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

Brazilian guideline for screening and diagnosis of type 2 diabetes: a position statement from the Brazilian Diabetes Society

BACKGROUND

Patients with type 2 diabetes (T2D) often experience prolonged periods of asymptomatic hyperglycemia, which significantly increases the risk of developing chronic complications related to diabetes. Screening programs for individuals at high risk for T2D provide valuable opportunities not only for early diagnosis but also for detecting intermediate hyperglycemic states, commonly referred to as prediabetes. Interventions aimed at preventing diabetes in this group can successfully delay or even avoid the onset of the disease and its associated burdens. This review is an update of the Brazilian Diabetes Society (Sociedade Brasileira de Diabetes [SBD]) evidence-based guideline for diagnosing diabetes and screening T2D.

METHODS

The methodology was previously published and defined by the internal institutional steering committee. The working group drafted the manuscript by selecting vital clinical questions for a narrative review, utilizing MEDLINE via PubMed to identify relevant studies. The review assessed the best available evidence, including randomized clinical trials (RCTs), meta-analyses, and high-quality observational studies related to the diagnosis of diabetes.

RESULTS AND CONCLUSIONS

Fifteen specific recommendations were formulated. Screening is recommended for adults aged 35 and older or younger individuals with obesity and additional risk factors. For children and adolescents, screening is recommended starting at age ten or the onset of puberty if they are overweight or obese and have additional risk factors. Fasting plasma glucose (FPG) and HbA1c are recommended as initial screening tests. The oral glucose tolerance test (OGTT) is recommended for high-risk individuals with normal HbA1c and FPG or those with prediabetes. The 1-h OGTT is preferred over the 2-h OGTT, as it is both more practical and a superior test. A structured approach to reevaluation intervals is provided.

Evidence-based screening, clinical care and health education recommendations for Alaska Native peoples with prediabetes living in southcentral Alaska: findings from the Alaska EARTH follow-up study

Pre-diabetes (pre-DM) is a strong predictor of diabetes (DM) over time. This study investigated how much of the recent increase in pre-DM identified among Alaska Native (AN) peoples living in urban southcentral Alaska may be due to changes in diagnostic methods. We used clinical and demographic data collected at baseline between 2004 and 2006 and at follow-up collected between 2015 and 2017 from the urban southcentral Alaska Education and Research Towards Health (EARTH) cohort. We used descriptive statistics and logistic regression to explore differences in demographic and clinical variables among the identified pre-DM groups. Of 388 participants in the follow-up study, 243 had A1c levels indicating pre-DM with only 20 demonstrating pre-DM also by fasting blood glucose (FBG). Current smoking was the sole predictor for pre-DM by A1c alone while abdominal obesity and elevated FBG-predicted pre-DM by A1c+FBG. No participants had an elevated FBG without an A1c elevation. A substantial portion of the rise in pre-DM found among urban southcentral AN peoples in the EARTH follow-up study was due to the addition of A1c testing. Pre-DM by A1c alone should be used to motivate behavioural changes that address modifiable risk factors, including smoking cessation, physical activity and weight management.

Assessing Patterns of Continuous Glucose Monitoring Use and Metrics of Glycemic Control in Type 1 Diabetes and Type 2 Diabetes Patients in the Veterans Health Care System: Integrating Continuous Glucose Monitoring Device Data with Electronic Health Records Data

Objective: To integrate long-term daily continuous glucose monitoring (CGM) device data with electronic health records (EHR) for patients with type 1 and type 2 diabetes (T1D and T2D) in the national Veterans Affairs Healthcare System to assess real-world patterns of CGM use and the reliability of EHR-based CGM information. Research Design and Methods: This observational study used Dexcom CGM device data linked with EHR (from 2015 to 2020) for a large national cohort of patients with diabetes. We tracked the initiation and consistency of CGM use, assessed concordance of CGM use and measures of glucose control between CGM device data and EHR records, and examined results by age, ethnicity, and diabetes type. Results: The time from pharmacy release of CGM to patients to initiation of uploading CGM data to Dexcom servers averaged 3 weeks but demonstrated wide variation among individuals; importantly, this delay decreased markedly over the later years. The average daily wear time of CGM exceeded 22 h over nearly 3 years of follow-up. Patterns of CGM use were generally consistent across age, race/ethnicity groups, and diabetes type. There was strong concordance between EHR-based estimates of CGM use and Dexcom CGM wear time and between estimates of glucose control from both sources. Conclusions: The study demonstrates our ability to reliably integrate CGM devices and EHR data to provide valuable insights into CGM use patterns. The results indicate in the real-world environment that CGM is worn consistently over many years for both patients with T1D and T2D within the Veterans Affairs Healthcare System and is similar across major race/ethnic groups and age-groups.

Evaluating HbA1c-to-average glucose conversion with patient-specific kinetic models for diverse populations

The discrepancy between estimated glycemia from HbA1c values and actual average glucose (AG) levels has significant implications for treatment decisions and patient understanding. Factors contributing to the gap include red blood cell (RBC) lifespan and glucose uptake into the RBC. Personalized models have been proposed to enhance AG prediction accuracy by considering interpersonal variation. This study contributes to our understanding of personalized models for estimating AG from HbA1c. Utilizing data from seven studies (340 participants), including Hispanic/Latino populations with or at risk of non-insulin-treated type 2 diabetes (T2D), we examined kinetic features across cohorts. Additionally, the study simulated scenarios to understand data requirements for improving accuracy. Personalized approaches improved agreement between AG estimations and CGM-AG, particularly with four or more weeks of training CGM data. A multiple linear regression model using kinetic parameters and added clinical features was shown to improve the accuracy of personalized models further. As CGM usage extends beyond type 1 diabetes, there is growing interest in leveraging CGM data for clinical decision-making. Patient-specific models offer a valuable tool for managing glycemic status in patients with discordant HbA1c and AG values.

What Is the Influence of HIV Serostatus on HbA1c? A Prospective Analysis Using Continuous Glucose Monitoring

OBJECTIVE

Type 2 diabetes (T2D) is reported to be more common in people living with HIV (PLWH). Clinical guidelines recommend screening for diabetes in PLWH, but there is no agreed method due to studies reporting HbA1c is falsely low in PLWH. These studies were performed in the early HIV era when participants were taking older preparations of antiretroviral therapy that are rarely used today. We aimed to investigate whether HIV serostatus influences HbA1c.

RESEARCH DESIGNS AND METHODS

We conducted a prospective cohort study of PLWH and age- and sex-matched HIV-negative participants who were purposely recruited from clinics in Brighton, U.K. Each participant wore a Dexcom G6 continuous glucose monitor (CGM) for up to 10 days, had glucose measured during an oral glucose tolerance test, and fructosamine and paired HbA1c were measured. We performed regression analysis to assess the influence of HIV on HbA1c and used a separate model for CGM glucose, venous glucose, and fructosamine. In addition, we included predictor variables used in previous studies that explored HbA1c discrepancy.

RESULTS

We recruited 60 PLWH (90% men, 50% with T2D, mean ± SD age 57 ± 10.7 years, 100% undetectable viral load) and 48 people without HIV (92% men, 30% with T2D, mean age 57.7 ± 8.9 years). We found that HIV serostatus did not have a significant influence on HbA1c within the regression models.

CONCLUSIONS

We performed a comprehensive assessment of glycemia to assess whether HIV serostatus influences HbA1c. We did not find any strong evidence that HIV serostatus influenced HbA1c. The results of our study support incorporating HbA1c into routine clinical blood work in PLWH.

The role of glycated hemoglobin in the diagnosis of prediabetes and diabetes mellitus in young women with polycystic ovary syndrome

OBJECTIVE

To compare glycated hemoglobin (HbA1c) and the oral glucose tolerance test (OGTT) for the diagnosis of prediabetes and diabetes in young women with polycystic ovary syndrome (PCOS).

PATIENTS AND DESIGN

This cross-sectional study included 154 women aged 20-40 years with a diagnosis of PCOS, who were screened for prediabetes and diabetes by the OGTT and HbA1c. Women with diabetes, hyperprolactinemia, thyroid or adrenal diseases, and anemia and users of hormonal contraception or corticosteroids were excluded.

MEASUREMENTS

Clinical, biochemical and ultrasound data were collected from the electronic medical records. The women were classified as having normal glucose metabolism, prediabetes, or diabetes based on the diagnostic tests. Sensitivity and specificity were calculated and the Kappa method was used to assess agreement between the two methods.

RESULTS

According to the OGTT and HbA1c values, 79.2% and 76% of the women were within the normal range, respectively, 16.8% and 19.5% had prediabetes, and 4% and 4.5% had diabetes (p > .05). The Kappa coefficient of 0.41 (95% confidence interval: 0.24-0.58) indicated medium agreement between methods. Considering the OGTT as the gold standard, the specificity of HbA1c was 89.5% and sensitivity was 85.7% in the diagnosis of prediabetes and 100% and 66.7%, respectively, in the diagnosis of diabetes.

CONCLUSION

The HbA1c, when compared to the OGTT, showed high sensitivity and specificity in the diagnosis of prediabetes in young women with PCOS.

Association between the triglyceride-glucose index and impaired cardiovascular fitness in non-diabetic young population

BACKGROUND

The triglyceride-glucose (TyG) index has been linked to the onset, progression, and prognosis of cardiovascular disease (CVD) in middle-aged and elderly individuals. Nevertheless, the relationship between the TyG index and impaired cardiovascular fitness (CVF) remains unexplored in non-diabetic young population.

METHODS

We used data from the National Health and Nutrition Examination Survey (NHANES) study (1999-2004) to conduct a cross-sectional study of 3364 participants who completed an examination of CVF. Impaired CVF was defined as low and moderate CVF levels determined by estimated maximal oxygen consumption (Vo2max), based on sex- and age-specific criteria. The TyG index was calculated by [Formula: see text].

RESULTS

The age (median with interquartile range) of the study population was 28 (19-37) years, and the TyG index (median ± standard deviation) was 8.36 ± 0.52. A significant association between the TyG index and impaired CVF was found in multivariable logistical regression analysis (per 1-unit increase in the TyG index: OR, 1.46; 95% Cl 1.13-1.90). A dose‒response relationship between the TyG index and impaired CVF was presented by restricted cubic splines (RCS). A significant interaction (p = 0.027) between sex and the TyG index for impaired CVF was found in the population aged < 20 years.

CONCLUSIONS

In non-diabetic young population, individuals with higher TyG index values are at an increased likelihood of encountering impaired CVF. Furthermore, sex may exert an impact on CVF, as males tend to be more susceptible to impaired CVF under comparable TyG index conditions.

Racial and Ethnic Differences in the Association Between Mean Glucose and Hemoglobin A1c

Background: Studies have reported significantly higher hemoglobin A1c (A1C) in African American patients than in White patients with the same mean glucose, but less is known about other racial/ethnic groups. We evaluated racial/ethnic differences in the association between mean glucose, based on continuous glucose monitor (CGM) data, and A1C. Methods: Retrospective study among 1788 patients with diabetes from Kaiser Permanente Northern California (KPNC) who used CGM devices during 2016 to 2021. In this study population, there were 5264 A1C results; mean glucose was calculated from 124,388,901 CGM readings captured during the 90 days before each A1C result. Hierarchical mixed models were specified to estimate racial/ethnic differences in the association between mean glucose and A1C. Results: Mean A1C was 0.33 (95% confidence interval: 0.23-0.44; P < 0.0001) percentage points higher among African American patients relative to White patients for a given mean glucose. A1C results for Asians, Latinos, and multiethnic patients were not significantly different from those of White patients. The slope of the association between mean glucose and A1C did not differ significantly across racial/ethnic groups. Variance for the association between mean glucose and A1C was substantially greater within groups than between racial/ethnic groups (65% vs. 9%, respectively). Conclusions: For African American patients, A1C results may overestimate glycemia and could lead to premature diabetes diagnoses, overtreatment, or invalid assessments of health disparities. However, most of the variability in the mean glucose-A1C association was within racial/ethnic groups. Treatment decisions driven by guideline-based A1C targets should be individualized and supported by direct measurement of glycemia.

Effect of biological variation in HbA1c and blood glucose on the diagnosis of prediabetes

INTRODUCTION

People with a low or high haemoglobin glycation index (HGI) have lower or higher HbA1c than other people with the same FPG. This study compared the prevalence of prediabetes based on FPG, 2hOGTT and HbA1c in people with low, moderate or high HGI.

METHODS

Prediabetes was diagnosed based on ADA cutpoints in 10,488 NHANES participants without self-reported diabetes. HGI was calculated as the difference between a participant's observed HbA1c and a predicted HbA1c where predicted HbA1c = 0.024 FPG + 3.1. Participants were divided into low (HGI < -0.15%), moderate (HGI -0.15% to +0.15%) and high (HGI > +0.15%) HGI subgroups.

RESULTS

The prevalence of prediabetes was 42.4% based on FPG, 27.2% based on HbA1c and 17.2% based on 2hOGTT. FPG and HbA1c thus overdiagnosed prediabetes by 25.2% and 10.0%, respectively, compared to the OGTT gold standard. Prevalence was (1) similar in low, moderate and high HGI participants based on 2hOGTT, (2) highest in low HGI participants based on FPG, and (3) highest in high HGI participants based on HbA1c. Among participants with mismatched FPG and HbA1c, OGTT was normal in (1) 79.5% of participants with normal FPG but prediabetic HbA1c (mean HGI = +0.53%), and (2) 75.2% of participants with normal HbA1c but prediabetic FPG (mean HGI = -0.30%).

CONCLUSIONS

FPG overdiagnosed prediabetes in people with low HGI. HbA1c overdiagnosed prediabetes in people with high HGI. Clinical use of HGI could improve prediabetes diagnosis and help health care providers avoid inappropriate or delayed treatment of people with extremes of HGI.

Oral Manifestations: A Reliable Indicator for Undiagnosed Diabetes Mellitus Patients

OBJECTIVES

 This article identifies undiagnosed DM (UDM) cases in the Pakistani population by perceiving the signs and symptoms of DM and associating them with oral manifestations.

MATERIAL AND METHODS

 In this cross-sectional study, patients showing at least three or more classical or warning signs like polydipsia, polyuria, polyphagia, and general weakness were considered UDM cases. Detailed oral examination for gingivitis, periodontitis, halitosis, xerostomia, and tongue manifestations was done followed by the hemoglobin A1c (HbA1c) analysis.

RESULTS

 Out of 5,878 patients, 214 UDM cases were identified, where 31.8% and 39.7% of the patients were diagnosed as prediabetics and diabetics, respectively, based on HbA1c analysis. Prevalence of gingivitis (97.6%), fissured tongue (91.8%), generalized periodontitis (85.9%), thick saliva (87.1%), xerostomia (84.7%), burning mouth syndrome (63.5%), yellow discoloration of tongue (57.6%), and ecchymosis/ulcers (43.5%) were more in diabetics as compared to prediabetic patients and normal population.

CONCLUSION

 The oral manifestations can be crucial for identifying UDM cases. Dentists can play a pivotal role by taking detailed history and thorough oral examination. If three or more symptoms as concluded above are present, an HbA1c analysis should be conducted to prevent preop and postop complications associated with DM.

The clinical significance of serum HbA1c to diagnose diabetes mellitus during acute pancreatitis

AIMS

To investigate the prevalence of diabetes mellitus (DM) in acute pancreatitis (AP) patients and to explore the extent to which inflammatory stress affects plasma glucose (PG) levels in AP patients.

METHODS

A retrospective analysis of 2163 AP patients was performed. The PG differences among AP patients under differing pancreatic necrosis conditions and inflammation severity were compared. Receiver operating characteristic curves were used to assess whether fasting PG in the inflammatory stage of AP might be used for DM screening.

RESULTS

The overall DM prevalence was 19.97% in AP patients, 32.41% of whom had newly diagnosed DM (based on HbA1c levels in patients who self-reported no DM). The DM prevalence was 46.93% in hyperlipidemic AP patients, 44.14% of whom had newly diagnosed DM. In patients with and without pancreatic necrosis, the optimal PG thresholds for the screening of newly diagnosed DM were 10.40 mmol/L and 8.21 mmol/L, respectively, with an AUC of 0.959 ± 0.034 (P < 0.001) and 0.972 ± 0.006 (P < 0.001), respectively.

CONCLUSIONS

For hospitalized AP patients and fasting PG levels exceeding 10 mmol/L (with necrosis) or 8 mmol/L (without necrosis) (P < 0.001), HbA1c testing is recommended to investigate the presence of comorbid undiagnosed DM.

Protein glycation in diabetes mellitus

Diabetes mellitus is the ninth leading cause of mortality worldwide. It is a complex disease that manifests as chronic hyperglycemia. Glucose exposure causes biochemical changes at the proteome level as reflected in accumulation of glycated proteins. A prominent example is hemoglobin A1c (HbA1c), a glycated protein widely accepted as a diabetic indicator. Another emerging biomarker is glycated albumin which has demonstrated utility in situations where HbA1c cannot be used. Other proteins undergo glycation as well thus impacting cellular function, transport and immune response. Accordingly, these glycated counterparts may serve as predictors for diabetic complications and thus warrant further inquiry. Fortunately, modern proteomics has provided unique analytic capability to enable improved and more comprehensive exploration of glycating agents and glycated proteins. This review broadly covers topics from epidemiology of diabetes to modern analytical tools such as mass spectrometry to facilitate a better understanding of diabetes pathophysiology. This serves as an attempt to connect clinically relevant questions with findings of recent proteomic studies to suggest future avenues of diabetes research.

2. Classification and Diagnosis of Diabetes: Standards of Care in Diabetes-2023

The American Diabetes Association (ADA) "Standards of Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, a multidisciplinary expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations and a full list of Professional Practice Committee members, please refer to Introduction and Methodology. Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

Criteria for prediabetes and posttransplant diabetes mellitus after kidney transplantation: A 2-year diagnostic accuracy study of participants from a randomized controlled trial

Posttransplant diabetes mellitus (PTDM) and prediabetes (impaired glucose tolerance [IGT] and impaired fasting glucose [IFG]) are associated with cardiovascular events. We assessed the diagnostic performance of fasting plasma glucose (FPG) and HbA1c as alternatives to oral glucose tolerance test (OGTT)-derived 2-hour plasma glucose (2hPG) using sensitivity and specificity in 263 kidney transplant recipients (KTRs) from a clinical trial. Between visits at 6, 12, and 24 months after transplantation, 28%-31% of patients switched glycemic category (normal glucose tolerance [NGT], IGT/IFG, PTDM). Correlations of FPG and HbA1c against 2hPG were lower at 6 months (r = 0.59 [FPG against 2hPG]; r = 0.45 [HbA1c against 2hPG]) vs. 24 months (r = 0.73 [FPG against 2hPG]; r = 0.74 [HbA1c against 2hPG]). Up to 69% of 2hPG-defined PTDM cases were missed by conventional HbA1c and FPG thresholds. For prediabetes, concordance of FPG and HbA1c with 2hPG ranged from 6%-9%. In conclusion, in our well-defined randomized trial cohort, one-third of KTRs switched glycemic category over 2 years and although the correlations of FPG and HbA1c with 2hPG improved with time, their diagnostic concordance was poor for PTDM and, especially, prediabetes. Considering posttransplant metabolic instability, FPG's and HbA1c 's diagnostic performance, the OGTT remains indispensable to diagnose PTDM and prediabetes after kidney transplantation.

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.

PNPLA3 I148M Polymorphism Influences Renal Function in Children With Obesity and Prediabetes

OBJECTIVE

Nonalcoholic fatty liver disease negatively impacts on renal function with the contribution of the I148 M variant in the patatin-like phospholipase-containing domain 3 (PNPLA3) gene. We hypothesized that children with prediabetes present with a lower estimated glomerular filtration rate (eGFR) than those with normal glucose tolerance (NGT) and that the 148M PNPLA3 allele could play a worsening role. We aimed evaluating the influence of the I148 M PNPLA3 polymorphism on the relationship between the eGFR and prediabetes in children with obesity.

METHODS

One thousand thirty-six children underwent to complete assessment and were genotyped for the I148 M PNPLA3 polymorphism.

RESULTS

Patients with prediabetes showed lower eGFR levels (171.03 ± 40.32 vs. 190.80 ± 41.71 mL/min/1.73 m2; P = .001) and higher prevalence of nonalcoholic fatty liver disease (80% vs. 59%; P = .003) than those with NGT. Children with prediabetes showed lower eGFR levels than those with NGT (150.97 ± 14.56 vs. 192.88 ± 40.09; P < .0001) among carriers of the PNPLA3 148M allele. This was not confirmed among patients homozygous for the PNPLA3 I148 allele. A general linear model for eGFR variance confirmed an inverse and significant association of the eGFR with prediabetes in patients carrying the 148M PNPLA3 allele but not in patients homozygous for the PNPLA3 I148 allele.

CONCLUSIONS

Prediabetes negatively affects renal function in children with obesity. This effect is heightened in patients carrying the PNPLA3 148M allele.

Interindividual variability in average glucose-glycated haemoglobin relationship in type 1 diabetes and implications for clinical practice

AIM

Glycated haemoglobin (HbA1c) can fail to reflect average glucose levels, potentially compromising management decisions. We analysed variability in the relationship between mean glucose and HbA1c in individuals with diabetes.

MATERIALS AND METHODS

Three months of continuous glucose monitoring and HbA1c data were obtained from 216 individuals with type 1 diabetes. Universal red blood cell glucose transporter-1 Michaelis constant KM and individualized apparent glycation ratio (AGR) were calculated and compared across age, racial and gender groups.

RESULTS

The mean age (range) was 30 years (8-72) with 94 younger than 19 years, 78 between 19 and 50 years, and 44 were >50 years. The group contained 120 women and 96 men with 106 white and 110 black individuals. The determined KM value was 464 mg/dl and AGR was (mean ± SD) 72.1 ± 7 ml/g. AGR, which correlated with red blood cell lifespan marker, was highest in those aged >50 years at 75.4 ± 6.9 ml/g, decreasing to 73.2 ± 7.8 ml/g in 19-50 years, with a further drop to 71.0 ± 5.8 ml/g in the youngest group (p <0 .05). AGR differed between white and black groups (69.9 ± 5.8 and 74.2 ± 7.1 ml/g, respectively; p < .001). In contrast, AGR values were similar in men and women (71.5 ± 7.5 and 72.5 ± 6.6 ml/g, respectively; p = .27). Interestingly, interindividual AGR variation within each group was at least four-fold higher than average for between-group variation.

CONCLUSIONS

In this type 1 diabetes cohort, ethnicity and age, but not gender, alter the HbA1c-glucose relationship with even larger interindividual variations found within each group than between groups. Clinical application of personalized HbA1c-glucose relationships has the potential to optimize glycaemic care in the population with diabetes.

Metabolic Effects of an Oral Glucose Tolerance Test Compared to the Mixed Meal Tolerance Tests: A Narrative Review

The oral glucose tolerance test (OGTT) is recommended for assessing abnormalities in glucose homeostasis. Recognised as the gold standard test for diagnosing diabetes, the OGTT provides useful information about glucose tolerance. However, it does not replicate the process of absorption and digestion of complex foods, such as that which occurs with a mixed meal tolerance test (MMTT), an alternative that is still not well explored in the diagnosis of metabolic alterations. The MMTT could be an asset in detecting glucose homeostasis disorders, including diabetes since it has more similarities to the common dietary pattern, allowing early detection of subtle changes in metabolic homeostasis in response to combined nutrients. This alternative has the advantage of being more tolerable and pleasant to patients since it induces a more gradual increase in blood glucose, thus reducing the risk of rebound hypoglycemia and other related complications. The present article reviewed the clinical data available regarding the possibility of screening or diagnosing altered glucose homeostasis, including type 2 diabetes mellitus, with the MMTT.

HbA1c Is Disproportionately Higher in Women and Older People With Type 1 Diabetes Compared With Flash Glucose Monitoring Metrics of Glycemic Control

AIMS

Discrepancy between HbA1c and glucose exposure may have significant clinical implications. We sought to assess predictors of disparity between HbA1c and flash monitoring metrics and how these relate to microvascular complications.

METHODS

We conducted a cross-sectional study of adults with type 1 diabetes (n = 518). We assessed the relationship between clinic HbA1c and flash monitoring metrics, predictors of discrepancy between these measurements, and whether discrepancy was associated with microvascular complications.

RESULTS

Actual HbA1c and estimated HbA1c were strongly correlated (r = .779, P < .001). The likelihood of having a higher actual HbA1c than estimated HbA1c was greater with increasing age (OR = 1.055 per year, P < .001) and lower in men (OR = .208, P < .001). HbA1c was significantly lower in men (58 mmol/mol [51-67]) (7.5% [6.8-8.3]) compared to women (61 mmol/mol [54-70], P = .021) (7.7% [7.1-8.6]), despite no significant differences in any flash monitoring metrics. Whereas HbA1c was not different between younger (≤39 years) and older individuals (>39 years) despite significantly higher glucose exposure, in younger people, based on multiple flash monitoring metrics. Having a lower estimated than actual HbA1c was independently associated with a lower prevalence of retinopathy (OR = .55, P = .004).

CONCLUSIONS

HbA1c appears to overestimate glucose exposure in women and older people with type 1 diabetes. This has potentially important clinical implications, as is hinted at by the independent relationship with retinopathy prevalence. It may also be of relevance when considering the use of HbA1c for the diagnosis of diabetes.

American Diabetes Association Professional Practice Committee. 2. Classification and Diagnosis of Diabetes: Standards of Medical Care in Diabetes-2022

The American Diabetes Association (ADA) "Standards of Medical Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, a multidisciplinary expert committee (https://doi.org/10.2337/dc22-SPPC), are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations, please refer to the Standards of Care Introduction (https://doi.org/10.2337/dc22-SINT). Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

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.

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

AIMS

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

HbA1c Screening for Diabetes in Patients with Acute Coronary Syndrome: A Worthwhile Test or a Pitfall?

Background: Diagnostic concordance between HbA1c and other glucose-based tests is imperfect, and data on this problem in acute coronary syndrome (ACS) are still lacking. The aim of this study was to identify undiagnosed glucose abnormalities in ACS patients, and to compare the effectiveness and consistency of the diagnostic screening based on HbA1c to the oral glucose tolerance test (OGTT). Methods: The study group consisted of 121 ACS patients, mean age 62.3 ± 11.6 years, without known glucose abnormalities. HbA1c, admission and fasting plasma glucose in the first days of hospitalization were assessed and referred to the results of OGTT performed two weeks after discharge. Results: OGTT identified normoglycemia in 45%, pre-diabetes in 39.4%, and diabetes in 15.6%, while HbA1c revealed these categories in 39.7%, 51.2%, and 9.1%, respectively. With an HbA1c cut-off ≥6.5% (48 mmol/mol) diagnostic for diabetes, the sensitivity of the method was 41%, while specificity was 98%, compared to the OGTT. The optimal HbA1c cut-off value at the crossing of sensitivity and specificity curves was 5.9%. The HbA1c value recommended for the diagnosis of pre-diabetes and optimal cut-off point were the same (5.7%). Conclusions: Using HbA1c without OGTT in an early but stable phase of ACS may result in a significant underdiagnosis of diabetes.

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

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

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.

2. Classification and Diagnosis of Diabetes: Standards of Medical Care in Diabetes-2021

The American Diabetes Association (ADA) "Standards of Medical Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, a multidisciplinary expert committee (https://doi.org/10.2337/dc21-SPPC), are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations, please refer to the Standards of Care Introduction (https://doi.org/10.2337/dc21-SINT). Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

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.