with poorer HbA1c clusters; similar factors were associated with persistent HbA1c missingness.

CONCLUSION

The present study found the potential for therapeutic inertia among a significant proportion of T2DM patients with obesity on basal-bolus insulin. Subgrouping T2DM patients based on HbA1c missingness and HbA1c trajectories can inform disease management strategies.

Association between hemoglobin glycation index and non-alcoholic fatty liver disease

OBJECTIVE

The hemoglobin glycation index (HGI) reflects biological variability in hemoglobin A1c. Even so, studies on the relationship between HGI and non-alcoholic fatty liver disease (NAFLD) are limited. Therefore, this study aimed to explore the relationship between HGI and NAFLD. In addition, the study also aimed to provide new methods to identify patients with a high risk for the development of NAFLD.

METHODS

This was a retrospective study based on physical examination data from Japan. Patients were divided into quartiles (Q1-Q4) according to their HGI level; the lowest quartile (Q1) was used as the reference group. Patents were also classified into two subgroups based on the presence or absence of NAFLD. Baseline characteristics between the groups were compared. Multivariate logistic regression analysis was used to investigate the association between the HGI and NAFLD. A mediation analysis examined the mediation relationship between HGI and NAFLD. Subgroup analyses were performed to the reliability of the results.

RESULTS

A total of 14280 patients were eligible for inclusion in this study; 2515 had NAFLD. Patients in the NAFLD group had higher levels of HGI than patients in the non-NAFLD group. Increases in HGI correlated with an increased risk of NAFLD. After adjusting for confounding factors, the multivariate logistic regression analysis revealed that HGI was positively related to the prevalence of NAFLD. In addition, mediation analysis showed that body mass index (BMI) partly mediated the indirect impact of HGI on NAFLD preference. Subgroup analyses were performed according to age, sex, smoking status, and waist circumference. Our results indicated that HGI significantly correlated with NAFLD in patients with one of the following factors: age ≤60 years, BMI >28 kg/m², female sex, a history of smoking, and abdominal obesity.

CONCLUSIONS

HGI was an independent risk factor for NAFLD, and BMI partly mediated the association between HGI and NAFLD.

High hemoglobin glycation index is associated with increased risk of diabetes: A population-based cohort study in China

PURPOSE

The hemoglobin glycation index (HGI) quantifies the mismatch between glycated hemoglobin A1c and average glycemia among individuals. Currently, it is unknown the potential role of HGI in exhaustively evaluating the progression of glucose metabolism/the risk of developing diabetes mellitus. Therefore, this study aimed to investigate the association between HGI and the risk of incident diabetes.

METHODS

A total of 7,345 participants aged at least 40 years and without diabetes were divided into three groups according to the tertile of their baseline HGI level and followed for a median of 3.24 years to track new-onset diabetes. Using multivariate Cox regression analyses, we explored the association between the HGI, both categorized and continuous, and incident diabetes.

RESULTS

During follow-up, 742 subjects (263 males and 479 females) developed diabetes mellitus. Higher HGI was associated with an increased risk of diabetes, even when adjusted for confounding factors, and every standard deviation increase in HGI was associated with a significant risk increase of 30.6% for diabetes (hazard ratio 1.306, 95% confidence interval 1.232-1.384).

CONCLUSIONS

Participants with a higher HGI were at a higher risk of future diabetes, irrespective of their glycemic conditions. Consequently, HGI may be employed to identify individuals at high risk for diabetes.

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.

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.

Recent Advances in Non-Invasive Blood Pressure Monitoring and Prediction Using a Machine Learning Approach

Blood pressure (BP) monitoring can be performed either invasively via arterial catheterization or non-invasively through a cuff sphygmomanometer. However, for conscious individuals, traditional cuff-based BP monitoring devices are often uncomfortable, intermittent, and impractical for frequent measurements. Continuous and non-invasive BP (NIBP) monitoring is currently gaining attention in the human health monitoring area due to its promising potentials in assessing the health status of an individual, enabled by machine learning (ML), for various purposes such as early prediction of disease and intervention treatment. This review presents the development of a non-invasive BP measuring tool called sphygmomanometer in brief, summarizes state-of-the-art NIBP sensors, and identifies extended works on continuous NIBP monitoring using commercial devices. Moreover, the NIBP predictive techniques including pulse arrival time, pulse transit time, pulse wave velocity, and ML are elaborated on the basis of bio-signals acquisition from these sensors. Additionally, the different BP values (systolic BP, diastolic BP, mean arterial pressure) of the various ML models adopted in several reported studies are compared in terms of the international validation standards developed by the Advancement of Medical Instrumentation (AAMI) and the British Hypertension Society (BHS) for clinically-approved BP monitors. Finally, several challenges and possible solutions for the implementation and realization of continuous NIBP technology are addressed.

Control of Blood Pressure and Risk of Cardiovascular Disease and Mortality in Elderly Chinese: A Real-World Prospective Cohort Study

BACKGROUND

The STEP trial (Strategy of Blood Pressure Intervention in the Elderly Hypertensive Patients) showed that older hypertensive patients might benefit from a target systolic blood pressure (SBP) of 110 to <130 mm Hg. We examined whether this target SBP is associated with a decreased risk of cardiovascular disease (CVD) and all-cause mortality among elderly Chinese in real-world settings.

METHODS

This prospective study included 13 383 CVD-free participants aged 60 to 80 years and with SBP within 110 to <150 mm Hg at baseline. Inverse probability of treatment weighting was used to adjust for baseline differences. Weighted Cox proportional hazards models yielded adjusted hazard ratios (HRs) and 95% CIs of CVD and all-cause mortality associated with normalized SBP (110 to <130 mm Hg).

RESULTS

During a median follow-up of 13.01 years, we identified 1727 cases of CVD and 3742 deaths. After inverse probability of treatment weighting, compared with non-normalized SBP, normalized SBP was associated with a decreased risk of CVD (HR, 0.81 [95% CI, 0.76-0.87]) and all-cause mortality (HR, 0.89 [95% CI, 0.85-0.93]). Beneficial effects of longitudinal normalized SBP presented by the updated mean SBP were also observed for CVD (HR, 0.88 [95% CI, 0.78-0.93]) and all-cause mortality (HR, 0.93 [95% CI, 0.88-0.97]). Multiple sensitivity analyses yielded similar results.

CONCLUSIONS

The SBP target of 110 to <130 mm Hg recommended by the STEP trial was associated a lower risk of CVD and all-cause mortality than was SBP of 130 to <150 mm Hg among elderly Chinese in real-world settings.

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.

Associations of handgrip strength with morbidity and all-cause mortality of cardiometabolic multimorbidity

BACKGROUND

Cardiometabolic multimorbidity (CM) is an increasing public health and clinical concern. However, predictors for the development and prognosis of CM are poorly understood. The aims of this study were to investigate the relation between handgrip strength (HGS) and the risk of CM and to examine the association of HGS with all-cause mortality risk among patients with CM.

METHODS

This prospective cohort study involved 493,774 participants from the UK Biobank. CM was defined as the simultaneous occurrence of two or more of the following conditions: type 2 diabetes, stroke, and coronary heart disease (CHD). Cox proportional hazards models were performed to estimate hazard ratios (HRs) and 95% confidence intervals (95% CIs).

RESULTS

During a median follow-up of 12.1 years, 4701 incident CM cases were documented among participants with none cardiometabolic disease at baseline. Compared with the fourth quartile (Q4), the multivariable adjusted HR (95% CI) value of Q1 of HGS for developing CM was 1.46 (1.34-1.60). In participants with one cardiometabolic disease at baseline, participants in Q1 of HGS also possessed higher risk of CM than those in Q4, with HRs (95% CIs) being 1.35 (1.23-1.49) in patients with type 2 diabetes, 1.23 (1.04-1.46) in patients with stroke, and 1.23 (1.11-1.36) in patients with CHD. For participants with CM at recruitment, HGS was also associated with the risk of all-cause mortality (Q1 vs. Q4 HR: 1.57, 95% CI: 1.36-1.80).

CONCLUSIONS

Our study provided novel evidence that HGS could be an independent predictor of morbidity and all-cause mortality of CM.

Association of Hemoglobin Glycation Index With Contrast-Induced Acute Kidney Injury in Patients Undergoing Coronary Angiography: A Retrospective Study

Background: The hemoglobin glycation index (HGI) quantifies interindividual variation in glycation and is positively associated with cardiovascular diseases. However, the association between HGI and contrast-induced acute kidney injury (CI-AKI) remains unclear. Therefore, this study aimed to assess the association of HGI with CI-AKI.

Methods: In this observational study, a total of 3,142 patients undergoing coronary angiography (CAG) or percutaneous coronary intervention (PCI) were included. The HGI was calculated as the difference between the measured glycated hemoglobin (HbA1c) and predicted HbA1c. CI-AKI was defined as an increase of either 25% or 0.5 mg/dl (44.2 μmol/L) in the serum creatinine (SCr) level within 72 h following the exposure to contrast medium. Piecewise linear regression analysis was conducted to testify the association of HGI with the proportion of SCr elevation. Modified Poisson’s regression analysis was performed to determine the association between HGI and CI-AKI. Exploratory analysis was also performed according to the stratification of HbA1c levels.

Results: Among 3,142 patients, the average age was 66.9 years and 483 of them (15.4%) suffered CI-AKI. Piecewise linear regression analysis demonstrated the linear association of HGI with the proportion of SCr elevation on both positive and negative sides of HGI [HGI <0: β = −9.537, 95% CI (−12.057 to −7.017), p < 0.001; HGI ≥0: β = 1.655, 95% CI (0.125 to 3.186), p = 0.034]. Modified Poisson’s regression analysis showed that the higher absolute value of HGI was strongly associated with higher incidence of CI-AKI [(<−1.0 vs. −0.2 to 0.2): aRR = 1.897, 95% CI [1.467 to 2.452], p < 0.001 (≥1.0 vs. −0.2 to 0.2): aRR = 1.545, 95% CI (1.171 to 2.037), p = 0.002]. Furthermore, the results in exploratory analysis showed that such association still remained irrespective of HbA1c levels.

Conclusion: The higher absolute value of HGI was strongly associated with higher incidence of CI-AKI in patients undergoing CAG and PCI.

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.

Cardiovascular risk prediction in type 2 diabetes: a comparison of 22 risk scores in primary care settings

AIMS/HYPOTHESIS

We aimed to compare the performance of risk prediction scores for CVD (i.e., coronary heart disease and stroke), and a broader definition of CVD including atrial fibrillation and heart failure (CVD+), in individuals with type 2 diabetes.

METHODS

Scores were identified through a literature review and were included irrespective of the type of predicted cardiovascular outcome or the inclusion of individuals with type 2 diabetes. Performance was assessed in a contemporary, representative sample of 168,871 UK-based individuals with type 2 diabetes (age ≥18 years without pre-existing CVD+). Missing observations were addressed using multiple imputation.

RESULTS

We evaluated 22 scores: 13 derived in the general population and nine in individuals with type 2 diabetes. The Systemic Coronary Risk Evaluation (SCORE) CVD rule derived in the general population performed best for both CVD (C statistic 0.67 [95% CI 0.67, 0.67]) and CVD+ (C statistic 0.69 [95% CI 0.69, 0.70]). The C statistic of the remaining scores ranged from 0.62 to 0.67 for CVD, and from 0.64 to 0.69 for CVD+. Calibration slopes (1 indicates perfect calibration) ranged from 0.38 (95% CI 0.37, 0.39) to 0.74 (95% CI 0.72, 0.76) for CVD, and from 0.41 (95% CI 0.40, 0.42) to 0.88 (95% CI 0.86, 0.90) for CVD+. A simple recalibration process considerably improved the performance of the scores, with calibration slopes now ranging between 0.96 and 1.04 for CVD. Scores with more predictors did not outperform scores with fewer predictors: for CVD+, QRISK3 (19 variables) had a C statistic of 0.68 (95% CI 0.68, 0.69), compared with SCORE CVD (six variables) which had a C statistic of 0.69 (95% CI 0.69, 0.70). Scores specific to individuals with diabetes did not discriminate better than scores derived in the general population: the UK Prospective Diabetes Study (UKPDS) scores performed significantly worse than SCORE CVD (p value <0.001).

CONCLUSIONS/INTERPRETATION

CVD risk prediction scores could not accurately identify individuals with type 2 diabetes who experienced a CVD event in the 10 years of follow-up. All 22 evaluated models had a comparable and modest discriminative ability.

Correlation between the Variability of Glycosylated Hemoglobin and Cardiovascular Risk in New-Onset T2DM Patients

Objective

To investigate the relationship between glycosylated hemoglobin variant index and cardiovascular disease in patients with type 2 diabetes.

Methods

A total of 120 patients with type 2 diabetes who were admitted to the Department of Endocrinology in Chun'an Branch of Zhejiang Provincial People's Hospital from January 2014 to January 2017 were enrolled. The clinical data, fasting blood glucose, and glycosylated hemoglobin levels of the patients were collected, and HGI was obtained by calculating the FPG level into the formula. Follow-up for three years was performed to observe the cardiovascular disease (including coronary heart disease and ischemic stroke) in patients. The occurrence of CVD was analyzed in patients with different levels of HGI. Multivariate logistics regression analysis was used to analyze the risk factors of CVD in patients with T2DM.

Results

After three years of follow-up, 8 cases of 120 patients were lost to follow-up. In the end, 24 cases of CVD occurred in 112 patients, with an incidence rate of 21.43%. Comparing the clinical data of CVD patients and non-CVD patients, it was found that the proportion of age, FPG, HbA1c, HGI, and insulin control in the CVD group was higher than that of the non-CVD group, and the difference was statistically significant (P < 0.05). After grouping according to different HGI levels, it was found that with the increase of HGI level, the proportion of HbA1c, FPG, TC, CVD, and insulin use showed an upward trend (P < 0.05). Multivariate logistic regression analysis showed that high HGI level (OR = 4.660), older age (OR = 4.815), and higher FPG level (OR = 1.717) are independent risk factors that affect T2DM patients with cardiovascular disease (P < 0.05).

Conclusion

High HGI is independently associated with CVD events in patients with type 2 diabetes. HGI testing is helpful for clinical assessment of personalized assessment and prediction of cardiovascular risk in patients with diabetes.

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.

Association of low fasting C-peptide levels with cardiovascular risk, visit-to-visit glucose variation and severe hypoglycemia in the Veterans Affairs Diabetes Trial (VADT)

Aims

Low C-peptide levels, indicating beta-cell dysfunction, are associated with increased within-day glucose variation and hypoglycemia. In advanced type 2 diabetes, severe hypoglycemia and increased glucose variation predict cardiovascular (CVD) risk. The present study examined the association between C-peptide levels and CVD risk and whether it can be explained by visit-to-visit glucose variation and severe hypoglycemia.

Materials and methods

Fasting C-peptide levels at baseline, composite CVD outcome, severe hypoglycemia, and visit-to-visit fasting glucose coefficient of variation (CV) and average real variability (ARV) were assessed in 1565 Veterans Affairs Diabetes Trial participants.

Results

There was a U-shaped relationship between C-peptide and CVD risk with increased risk with declining levels in the low range (< 0.50 nmol/l, HR 1.30 [95%CI 1.05–1.60], p = 0.02) and with rising levels in the high range (> 1.23 nmol/l, 1.27 [1.00–1.63], p = 0.05). C-peptide levels were inversely associated with the risk of severe hypoglycemia (OR 0.68 [0.60–0.77]) and visit-to-visit glucose variation (CV, standardized beta-estimate − 0.12 [SE 0.01]; ARV, − 0.10 [0.01]) (p < 0.0001 all). The association of low C-peptide levels with CVD risk was independent of cardiometabolic risk factors (1.48 [1.17–1.87, p = 0.001) and remained associated with CVD when tested in the same model with severe hypoglycemia and glucose CV.

Conclusions

Low C-peptide levels were associated with increased CVD risk in advanced type 2 diabetes. The association was independent of increases in glucose variation or severe hypoglycemia. C-peptide levels may predict future glucose control patterns and CVD risk, and identify phenotypes influencing clinical decision making in advanced type 2 diabetes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12933-021-01418-z.

Leisure-Time Physical Activity and Glycemic Control Independently Predicts Cardiac Autonomic Neuropathy in Type 2 Diabetes Mellitus

BACKGROUND

Though cardiac autonomic neuropathy (CAN) is a common complication of type 2 diabetes mellitus (T2DM); still, there is lack of clarity on pathophysiological correlates for its onset and progression. Therefore, the purpose of this study was to investigate the predictive ability of lifestyle and cardiometabolic risk factors for CAN in T2DM patients.

METHODS

A total of 105 Indian T2DM patients were recruited in the present study. Cardiometabolic risk factors, such as glycemic control, lipids, resting heart rate, systolic and diastolic blood pressure, and lifestyle risk parameters, such as physical activity levels and sleep quality were assessed. Standard cardiovascular autonomic reflex tests were performed for diagnosing CAN by Ewing's criteria.

RESULTS

Leisure-time physical activity and glycosylated hemoglobin were significant independent predictors of CAN in T2DM. Leisure-time physical activity and glycosylated hemoglobin predicted the occurrence of CAN at cutoff values ≤4.68 metabolic equivalent-hours per week (P = .007) and >7.5% (P = .002), respectively.

CONCLUSIONS

The T2DM patients should be encouraged to engage in leisure-time physical activity of at least 4.68 metabolic equivalent-hours per week (equivalent to 1.2 h of walk or 0.6 h of jog per week) and therapeutic strategies for controlling hyperglycemia in T2DM should aim to reduce glycosylated hemoglobin below 7.5% to reduce CAN occurrence.

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.

Modeling conditional reference regions: Application to glycemic markers

Many clinical decisions are taken based on the results of continuous diagnostic tests. Usually, only the results of one single test is taken into consideration, the interpretation of which requires a reference range for the healthy population. However, the use of two different tests, can be necessary in the diagnosis of certain diseases. This obliges a bivariate reference region be available for their interpretation. It should also be remembered that reference regions may depend on patient variables (eg, age and sex) independent of the suspected disease. However, few proposals have been made regarding the statistical modeling of such reference regions, and those put forward have always assumed a Gaussian distribution, which can be rather restrictive. The present work describes a new statistical method that allows such reference regions to be estimated with no insistence on the results being normally distributed. The proposed method is based on a bivariate location-scale model that provides probabilistic regions covering a specific percentage of the bivariate data, dependent on certain covariates. The reference region is estimated nonparametrically and the nonlinear effects of continuous covariates via polynomial kernel smoothers in additive models. The bivariate model is estimated using a backfitting algorithm, and the optimal smoothing parameters of the kernel smoothers selected by cross-validation. The model performed satisfactorily in simulation studies under the assumption of non-Gaussian conditions. Finally, the proposed methodology was found to be useful in estimating a reference region for two continuous diagnostic tests for diabetes (fasting plasma glucose and glycated hemoglobin), taking into account the age of the patient.

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.

Correlation Between Hemoglobin Glycosylation Index and Nerve Conduction Velocity in Patients with Type 2 Diabetes Mellitus

OBJECTIVE

This study aimed to investigate the relationship between hemoglobin glycation variation index (HGI) and peripheral nerve conduction velocity (NCV) in patients with type 2 diabetes mellitus (T2DM).

MATERIALS AND METHODS

This is a cross-sectional study, including 324 patients with T2DM were included in this study. Basic information and blood indicators were collected. The motor conduction velocities (MCV) of the bilateral ulnar nerve, median nerve, and common peroneal nerve, and the sensory conduction velocities (SCV) of the ulnar nerve, median nerve, and superficial peroneal nerve were measured. The patients were divided into two groups according to the NCV: normal nerve conduction group (NCVN group) and abnormal nerve conduction group (NCVA group). When the NCV is less than the specific normal value, the patients were divided into the NCVA group. HGI was calculated as the difference between the measured and predicted values of glycosylated hemoglobin (HbA1c) using the linear relationship between HbA1c level and fasting plasma glucose levels. At last, all study participants were divided into High HGI and Low HGI groups using the median of HGI as the boundary. The study also analyzed the correlation between HGI and NCV.

RESULTS

Compared to the NCVN group, the HGI levels of the NCVA group were higher (P < 0.001). The prevalence of NCVA in the high HGI group was higher than that in the low HGI group (P = 0.004). HGI was negatively correlated with bilateral ulnar nerve MCV, bilateral median nerve MCV, bilateral common peroneal nerve MCV, bilateral median nerve SCV and left superficial peroneal nerve SCV, and the correlation still existed after adjusting for confounding factors.

CONCLUSION

This study found that HGI is inversely associated with NCV in patients with T2DM, and this correlation is higher between HGI and MCV of peripheral nerve.

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.

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.

MiR-92b-3p is Induced by Advanced Glycation End Products and Involved in the Pathogenesis of Diabetic Nephropathy

Purpose

The current study aims to examine the effects of advanced glycation end products (AGEs) on the microRNA (miRNA) expression profile in the kidney tissues of rats.

Methods

Wistar rats were randomly divided into three equal experiment groups: the AGE group, the RSA group, and the control group. The rats in the AGE group and the RSA group were administered with advanced glycation end products (AGEs) and rat serum albumin (RSA) via the tail vein, respectively, whereas the control group received PBS. Total RNA was prepared from the rat kidney tissues, and the miRNA expression profiles in different experiment groups were compared by microarray analysis. The expression levels of selected differential miRNAs were verified by RT-qPCR. Target gene prediction was conducted using algorithms such as TargetScan, miRanda, and PICTar. Functional analysis was performed to determine the putative biological roles of the validated miRNAs.

Results

The microarray study revealed 451 upregulated and 320 downregulated miRNAs in the AGE group compared with the RSA group (p < 0.05). Seven miRNAs, including miR-21-5p, miR-92b-3p, miR-140-3p, miR-196a-5p, miR-181b-5p, miR-186-5p, and miR-192-5p, were screened and verified using RT-qPCR, of which, the change of miR-92b-3p was the most obvious according to the miRNA expression different multiple and p < 0.05). Seven miRNAs, including miR-21-5p, miR-92b-3p, miR-140-3p, miR-196a-5p, miR-181b-5p, miR-186-5p, and miR-192-5p, were screened and verified using RT-qPCR, of which, the change of miR-92b-3p was the most obvious according to the miRNA expression different multiple and

Conclusion

The results of the current study suggested that miR-92b-3p could mediate AGE-induced development of renal abnormalities through targeting Smad7 in rats with DN.

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.

Long noncoding RNA Crnde attenuates cardiac fibrosis via Smad3-Crnde negative feedback in diabetic cardiomyopathy

Diabetic cardiomyopathy (DCM)-ventricular dysfunction in the absence of underlying heart disease-is a common complication of diabetes and a leading cause of mortality associated with the disease. In DCM, cardiac fibrosis is the main cause of heart failure. Although it is well-established that the transforming growth factor-beta signaling pathway plays a part in inducing cardiac fibrosis in DCM, details of the molecular mechanism involved remain elusive. Therefore, it is crucial to study the gene reg;ulation of key signaling effectors in DCM-associated cardiac fibrosis. A recently emerged hotspot in the field of gene regulation is the role of long noncoding RNAs (lncRNAs). Recent evidence indicates that lncRNAs play a critical role in cardiac fibrosis; however, in DCM, the function of these regulatory RNAs have not been studied in depth. In this study, we identified a conserved cardiac-specific lncRNA named colorectal neoplasia differentially expressed (Crnde). By analyzing 376 human heart tissues, it was found that Crnde expression is negatively correlated with that of cardiac fibrosis marker genes. Moreover, Crnde expression was shown to be enriched in cardiac fibroblasts (CFs). Overexpression of Crnde attenuated cardiac fibrosis and enhanced cardiac function in mice with DCM. Further, in vitro experiments showed that Crnde negatively regulates the myofibroblast differentiation of CFs. The expression of Crnde was activated by SMAD family member 3 (Smad3), shedding light on the underlying molecular mechanism. Interestingly, Crnde also inhibited the transcriptional activation of Smad3 on target genes, thereby inhibiting the expression of myofibroblastic marker genes in CFs. Overall, our data provide valuable insights into the development of potential anti-cardiac fibrosis strategies centered on lncRNAs, for the treatment of DCM.