HbA1c: a review of non-glycaemic variables

Nonlinear association between hemoglobin glycation index and mortality in ischemic stroke Patients: Insights from the MIMIC-IV database

AIMS

Hemoglobin glycation index (HGI) is closely associated with adverse outcomes in several diseases. However, few studies have investigated the correlation between HGI and prognosis in patients with critical ischemic stroke.

METHODS

A cohort of patients was established from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Kaplan-Meier analysis, multivariate regression models, and restricted cubic splines (RCS) were used to investigate the associations between HGI and different outcomes. Mediation models were constructed to determine the mediating role of white blood cell (WBC) counts.

RESULTS

This study included 2,332 participants. In-hospital mortality differs significantly across HGI groups (24.43 %, 11.82 %, and 10.14 %, P < 0.001). Multivariate regression analyses found that lower HGI was significantly associated with greater mortality risk. Nonlinear analyses revealed an L-shaped association between HGI and short-term mortality (30-day and in-hospital), while a reverse J-shaped relationship emerged for long-term (365-day) mortality. Mediation analysis revealed that WBC counts mediated the association with proportions (%) of 33.73, 19.65, and 30.00, respectively.

CONCLUSION

Lower HGI is consistently related to poorer outcomes in patients with critical ischemic stroke. Higher HGI could be a protective factor in the short term but might increase mortality risk in the long term. WBC counts significantly mediate the association.

Association between hemoglobin glycation index and the risk of cardiovascular disease in early-stage cardiovascular-kidney-metabolic syndrome: evidence from the China health and retirement longitudinal study

Background

Cardiovascular-kidney-metabolic (CKM) syndrome reflects the interplay among metabolic risk factors, chronic kidney disease, and cardiovascular disease (CVD). While the hemoglobin glycation index (HGI) has demonstrated prognostic value for cardiovascular events, its clinical utility remains unexplored in early-stage CKM syndrome.

Methods

Participants with early-stage CKM syndrome (stage 0-3) were recruited from the China Health and Retirement Longitudinal Study (CHARLS) database. Using k-means clustering analysis, the participants were classified according to the values of HGI measured at baseline and 3 years later, respectively. The primary outcome was self-reported CVD during the follow-up of at least 3 years. Extreme gradient boosting (XGBoost) algorithm was applied, with the Shapley additive explanation (SHAP) method used to determine feature importance. Multivariable logistics proportional regression analysis the association between HGI and CVD, and restricted cubic spline (RCS) regression assessed potential nonlinear relationships.

Results

A total of 4676 eligible participants were included in the final analysis, with 944 (20.19%) progressed to CVD within 10 years. Among the baseline clinical features, HGI ranked the second for the impact on the occurrence of CVD. According to the changes of HGI values, the participants were clustered into 4 classes. Compared to the class 1 with lower level of HGI, higher risk of CVD was observed in class 3 (adjusted OR: 1.34, 95% CI: 1.06-1.69, P = 0.013) and class 4 (adjusted OR: 1.65, 95% CI: 1.01-2.45, P = 0.025) with higher and rapidly increasing level of HGI. RCS analysis showed cumulative HGI and the risk of CVD were linearly related (P for nonlinearity = 0.967). Subgroup analyses confirmed the stability of the association. Additionally, the SHAP plot revealed that HGI were the more important features than traditional risk factors such as FBG for predicting CVD.

Conclusion

HGI is associated with an elevated risk of CVD in participants with early-stage CKM syndrome. HGI can serve as an independent biomarker for guiding clinical decision-making and managing patient outcomes.

Glucose management indicator: Do we need device-specific equations?

AIM

Glucose management indicator (GMI) may not perform equally well for different continuous glucose monitoring (CGM) systems. Thus, we aimed to develop device-specific GMI for the Guardian 3 and 4 sensors, compare them to the original GMI, and investigate the association between the glycaemic gap (=HbA1c-GMI) and HbA1c.

METHODS

In a single-centre, observational study of adult type 1 diabetes patients using Guardian Sensor 3 (G3) and 4 (G4) CGM devices, we estimated HbA1c using CGM-derived mean glucose for both CGMs using linear mixed models. We compared the estimates and their residuals (G3-gap and G4-gap) to the original GMI and its residuals (Bergenstal-gap) using regression and Bland-Altman plots.

RESULTS

We included 120 adult type 1 diabetes patients (90 with G3 and 30 with G4) and 194 measurement points. We found that for G3 and G4 sensors, GMI significantly underestimated glycaemia in high HbA1c ranges, reaching the clinically significant 0.5 %[4.4 mmol/mol] difference at 7.6 % [60 mmol/mol] for G3 and 8.3 % [67 mmol/mol] for G4 sensors. For G4, GMI significantly overestimated glycaemia in the lower HbA1c range. We found a strong relationship between all 3 gaps and HbA1c, and the slope was steeper for the Bergenstal-gap versus the sensor-specific G3 and G4 gaps. The G3-gap was approximately half as large as the Bergenstal-gap for HbA1c > 7 % [53 mmol/mol], and the G4-gap is approximately half of the Bergenstal-gap for the whole HbA1c range.

CONCLUSION

Device-specific GMI equations could reduce the risk of clinically significant under- and overestimation of HbA1c, improving clinical decision-making.

Glycated albumin and fructosamine do not improve accuracy of glycaemic control assessment in patients with conditions reported to affect HbA1c reliability

AIMS

HbA1c testing in African populations may be limited due to high prevalence of hemoglobinopathies, anaemia, malaria and renal impairment. We aimed to assess the performance of glycated albumin (GA) and fructosamine in comparison to HbA1c for determining glycaemic control in Africans living with type 2 diabetes.

METHODS

We compared the relationship between fructosamine, GA, and HbA1c with mean continuous glucose monitoring (CGM) glucose and assessed the impact of sickle cell trait (SCT), anaemia and renal impairment on the relationship between each measure and CGM glucose.

RESULTS

The overall association of HbA1c, GA and fructosamine with CGM glucose was similar (r = 0.88 [95%CI: 0.84, 0.91], 0.84 [0.79, 0.88] and 0.84 [0.79, 0.88]), respectively. For detecting those with mean CGM glucose >8 mmol/L HbA1c had similar diagnostic accuracy to GA and fructosamine, even in those with conditions reported to affect HbA1c performance (n = 63). We found no evidence that SCT (n = 43/192) altered the relationship between HbA1c, fructosamine or GA with CGM glucose (p > 0.3 for all). However, individuals with anaemia showed an underestimation of CGM glucose by HbA1c and fructosamine compared to those without anaemia (p for interaction <0.005 for both). In contrast, GA with average CGM glucose between those with anaemia and those without were not significantly different.

CONCLUSIONS

Switching to fructosamine or GA is unlikely to improve the accuracy of laboratory glycaemic monitoring beyond that of HbA1c in a population with high prevalence of conditions reported to affect HbA1c reliability.

Association between stress hyperglycemia ratio and acute kidney injury development in patients with sepsis: a retrospective study

Background

Stress hyperglycemia ratio (SHR), which adjusts blood glucose levels using glycated hemoglobin to eliminate the influence of chronic hyperglycemia, has been demonstrated to have superior predictive value than absolute hyperglycemia. However, its predictive value for sepsis-associated acute kidney injury (SA-AKI) remains unclear. This study aimed to investigate the relationship between the SHR and the risk of developing SA-AKI.

Methods

Data were extracted from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Restricted cubic splines (RCS) were employed to depict the relationship between SHR and the likelihood of SA-AKI, determining an optimal cut-off value. Based on this threshold, patients were categorized into two groups. Logistic regression was utilized to evaluate SHR's predictive value for SA-AKI, with adjustments for confounding variables. Propensity score matching (PSM) was applied to balance baseline characteristics. Subgroup and sensitivity analyses were conducted.

Results

A total of 2,249 patients were included. The RCS curve indicated a non-linear positive association between SHR and the likelihood of SA-AKI (P for non-linearity < 0.001), with an optimal cut-off at 1.55. Accordingly, patients were divided into SHR ≤ 1.55 and SHR > 1.55 subgroups, comprising 1,131 and 1,118 individuals, respectively. A higher incidence of SA-AKI was observed in the SHR > 1.55 group (38.64% vs. 27.23%, P < 0.001). This association persisted after baseline adjustment through PSM. Logistic regression analysis confirmed that SHR > 1.55 was linked to increased odds of SA-AKI in both unadjusted (OR: 1.68, P < 0.001) and adjusted models (OR: 1.73, P < 0.001), with SHR ≤ 1.55 serving as the reference. In subgroup analysis, all subgroups consistently demonstrated a significant association between SHR > 1.55 and elevated odds of SA-AKI (all OR > 1). Sensitivity analysis validated that SHR > 1.55 remained significantly correlated with SA-AKI occurrence in the survival subgroup (OR: 1.46, P < 0.001) and the non-CKD subgroup (OR: 1.69, P < 0.001).

Conclusion

The findings indicate a non-linear positive relationship between SHR and the likelihood of SA-AKI in patients with sepsis, suggesting that SHR could be a potential predictor for SA-AKI.

Multi-omics approaches for biomarker discovery and precision diagnosis of prediabetes

Recent advancements in multi-omics technologies have provided unprecedented opportunities to identify biomarkers associated with prediabetes, offering novel insights into its diagnosis and management. This review synthesizes the latest findings on prediabetes from multiple omics domains, including genomics, epigenomics, transcriptomics, proteomics, metabolomics, microbiomics, and radiomics. We explore how these technologies elucidate the molecular and cellular mechanisms underlying prediabetes and analyze potential biomarkers with predictive value in disease progression. Integrating multi-omics data helps address the limitations of traditional diagnostic methods, enabling early detection, personalized interventions, and improved patient outcomes. However, challenges such as data integration, standardization, and clinical validation and translation remain to be resolved. Future research leveraging artificial intelligence and machine learning is expected to further enhance the predictive power of multi-omics technologies, contributing to the precision diagnosis and tailored management of prediabetes.

Emerging biomarkers in type 2 diabetes mellitus

Diabetes mellitus is a chronic condition caused by high blood glucose resulting from insufficient insulin production or cellular resistance to insulin action or both. It is one of the fastest-growing public health concerns worldwide. Development of long-term nephropathy, retinopathy, neuropathy, and cardiovascular disease are some of the complications commonly associated with poor blood glycemic control. Type 2 diabetes mellitus (T2DM), the most prevalent type of diabetes, accounts for around 95 % of all cases globally. Although middle-aged or older adults are more likely to develop T2DM, its prevalence has grown in children and young people due to increased obesity, sedentary lifestyle and poor nutrition. Furthermore, it is believed that more than 50 % of cases go undiagnosed annually. Routine screening is essential to ensure early detection and reduce risk of life-threatening complications. Herein, we review traditional biomarkers and highlight the ongoing pursuit of novel and efficacious biomarkers driven by the objective of achieving early, precise and prompt diagnoses. It is widely acknowledged that individual biomarkers will inevitably have certain limitations necessitating the need for integrating multiple markers in screening.

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.

Novel indicator of microvascular complications in patients with type 2 diabetes mellitus and shortened erythrocyte lifespan: a multicenter cross-sectional analysis

INTRODUCTION

In this study, we assessed whether the ratio of glucose management index (GMI) to glycated albumin (GA) was linked to microvascular complications in patients with type 2 diabetes mellitus (T2DM) who also possessed a shortened erythrocyte lifespan.

METHODS

This study encompassed individuals from the Tianjin Diabetic Retinopathy Screening Cohort who completed continuous glucose monitoring and had an erythrocyte lifespan of under 90 days. Differences in GMI/GA were compared between the T2DM patients with or without microvascular complications, including diabetic kidney disease (DKD) and diabetic retinopathy (DR). The relationship between GMI/GA and microvascular complications (DKD and/or DR) was assessed by dividing GMI/GA into three groups based on tertiles.

RESULTS

Our study comprised 140 participants with T2DM (62 men and 78 women, with a median age of 67 years) with a median DM duration of 9.68 years, a mean glycated hemoglobin A1c (HbA1c) value of 7.10%, and a median GA value of 16.10%. As expected, the lower GMI/GA group exhibited higher HbA1c and GA (P < 0.001) with similar mean glucose levels (P = 0.099). GMI/GA values were significantly higher in participants without microvascular complications than in those with microvascular complications, including DKD and/or DR (P < 0.05). After adjusting for confounders, the lowest GMI/GA group (T1) had a 3.601-fold increased risk of microvascular complications (95% CI, 1.364-9.508, P = 0.010) and a 3.830-fold increased risk of DKD, specifically (95% CI, 1.364-12.222, P = 0.023) relative to the highest group (T3).

CONCLUSION

GMI/GA serves as a novel risk indicator for microvascular complications in T2DM, independent of HbA1c.

Abnormally Low HbA1c Caused by Hemolytic Anemia, a Case Report and Literature Review

Hemoglobin A1c is a widely used diagnostic tool for monitoring glycemic control in diabetes management. However, its accuracy can be influenced by various factors. We present a case of a 17-year-old boy with abnormally low Hemoglobin A1c levels caused by warm autoantibody-induced hemolytic anemia. This case highlights the importance of considering conditions that may affect erythrocyte survival, and the potential interferences when interpreting Hemoglobin A1c results to ensure accurate diagnosis and effective management of diabetes.

Factors associated with severity and anatomical distribution of diabetic foot ulcer in a tertiary care hospital in Bangladesh: A cross-sectional study

Diabetic foot ulcers are characterized by disturbances in the epidermis and/or a portion of the dermis in patients with the disease. With over a million amputations performed annually, it has also emerged as one of the primary causes of lower limb amputation globally. To better understand the severity and anatomical distribution of ulcerated areas in patients with type II diabetes mellitus, this study aimed to identify the factors associated with diabetic foot ulcers (DFUs). This descriptive cross-sectional study was conducted at M Abdur Rahim Medical College Hospital in Dinajpur, Bangladesh, from July to September 2023. The study population was selected using a purposive sampling technique based on the patients' availability during their usual and regular treatment at MARMCH. Using a Bangla questionnaire data was obtained to evaluate the DFUs, in addition to measuring blood pressure and assessing the affected area's neurological function. The severity of the ulcer is calculated by using the Wagner grading system. Data was analyzed by using STATS v15 and chi-square was applied. A total of 113 DFU patients took part in this study. The mean age in years was 56 ± 12 (SD + mean) and the male proportion was greater (61.9%). Most of them (93.91%) were negligent about foot care and suffered from severe DFU (86.37%). The majority of respondents (57.94%) had a right foot ulcer, of which 94.50% had severe ulcers. Almost all ulcers were severe (86.14%) and measured <5 cm in diameter (69.71%). The results highlight the tremendous burden of DFUs, which can have serious consequences and substantial mental and economic effects on patients' healthcare systems.

Hemoglobin glycation index and cardiovascular outcomes in patients with diabetes and coronary artery disease: insights from a large cohort study

BACKGROUND/OBJECTIVES

The hemoglobin glycation index (HGI) has been demonstrated to serve as a substitute for the individual bias in glycosylated hemoglobin A1c (HbA1c). Our objective was to assess the correlation between HGI and cardiovascular (CV) outcomes in patients with diabetes and coronary artery disease (CAD).

SUBJECTS/METHODS

We sequentially recruited 11921 patients with diabetes and CAD at Fuwai Hospital. The patients were categorized into five groups based on their HGI quintiles, ranging from Q1 to Q5. The primary endpoint was the occurrence of major adverse cardiac events (MACEs), which included CV death and nonfatal myocardial infarction.

RESULTS

During the median 3-year follow-up, 327 (2.7%) MACEs were observed. A U-shaped relationship between HGI and 3-year MACEs was demonstrated by restricted cubic spline (RCS) after multivariable adjustment (nonlinear P = 0.014). The Kaplan-Meier curves demonstrated that the Q2 group had the lowest risk of MACE (P = 0.006). When comparing the HGI Q2 group, multivariable Cox regression models showed that both low (Q1) and high (Q4 or Q5) HGI were linked to a higher risk of MACEs (all P < 0.05). Patients with a low HGI (Q1) had a significantly increased risk of all-cause and CV death, with a 1.70-fold increase in both cases (both P < 0.05).

CONCLUSIONS

In individuals with diabetes and established CAD, HGI levels were found to have a U-shaped relationship with the occurrence of MACEs over a period of three years. Significantly, those with low HGI had an increased risk of CV death.

Vitamin D Status, Vitamin D Receptor Polymorphisms, and Risk of Type 2 Diabetes: A Prospective Cohort Study

CONTEXT

Vitamin D status has been associated with risk of type 2 diabetes (T2D), but evidence is scarce regarding whether such relation differs by glycemic status.

OBJECTIVE

To prospectively investigate the association between serum 25-hydroxyvitamin D (25(OH)D) and risk of incident T2D across the glycemic spectrum and the modification effect of genetic variants in the vitamin D receptor (VDR).

METHODS

This prospective study included 379 699 participants without T2D at baseline from the UK Biobank. Analyses were performed according to glycemic status and HbA1c levels. Cox proportional hazard models were used to calculate hazard ratios (HRs) and 95% CIs.

RESULTS

During a median of 14.1 years of follow-up, 6315 participants with normoglycemia and 9085 patients with prediabetes developed T2D. Compared with individuals with 25(OH)D < 25 nmol/L, the multivariable-adjusted HRs (95% CIs) of incident T2D for those with 25(OH)D ≥ 75 nmol/L was 0.62 (0.56, 0.70) among the normoglycemia group and 0.64 (0.58, 0.70) among the prediabetes group. A significant interaction was observed between 25(OH)D and VDR polymorphisms among participants with prediabetes (P interaction = .017), whereby the reduced HR of T2D associated with higher 25(OH)D was more prominent in those carrying the T allele of rs1544410. Triglyceride levels mediated 26% and 34% of the association between serum 25(OH)D and incident T2D among participants with normoglycemia and prediabetes, respectively.

CONCLUSION

Higher serum 25(OH)D concentrations were associated with lower T2D risk across the glycemic spectrum below the threshold for diabetes, and the relations in prediabetes were modified by VDR polymorphisms. Improving the lipid profile, mainly triglycerides, accounted for part of the favorable associations.

An incidental finding of a hemoglobin E variant in a diabetic patient with an abnormal glycated hemoglobin level: a case report

BACKGROUND

Glycated hemoglobin is a well-known marker for evaluating long-term glycemic control. However, the accuracy of glycated hemoglobin measurement can be affected by the presence of hemoglobin variants, which makes the determination and interpretation of glycated hemoglobin values in terms of glycemic control not only difficult but also misleading. Here we present the first ever case of a patient with type 2 diabetes with hemoglobin E from Nepal, diagnosed incidentally because of spurious glycated hemoglobin levels.

CASE PRESENTATION

A 45-year-old Hindu Mongolian female with a history of type 2 diabetes for around 9 years but not very compliant with follow-ups was referred to our facility for plasma fasting and postprandial blood glucose levels and glycated hemoglobin. Fasting and postprandial blood sugars were found to be high. A consistent very low glycated hemoglobin by two different high-performance liquid chromatography (HPLC) methods compelled us to call the patient for a detailed clinical history and for the records of investigations done in the past. The patient has been a known case of type 2 diabetes for around 9 years and presented irregularly for follow-up visits. Around 4 years ago, she presented to a healthcare facility with fatigue, severe headaches, pain in the abdomen, discomfort, and dizziness for a couple of months, where she was shown to have high blood glucose. She was referred to a tertiary-level hospital in Kathmandu, where she was prescribed metformin 500 mg once daily (OD). Due to her abnormal hemoglobin A1c reports, she was then sent to the National Public Health Laboratory for repeat investigations. Her blood and urine investigations were sent. Complete blood count findings revealed high red blood cell and white blood cell counts, a low mean corpuscular volume, and a high red cell distribution width-coefficient of variation. Other parameters, including serum electrolytes, renal function tests, liver function tests, and urine routine examinations, were within normal limits. A peripheral blood smear revealed microcytic hypochromic red cells with some target cells. Hemoglobin electrophoresis showed a very high percentage of hemoglobin E, a very low percentage of hemoglobin A2, and normal proportions of hemoglobin A and hemoglobin F. A diagnosis of homozygous hemoglobin E was made, and family screening was advised.

CONCLUSIONS

Clinicians should be aware of the limitations of glycated hemoglobin estimation by ion exchange high-performance liquid chromatography in patients with hemoglobin E and other hemoglobin variants. If the clinical impression and glycated hemoglobin test results do not match, glycated hemoglobin values should be determined with a second method based on a different principle, and glycemic status should be confirmed through alternative investigations, preferably those that are not influenced by the presence of hemoglobin variants (for example, boronate affinity chromatography, fructosamine test, glycated albumin test, the oral glucose tolerance test, continuous glucose monitoring, etc.). Consistent or even doubtful results should also raise the suspicion of a hemoglobin variant, which should be confirmed through further evaluation and investigations.

Emerging biosensor probes for glycated hemoglobin (HbA1c) detection

Glycated hemoglobin (HbA1c), originating from the non-enzymatic glycosylation of βVal1 residues in hemoglobin (Hb), is an essential biomarker indicating average blood glucose levels over a period of 2 to 3 months without external environmental disturbances, thereby serving as the gold standard in the management of diabetes instead of blood glucose testing. The emergence of HbA1c biosensors presents affordable, readily available options for glycemic monitoring, offering significant benefits to small-scale laboratories and clinics. Utilizing nanomaterials coupled with high-specificity probes as integral components for recognition, labeling, and signal transduction, these sensors demonstrate exceptional sensitivity and selectivity in HbA1c detection. This review mainly focuses on the emerging probes and strategies integral to HbA1c sensor development. We discussed the advantages and limitations of various probes in sensor construction as well as recent advances in diverse sensing strategies for HbA1c measurement and their potential clinical applications, highlighting the critical gaps in current technologies and future needs in this evolving field.

HIV and type 2 diabetes: An evolving story

INTRODUCTION

Diabetes is widely reported to be more common in people living with HIV (PLWH). Much of the data supporting this originated during the earlier HIV era. The perceived increased risk of type 2 diabetes is reflected in HIV clinical guidelines that recommend screening for diabetes in PLWH on anti-retroviral therapy (ART). However, international HIV clinical guidelines do not agree on the best marker of glycaemia to screen for diabetes. This stems from studies that suggest HbA1c underestimates glycaemia in PLWH.

METHODS

Within this review we summarise the literature surrounding the association of HIV and type 2 diabetes and how this has changed over time. We also present the evidence on HbA1c discrepancy in PLWH.

CONCLUSION

We suggest there is no basis to any international guidelines to restrict HbA1c based on HIV serostatus. We recommend, using the current evidence, that PLWH should be screened annually for diabetes in keeping with country specific guidance. Finally, we suggest future work to elucidate phenotype and natural history of type 2 diabetes in PLWH across all populations.

Lower Dietary Magnesium Is Associated with a Higher Hemoglobin Glycation Index in the National Health and Nutrition Examination Survey

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

Discordance Between Glycated Hemoglobin A1c and the Glucose Management Indicator in People With Diabetes and Chronic Kidney Disease

INTRODUCTION

Assessment of glucose exposure via glycated hemoglobin A1c (HbA1c) has limitations for interpretation in individuals with diabetes and chronic kidney disease (CKD). The glucose management indicator (GMI) derived from continuous glucose monitoring (CGM) data could be an alternative. However, the concordance between HbA1c measured in laboratory and GMI (HbA1c-GMI) is uncertain in individuals with CKD. The purpose of this study is to analyze this discrepancy.

MATERIAL AND METHOD

We performed a multicentric, retrospective, observational study. A group of individuals with diabetes and CKD (n = 170) was compared with a group of individuals with diabetes without CKD (n = 185). All individuals used an intermittently scanned continuous glucose monitoring (isCGM). A comparison of 14-day and 90-day glucose data recorded by the isCGM was performed to calculate GMI and the discordance between lab HbA1c and GMI was analyzed by a Bland-Altman method and linear regression.

RESULTS

HbA1c-GMI discordance was significantly higher in the CKD group versus without CKD group (0.78 ± 0.57 [0.66-0.90] vs 0.59 ± 0.44 [0.50-0.66]%, P < .005). An absolute difference >0.5% was found in 68.2% of individuals with CKD versus 42.2% of individuals without CKD. We suggest a new specific formula to estimate HbA1c from the linear regression between HbA1c and mean glucose CGM, namely CKD-GMI = 0.0261 × 90-day mean glucose (mg/L) + 3.5579 (r2 = 0.59).

CONCLUSIONS

HbA1c-GMI discordance is frequent and usually in favor of an HbA1c level higher than the GMI value, which can lead to errors in changes in glucose-lowering therapy, especially for individuals with CKD. This latter population should benefit from the CGM to measure their glucose exposure more precisely.

Expert Recommendations for Using Time-in-Range and Other Continuous Glucose Monitoring Metrics to Achieve Patient-Centered Glycemic Control in People With Diabetes

New metrics for assessing glycemic control beyond HbA1c have recently emerged due to the increasing use of continuous glucose monitoring (CGM) in diabetes clinical practice. Among them, time in range (TIR) has appeared as a simple and intuitive metric that correlates inversely with HbA1c and has also been newly linked to the risk of long-term diabetes complications. The International Consensus on Time in Range established a series of target glucose ranges (TIR, time below range and time above range) and recommendations for time spent within these ranges for different diabetes populations. These parameters should be evaluated together with the ambulatory glucose profile (AGP). Using standardized visual reporting may help people with diabetes and healthcare professionals in the evaluation of glucose control in frequent clinical situations. The objective of the present review is to provide practical insights to quick interpretation of patient-centered metrics based on flash glucose monitoring data, as well as showing some visual examples of common clinical situations and giving practical recommendations for their management.

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

INTRODUCTION

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

METHODS

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

RESULTS

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

CONCLUSION

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

The risk of clinical misinterpretation of HbA1c: Modelling the impact of biological variation and analytical performance on HbA1c used for diagnosis and monitoring of diabetes

BACKGROUND

The validity of clinical interpretation of HbA1c depends on the analytical performance of the method and the biological variation of HbA1c in patients. The contribution of non-glucose related factors to the biological variation of HbA1c (NGBVA1c) is not known. This paper explores the cumulative impact of analytical errors and NGBVA1c on the risk of misinterpretation.

METHODS

A model has been developed to predict the risk of misinterpretation of HbA1c for diagnosis and monitoring with variables for analytical performance and levels of NGBVA1c.

RESULTS

The model results in probabilities of misinterpretation for a given HbA1c.

EXAMPLE

for an HbA1c 43 mmol/mol (6.1%), bias 1 mmol/mol (0.09%), CV 3% (2%) used for diagnosis, the probabilities of misinterpretation range from 1 to 19% depending on the contribution of NGBVA1c to the biological variation of HbA1c.

CONCLUSIONS

In addition to analytical bias and imprecision, NGBVA1c contributes to the risk of misinterpretation, but the relative impact is different per clinical application of HbA1c. For monitoring, imprecision is the predominating factor, for diagnosis both biological variation and analytical bias. Given the increasing use of HbA1c for diagnosis, increase of knowledge on NGBVA1c, decrease of analytical bias, and awareness of the risk of misinterpretation are required.

Intensified glycemic control by HbA1c for patients with coronary heart disease and Type 2 diabetes: a review of findings and conclusions

The occurrence and development of coronary heart disease (CHD) are closely linked to fluctuations in blood glucose levels. While the efficacy of intensified treatment guided by HbA1c levels remains uncertain for individuals with diabetes and CHD, this review summarizes the findings and conclusions regarding HbA1c in the context of CHD. Our review showed a curvilinear correlation between regulated level of HbA1c and therapeutic effectiveness of intensified glycemic control among patients with type 2 diabetes and coronary heart disease. It is necessary to optimize the dynamic monitoring indicators of HbA1c, combine genetic profiles, haptoglobin phenotypes for example and select more suitable hypoglycemic drugs to establish more appropriate glucose-controlling guideline for patients with CHD at different stage of diabetes.

Racial and Ethnic Equity in Care for Hypertension and Diabetes in an Urban Indian Health Organization

Approximately 70% of American Indian/Alaska Native (AI/AN) individuals reside in urban areas. Urban Indian Health Organizations (UIHOs) provide culturally engaged primary care for AI/AN patients and members of other racial and ethnic groups who have experienced disparities in diabetes and hypertension care, and are commonly affected by social and economic barriers to care. We assessed whether disparities were present between the racial and ethnic groups served by the largest UIHO in the USA. We developed retrospective cohorts of patients with hypertension or diabetes receiving primary care from this UIHO, measuring differences between AI/AN, Spanish-preferring Latinx, English-preferring Latinx, Black, and White patients in mean systolic blood pressure (SBP) and mean hemoglobin A1c (A1c) as primary outcomes. To assess processes of care, we also compared visit intensity, missed visits, and medication treatment intensity in regression models adjusted for sociodemographic and clinical characteristics. For hypertension (n = 2148), adjusted mean SBP ranged from 135.8 mm Hg among Whites to 141.3 mm Hg among Blacks (p = 0.06). For diabetes (n = 1211), adjusted A1c ranged from 7.7% among English-preferring Latinx to 8.7% among Blacks (p = 0.38). Care processes for both hypertension and diabetes varied across groups. No group consistently received lower-quality care. This UIHO provided care of comparable quality for hypertension and diabetes among urban-dwelling AI/ANs and members of other racial, ethnic, and language preference groups. Systematic assessments of care quality in UIHOs may help demonstrate the importance of their role in providing care and improve the quality of care.

The prediabetes conundrum: striking the balance between risk and resources

The current definition of prediabetes is controversial and subject to continuous debate. Nonetheless, prediabetes is a risk factor for type 2 diabetes, is highly prevalent and is associated with diabetic complications and mortality. Thereby, it has the potential to become a huge strain on healthcare systems in the future, necessitating action from legislators and healthcare providers. But how do we best reduce its associated burden on health? As a compromise between differing opinions in the literature and among the authors of this article, we suggest stratifying individuals with prediabetes according to estimated risk and only offering individual-level preventive interventions to those at high risk. At the same time, we argue to identify those with prediabetes and already established diabetes-related complications and treat them as we would treat individuals with established type 2 diabetes.

Predicting the HbA1c level following glucose-lowering interventions in individuals with HbA1c-defined prediabetes: a post-hoc analysis from the randomized controlled PRE-D trial

PURPOSE

To investigate whether the prediction of post-treatment HbA_1c levels can be improved by adding an additional biomarker of the glucose metabolism in addition to baseline HbA_1c.

METHODS

We performed an exploratory analysis based on data from 112 individuals with prediabetes (HbA_1c 39-47 mmol) and overweight/obesity (BMI ≥ 25 kg/m²), who completed 13 weeks of glucose-lowering interventions (exercise, dapagliflozin, or metformin) or control (habitual living) in the PRE-D trial. Seven prediction models were tested; one basic model with baseline HbA_1c as the sole glucometabolic marker and six models each containing one additional glucometabolic biomarker in addition to baseline HbA_1c. The additional glucometabolic biomarkers included: 1) plasma fructosamine, 2) fasting plasma glucose, 3) fasting plasma glucose × fasting serum insulin, 4) mean glucose during a 6-day free-living period measured by a continuous glucose monitor 5) mean glucose during an oral glucose tolerance test, and 6) mean plasma glucose × mean serum insulin during the oral glucose tolerance test. The primary outcome was overall goodness of fit (R²) from the internal validation step in bootstrap-based analysis using general linear models.

RESULTS

The prediction models explained 46-50% of the variation (R²) in post-treatment HbA1c with standard deviations of the estimates of ~2 mmol/mol. R² was not statistically significantly different in the models containing an additional glucometabolic biomarker when compared to the basic model.

CONCLUSION

Adding an additional biomarker of the glucose metabolism did not improve the prediction of post-treatment HbA_1c in individuals with HbA_1c-defined prediabetes.

Evaluation of the hemoglobin a1c test in detecting pediatric prediabetes

Aim: The aim of this study is to evaluate the diagnostic performance of the hemoglobin a1c (Hba1c) test in pediatric prediabetes, and to determine the cut-off value for the pediatric age , to examine the relationship of the Hba1c test between glucose levels,. Materials and Methods: This study was carried out by retrospectively evaluating the data of 548 children. Prediabetes cases were determined by taking fasting and oral glucose tolerance test (OGTT) 2 hour (2h) glucose levels as a reference. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated for Hba1c, fasting, and OGTT 2h glucose tests. The area under the curve (AUC) was calculated for each test by receiver-operating characteristic analysis. Results: Based on glucose values, 1.6% of individuals were assigned to the diabetes mellitus, 14.6% to prediabetes, and 83.8% to normoglycemia group. When 5.7 was used as the threshold value for Hba1c in prediabetes, the sensitivity was 31.3%, specificity was 87.8%, PPV was 30.9%, and NPV was 88.0%, AUC:0,686. The optimal cut-off value of Hba1c was determined as 5.35%. At this value, the sensitivity was calculated as 66.3% and the specificity as 61.4%. Conclusion: Although the use of adult HbA1c criteria for the diagnosis of prediabetes in the pediatric ages is controversial due to the differences between the results of OGTT and HbA1c-based tests, prediabetes screening is still important. HbA1c≥5.35 will be useful to follow up on children with prediabetes in terms of risk and to screen them with OGTT.

A Statistical Simulation to Evaluate the Robustness of Hb A1c Measurement in the Presence of Quantitative Error

BACKGROUND

The performance requirements for hemoglobin (Hb) A1c analysis have been questioned as analytic methods have improved. We developed a statistical simulation that relates error to the clinical utility of an oft-used laboratory test, as a means of assessing test performance expectations.

METHODS

Finite mixture modeling of the Centers for Disease Control and Prevention-National Health and Nutrition Examination Survey (NHANES) 2017-2020 Hb A1c data in conjunction with Monte Carlo sampling were used to model and simulate a population prior to the introduction of error into the results. The impact of error on clinical utility was assessed by categorizing the results using the American Diabetes Association (ADA) diagnostic criteria and assessing the sensitivity and specificity of Hb A1c under various degrees of error (bias and imprecision).

RESULTS

With the current allowable total error threshold of 6% for Hb A1c measurement, the simulation estimated a worst case between 50% and 60% for both test sensitivity and specificity for the non-diabetic category. Similarly, sensitivity and specificity estimates for the pre-diabetic category were 30% to 40% and 60% to 70%, respectively. Finally, estimates for the diabetic category yielded values of 80% to 90% for sensitivity and >90% for specificity.

CONCLUSIONS

Bias and imprecision greatly affect the clinical utility of Hb A1c for all patient groups. The simulated error demonstrated in this modeling impacts 3 critical applications of the Hb A1c in diabetes management: the capacity to reliably screen, diagnostic accuracy, and utility in diabetes monitoring.

Novel clusters of newly-diagnosed type 2 diabetes and their association with diabetic retinopathy: a 3-year follow-up study

BACKGROUND

Cluster analysis may assist in stratifying heterogeneous clinical presentations of type 2 diabetes (T2D). However, the association of cluster-based subgroups with diabetes-related outcomes such as diabetic retinopathy remains unclear. This study was aimed to address this issue with novel clusters of T2D derived from four simple parameters.

METHOD

We developed a k-means clustering model in participants with newly diagnosed T2D (N = 1910) from the SENSIBLE and SENSIBLE-Addition studies, based on body mass index (BMI), waist circumference (WC), mean arterial pressure (MAP), and hemoglobin A1c (HbA1c). Diabetic retinopathy was ascertained with the protocol from the Early Treatment of Diabetic Retinopathy Study. Participants (N = 515) without diabetic retinopathy at baseline were followed-up for 3 years. Logistic regression analyses were performed to obtain the odds ratios (ORs) and 95% confidence intervals (CIs).

RESULTS

Three clusters were identified, with cluster 0, 1 and 2 accounting for 48.2, 8.9 and 42.9%, respectively. Participants with T2D were featured by the lowest BMI, WC, MAP, and HbA1c in cluster 0, poor glycemic condition in cluster 1, and the highest BMI, WC, and MAP in cluster 2. Compared with cluster 0, cluster 1 was associated with increased odds of diabetic retinopathy in both the cross-sectional study (OR 6.25, 95% CI: 3.19-12.23) and the cohort study (OR 9.16, 95% CI: 2.08-40.34), while cluster 2 was not. Moreover, most participants remained their clusters unchanged during follow-up.

CONCLUSIONS

Our cluster-based analysis showed that participants with poor glycemic condition rather than high blood pressure and obesity had higher risk of diabetic retinopathy.

Hyperglycemia First Detected in Pregnancy in South Africa: Facts, Gaps, and Opportunities

This review contextualizes hyperglycemia in pregnancy from a South-African perspective. It aims to create awareness of the importance of hyperglycemia in pregnancy in low-middle-income countries. We address unanswered questions to guide future research on sub-Saharan African women with hyperglycemia first detected in pregnancy (HFDP). South African women of childbearing age have the highest prevalence of obesity in sub-Saharan Africa. They are predisposed to Type 2 diabetes (T2DM), the leading cause of death in South African women. T2DM remains undiagnosed in many African countries, with two-thirds of people living with diabetes unaware. With the South African health policy's increased focus on improving antenatal care, women often gain access to screening for non-communicable diseases for the first time in pregnancy. While screening practices and diagnostic criteria for gestational diabetes mellitus (GDM) differ amongst geographical areas in South Africa (SA), hyperglycemia of varying degrees is often first detected in pregnancy. This is often erroneously ascribed to GDM, irrespective of the degree of hyperglycemia and not overt diabetes. T2DM and GDM convey a graded increased risk for the mother and fetus during and after pregnancy, with cardiometabolic risk accumulating across the lifespan. Resource limitations and high patient burden have hampered the opportunity to implement accessible preventative care in young women at increased risk of developing T2DM in the broader public health system in SA. All women with HFDP, including those with true GDM, should be followed and undergo glucose assessment postpartum. In SA, studies conducted early postpartum have noted persistent hyperglycemia in a third of women after GDM. Interpregnancy care is advantageous and may attain a favourable metabolic legacy in these young women, but the yield of return following delivery is suboptimal. We review the current best evidence regarding HFDP and contextualize the applicability in SA and other African or low-middle-income countries. The review identifies gaps and shares pragmatic solutions regarding clinical factors that may improve awareness, identification, diagnosis, and management of women with HFDP.

Association between fat mass index, fat-free mass index and hemoglobin A1c in a Japanese population: The Tohoku Medical Megabank Community-based Cohort Study

AIMS/INTRODUCTION

Fat mass and fat-free mass affect glycated hemoglobin A1c (HbA1c) levels and blood glucose levels, respectively. The aim of the present study was to examine the association between the fat mass index and fat-free mass index with HbA1c.

MATERIALS AND METHODS

We carried out a cross-sectional study that included 3,731 men and 9,191 women aged ≥20 years, living in Miyagi Prefecture, Japan, who were not treated for diabetes. The fat mass index and fat-free mass index were calculated as fat mass and fat-free mass divided by the height squared, respectively. The indices were classified into sex-specific quartiles and combined into 16 groups. An analysis of covariance was used to assess associations between the combined fat mass index and fat-free mass index with HbA1c adjusted for potential confounders. The linear trend test was carried out by stratifying the fat mass index and fat-free mass index, entering the number as a continuous term in the regression model.

RESULTS

In multivariable models, a higher fat mass index was related to higher HbA1c levels in men and women in all fat-free mass index subgroups (P < 0.001 for linear trend). When we excluded the participants who had been identified as having diabetes, the fat-free mass index was also related to higher HbA1c levels in most fat mass index subgroups (P < 0.05 for linear trend).

CONCLUSIONS

Fat mass index was positively related to HbA1c levels. The fat-free mass index was also related to HbA1c levels when we excluded participants who had been identified as having have diabetes.

A guide for the use of LibreView digital diabetes platform in clinical practice: Expert paper of the Italian Working Group on Diabetes and Technology

Wider access to continuous glucose monitoring systems, including flash glucose monitoring, has enabled people with diabetes to achieve lower HbA1c levels and reduce the amount of time they spend in hypoglycaemia or hyperglycaemia, and has improved their quality of life. An International Consensus Panel proposed different target glucose ranges and recommendations according to different ages and situations (adults, young people and children with type 1 or type 2 diabetes, as well as elderly people who are at higher risk of hypoglycaemia, and women with diabetes during pregnancy). In this expert opinion, we interpret the international recommendations in the context of established clinical practice for diabetes care, and propose three different step-by-step algorithms to help the healthcare professionals use the most innovative glucose metrics, including time in glucose ranges, glucose management indicator, coefficient of variation, and ambulatory glucose profile. In detail, we focus on glucose metrics as measured by the FreeStyle Libre system and as visualized on the LibreView digital diabetes platform to support appropriate interpretation of flash glucose monitoring data. This is specifically structured for healthcare professionals and general practitioners who may have a low level of confidence with diabetes technology, with the aim of optimizing diabetes management, ensuring effective use of healthcare resources and to maximise outcomes for people with diabetes.

Report from the CVOT Summit 2021: new cardiovascular, renal, and glycemic outcomes

The 7th Cardiovascular Outcome Trial (CVOT) Summit on Cardiovascular, Renal, and Glycemic Outcomes, was held virtually on November 18-19, 2021. Pursuing the tradition of the previous summits, this reference congress served as a platform for in-depth discussion and exchange on recently completed CVOTs. This year's focus was placed on the outcomes of EMPEROR-Preserved, FIGARO-DKD, AMPLITUDE-O, SURPASS 1-5, and STEP 1-5. Trial implications for diabetes and obesity management and the impact on new treatment algorithms were highlighted for endocrinologists, diabetologists, cardiologists, nephrologists, and general practitioners. Discussions evolved from outcome trials using SGLT2 inhibitors as therapy for heart failure, to CVOTs with nonsteroidal mineralocorticoid receptor antagonists and GLP-1 receptor agonists. Furthermore, trials for glycemic and overweight/obesity management, challenges in diabetes management in COVID-19, and novel guidelines and treatment strategies were discussed.Trial registration The 8th Cardiovascular Outcome Trial Summit will be held virtually on November 10-11, 2022 ( http://www.cvot.org ).

Multinational evaluation of clinical decision-making in the treatment and management of mild-to-moderate ulcerative colitis

OBJECTIVES

To understand current thinking and clinical decision-making in the treatment and management of patients with mild-to-moderate ulcerative colitis (UC).

METHODS

This multinational, survey-based study was conducted in 2021. Two meetings were held, involving 11 IBD specialists, that used a series of questions and discussion to identify all factors possibly related to the management of UC. The importance of identified factors was assessed using an online questionnaire covering three scenarios - active disease, remission and patient empowerment. Each factor was scored on a scale of 0 (very-unimportant) to 100 (very-important) within each scenario, by a separate group of healthcare professionals working in IBD.

RESULTS

A total of 157 individual factors were identified by the 11 IBD specialists and scored in the three scenarios by 56 respondents (52; 93% specialist gastroenterologists) from Europe and North America (25; 45%), South America (19; 34%) and the Middle East, Asia and Australia (12; 21%). For all scenarios, factors related to educating patients regarding UC and its treatment and understanding of patient goals ranked highest, ahead of clinical considerations regarding disease activity and treatment history. Setting realistic short-term treatment targets was a key consideration. 5-ASA optimisation and use of faecal calprotectin monitoring were core strategies across the three scenarios tested. Support for patients during longer-term management of their disease, starting from initial flare, was an important recurring theme.

CONCLUSION

The current management approach for mild-to-moderate UC was found to be guided primarily by the patient's perspectives and goals, alongside assessment of their medical and disease history.

Hemoglobin within normal range is negatively related to hemoglobin A1c in a nondiabetic American population aged 16 years and older

BACKGROUND

Protein glycosylated hemoglobin, hemoglobin A1c (HbA1c) binds hemoglobin (Hb) in red blood cells to blood glucose. However, the relationship between Hb and HbA1c remains unclear.

AIM

To elucidate their relationship in a nondiabetic population aged ≥ 16 years in the United States, using data from the 1999-2018 National Health and Nutrition Examination Survey.

METHODS

This study was based on data from 44560 adults aged ≥ 16 years, excluding those with diabetes. The relationship was estimated using a multivariate regression. We also used piecewise linear regression for subgroup analysis based on age and sex stratification and analysis of the threshold effects of Hb on HbA1c.

RESULTS

Hb and HbA1c levels were negatively correlated in the unadjusted model (β = -0.01; 95%CI: -0.01, -0.01). The correlation was significantly negative when the regression model was minimally regulated and stratified by age and sex, and remained negative when the model was further regulated (more than 10%) to identify covariates with the HbA1c level influence estimates. In subgroup analyses based on age and sex stratification, the association remained negative when the covariates were controlled. A nonlinear relationship was observed between them when the Hb levels reached the tipping point (13.2 g/dL) (adjusted odds ratio, -0.04; 95%CI: -0.05, -0.03) and when the Hb levels exceeded 13.2 g/dL (adjusted odds ratio, -0.10; 95%CI: -0.10, -0.09).

CONCLUSION

Our study shows that normal Hb levels are negatively correlated with HbA1c in nondiabetic Americans aged ≥ 16 years.

Coreopsis tinctoria and Its Flavonoids Ameliorate Hyperglycemia in Obese Mice Induced by High-Fat Diet

With the prevalence of obesity all over the world, human health has been seriously affected. In particular, the number of diabetic and cardiovascular diseases has increased dramatically. The herb Coreopsis tinctoria (C. tinctoria) shows diverse biological and pharmacological activities, which are mainly attributed to its flavonoids. However, the specific functional substances that play an active role in C. tinctoria remain unclear, and its mechanism has not been deeply explored. In this study, we established a diet-induced obesity (DIO) mice model and treated mice with C. tinctoria or kaempferol for 8 weeks. The results showed that both C. tinctoria and kaempferol lowered body weight, reduced fasting blood glucose, and improved glucose tolerance and insulin resistance to alleviate obesity in DIO mice. The level of hemoglobin A1c also decreased significantly after treatment with C. tinctoria and kaempferol. Moreover, the administration of C. tinctoria and kaempferol also restored gut microbiota imbalance and significantly increased Desulfovibrio and Butyricimonas levels, which have been reported to improve glucose metabolism and intestinal health. In general, our study shows that C. tinctoria is a potential hypoglycemic substance for obesity and may reduce blood glucose by regulating gut microbiota, and that kaempferol is one of the effective substances of C. tinctoria.

Clinical and patient-centered implementation outcomes of mHealth interventions for type 2 diabetes in low-and-middle income countries: a systematic review

BACKGROUND

The prevalence of Type 2 Diabetes is rising in Low- and Middle-Income Countries (LMICs), affecting all age categories and resulting in huge socioeconomic implications. Mobile health (mHealth) is a potential high-impact approach to improve clinical and patient-centered outcomes despite the barriers of cost, language, literacy, and internet connectivity. Therefore, it is valuable to examine the clinical and implementation outcomes of mHealth interventions for Type 2 Diabetes in LMICs.

METHODS

The Preferred Reporting Items for Systematic review and Meta-Analysis (PRISMA) guidelines were applied in framing and reporting the review criteria. A systematic search of Cochrane Library, Web of Science, PubMed, Scopus, and Ovid databases was performed through a combination of search terms. Randomized Controlled Trials (RCTs) and cohort studies published in English between January 2010 and August 2021 were included. Risk of bias for missing results in the included studies was assessed using the Cochrane risk-of-bias tool for randomized trials (RoB 2). Quantitative and qualitative methods were used to synthesize the results.

RESULTS

The search identified a total of 1161 articles. Thirty studies from 14 LMICs met the eligibility criteria. On clinical outcomes, 12 and 9 studies reported on glycated hemoglobin (HbA1c )and fasting blood glucose (FBG) respectively. Text messages was the most commonly applied mHealth approach, used in 19 out of the 30 studies. Ten out of the 12 studies (83.3%) that reported on HbA1c had a percentage difference of <0.3% between the mHealth intervention and the comparison group. Additionally, studies with longer intervention periods had higher effect size and percentage difference on HbA1c (1.52 to 2.92%). Patient-centred implementation outcomes were reported variedly, where feasibility was reported in all studies. Acceptability was reported in nine studies, appropriateness in six studies and cost in four studies. mHealth evidence reporting and assessment (mERA) guidelines were not applied in all the studies in this review.   CONCLUSION: mHealth interventions in LMICs are associated with clinically significant effectiveness on HbA1 but have low effectiveness on FBG. The application of mERA guidelines may standardize reporting of patient-centered implementation outcomes in LMICs.

TRIAL REGISTRATION

PROSPERO: Registration ID 154209.

Glycemic Variability Within 1 Year Following Surgery for Stage II-III Colon Cancer

OBJECTIVE

To examine glycemic variability within 1 month and 1 year following surgery among adult patients, with and without Type 2 Diabetes (T2D), treated for stage II-III colon cancer.

METHOD

A retrospective analysis of electronic health record data was conducted. Glycemic variability (i.e., standard deviation [SD] and coefficient of variation [CV] of > 2 blood glucose measures) was assessed within 1 month and within 1 year following colon surgery. Chi-square (χ²), Fisher's exact, and Mann-Whitney U tests were used for the analyses.

RESULTS

Among the sample of 165 patients with stage II-III colon cancer, those with T2D had higher glycemic variability compared to patients without T2D (p < .001), with values within 1 month following surgery (SD = 44.69 mg/dL, CV = 27.4%) vs (SD = 20.55 mg/dL, CV = 17.53%); and within 1 year following surgery (SD = 45.04 mg/dL, CV = 29.04%) vs (SD = 21.36 mg/dL, CV = 18.6%). Associations were found between lower body mass index and higher glycemic variability (i.e., SD [r = -.413, p < .05] and CV [r = -.481, p < .01]) within 1 month following surgery in patients with T2D. Higher preoperative glucose was associated with higher glycemic variability (i.e., SD r = .448, p < .01) within 1 year in patients with T2D. Demographic and clinical characteristics were weakly associated with glycemic variability in patients without T2D.

CONCLUSIONS

Patients with stage II-III colon cancer with T2D experienced higher glycemic variability within 1 month and within 1 year following surgery compared to those without T2D. Associations between glycemic variability and demographic and clinical characteristics differed by T2D status. Further research in prospective studies is warranted.

The effect of age and sex on glycated hemoglobin in dogs

We investigated the effect of age and sex on canine glycated hemoglobin (HbA1c) using a validated capillary electrophoresis assay. Aliquots of EDTA blood samples collected for routine health checks were used. HbA1c was measured using the Capillarys 2 flex-piercing system (Sebia). We included 58 clinically and hematologically healthy, normoglycemic dogs (29 males, 29 females), allocated to 3 age groups: young (14 dogs <1-y-old), adult (31 dogs 1-7.9-y-old), and senior (13 dogs ≥8-y-old). The mean (± SD) HbA1c was not significantly different (p = 0.428) between the age groups (young: 1.68 ± 0.54%; adult: 1.59 ± 0.41%; senior: 1.80 ± 0.57%). The HbA1c was not significantly correlated with age (rho = 0.144, p = 0.280). The median (range) HbA1c was not significantly different (p = 0.391) between male [1.7% (0.5-2.5%)] and female [1.5% (1.0-2.7%)] dogs. Age and sex do not appear to affect canine HbA1c; however, a study of geriatric dogs would be needed to fully exclude an effect of age on HbA1c.

Sumac fruit supplementation improve glycemic parameters in patients with metabolic syndrome and related disorders: A systematic review and meta-analysis

BACKGROUND

Metabolic syndrome (MetS) is the one of the main causes of mortality worldwide. Several randomized controlled trials (RCTs) have revealed the beneficial effects of sumac (Rhus coriaria) on cardiometabolic risk factors. However, the entirety of the evidence has yet to be summarized in a systematic review.

OBJECTIVE

The aim of this systematic review and meta-analysis was to evaluate the effects of sumac on several cardiometabolic risk factors in patients with MetS and related disorders.

METHODS

We reviewed Medline, Scopus, Web of Science and Cochrane CENTRAL for RCTs published from inception to December 2020 evaluating the impact of sumac in adults with MetS or related disorders. Outcome measures included anthropometric measures, glycemic indices, blood lipids, blood pressure and liver enzymes. Pooled effect sizes were reported as standard mean differences (SMDs) and 95% confidence intervals (CIs). Trials were pooled using a random effects model.

RESULTS

Nine studies enrolling 526 participants met the inclusion criteria for this meta-analysis. Our results indicate that sumac intake significantly decrease fasting blood sugar (FBS) (SMD: -0.28; 95% CI: -0.54, -0.02; I² = 00.0%), insulin (SMD: -0.67; 95% CI: -0.99, -0.36; I² = 03.7%), and insulin resistance (measured through the Homeostatic Model Assessment of Insulin Resistance (HOMA-IR)) (SMD: -0.79; 95% CI: -1.24, -0.34; I² = 50.1%). Sumac intake did not have a significant impact on weight, body mass index (BMI), waist circumference (WC), hip circumference (HC), waist to hip ratio (WHR), HbA1c, total cholesterol (TC), triglycerides (TG), high density lipoproteins (HDL), low density lipoprotein (LDL), systolic blood pressure (SBP), diastolic blood pressure (DBP), aspartate transaminase (AST) and alanine transaminase (ALT).

CONCLUSION

Sumac, as an adjuvant therapy, may decrease serum levels of FBS, insulin and HOMA-IR. However, due to high heterogeneity in the included studies, these findings must be interpreted with great caution. Larger, well-designed placebo-controlled clinical trials are still needed to further evaluate the capacity of sumac as a complementary treatment to control MetS risk factors.

HbA1c performs well in monitoring glucose control even in populations with high prevalence of medical conditions that may alter its reliability: the OPTIMAL observational multicenter study

INTRODUCTION

The utility of HbA1c (glycosylated hemoglobin) to estimate glycemic control in populations of African and other low-resource countries has been questioned because of high prevalence of other medical conditions that may affect its reliability. Using continuous glucose monitoring (CGM), we aimed to determine the comparative performance of HbA1c, fasting plasma glucose (FPG) (within 5 hours of a meal) and random non-fasting glucose (RPG) in assessing glycemic burden.

RESEARCH DESIGN AND METHODS

We assessed the performance of HbA1c, FPG and RPG in comparison to CGM mean glucose in 192 Ugandan participants with type 2 diabetes. Analysis was undertaken in all participants, and in subgroups with and without medical conditions reported to affect HbA1c reliability. We then assessed the performance of FPG and RPG, and optimal thresholds, in comparison to HbA1c in participants without medical conditions thought to alter HbA1c reliability.

RESULTS

32.8% (63/192) of participants had medical conditions that may affect HbA1c reliability: anemia 9.4% (18/192), sickle cell trait and/or hemoglobin C (HbC) 22.4% (43/192), or renal impairment 6.3% (12/192). Despite high prevalence of medical conditions thought to affect HbA1c reliability, HbA1c had the strongest correlation with CGM measured glucose in day-to-day living (0.88, 95% CI 0.84 to 0.91), followed by FPG (0.82, 95% CI 0.76 to 0.86) and RPG (0.76, 95% CI 0.69 to 0.81). Among participants without conditions thought to affect HbA1c reliability, FPG and RPG had a similar diagnostic performance in identifying poor glycemic control defined by a range of HbA1c thresholds. FPG of ≥7.1 mmol/L and RPG of ≥10.5 mmol/L correctly identified 78.2% and 78.8%, respectively, of patients with an HbA1c of ≥7.0%.

CONCLUSIONS

HbA1c is the optimal test for monitoring glucose control even in low-income and middle-income countries where medical conditions that may alter its reliability are prevalent; FPG and RPG are valuable alternatives where HbA1c is not available.

Hemoglobin Fukuoka caused unexpected hemoglobin A1c results: A case report

BACKGROUND

Glycated hemoglobin (Hb) (HbA_1c) is an indicator that is used to diagnose and monitor the treatment of diabetes. Many factors can affect the detection of HbA_1c. One of the most important of these factors is the Hb variant. Here, we report a rare Hb variant and evaluate its effect on HbA_1c.

CASE SUMMARY

A 35-year-old man was suspected of harboring an Hb variant following the measurement of HbA_1c with the Variant II Turbo 2.0 Hb detection system during a routine examination. Subsequently, we used the Arkray HA-8160 and ARCHITECT c4000 system to reanalyze HbA_1c. Finally, the Hb variant was detected with a Capillary2FP analyzer that operates on the principle of capillary electrophoresis. We also used gene sequencing to investigate the mutation site. The value of HbA_1c detected with the Variant II Turbo 2.0 system was 52.7%. However, the Arkray HA-8160 system did not display a result while the ARCHITECT c16000 system showed a result of 5.4%. The Capillary2FP analyzer did not reveal any abnormal Hb zones. However, gene sequencing identified the presence of a mutation in the Hb β2 chain [CD2(CAC>TAC), His>Tyr, HBB: c.7C>T]; the genotype was Hb Fukuoka.

CONCLUSION

Hb variants could cause abnormal HbA_1c results. For patients with Hb variants, different methods should be used to detect HbA_1c.

Is Glycated Hemoglobin A1c Level Associated with Adverse Pregnancy Outcomes of Women Affected by Pre-Gestational Diabetes?

Background and Objectives: This observational study aims to determine the correlation between glycemic control with the HbA1c value and adverse obstetric outcome in women affected by pre-gestational diabetes. Materials and Methods: A retrospective analysis has been performed at the University Hospital of Udine. Only patients with a singleton pregnancy, pre-gestational diabetes, and known level of Hb A1c throughout pregnancy were included in the study. Results: According to the HbA1c level, at the beginning of pregnancy, 49 patients with HbA1c ≤ 7.0% were compared with 45 patients with HbA1c > 7.0%. Maternal age at diagnosis of the disease was significantly higher in the group with HbA1c ≤ 7% than in the group with HbA1c > 7%, 26.00 (18.00–32.00) vs. 20.00 (12.50–27.00). Women with HbA1c ≤ 7.0% reached, at term of pregnancy, significantly lower levels of HbA1c, 5.8% (5.7–6.0) vs. 6.7% (6.3–7.3). Daily insulin units were statistically different between the two groups at the end of pregnancy (47.92 (39.00–67.30) vs. 64.00 (48.00–82.00)). Proteinuria was significantly higher in the group with HbA1c > 7.0%, who delivered at earlier gestational age (37.57 (35.57–38.00) vs. 38.14 (38.00–38.43). Moreover, women with HbA1c > 7.0% had a significantly higher prevalence of an adverse composite outcome. Of note, in multivariate logistic regression analysis, pregnancy complications were significantly correlated to pre-pregnancy HbA1c > 7.0% (OR 2.95 CI.95 1.16–7.48, p < 0.05) independently of age, insulin treatment, and type of diabetes. Conclusions: Our data, obtained from a single-center cohort study, suggest that starting pregnancy with poor glycemic control might predict more complex management of diabetes in the following trimesters.

The effects of Elaeagnus angustifolia L. on lipid and glycaemic profiles and cardiovascular function in menopausal women: A double-blind, randomized, placebo-controlled study

AIMS

The reduced production of ovarian hormones is considered to be the cause of an increase in the incidence of heart disease in women after menopause. Phytoestrogens are found in various herbal sources and are considered as an alternative to hormone therapy because of structural similarity with oestrogen. Elaeagnus angustifolia L., known as Senjed in Persian, is used in Iranian traditional medicine with various medicinal properties, contains valuable compounds, including two types of phytoestrogens. The aim of the present study was to investigate the efficacy of E. angustifolia fruit on the cardiovascular function, lipid and glycaemic profiles in postmenopausal women.

METHODS

In this double-blind placebo-controlled clinical trial, 58 postmenopausal women were randomly assigned into two experimental groups of medicinal herb (15 g/day of the whole E. angustifolia fruit powder) and placebo (15 g/day of isomalt + corn starch). Before the trial and after 10 weeks of the treatment, cardiovascular function (heart rate, blood pressure), serum glycaemic profile (fasting blood glucose; glycated haemoglobin, HbA1C), insulin and lipid profile (total cholesterol, TC; triglyceride, TG; LDL-C and HDL-C) were measured.

RESULTS

Heart rate, and serum level of LDL-C and HDL-C significantly decreased after treatment with E. angustifolia. Changes in glycaemic profile were not clinically significant. In addition, some studied biochemical parameters significantly changed in the placebo group.

CONCLUSIONS

E. angustifolia was somewhat effective in improving cardiovascular function and lipid profile, as well as the overall health of postmenopausal women. However, the use of isomalt and corn starch in menopausal women needs further investigation.

Association between hemoglobin within the normal range and hemoglobin A1c among Chinese non-diabetes adults

BACKGROUND

Hemoglobin A1c (HbA1c) is the product of a non-enzymatic chemical reaction between hemoglobin (Hb) and glucose. However, the association between Hb and HbA1c remains to be fully elucidated in view of the controversial findings reported to date. Therefore, our aim in this study was to evaluate the association between Hb levels within the normal range and HbA1c levels among Chinese non-diabetes adults using cross-sectional data from the China Health and Nutrition Survey 2009.

METHODS

Our analysis was based on the data of 1659 non-diabete adults 20-49 years of age. Multivariable linear models were applied to examine the association between Hb and HbA1c levels. Subgroup analyses stratified by age and sex were also performed.

RESULTS

The association between Hb and HbA1c levels was positive in the unadjusted model (β =0.020, 95% CI: 0.008, 0.032). However, this association did not remain significant when the regression model was minimally adjusted for age and sex (β =0.006, 95% CI: - 0.014, 0.024); this association became negative when the model was further adjusted for covariates whose effect estimates of HbA1c levels more than 10% (β = - 0.042, 95% CI: - 0.064, - 0.020). The association remained negative on subgroup analyses stratified by age (20-34 years: β = - 0.052, 95% CI: - 0.091, - 0.013; 35-49 years: β = - 0.041, 95% CI: - 0.068, - 0.014) and sex (men: β = - 0.042, 95% CI: - 0.074, - 0.010; women: β = - 0.042, 95% CI: - 0.073, - 0.012) when controlling for covariates.

CONCLUSIONS

Our findings revealed that Hb levels within the normal range were negatively associated with HbA1c levels among Chinese non-diabetes adults. Confounding factors, such as red blood cell counts can affect the association between Hb and HbA1c levels.

Oral glucose tolerance test does not affect degree of hemoglobin glycation as measured by routine assay

BACKGROUND

Hemoglobin A1c (HbA1c) is an accurate index of fluctuation in glycemia over the 2-3 months prior to quantitative assessment. During this time, hemoglobin (Hb) slowly glycates until it shows the properties of advanced glycation end-products. Glycation kinetics is intensified by prolonged glucose exposure. In subjects undergoing oral glucose tolerance testing (OGTT), immediately after ingestion, glucose is ostensibly transported by the glucose transporter 1 (GLUT1) to erythrocyte corpuscular hemoglobin. The earliest significant measurable level of hemoglobin glycation associated with this transportation is still not clear.

SUBJECTS AND METHODS

We attempted to explore the early impact of short-term glucose load on HbA1c levels, because it is now known that transmembrane GLUT1-mediated glucose transport occurs immediately. A total of 88 participants (46 patients and 42 clinically healthy controls) underwent fasting plasma glucose quantitation during an OGTT. HbA1c, revealed by a monoclonal anti-glycation epitope antibody and adiponectin, was quantitated before (T0) and 2 hours (T120) after 80 g glucose ingestion.

RESULTS

Wilcoxon test revealed that the HbA1c values did not significantly vary (P=0.15) during the OGTT, whereas glucose concentration varied strongly between T0 and T120.

DISCUSSION

It is well known that quantitative estimation of HbA1c is informative for clinical care, independently of glucose level. The molecular mechanisms and dynamics by which glucose enters/exits red blood cells are incompletely known and may differ between individuals. We here show, for the first time, that HbA1c levels do not significantly increase during OGTT, supporting the view that non-enzymatic glycation of hemoglobin occurs slowly and that glycation during the 2 hours of an OGTT is insignificant.

The trials and tribulations of determining HbA1c targets for diabetes mellitus

Glycated haemoglobin (HbA1c) is considered the gold standard for predicting glycaemia-associated risks for the microvascular and macrovascular complications of diabetes mellitus over 5-10 years. The value of HbA1c in the care of patients with type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM) is unassailable, yet HbA1c targets remain contentious. Guidelines from diabetes care organizations recommend conflicting HbA1c targets - generally between 6.5% and 8%. However, all such organizations advocate for individualization of HbA1c targets, leaving both health-care providers and their patients confused about what HbA1c target is appropriate in an individual patient. In this Review, we outline the landmark T1DM and T2DM trials that informed the current guidelines, we discuss the evidence that drives individualized HbA1c targets, we examine the limitations of HbA1c, and we consider alternatives for monitoring glycaemic control. Ultimately, in synthesizing this literature, we argue for an HbA1c target of <7% for most individuals, but emphasize the importance of helping patients determine their own personal goals and determinants of quality of life that are independent of a particular glycaemic target. We also recognize that as newer technologies and anti-hyperglycaemic therapies emerge, glycaemic targets will continue to evolve.

Glycemic variability in patients with gastrointestinal cancer: An integrative review

PURPOSE

Glycemic variability is associated with risks for adverse events in patients with cancer. Several studies have evaluated the presence and impact of hyperglycemia and/or hypoglycemia in patients with cancer; however, few studies have evaluated glycemic variability. The purpose of this integrative review of studies in patients with gastrointestinal cancers was to investigate the presence and methods of reporting glycemic variability during and following treatments.

METHODS

A comprehensive review of the literature was conducted. PubMed, CINAHL, EMBASE, and Cochrane databases were searched for publications between 1/1/1969 and 7/24/2019. Studies of patients with gastrointestinal cancer following surgery, during treatment, and <5 years following treatment were included and evaluated by cancer type and method of glucose and glycemic variability measurement.

RESULTS

Among 1526 patients with gastrointestinal cancer across 19 studies, gastric and pancreatic cancers were most prevalent. Timing of glucose testing and methods of analyzing glycemic variability varied. Most analyses used the standard deviation or interquartile range. Glycemic variability was more prevalent among patients with Type 2 Diabetes and among those with pancreatic cancer. In some patients glycemic variability remained notable > one year following surgery despite improvements in glycemic control.

CONCLUSION

Patients with gastrointestinal cancer experience glycemic variability during and up to one year following treatment. There was heterogeneity in methods related to timing of testing and reporting glycemic variability among the 19 studies in this review. Future investigations need to identify the presence and define the methods of measuring glycemic variability in patients with gastrointestinal cancer.

Relative Hyperglycemia Is an Independent Determinant of In-Hospital Mortality in Patients With Critical Illness

OBJECTIVES

To determine whether relative hyperglycemia was associated with in-hospital mortality in critically ill patients independent of other prognostic variables and whether this association is affected by background glycemia.

DESIGN

Prospective observational study.

SETTING

Mixed medical-surgical ICU in a metropolitan teaching hospital.

PATIENTS

From 2,617 admissions to ICU between January 27, 2016, and March 30, 2017, 1,262 consecutive patients who met inclusion and exclusion criteria were studied.

INTERVENTIONS

Glycosylated hemoglobin was used to estimate average glucose concentration over the prior 3 months. Glucose concentration on ICU admission was divided by estimated average glucose concentration to calculate the stress hyperglycemia ratio, an index of relative glycemia. Risk of death score was calculated using data submitted to the Australia and New Zealand Intensive Care Society.

MEASUREMENTS AND MAIN RESULTS

In this study, there were 186 deaths (14.7%). Admission glucose was significantly associated with mortality in univariate analysis (odds ratio = 1.08 per mmol/L glucose increment; p < 0.001) but not after adjustment for risk of death score (odds ratio = 1.01; p = 0.338). In contrast, stress hyperglycemia ratio was significantly associated with mortality both in univariate analysis (odds ratio = 1.09 per 0.1 stress hyperglycemia ratio increment; p < 0.001) and after adjustment for risk of death score (odds ratio = 1.03; p = 0.014). Unlike admission glucose concentration, stress hyperglycemia ratio was significantly associated with mortality in patients with glycosylated hemoglobin less than 6.5% (odds ratio = 1.08 per 0.1 stress hyperglycemia ratio increment; p < 0.001) and glycosylated hemoglobin greater than or equal to 6.5% (48 mmol/mol) (odds ratio = 1.08 per 0.1 stress hyperglycemia ratio increment; p = 0.005).

CONCLUSIONS

Unlike absolute hyperglycemia, relative hyperglycemia, as assessed by the stress hyperglycemia ratio, independently predicts in-hospital mortality in critically ill patients across the glycemic spectrum. Future studies should investigate whether using measures of relative hyperglycemia to determine individualized glycemic treatment targets improves outcomes in ICU.

A Review of Continuous Glucose Monitoring-Based Composite Metrics for Glycemic Control

We performed a literature review of composite metrics for describing the quality of glycemic control, as measured by continuous glucose monitors (CGMs). Nine composite metrics that describe CGM data were identified. They are described in detail along with their advantages and disadvantages. The primary benefit to using composite metrics in clinical practice is to be able to quickly evaluate a patient's glycemic control in the form of a single number that accounts for multiple dimensions of glycemic control. Very little data exist about (1) how to select the optimal components of composite metrics for CGM; (2) how to best score individual components of composite metrics; and (3) how to correlate composite metric scores with empiric outcomes. Nevertheless, composite metrics are an attractive type of scoring system to present clinicians with a single number that accounts for many dimensions of their patients' glycemia. If a busy health care professional is looking for a single-number summary statistic to describe glucose levels monitored by a CGM, then a composite metric has many attractive features.