Tests of glycemia in diabetes

Associations Between HbA1c and Glucose Time in Range Using Continuous Glucose Monitoring in Type 1 Diabetes: Cross-Sectional Population-Based Study

INTRODUCTION

Continuous glucose monitoring (CGM) introduces novel indicators of glycemic control.

METHODS

This cross-sectional study, based on the Swedish National Diabetes Register, examines 27,980 adults with type 1 diabetes. It explores the relationships between HbA1c (glycated hemoglobin) and various CGM-derived metrics, including TIR (time in range, representing the percentage of time within the range of 4-10 mmol/l for 2 weeks), TAR (time above range), TBR (time below range), mean glucose, standard deviation (SD), and coefficient of variation (CV). Pearson correlation coefficients and linear regression models were utilized for estimation.

RESULTS

The analysis included 46% women, 30% on insulin pump, 7% with previous coronary heart disease and 64% with retinopathy. Mean ± SD values were age 48 ± 18 years, diabetes duration 25 ± 16 years, HbA1c 58.8 ± 12.8 mmol/mol, TIR 58.8 ± 19.0%, TAR 36.3 ± 20.0%, TBR 4.7 ± 5.4%, mean sensor glucose 9.2 ± 2.0 mmol/l, SD 3.3 ± 1.0 mmol/l, and CV 36 ± 7%. The overall association between HbA1c and TIR was - 0.71 (Pearson's r), with R2 0.51 in crude linear regression and 0.57 in an adjusted model. R2 values between HbA1c and CGM mean glucose were 0.605 (unadjusted) 0.619 (adjusted) and TAR (unadjusted 0.554 and fully adjusted 0.568, respectively), while fully adjusted R2 values were 0.458, 0.175 and 0.101 between HbA1c and CGM SD, CGM CV and TBR, respectively.

CONCLUSIONS

This descriptive study demonstrates that the degree of association between HbA1c and new and readily available CGM-derived metrics, i.e., time in range (TIR), time above range (TAR), and CGM mean glucose, is robust in assessing the management of individuals with type 1 diabetes in clinical settings. Metrics from CGM that pertain to variability and hypoglycemia exhibit only weak correlations with HbA1c.

Assessing Glycosylated Hemoglobin Thresholds for Development of Cardiovascular Disease by Racial and Ethnic Groups

BACKGROUND

Diabetes is the strongest risk factor for cardiovascular disease, and although glycosylated hemoglobin (HbA1c) levels are known to vary by race, no racial and ethnic-specific diagnostic thresholds exist for diabetes in prediction of cardiovascular disease events. The purpose of this study is to determine whether HbA1c thresholds for predicting major adverse cardiovascular events (MACEs) differ among racial and ethnic groups.

METHODS AND RESULTS

This is a retrospective cohort study of Kaiser Permanente Northern California adult members (n=309 636) with no history of cardiovascular disease who had HbA1c values and race and ethnicity data available between 2014 and 2019. Multivariable logistic regression was used to evaluate the odds of MACEs by the following racial and ethnic groups: Filipino, South Asian, East Asian, Black, White, and Hispanic. A Youden index was used to calculate HbA1c thresholds for MACE prediction by each racial and ethnic group, stratified by sex. Among studied racial and ethnic groups, South Asian race was associated with the greatest odds of MACEs (1.641 [95% CI, 1.456-1.843]; P<0.0001). HbA1c was a positive predictor for MACEs, with an odds ratio of 1.024 (95% CI, 1.022-1.025) for each 0.1% increment increase in HbA1c. HbA1c values varied between 6.0% and 7.6% in MACE prediction by race and ethnicity and sex. White individuals, South Asian individuals, East Asian women, and Black men had HbA1c thresholds for MACE prediction in the prediabetic range, between 6.0% and 6.2%. Black women, Hispanic men, and East Asian men had HbA1c thresholds of 6.2% to 6.6%, less than the typical threshold of 7.0% that is used as a treatment goal.

CONCLUSIONS

Findings suggest that the use of race and ethnic- and sex-specific HbA1c thresholds may need to be considered in treatment goals and cardiovascular disease risk estimation.

Seasonal variation of HbA1c levels in diabetic and non-diabetic patients

Background

Hemoglobin A1c (HbA1c) serves as a pivotal marker for long-term glycemic control. The Diabetes Control and Complications Trial (DCCT) established its relevance, yet gaps exist in understanding potential seasonal variations in HbA1c levels among diabetic patients. The study highlights the need to explore potential seasonal variations in HbA1c levels and their impact on diabetic patients.

Materials and methods

This is an observational study conducted in a tertiary care hospital from January to December 2019, the study analyzed HbA1c levels in 8138 patients. Blood samples were collected using Potassium EDTA-containing vials and processed with an automated analyzer. Seasonal variations were explored using time series analysis.

Results

Mean HbA1c levels peaked during the monsoon (June to September) and were lowest in autumn (October to November). Subgroup analysis revealed differences in patients with HbA1c values below and above 6.5 %. Those with controlled blood sugar showed higher levels in winter (December to February) and monsoon (June to September), while patients with HbA1c values ≥ 6.5 % exhibited significantly lower levels in monsoon (June to September) and autumn (October to November) compared to summer (March to May).

Conclusion

In contrast to global trends, Indian patients demonstrated distinct seasonal variations in HbA1c levels. The highest levels during the monsoon (June to September) may be linked to reduced outdoor activity and dietary changes. The study emphasizes the need for tailored diabetes management considering seasonal influences. Further extensive, longitudinal studies across diverse Indian regions are recommended to comprehensively grasp the impact of seasonal changes on diabetes outcomes.

Relationship between glycated hemoglobin levels and three-month outcomes in acute ischemic stroke patients with or without diabetes: a prospective Korean cohort study

OBJECTIVE

In patients experiencing acute ischemic stroke, there is ongoing debate surrounding the connection between chronic hyperglycemic status and their initial clinical outcomes. Our objective was to examine the connection between glycated hemoglobin (HbA1c) levels and adverse clinical outcomes at both 3-months adverse clinical outcomes in individuals with acute ischemic stroke (AIS) with and without diabetes.

METHODS

The present prospective cohort study involved 896 AIS patients without diabetes and 628 with diabetes treated at a South Korean hospital from January 2010 to December 2016. The target independent variable is HbA1c. The outcome variable is a modified Rankin scale score ≥ 3. A binary logistic regression model was applied to assess the connection between HbA1c levels and 3-month poor clinical outcomes in AIS patients with and without diabetes. Additionally, a generalized additive model and smoothed curve fitting were utilized to explore potential nonlinear associations between HbA1c levels and 3-month adverse clinical outcomes in AIS patients with and without diabetes.

RESULTS

The binary logistic regression model could not identify any statistically significant connection between HbA1c and 3-month adverse clinical outcomes in AIS patients, both those with and without diabetes, after correcting for various factors. However, a nonlinear relationship emerged between HbA1c and 3-month adverse clinical outcomes in AIS patients with diabetes. The inflection point for HbA1c was determined to be 6.1%. For HbA1c values ≤ 6.1%, an inverse association was observed between HbA1c and 3-month adverse clinical outcomes in diabetic AIS patients, and each 1% increase in HbA1c in AIS patients with DM was associated with an 87% reduction in 3-month adverse clinical outcomes (OR = 0.13, 95% CI: 0.02-0.81). Conversely, when HbA1c exceeded 6.1%, a positive association between HbA1c and 3-month adverse clinical outcomes became apparent in diabetic AIS patients, and each 1% increase in HbA1c in AIS patients with DM was associated with a 23% increase in 3-month adverse clinical outcomes (OR = 1.23, 95%CI: 1.03-1.47). However, it's important to note that no significant linear or nonlinear relationships were observed between HbA1c levels and 3-month adverse clinical outcomes in AIS patients without diabetes.

CONCLUSION

Our findings suggest a nonlinear connection and threshold effect between HbA1c and 3-month adverse clinical outcomes in AIS patients with diabetes. AIS patients with diabetes had a lower risk of 3-month adverse clinical outcomes when their HbA1c control was close to 6.1%. Our findings may aid treatment decision-making and potentially guide interventions to optimize glycemic control in AIS patients.

Uncommon causes of hemoglobin E flags identified during measurement of hemoglobin A1c by ion-exchange high-performance liquid chromatography

We present 3 cases of discordant results from screening hemoglobin A1c (HbA1c) measured by ion-exchange high-performance liquid chromatography (HPLC) all due to various forms of interference and flagged by the instrument as "suspected hemoglobin E (HbE)." The first case was due to a rare hemoglobin variant, later confirmed to be hemoglobin Hoshida, the second due to "true" heterozygous HbE, and the third a result of analytical artifact causing splitting of the HbA1c peak without an underlying variant hemoglobin. We examine the similarities in these cases along with the laboratory work-up to classify each cause of interference to demonstrate the wide array of potential causes for the suspected HbE flag and why it warrants proper work-up. Because there is no standardized method of reporting out hemoglobin variant interference in HbA1c measurement, we discuss our laboratory's process of investigating discordant HbA1c measurements and reporting results in cases with variant interference as 1 possible model to follow, along with discussing the associated laboratory, ethical, and clinical considerations. We also examine the structure of hemoglobin Hoshida, HbE, and conduct a brief literature review of previous reports.

Effects of short-term sugary beverage consumption on glucose control and cardiovascular disease risk factors: A randomized controlled parallel-arm trial

OBJECTIVE

To determine differences in glucose control and cardiovascular disease risk factors following three weeks of added soda, 100% fruit juice, or water in apparently healthy, college-aged adults.

PARTICIPANTS

Thirty-six adults (18 males; 18 females) between the ages of 18 and 30 years of age.

METHODS

A 3-arm randomized controlled parallel-arm trial; at baseline and after three weeks consuming the assigned beverage, participants completed glucose control and cardiovascular disease risk factor assessments.

RESULTS

There were no significant differences between beverage conditions for glucose control or cardiovascular disease risk factors (ps > 0.05). There were no significant changes in caloric intake or differences in caloric intake between conditions, p = 0.17.

CONCLUSIONS

In healthy, young adults, under free-living conditions, short-term consumption of two commercially packaged servings of SBs did not lead to significant glucose control or cardiovascular disease risk factor changes, indicating potential compensation and/or resilience to negative short-term effects.

Usefulness of glycated albumin level as a glycemic index complementing glycosylated hemoglobin in diabetic children and adolescents

PURPOSE

Glycated albumin (GA) is a glycemic marker reflecting the average serum glucose of the previous 2 weeks. This study aimed to evaluate the usefulness of GA as a glycemic index to complement glycosylated hemoglobin (HbA1c) in children and adolescents.

METHODS

Fifty-four children and adolescents with diabetes mellitus (DM) and 97 children and adolescents without DM (NDM) were enrolled. The correlation between mean blood glucose (MG) and GA compared to HbA1c was investigated in the DM group. The correlation between fasting glucose (FG) and GA compared to HbA1c was investigated in the NDM group. Factors affecting GA, HbA1c, and GA/HbA1c were analyzed.

RESULTS

In the DM group, positive correlations were observed between MG and GA (P=0.003), between MG and HbA1c (P=0.001), and between GA and HbA1c (P<0.001). The correlation coefficient between MG and GA did not differ from that between MG and HbA1c in the DM group (P=0.811). Among patients with DM, those whose standardized body mass index standard deviation score (BMI SDS) was ≥2 had a lower GA/HbA1c compared with those whose BMI SDS was <2 (P=0.001). In the NDM group, there were no significant correlations between FG and GA, between FG and HbA1c, or between GA and HbA1c. The NDM subjects whose BMI SDS was ≥2 had a lower GA/HbA1c than did the NDM subjects whose BMI SDS was <2 (P=0.003).

CONCLUSION

GA is comparable with HbA1c in reflecting glycemic control in children and adolescents with DM. GA is affected by obesity in children and adolescents with or without DM.

Association between glycated haemoglobin and the risk of chronic obstructive pulmonary disease: A prospective cohort study in UK biobank

AIMS

To investigate the association between glycated haemoglobin (HbA1c) levels and chronic obstructive pulmonary disease (COPD) incidents in the general population, and the association between HbA1c levels and mortality in patients with COPD.

MATERIALS AND METHODS

We investigated the association of HbA1c levels with COPD risk in the general population in the UK Biobank, using data from 420 065 participants. Survival analysis was conducted for 18 854 patients with COPD. We used restricted cubic spline analysis to assess the dose-response relationship between HbA1c levels and COPD risk and survival. Cox proportional hazards regression models were used to estimate hazard ratios (HRs) with 95% confidence intervals (CIs).

RESULTS

During a median follow-up of 12.3 years, 11 556 COPD cases were recorded. HbA1c had a non-linear relationship with COPD risk (p for non-linearity < .05). Compared with the quintile 2 (32.2-<34.3 mmol/mol), those with HbA1c levels above 38.7 mmol/mol (quintile 5) had a 22% (HR, 1.22, 95% CI: 1.15-1.30) higher risk of COPD. Compared with the HbA1c decile 2 (30.5-<32.2 mmol/mol), the HRs (95% CI) of COPD risk were 1.16 (1.03-1.30) and 1.36 (1.24-1.50) in the lowest HbA1c decile (<30.5 mmol/mol) and highest decile (≥41.0 mmol/mol), respectively. The increased COPD risk associated with HbA1c was more pronounced in younger, current smokers, passive smokers, and participants with a higher Townsend deprivation index (all p for interaction < .05). Among patients with COPD, 4569 COPD cases died (488 because of COPD) during a median follow-up of 5.4 years. Regarding COPD survival, HbA1c had a non-linear relationship with all-cause death (p for non-linearity < .05). Those with HbA1c quintile 5 (≥38.7 mmol/mol) had a 23% (HR, 1.23, 95% CI: 1.10-1.37) higher risk of all-cause death compared with the quintile 2 (32.2-<34.3 mmol/mol). Compared with the HbA1c decile 4 (33.3-<34.3 mmol/mol), those in the lowest HbA1c decile (<30.5 mmol/mol) and highest HbA1c decile (≥41.0 mmol/mol) had 22% (HR, 1.22; 95% CI: 1.01-1.47) and 28% (HR, 1.28; 95% CI: 1.11-1.48) higher risk for overall death. However, no significant association was observed between HbA1c levels and the risk of COPD-specific death.

CONCLUSIONS

Our findings indicated that lower and higher HbA1c levels were associated with a higher risk of COPD. In COPD cases, lower and higher HbA1c levels were associated with a higher COPD all-cause death risk.

Causal relationships between type 2 diabetes, glycemic traits and keratoconus

Purpose

The relationship between diabetes mellitus and keratoconus remains controversial. This study aimed to assess the potential causal relationships among type 2 diabetes, glycemic traits, and the risk of keratoconus.

Methods

We used a two-sample Mendelian randomization (MR) design based on genome-wide association summary statistics. Fasting glucose, proinsulin levels, adiponectin, hemoglobin A1c (HbA1c) and type 2 diabetes with and without body mass index (BMI) adjustment were used as exposures and keratoconus was used as the outcome. MR analysis was performed using the inverse-variance weighted method, MR-Egger regression method, weighted-mode method, weighted median method and the MR-pleiotropy residual sum and outlier test (PRESSO).

Results

Results showed that genetically predicted lower fasting glucose were significantly associated with a higher risk of keratoconus [IVW: odds ratio (OR) = 0.382; 95% confidence interval (CI) = 0.261-0.560; p = 8.162 × 10-7]. Genetically predicted lower proinsulin levels were potentially linked to a higher risk of keratoconus (IVW: OR = 0.739; 95% CI = 0.568-0.963; p = 0.025). In addition, genetically predicted type 2 diabetes negatively correlated with keratoconus (IVW: BMI-unadjusted: OR = 0.869; 95% CI = 0.775-0.974, p = 0.016; BMI-adjusted: OR = 0.880, 95% CI = 0.789-0.982, p = 0.022). These associations were further corroborated by the evidence from all sensitivity analyses.

Conclusion

These findings provide genetic evidence that higher fasting glucose levels are associated with a lower risk of keratoconus. However, further studies are required to confirmed this hypothesis and to understand the mechanisms underlying this putative causative relationship.

Diabetes knowledge predicts HbA1c levels of people with type 2 diabetes mellitus in rural China: a ten-month follow-up study

Improving diabetes self-management (DSM) is facing real-world challenges among people with type 2 diabetes mellitus (T2DM) who have a low education level in resource-limited areas. This study aimed to investigate whether diabetes knowledge could predict glycemic levels in people with T2DM in rural China. This analytical cross-sectional study recruited 321 people with T2DM from eight villages by purposive sampling at baseline. After 10 months, 206 patients completed the follow-up survey and HbA1c tests, with a response rate of 64.17% (206/321). Multiple regression analysis was employed to explore the correlation between diabetes knowledge and HbA1c levels. The patient's diabetes knowledge was significantly negatively correlated with HbA1c levels before and after controlling for covariates in both hierarchical multiple regression and multiple logistic regression (p < 0.01). In addition, other influencing factors, including sex, age, marital status, employment status, income, and HbA1c levels at baseline, were also identified. Diabetes knowledge could predict HbA1c levels significantly among patients with low education levels in rural China. Therefore, interventions on improving diabetes knowledge need to be strengthened for patients in rural China so that they can improve their health outcomes and reduce the disease burden.

Glycated Albumin Correlates With Time-in-Range Better Than HbA1c or Fructosamine

CONTEXT

Intermediate-term glycemic control metrics may represent a viable alternative to continuous glucose monitoring (CGM) in patients without access to CGM.

OBJECTIVE

This work aimed to compare the relationship between CGM parameters and glycated albumin (GA), glycated hemoglobin A1c (HbA1c), and fructosamine for 24 weeks.

METHODS

We conducted exploratory comparative analyses of CGM subgroup data from a previously published 24-week prospective study of assay performance in 8 US clinics. Participants included 34 individuals with type 1 (n = 18) and type 2 diabetes (n = 16) undergoing changes to improve glycemic control (n = 22; group 1) or with stable diabetes therapy (n = 12; group 2). Main outcome measures included Pearson correlations between CGM and glycemic indices and receiver operating characteristic (ROC) analysis of glycemic index values predictive of time in range (TIR) greater than 70%.

RESULTS

At weeks 4 and 8, GA correlations with TIR were higher than HbA1c correlations in group 1. In group 2, GA correlations with TIR were statistically significant, whereas HbA1c correlations were not. In both groups over the first 12 weeks, GA correlations with TIR were higher than fructosamine-TIR correlations. In the ROC analysis, GA predicted a TIR greater than 70% during weeks 2 to 24 (area under the curve >0.80); HbA1c was predictive during weeks 12 to 24. Cutoff values for TIR greater than 70% were 17.5% (sensitivity and specificity, 0.88) for GA and 7.3% (0.86) for HbA1c.

CONCLUSION

GA is the most accurate predictor of TIR over 8 weeks compared with other glycemic indices, which may assist in clinical evaluation of changes in treatment where CGM is not possible and it is too early to use HbA1c (NCT02489773).

Undetectable high-performance liquid chromatography haemoglobin A1c on variant haemoglobin E phenotype: a case report

The gold standard for long-term monitoring of diabetic patients is glycated haemoglobin (HbA1c), which is routinely tested for glycaemic control. Furthermore, the National glycohemoglobin standardization program (NGSP) has designated high-performance liquid chromatography (HPLC) as the reference method for HbA1c measurement. A woman from the Sumba tribe, Indonesia, aged 52, visited the Internal Medicine Clinic for a routine check-up. She had been taking diabetic and hypertension medicines on a regular basis for over 10 years. The HPLC procedure yielded "no result" for the patient's HbA1c assessment and there was no peak on the HPLC graphic. However, there was a discrepancy between the data history of HbA1c measured by turbidimetric method (average of 51 mmol/mol, reference range < 48 mmol/mol), fasting blood glucose (average of 7.7 mmol/L, reference range < 7.0 mmol/L) and 2-hour plasma glucose (average of 13 mmol/L, reference range < 11.1 mmol/L). Glycated albumin was 3.1 mmol/L (reference range 1.8-2.4 mmol/L). Haemoglobin electrophoresis identified homozygote haemoglobinopathy E (HbE). Patients with haemoglobin variants are proposed to utilize glycated albumin.

Sensitivity and specificity of three diabetes diagnostic criteria in people with non-alcoholic fatty liver disease (NAFLD) and otherwise healthy people: Analysis of NHANES III

AIMS

Establishing whether fasting plasma glucose (FPG), postprandial glucose (PPG), and HbA1c have the same diagnostic accuracy in NAFLD versus otherwise healthy people could inform T2DM screening recommendations for those with NAFLD.

METHODS

Cross-sectional analysis of the Third National Health and Nutrition Examination Survey (NHANES III) 1989-1994. T2DM was defined as PPG ≥ 200 mg/dL, FPG ≥ 126 mg/dL, or HbA1c ≥ 6.5 %. We estimated sensitivity and specificity between the six pairwise combinations between the three T2DM definitions in people with and without NAFLD. With Poisson regressions, we investigated if people with NAFLD were more likely to have T2DM with two diagnostic criteria yet not with the third one.

RESULTS

There were 3652 people with mean age 55.6 years and 49.4 % were men; 673 (18.4 %) people had NAFLD. Compared to NAFLD-free individuals, those with NAFLD had lower specificity in all pairwise comparisons except when PPG was the reference vs HbA1c [98.28 % (95 % CI: 97.73 %-98.72 %) in people without NAFLD vs 96.15 % (95 % CI: 94.28 %-97.54 %)]. The sensitivity of FPG was slightly superior to PPG and HbA1c in people without NAFLD; for example, 64.62 % (95 % CI: 55.75 %-72.80 %) for FPG vs 56.58 % (95 % CI: 44.71 %-67.92 %) for HbA1c. People with NAFLD were more likely to be diagnosed with FPG and PPG yet not with HbA1c (PR=2.15; p = 0.020).

CONCLUSIONS

While these T2DM diagnostic criteria may capture different patients both in people with and without NAFLD, in the NAFLD population FPG appears to have the best sensitivity and there were no differences between PPG and HbA1c in terms of specificity.

Guidelines and Recommendations for Laboratory Analysis in the Diagnosis and Management of Diabetes Mellitus

BACKGROUND

Numerous laboratory tests are used in the diagnosis and management of diabetes mellitus. The quality of the scientific evidence supporting the use of these assays varies substantially.

APPROACH

An expert committee compiled evidence-based recommendations for laboratory analysis in screening, diagnosis, or monitoring of diabetes. The overall quality of the evidence and the strength of the recommendations were evaluated. The draft consensus recommendations were evaluated by invited reviewers and presented for public comment. Suggestions were incorporated as deemed appropriate by the authors (see Acknowledgments). The guidelines were reviewed by the Evidence Based Laboratory Medicine Committee and the Board of Directors of the American Association for Clinical Chemistry and by the Professional Practice Committee of the American Diabetes Association.

CONTENT

Diabetes can be diagnosed by demonstrating increased concentrations of glucose in venous plasma or increased hemoglobin A1c (HbA1c) in the blood. Glycemic control is monitored by the people with diabetes measuring their own blood glucose with meters and/or with continuous interstitial glucose monitoring (CGM) devices and also by laboratory analysis of HbA1c. The potential roles of noninvasive glucose monitoring, genetic testing, and measurement of ketones, autoantibodies, urine albumin, insulin, proinsulin, and C-peptide are addressed.

SUMMARY

The guidelines provide specific recommendations based on published data or derived from expert consensus. Several analytes are found to have minimal clinical value at the present time, and measurement of them is not recommended.

Determination of Glucose-Independent Racial Disparity in HbA1c for Youth With Type 1 Diabetes in the Era of Continuous Glucose Monitoring

BACKGROUND

The magnitude and importance of higher HbA1c levels not due to mean blood glucose (MBG) in non-Hispanic black (B) versus non-Hispanic white (W) individuals is controversial. We sought to clarify the relationship of HbA1c with glucose data from continuous glucose monitoring (CGM) in a young biracial population.

METHODS

Glycemic data of 33 B and 85 W, healthy youth with type 1 diabetes (age 14.7 ± 4.8 years, M/F = 51/67, duration of diabetes 5.4 ± 4.7 years) from a factory-calibrated CGM was compared with HbA1c. Hemoglobin glycation index (HGI) = assayed HbA1c - glucose management index (GMI).

RESULTS

B patients had higher unadjusted levels of HbA1c, MBG, MBGSD, GMI, and HGI than W patients. Percent glucose time in range (TIR) and percent sensor use (PSU) were lower for B patients. Average HbA1c in B patients 8.3% was higher than 7.7% for W (P < .0001) after statistical adjustment for MBG, age, gender, insulin delivery method, and accounting for a race by PSU interaction effect. Higher HbA1c persisted in B patients when TIR was substituted for MBG. Predicted MBG was higher in B patients at any level of PSU. The 95th percentile for HGI was 0.47 in W patients, and 52% of B patients had HGI ≥ 0.5. Time below range was similar for both.

CONCLUSIONS

Young B patients have clinically relevant higher average HbA1c at any given level of MBG or TIR than W patients, which may pose an additional risk for diabetes complications development. HGI ≥ 0.5 may be an easy way to identify high-risk patients.

Guidelines and Recommendations for Laboratory Analysis in the Diagnosis and Management of Diabetes Mellitus

BACKGROUND

Numerous laboratory tests are used in the diagnosis and management of diabetes mellitus. The quality of the scientific evidence supporting the use of these assays varies substantially.

APPROACH

An expert committee compiled evidence-based recommendations for laboratory analysis in screening, diagnosis, or monitoring of diabetes. The overall quality of the evidence and the strength of the recommendations were evaluated. The draft consensus recommendations were evaluated by invited reviewers and presented for public comment. Suggestions were incorporated as deemed appropriate by the authors (see Acknowledgments). The guidelines were reviewed by the Evidence Based Laboratory Medicine Committee and the Board of Directors of the American Association of Clinical Chemistry and by the Professional Practice Committee of the American Diabetes Association.

CONTENT

Diabetes can be diagnosed by demonstrating increased concentrations of glucose in venous plasma or increased hemoglobin A1c (Hb A1c) in the blood. Glycemic control is monitored by the people with diabetes measuring their own blood glucose with meters and/or with continuous interstitial glucose monitoring (CGM) devices and also by laboratory analysis of Hb A1c. The potential roles of noninvasive glucose monitoring, genetic testing, and measurement of ketones, autoantibodies, urine albumin, insulin, proinsulin, and C-peptide are addressed.

SUMMARY

The guidelines provide specific recommendations based on published data or derived from expert consensus. Several analytes are found to have minimal clinical value at the present time, and measurement of them is not recommended.

Characterizing common and rare variations in non-traditional glycemic biomarkers using multivariate approaches on multi-ancestry ARIC study

Glycated hemoglobin, fasting glucose, glycated albumin, and fructosamine are biomarkers that reflect different aspects of the glycemic process. Genetic studies of these glycemic biomarkers can shed light on unknown aspects of type 2 diabetes genetics and biology. While there exists several GWAS of glycated hemoglobin and fasting glucose, very few GWAS have focused on glycated albumin or fructosamine. We performed a multi-phenotype GWAS of glycated albumin and fructosamine from 7,395 White and 2,016 Black participants in the Atherosclerosis Risk in Communities (ARIC) study on the common variants from genotyped/imputed data. We found 2 genome-wide significant loci, one mapping to known type 2 diabetes gene (ARAP1/STARD10, p = 2.8 × 10-8) and another mapping to a novel gene (UGT1A, p = 1.4 × 10-8) using multi-omics gene mapping strategies in diabetes-relevant tissues. We identified additional loci that were ancestry-specific (e.g., PRKCA from African ancestry individuals, p = 1.7 × 10-8) and sex-specific (TEX29 locus in males only, p = 3.0 × 10-8). Further, we implemented multi-phenotype gene-burden tests on whole-exome sequence data from 6,590 White and 2,309 Black ARIC participants. Eleven genes across different rare variant aggregation strategies were exome-wide significant only in multi-ancestry analysis. Four out of 11 genes had notable enrichment of rare predicted loss of function variants in African ancestry participants despite smaller sample size. Overall, 8 out of 15 loci/genes were implicated to influence these biomarkers via glycemic pathways. This study illustrates improved locus discovery and potential effector gene discovery by leveraging joint patterns of related biomarkers across entire allele frequency spectrum in multi-ancestry analyses. Most of the loci/genes we identified have not been previously implicated in studies of type 2 diabetes, and future investigation of the loci/genes potentially acting through glycemic pathways may help us better understand risk of developing type 2 diabetes.

Electrochemical Biosensors for Whole Blood Analysis: Recent Progress, Challenges, and Future Perspectives

Whole blood, as one of the most significant biological fluids, provides critical information for health management and disease monitoring. Over the past 10 years, advances in nanotechnology, microfluidics, and biomarker research have spurred the development of powerful miniaturized diagnostic systems for whole blood testing toward the goal of disease monitoring and treatment. Among the techniques employed for whole-blood diagnostics, electrochemical biosensors, as known to be rapid, sensitive, capable of miniaturization, reagentless and washing free, become a class of emerging technology to achieve the target detection specifically and directly in complex media, e.g., whole blood or even in the living body. Here we are aiming to provide a comprehensive review to summarize advances over the past decade in the development of electrochemical sensors for whole blood analysis. Further, we address the remaining challenges and opportunities to integrate electrochemical sensing platforms.

The Impact of a Lockdown for the COVID-19 Pandemic on Seasonal HbA1c Variation in Patients with Type 2 Diabetes

Glycemic control in patients with type 2 diabetes may be disrupted due to restricted medical service access and lifestyle changes during COVID-19 lockdown period. This retrospective cohort study examined changes of HbA1c levels in adults with type 2 diabetes 12 weeks before and after May 19 in 2021, the date that COVID-19 lockdown began in Taiwan. The mean levels of HbA1c-after were significantly lower than HbA1c-before in 2019 (7.27 ± 1.27% vs 7.43 ± 1.38%, p < 0.001), 2020 (7.27 ± 1.28% vs 7.37 ± 1.34%, p < 0.001), and 2021 (7.03 ± 1.22% vs 7.17 ± 1.29%, p < 0.001). Considering the seasonal variation of HbA1c, ΔHbA1c values (HbA1c-after minus HbA1c-before) in 2020 (with sporadic COVID-19 cases and no lockdown) were not significantly different from 2021 (regression coefficient [95% CI] = 0.01% [−0.02%, 0.03%]), while seasonal HbA1c variation in 2019 (no COVID-19) was significantly more obvious than in 2021 (−0.05% [−0.07, −0.02%]). In conclusion, HbA1c level did not deteriorate after a lockdown measure during the COVID-19 pandemic in Taiwan. However, the absolute seasonal reduction in HbA1c was slightly less during the COVID-19 pandemic compared with the year without COVID-19.

A method for comparing multiple imputation techniques: A case study on the U.S. national COVID cohort collaborative

Healthcare datasets obtained from Electronic Health Records have proven to be extremely useful for assessing associations between patients' predictors and outcomes of interest. However, these datasets often suffer from missing values in a high proportion of cases, whose removal may introduce severe bias. Several multiple imputation algorithms have been proposed to attempt to recover the missing information under an assumed missingness mechanism. Each algorithm presents strengths and weaknesses, and there is currently no consensus on which multiple imputation algorithm works best in a given scenario. Furthermore, the selection of each algorithm's parameters and data-related modeling choices are also both crucial and challenging. In this paper we propose a novel framework to numerically evaluate strategies for handling missing data in the context of statistical analysis, with a particular focus on multiple imputation techniques. We demonstrate the feasibility of our approach on a large cohort of type-2 diabetes patients provided by the National COVID Cohort Collaborative (N3C) Enclave, where we explored the influence of various patient characteristics on outcomes related to COVID-19. Our analysis included classic multiple imputation techniques as well as simple complete-case Inverse Probability Weighted models. Extensive experiments show that our approach can effectively highlight the most promising and performant missing-data handling strategy for our case study. Moreover, our methodology allowed a better understanding of the behavior of the different models and of how it changed as we modified their parameters. Our method is general and can be applied to different research fields and on datasets containing heterogeneous types.

Causal Relationships Between Glycemic Traits and Myopia

Purpose

Little is known about whether sugar intake is a risk factor for myopia, and the influence of glycemic control remains unclear, with inconsistent results reported. This study aimed to clarify this uncertainty by evaluating the link between multiple glycemic traits and myopia.

Methods

We employed a two-sample Mendelian randomization (MR) design using summary statistics from independent genome-wide association studies. A total of six glycemic traits, including adiponectin, body mass index, fasting blood glucose, fasting insulin, hemoglobin A1c (HbA1c), and proinsulin levels, were used as exposures, and myopia was used as the outcome. The inverse-variance-weighted (IVW) method was the main applied analytic tool and was complemented with comprehensive sensitivity analyses.

Results

Out of the six glycemic traits studied, we found that adiponectin was significantly associated with myopia. The genetically predicted level of adiponectin was consistently negatively associated with myopia incidence: IVW (odds ratio [OR] = 0.990; P = 2.66 × 10-3), MR Egger (OR = 0.983; P = 3.47 × 10-3), weighted median method (OR = 0.989; P = 0.01), and weighted mode method (OR = 0.987; P = 0.01). Evidence from all sensitivity analyses further supported these associations. In addition, a higher HbA1c level was associated with a greater risk of myopia: IVW (OR = 1.022; P = 3.06 × 10-5).

Conclusions

Genetic evidence shows that low adiponectin levels and high HbA1c are associated with an increased risk of myopia. Given that physical activity and sugar intake are controllable variables in blood glycemia treatment, these findings provide new insights into potential strategies to delay myopia onset.

The effectiveness of self-management programme based on multilevel social resources utilization in diabetes mellitus patients: A randomized controlled study

AIMS

This study aimed to test the effects of a novel diabetes self-management education (DSME) programme focused on multilevel social resources utilization on improving self-management behaviour, social resources utilization and haemoglobin A_lc (HbA_1c ) in patients with type 2 diabetes mellitus (T2DM).

METHODS

A randomized controlled design was used. A total of 118 participants with T2DM from two communities were recruited through randomized sampling, and randomly assigned to the novel DSME group or the traditional DSME group. DSME focusing on multilevel social resources utilization was implemented in the novel DSME group. Data were collected at baseline (T₀ ), at the end of the intervention (T₁ ) and 3 months after the end of intervention (T₂ ) from 3 March to 16 November 2014.

RESULTS

Comparing these two groups, the participants in the novel DSME group reported significantly better improvement in self-management behaviour and social resources utilization at T₁ and T₂ (all p < 0.01). A significant difference was found in the mean improvement of HbA_1c level between the two groups at T₂ (p < 0.05).

CONCLUSIONS

The novel DSME programme focused on multilevel social resources utilization can effectively enhance T2DM patients' self-management behaviour and social resource utilization and lower HbA_1c levels. More importantly, the effects could last longer.

Interference of hemoglobin variants in HbA1c quantification

Fasting blood glucose and glycated hemoglobin (HbA_1c) are routine biomarkers to screen and monitor diabetes mellitus. HbA_1c results from glycation at the N-terminus of the β globin chain of tetrameric human hemoglobin. Fasting blood glucose level varies with the nature and amount of food intake, physical exercise, etc., and, accordingly, is a short-term measure of glucose control. In contrast, HbA_1c provides an average measure of glucose control for the long-term (8-12 weeks). Unfortunately, genetic variants of hemoglobin may interfere with HbA_1c quantification using ion exchange chromatography, capillary electrophoresis, immunoassay and boronate affinity chromatography. Mass spectrometry, however, measures total glycation of hemoglobin across both α and β globin chains and correlates well with the ion exchange based method. Additionally, mass spectrometry based quantification is not impacted by the presence of genetic variants of hemoglobin and thus might be a better analytical choice for diabetes mellitus.

Effects of 26 weeks of treatment with empagliflozin versus glimepiride on the myocardial glucose metabolic rate in patients with type 2 diabetes: The randomized, open-label, crossover, active-comparator FIORE trial

AIM

To determine whether treatment with empagliflozin was able to affect the myocardial glucose metabolic rate, as assessed by cardiac dynamic ¹⁸ F-fluorodeoxyglucose-positron emission tomography (¹⁸ F-FDG-PET) combined with euglycaemic-hyperinsulinaemic clamp compared with glimepiride in patients with type 2 diabetes.

MATERIALS AND METHODS

To further investigate the cardioprotective mechanism of sodium-glucose co-transporter-2 inhibitors, we performed a 26-week, randomized, open-label, crossover, active-comparator study to determine the effects of empagliflozin 10 mg versus glimepiride 2 mg daily on the myocardial glucose metabolic rate assessed by cardiac dynamic ¹⁸ F-FDG-PET combined with euglycaemic-hyperinsulinaemic clamp in 23 patients with type 2 diabetes. We also measured cardiac geometry and myocardial mechano-energetic efficiency, as well as systolic and diastolic function by echocardiography.

RESULTS

Compared with glimepiride, treatment with empagliflozin resulted in a greater reduction in the myocardial glucose metabolic rate from baseline to 26 weeks (adjusted difference -6.07 [-8.59, -3.55] μmol/min/100 g; P < .0001). Moreover, compared with glimepiride, empagliflozin led to significant reductions in left atrial diameter, left ventricular end-systolic and end-diastolic volumes, N-terminal pro b-type natriuretic peptide levels, blood pressure, heart rate, stroke work, and myocardial oxygen consumption estimated by the rate pressure product, and increases in ejection fraction, myocardial mechano-energetic efficiency, red blood cells, and haematocrit and haemoglobin levels.

CONCLUSIONS

The present study provides evidence that empagliflozin treatment in subjects with type 2 diabetes without coronary artery disease leads to a significant reduction in the myocardial glucose metabolic rate.

Does health information affect lifestyle behaviours? The impact of a diabetes diagnosis

Despite an increasing interest in the effect of health information on health-behaviours, evidence on the causal impact of a diagnosis on lifestyle factors is still mixed and does not often account for long-term effects. We explore the role of health information in individual health-related decisions by identifying the causal impact of a type-2 diabetes diagnosis on body mass index (BMI) and lifestyle behaviours. We employ a fuzzy regression discontinuity design (RDD) exploiting the exogenous cut-off value in the diagnosis of type-2 diabetes provided by a biomarker (glycated haemoglobin) drawn from unique administrative longitudinal data from Spain. We find that following a type-2 diabetes diagnosis individuals appear to reduce their weight in the short-term. Differently from previous studies, we also provide evidence of statistically significant long-term impacts of a type-2 diabetes diagnosis on BMI up to three years from the diagnosis. We do not find perceivable effects of a type-2 diabetes diagnosis on quitting smoking or drinking. Overall, health information appears to have a sustained causal impact on weight reduction, a key lifestyle and risk factor among individuals with type-2 diabetes.

Relation Between HbA1c and Lipid Profile Among Prediabetics, Diabetics, and Non-diabetics: A Hospital-Based Cross-Sectional Analysis

INTRODUCTION

An unusually high blood glucose level is a hallmark of diabetes mellitus, with an imbalance between insulin levels and insulin sensitivity leading to an insulin functional deficit. Since it serves as both a risk indicator and a gauge of long-term glycemic control, the HbA1c concentration is a crucial component of standard diabetes treatment. The use of the HbA1c concentration in the diagnosis of diabetes is expanding as the test's accuracy increases. Dyslipidemic profiles can appear before type 2 diabetes manifests itself and are independent risk factors for the disease. Additionally, dyslipidemia, especially in diabetics, might affect pancreatic beta-cell survival and activity. This study was undertaken with the aim to find out any correlation between HbA1c and lipid profile among diabetics, prediabetics, and non-diabetics.

METHODS

A total of 1,000 individuals with age 18-60 years were included in the study (non-diabetics = 186, prediabetics = 238, diabetics = 576). HbA1c was estimated by capillary electrophoresis and a lipid profile was done using a fully automatic chemistry analyzer.

RESULT

Diabetes was found to be significantly associated with dyslipidemia. In diabetics, a statistically significant increase in the level of triglyceride and very low-density lipoprotein (VLDL) was seen as compared to prediabetics. Diabetic women were found to be significantly more dyslipidemic as compared to diabetic males. The mean HbA1c among diabetics was found to be 8.3.

CONCLUSION

In hyperglycemia-induced dyslipidemia, raised triglyceride and VLDL were the most common findings, and combined lipid abnormalities were more commonly seen as compared to a single abnormality in the lipid profile. Patients with poor glycemic control more commonly develop dyslipidemia, which may be a reason for an increased incidence of cardiovascular catastrophes in such patients.

Glycated albumin is associated with all-cause and cardiovascular mortality among U.S. adults with and without diabetes: A retrospective cohort study

BACKGROUND AND AIMS

Glycated albumin (GA) reflects short-term glycemic control, but few data are available on its association with hard clinical outcomes. The purpose of this study is to evaluate the association between GA levels and all-cause and cardiovascular mortality in people with and without a previous diagnosis of diabetes.

METHODS AND RESULTS

Serum GA levels were measured in 12147 people from the general population (1319 with and 10828 without diabetes) that participated in the 1999-2004 cycles of the National Health and Nutrition Examination Survey (NHANES). We evaluated the association between GA and all-cause and cardiovascular mortality through December 2015 by linking NHANES data with data from the National Death Index. Associations were compared with those observed for hemoglobin A1c (HbA1c). After a median follow-up of 13 years, 2785 participants (619 with and 2166 without diabetes) died, 651 of cardiovascular causes. Multivariable-adjusted Cox proportional hazard models showed that higher baseline GA levels were significantly associated with a higher incidence of both outcomes in participants with (all-cause: HR 1.03, 95% CI 1.01-1.04; cardiovascular: HR 1.04, 95% CI 1.02-1.07) and without diabetes (all-cause: HR 1.05, 95% CI 1.03-1.08; cardiovascular: HR: 1.08, 95% CI 1.02-1.14); on the other hand, we found a trend for increased mortality with increasing HbA1c levels in patients with known diabetes, but not in participants without.

CONCLUSIONS

For a novel measure of hyperglycemia to be considered useful, its association with hard, long term clinical outcomes is of great importance. We showed that GA is associated with mortality in the general population independently of a previous diagnosis of diabetes.

Colorimetric acetone sensor based on ionic liquid functionalized drug-mediated silver nanostructures

The current work reports the drug-mediated synthesis of silver nanoparticles (AgNPs) and their functionalization with ionic liquid (IL) for acetone determination. The rationale behind the selection of the Augmentin drug was the aromaticity in its structure and the functional groups attached. These properties are not only supposed to work in the synthesis of the nanoparticles but also enhance their electron density. The nanoparticles were further coated with 1-H-3-methylimidazolium acetate IL, having conductivity and aromaticity in their structure. The synthesized nanoparticles have been characterized by different techniques such as FTIR, XRD, SEM, and EDX. Colorimetric determination of acetone was done by using IL capped AgNPs with the assistance of NaCl solution and results were analyzed by UV-Vis spectrophotometry. Low-cost, stable eosin dye works as a substrate and is consumed resulting in a color change from brown to transparent. The IL capped AgNPs act as a reducing agent for the production of reduced radical form of acetone which act on the carboxylate moiety and bubble it out in the form of CO₂. Different parameters such as (concentrations, loading of nanoparticles, time and pH, etc.) were optimized to get the best results of the proposed sensor. The sensor shows a wide linear range of (1 ×10^-8-2.40 ×10^-6 M), low limit of detection 2.66 × 10^-9 M, and limit of quantification 8.86 × 10^-9 M with an R² value of 0.997. The proposed sensor has been successfully applied to diabetic patient's urine samples for acetone detection with a visible colorimetric change. It showed good sensitivity and selectivity towards acetone detection.

Analytical Challenges in Diabetes Management: Towards Glycated Albumin Point-of-Care Detection

Diabetes mellitus is a worldwide-spread chronic metabolic disease that occurs when the pancreas fails to produce enough insulin levels or when the body fails to effectively use the secreted pancreatic insulin, eventually resulting in hyperglycemia. Systematic glycemic control is the only procedure at our disposal to prevent diabetes long-term complications such as cardiovascular disorders, kidney diseases, nephropathy, neuropathy, and retinopathy. Glycated albumin (GA) has recently gained more and more attention as a control biomarker thanks to its shorter lifespan and wider reliability compared to glycated hemoglobin (HbA1c), currently the “gold standard” for diabetes screening and monitoring in clinics. Various techniques such as ion exchange, liquid or affinity-based chromatography and immunoassay can be employed to accurately measure GA levels in serum samples; nevertheless, due to the cost of the lab equipment and complexity of the procedures, these methods are not commonly available at clinical sites and are not suitable to home monitoring. The present review describes the most up-to-date advances in the field of glycemic control biomarkers, exploring in particular the GA with a special focus on the recent experimental analysis techniques, using enzymatic and affinity methods. Finally, analysis steps and fundamental reading technologies are integrated into a processing pipeline, paving the way for future point-of-care testing (POCT). In this view, we highlight how this setup might be employed outside a laboratory environment to reduce the time from measurement to clinical decision, and to provide diabetic patients with a brand-new set of tools for glycemic self-monitoring.

Fucoxanthin: A Promising Phytochemical on Diverse Pharmacological Targets

Fucoxanthin (FX) is a special carotenoid having an allenic bond in its structure. FX is extracted from a variety of algae and edible seaweeds. It has been proved to contain numerous health benefits and preventive effects against diseases like diabetes, obesity, liver cirrhosis, malignant cancer, etc. Thus, FX can be used as a potent source of both pharmacological and nutritional ingredient to prevent infectious diseases. In this review, we gathered the information regarding the current findings on antimicrobial, antioxidant, anti-inflammatory, skin protective, anti-obesity, antidiabetic, hepatoprotective, and other properties of FX including its bioavailability and stability characteristics. This review aims to assist further biochemical studies in order to develop further pharmaceutical assets and nutritional products in combination with FX and its various metabolites.

Glucose-independent racial disparity in HbA1c is evident at onset of type 1 diabetes

OBJECTIVE

Higher levels of HbA1c, independent of blood glucose levels, have been described in Blacks compared to Whites patients with established diabetes. The goal of this study was to determine if glucose-independent racial disparity in HbA1C is evident at diabetes onset.

RESEARCH DESIGN AND METHODS

We conducted a retrospective single-center chart review of 189 youth with new onset Type 1 diabetes (T1D) 60 % Whites and 40 % Blacks. HbA1c, glucose and other biochemistry measures were obtained at presentation in the Emergency Department before initiation of any therapy. HbA1c levels were adjusted for presenting glucose, self-identified race, age, gender, hematocrit, and RDW-CV.

RESULTS

Blacks with T1D had statistically significant higher unadjusted HbA1c (11.9 ± 1.9 vs 11.04 ± 2.0 %, p = 0.004), initial glucose (530.6 ± 230.4 vs 442 ± 211.3 mg/dL, p = 0.0075) and lower pHs (7.28 ± 0.15 vs 7.33 ± 0.12, p = 0.02) compared to white patients. Least squares means of HbA1c remained higher in Black patients even after statistical adjustment for presenting glucose, age, gender, RDW-CV, and pH. In a multiple variable model (R² = 0.38, p < 0.0001) c-peptide was influenced by HCO₃ (p = 0.0035), gender (p = 0.0092), BMI (p < 0.0001), but not race or glucose.

CONCLUSIONS

HbA1c at initial presentation of T1D is higher in young Black patients compared to Whites even after adjustment for glucose, age, gender, and RDW-CV. This racial disparity is consistent with other studies in individuals without diabetes and patients with long-standing diabetes under treatment.

Effects of the selective serotonin reuptake inhibitor fluoxetine on glucose metabolism: A systematic review

OBJECTIVES

The metabolic effects of antidepressants should be considered when prescribing antidepressants due to the increasing risk of diabetes, obesity and cardiovascular disease. This study aims to explore the effects of fluoxetine on glucose and lipid metabolism in human body.

METHODS

Studies of the effects of fluoxetine on glucose and lipid metabolism were collected from the PubMed, MEDLINE and Embase databases without limiting the research design. The retrieval spanned between inception and January 2021. The main outcome measures were fasting blood glucose, glycosylated hemoglobin (mainly HbA1c) and body weight.

RESULTS

A total of 24 studies were retrieved, including 20 randomized controlled trials (RCTs), 1 prospective study and 3 case reports. The meta-analysis showed that FBG and HbA_1c levels were moderately decreased(MD-0.85[-1.75, -0.13], P = 0.02 and MD-0.55[-1.23, 0.13], P = 0.11 respectively) and body weight was significantly decreased (MD-3.01[-5.58, -0.44], P < 0.00001) with fluoxetine treatment compared with placebo. Both plasma triglyceride (TG) and total cholesterol (TC) levels decreased significantly (P < 0.00001).

CONCLUSION

Fluoxetine had a positive effect on improving blood glucose control in patients with disorders of glucose metabolism and was good for weight management in obese people despite significant heterogeneity between studies.

Real-world Benefits of Diabetes Management App Use and Self-monitoring of Blood Glucose on Glycemic Control: Retrospective Analyses

Background

Among self-care measures, the self-monitoring of blood glucose (SMBG) is a critical component for checking blood glucose levels. In addition, there is growing evidence suggesting that digital technologies are being adopted as an additional method for health care systems to increase patient contact. However, for patients with non–insulin-treated diabetes mellitus type 2 (DMT2), the value of SMBG was inconsistent among studies, and the evidence for digital technologies from real-world clinical practice is still limited.

Objective

Our study aimed to assess patients with non–insulin-treated DMT2 who were receiving care from a single clinic and analyze whether the use of a diabetes management app and SMBG behavior would affect glycemic control in a real-world clinical setting.

Methods

We collaborated with a large clinic focused on diabetes care in Taiwan that had been using the Health2Sync mobile app and web-based Patient Management Platform to collect the data. The patients were divided into 2 groups (app-engaged-user group and only-data-uploader group) according to different activities in the app, and blood glucose was recorded every month from 1 to 6 months after registration in the app. A sample of 420 patients was included in the analysis, and a linear mixed model was built to investigate which factors affected the patients’ blood glucose percentage change.

Results

Using the mixed model coefficient estimates, we found that the percentage change was significantly negative when the only-data-uploader group was set as the baseline (t=–3.873, df=1.81 × 10⁴; P<.001 for the patients of the app-engaged-user group). We found that for patients with shorter diabetes duration, their blood glucose decreased more than patients with longer diabetes duration (t=2.823, df=1.71 × 10⁴; P=.005 for the number of years of diabetes duration). In addition, we found that for younger patients, their blood glucose decreased more than older patients (t=2.652, df=1.71 × 10⁴; P=.008 for the age of the patients). Furthermore, the patients with an education level of junior high school or lower saw a significantly greater decrease in blood glucose percentage change than the patients with an education level of senior high school or higher (t=4.996, df=1.72 × 10⁴; P<.001 for the patients with an education level of senior high school or higher). We also found that the count of blood glucose measured enlarged the decrease along the interaction months (t=–8.266, df=1.97 × 10⁴; P<.001 for the nth month × the count of blood glucose in the nth month). Lastly, the gender of the patients did not significantly affect the percentage change (t=0.534, df=1.74 × 10⁴; P=.59 for female patients).

Conclusions

Our analysis showed the following: the blood glucose percentage change of the patients in the app-engaged-user group dropped more than that in the only-data-uploader group; shorter diabetes duration is associated with a steeper decrease in the patients’ blood glucose percentage change; the percentage decrease in blood glucose change in younger patients is greater than older patients; the blood glucose percentage change of the patients with an education level of junior high school or lower dropped more than those with an education level of senior high school or higher; and the more frequently the patients test SMBG each month, the greater the decrease in the patients’ blood glucose percentage. Further studies can be performed to consider the differences in daily behaviors such as exercise and diet across the patients and whether these factors could have vital effects on glycemic control.

Skin accumulation of advanced glycation end products and cardiovascular risk in Korean patients with type 2 diabetes mellitus

Background

The formation of advanced glycation end products (AGEs) takes place during normal aging; however, their production is faster in people having diabetes. The accumulated AGEs reportedly play a role in the occurrence of various age-related disorders. Furthermore, the skin autofluorescence (SAF) technique can be used to detect accumulated AGEs levels. There are few reports on the association between skin accumulation of AGEs and risk of complications in type 2 diabetes mellitus.

Methods

In this study, we aimed to describe the association between the skin accumulation of AGEs and cardiovascular risk factors in Korean patients with type 2 diabetes. A total of 310 Korean patients with diabetes were enrolled, and the levels of AGEs were measured using SAP. Levels of fasting blood glucose (FBS), triglycerides, total cholesterol, low- and high-density lipoprotein cholesterol, proteinuria, arterial pulse wave velocity (PWV), and blood vessel age were measured using an automatic waveform analyzer. General linear models were used to identify the independent effect of AGEs after adjusting for covariates (age, weight, and duration of diabetes).

Results

The skin levels of AGEs were strongly correlated with the diabetes duration. Significant independent associations were observed for AGEs with FBS (P < 0.01), proteinuria (P < 0.001), and PWV (P < 0.001). The advanced glycated product was independently associated to the arterial pulse wave conduction velocity that is used as a representative method for measuring arteriosclerosis by analysis early cardiovascular risk factors.

Conclusion

Our results show that an increase in SAF levels in Korean patients with type 2 diabetes is associated with PWV and vein age, and thereby with arterial stiffness. Therefore, our results suggest that AGEs are associated with cardiovascular risk factors. The level of AGEs can thus be used as an indicator of cardiovascular diseases in the clinical diagnosis of patients with type 2 diabetes.

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Unclear association between skin accumulation of AGEs and T2DM complication risk.

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Study Population: Korean patients with T2DM.

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Strong correlation between skin levels of AGEs and diabetes duration.

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Independent association between AGEs and arterial pulse wave conduction velocity.

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Association between increased SAF levels in with PWV, vein age, arterial stiffness.

Diagnostic circulating biomarkers to detect vision-threatening diabetic retinopathy: Potential screening tool of the future?

With the increasing prevalence of diabetes in developing and developed countries, the socio-economic burden of diabetic retinopathy (DR), the leading complication of diabetes, is growing. Diabetic retinopathy (DR) is currently one of the leading causes of blindness in working-age adults worldwide. Robust methodologies exist to detect and monitor DR; however, these rely on specialist imaging techniques and qualified practitioners. This makes detecting and monitoring DR expensive and time-consuming, which is particularly problematic in developing countries where many patients will be remote and have little contact with specialist medical centres. Diabetic retinopathy (DR) is largely asymptomatic until late in the pathology. Therefore, early identification and stratification of vision-threatening DR (VTDR) is highly desirable and will ameliorate the global impact of this disease. A simple, reliable and more cost-effective test would greatly assist in decreasing the burden of DR around the world. Here, we evaluate and review data on circulating protein biomarkers, which have been verified in the context of DR. We also discuss the challenges and developments necessary to translate these promising data into clinically useful assays, to detect VTDR, and their potential integration into simple point-of-care testing devices.

Metabolomic Analysis of Serum and Tear Samples from Patients with Obesity and Type 2 Diabetes Mellitus

Metabolomics strategies are widely used to examine obesity and type 2 diabetes (T2D). Patients with obesity (n = 31) or T2D (n = 26) and sex- and age-matched controls (n = 28) were recruited, and serum and tear samples were collected. The concentration of 23 amino acids and 10 biogenic amines in serum and tear samples was analyzed. Statistical analysis and Pearson correlation analysis along with network analysis were carried out. Compared to controls, changes in the level of 6 analytes in the obese group and of 10 analytes in the T2D group were statistically significant. For obesity, the energy generation, while for T2D, the involvement of NO synthesis and its relation to insulin signaling and inflammation, were characteristic. We found that BCAA and glutamine metabolism, urea cycle, and beta-oxidation make up crucial parts of the metabolic changes in T2D. According to our data, the retromer-mediated retrograde transport, the ethanolamine metabolism, and, consequently, the endocannabinoid signaling and phospholipid metabolism were characteristic of both conditions and can be relevant pathways to understanding and treating insulin resistance. By providing potential therapeutic targets and new starting points for mechanistic studies, our results emphasize the importance of complex data analysis procedures to better understand the pathomechanism of obesity and diabetes.

Treatment of periodontitis for glycaemic control in people with diabetes mellitus

BACKGROUND

Glycaemic control is a key component in diabetes mellitus (diabetes) management. Periodontitis is the inflammation and destruction of the underlying supporting tissues of the teeth. Some studies have suggested a bidirectional relationship between glycaemic control and periodontitis.  Treatment for periodontitis involves subgingival instrumentation, which is the professional removal of plaque, calculus, and debris from below the gumline using hand or ultrasonic instruments. This is known variously as scaling and root planing, mechanical debridement, or non-surgical periodontal treatment. Subgingival instrumentation is sometimes accompanied by local or systemic antimicrobials, and occasionally by surgical intervention to cut away gum tissue when periodontitis is severe. This review is part one of an update of a review published in 2010 and first updated in 2015, and evaluates periodontal treatment versus no intervention or usual care.  OBJECTIVES: To investigate the effects of periodontal treatment on glycaemic control in people with diabetes mellitus and periodontitis.

SEARCH METHODS

An information specialist searched six bibliographic databases up to 7 September 2021 and additional search methods were used to identify published, unpublished, and ongoing studies.  SELECTION CRITERIA: We searched for randomised controlled trials (RCTs) of people with type 1 or type 2 diabetes mellitus and a diagnosis of periodontitis that compared subgingival instrumentation (sometimes with surgical treatment or adjunctive antimicrobial therapy or both) to no active intervention or 'usual care' (oral hygiene instruction, education or support interventions, and/or supragingival scaling (also known as PMPR, professional mechanical plaque removal)). To be included, the RCTs had to have lasted at least 3 months and have measured HbA1c (glycated haemoglobin).

DATA COLLECTION AND ANALYSIS

At least two review authors independently examined the titles and abstracts retrieved by the search, selected the included trials, extracted data from included trials, and assessed included trials for risk of bias. Where necessary and possible, we attempted to contact study authors. Our primary outcome was blood glucose levels measured as glycated (glycosylated) haemoglobin assay (HbA1c), which can be reported as a percentage of total haemoglobin or as millimoles per mole (mmol/mol). Our secondary outcomes included adverse effects, periodontal indices (bleeding on probing, clinical attachment level, gingival index, plaque index, and probing pocket depth), quality of life, cost implications, and diabetic complications.

MAIN RESULTS

We included 35 studies, which randomised 3249 participants to periodontal treatment or control. All studies used a parallel-RCT design and followed up participants for between 3 and 12 months. The studies focused on people with type 2 diabetes, other than one study that included participants with type 1 or type 2 diabetes. Most studies were mixed in terms of whether metabolic control of participants at baseline was good, fair, or poor. Most studies were carried out in secondary care.  We assessed two studies as being at low risk of bias, 14 studies at high risk of bias, and the risk of bias in 19 studies was unclear. We undertook a sensitivity analysis for our primary outcome based on studies at low risk of bias and this supported the main findings. Moderate-certainty evidence from 30 studies (2443 analysed participants) showed an absolute reduction in HbA1c of 0.43% (4.7 mmol/mol) 3 to 4 months after treatment of periodontitis (95% confidence interval (CI) -0.59% to -0.28%; -6.4 mmol/mol to -3.0 mmol/mol). Similarly, after 6 months, we found an absolute reduction in HbA1c of 0.30% (3.3 mmol/mol) (95% CI -0.52% to -0.08%; -5.7 mmol/mol to -0.9 mmol/mol; 12 studies, 1457 participants), and after 12 months, an absolute reduction of 0.50% (5.4 mmol/mol) (95% CI -0.55% to -0.45%; -6.0 mmol/mol to -4.9 mmol/mol; 1 study, 264 participants). Studies that measured adverse effects generally reported that no or only mild harms occurred, and any serious adverse events were similar in intervention and control arms. However, adverse effects of periodontal treatments were not evaluated in most studies.

AUTHORS' CONCLUSIONS

Our 2022 update of this review has doubled the number of included studies and participants, which has led to a change in our conclusions about the primary outcome of glycaemic control and in our level of certainty in this conclusion. We now have moderate-certainty evidence that periodontal treatment using subgingival instrumentation improves glycaemic control in people with both periodontitis and diabetes by a clinically significant amount when compared to no treatment or usual care. Further trials evaluating periodontal treatment versus no treatment/usual care are unlikely to change the overall conclusion reached in this review.

Serum ketone body measurement in patients with diabetic ketoacidosis

Background

Diabetic ketoacidosis (DKA) is a critical manifestation in patients with diabetes mellitus. DKA has been conventionally diagnosed by the presence of hyperglycemia (blood glucose levels > 250 mg/dl) and metabolic acidosis (blood gas bicarbonate [HCO₃ ^-] < 18 mmol/l and pH in blood gas < 7.30). However, quantitative evaluation of serum ketone bodies has not been established. The current study investigates serum ketone body levels in patients suspected for DKA.

Methods

We have retrospectively evaluated patients with hyperglycemia whose serum ketone body levels at the outpatient clinic and emergency department were measured simultaneously with blood gas analysis during 2011-2019. Clinical backgrounds, severity of diabetes, serum ketone bodies, and blood gas factors were analyzed.

Results

Seventy-two patients were enrolled in the study, after the exclusion of patients who had ketosis due to factors other than diabetes. Serum ketone body levels were negatively correlated with the levels of blood HCO₃ ^- and pH. By receiver-operating-characteristic curve analyses, optimal cut-off values for diagnosis of DKA were determined at 6.3 mmol/l of beta-hydroxybutyrate, 1.4 mmol/l of acetoacetate, and 8.0 mmol/l of total ketone body, respectively. Moreover, serum ketone bodies appeared to effectively differentiate between type 1 and type 2 diabetes mellitus. The cut-off values were higher than those in previous reports.

Conclusions

Serum ketone body levels were thought to be useful in the diagnosis of DKA. Further investigations with increased numbers of patients are required to establish the appropriate application of serum ketone bodies in patients with DKA.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13340-022-00581-2.

Assessment of glycemia in chronic kidney disease

Reliable assessment of glycemia is central to the management of diabetes. The kidneys play a vital role in maintaining glucose homeostasis through glucose filtration, reabsorption, consumption, and generation. This review article highlights the role of the kidneys in glucose metabolism and discusses the benefits, pitfalls, and evidence behind the glycemic markers in patients with chronic kidney disease. We specifically highlight the role of continuous glucose monitoring as an emerging minimally invasive technique for glycemic assessment.

Predicting population: development and validation of a new predictive nomogram for evaluating medication nonadherence risk in a type 2 diabetes

Background

Diabetes mellitus is a growing global health challenge and affects patients of all ages. Treatment aims to keep blood glucose levels close to normal and to prevent or delay complications. However, adherence to antidiabetic medicines is often unsatisfactory.

Purpose

Here, we established and internally validated a medication nonadherence risk nomogram for use in Chinese type 2 diabetes mellitus (T2DM) patients.

Methods

This cross-sectional study was carried out from July-December 2020 on randomly selected T2DM patients visiting a diabetes clinic and included 753 participants. Adherence was analyzed based on an eight-item Morisky Medication Adherence Scale (MMAS-8). Other data, including patient demographics, treatment, complications, and comorbidities, were also collected on questionnaires. Optimization of feature selection to develop the medication nonadherence risk model was achieved using the least absolute shrinkage and selection operator regression model (LASSO). A prediction model comprising features selected from LASSO model was designed by applying multivariable logistic regression analysis. The decision curve analysis, calibration plot, and C-index were utilized to assess the performance of the model in terms of discrimination, calibration, and clinical usefulness. Bootstrapping validation was applied for internal validation.

Results

The prediction nomogram comprised several factors including sex, marital status, education level, employment, distance, self-monitoringofbloodglucose, disease duration, and dosing frequency of daily hypoglycemics (pills, insulin, or glucagon-like peptide-1). The model exhibited good calibration and good discrimination (C-index = 0.79, 95% CI [0.75-0.83]). In the validation samples, a high C-index (0.75) was achieved. Results of the decision curve analysis revealed that the nonadherence nomogram could be applied in clinical practice in cases where the intervention is decided at a nonadherence possibility threshold of 12%.

Conclusion

The number of patients who adhere to anti-diabetes therapy was small. Being single male, having no formal education, employed, far from hospital, long disease duration, and taking antidiabetics twice or thrice daily, had significant negative correlation with medication adherence. Thus, strategies for improving adherence are urgently needed.

Prognostic Significance of Admission Glucose Combined with Hemoglobin A1c in Acute Ischemic Stroke Patients with Reperfusion Therapy

Background: Elevated admission glucose and hemoglobin A1c (HbA1c) levels have been suggested to be associated with 90-day functional outcomes in acute ischemic stroke (AIS) patients with endovascular thrombectomy (EVT). However, whether the prognostic significance of admission glucose and that of HbA1c have a joint effect on patients with intravascular thrombolysis (IVT) and/or EVT remains unclear. This study aimed to explore the association between admission glucose combined with HbA1c and outcomes in patients with reperfusion therapy. Methods: Consecutive AIS patients treated with IVT and/or EVT between 2 January 2018 and 27 February 2021 in West China hospital were enrolled. Admission glucose and HbA1c levels were measured at admission. Participants were divided into four groups according to admission glucose level (categorical variable: <7.8 and ≥7.8 mmol/L) and HbA1c level (categorical variable: <6.5% and ≥6.5%): normal glucose and normal HbA1c (NGNA), normal glucose and high HbA1c (NGHA), high glucose and normal HbA1c (HGNA), and high glucose and high HbA1c (HGHA). The primary outcome was an unfavorable functional outcome defined as a modified Rankin Scale (mRS) ≥ 3. The secondary outcome was all-cause mortality at 90 days. Results: A total of 519 patients (mean age, 69.0 ± 13.4 years; 53.8% males) were included. Patients in the HGHA group had a significantly increased risk of unfavorable functional outcome (OR, 1.81; 95%CI, 1.01–3.23) and mortality (OR, 1.75; 95%CI, 1.01–3.06) at 90 days compared with those in the NGNA group after adjustment for confounders. There was no significant association between NGHA (OR, 0.43; 95%CI, 0.12–1.53) or HGNA (OR, 1.46; 95%CI, 0.84–2.56) and outcomes compared to the NGNA group. Conclusion: The combination of high admission glucose and high HbA1c level was significantly associated with unfavorable functional outcome and mortality at 90 days in AIS patients with reperfusion therapy.

Significance of Educational Literature and Diabetes Log Sheet on Hemoglobin A1c

Diabetes mellitus (DM) is a major cause of morbidity worldwide. The prevalence of DM has doubled over the last 35 years and is escalating. Various complications and manifestations of diabetes have caused numerous deaths worldwide, with numbers increasing every year. There have been many advances and breakthroughs over the past decade in the management of DM. The major focus of many research studies has been to evaluate effective medication combinations, preventative measures, and the way to control such morbid conditions. Our focus in this review is to discuss specific secondary prevention techniques with the diabetes log sheet and educational literature on its effectiveness in controlling diabetes. Hemoglobin A1c (HbA1c) has been accepted as a diabetes control measure in many resources worldwide. Here, we have assessed articles on the effectiveness of the diabetes log sheet and educational literature on HbA1c levels. We will begin with a few key points to acknowledge diabetes initially, followed by discussing the effectiveness of the diabetes log sheet and literature on HbA1c.

Glucose biosensors in clinical practice: principles, limits and perspectives of currently used devices

The demand of glucose monitoring devices and even of updated guidelines for the management of diabetic patients is dramatically increasing due to the progressive rise in the prevalence of diabetes mellitus and the need to prevent its complications. Even though the introduction of the first glucose sensor occurred decades ago, important advances both from the technological and clinical point of view have contributed to a substantial improvement in quality healthcare. This review aims to bring together purely technological and clinical aspects of interest in the field of glucose devices by proposing a roadmap in glucose monitoring and management of patients with diabetes. Also, it prospects other biological fluids to be examined as further options in diabetes care, and suggests, throughout the technology innovation process, future directions to improve the follow-up, treatment, and clinical outcomes of patients.

Is the level of serum lactate dehydrogenase a potential biomarker for glucose monitoring with type 2 diabetes mellitus?

INTRODUCTION

Type 2 diabetes mellitus (T2DM) is a metabolic disorder due to defects in insulin secretion or insulin resistance leading to the dysfunction and damage of various organs. To improve the clinical evaluation of short-term blood glycemic variability monitoring, it is critical to identify another blood cell status and nutritional status biomarker that is less susceptible to interference. This study identifies the significance of serum lactate dehydrogenase (LDH) level among T2DM patients treated in outpatient clinics and investigates the relationship of LDH level with other variables.

METHODS

This study comprised 72 outpatients with T2DM over 20 years of age. Blood samples were collected followed by a hematological analysis of serum glycated albumin (GA), LDH, fasting blood glucose, glycosylated hemoglobin, C-peptide, and insulin antibodies (insulin Ab).

RESULTS

Serum LDH level was significantly correlated with GA (p < 0.001), C-peptide (p = 0.04), insulin Ab (p = 0.03), and thyroid-stimulating hormone (TSH) levels (p = 0.04). Hence, we performed a linear regression analysis of hematological markers. GA (p < 0.001, r² = 0.45) and insulin Ab (p < 0.001, r² = 0.40) were significantly associated with LDH level. Then, we classified patients into low (<200 U/L) and high (≥200 U/L) serum LDH level groups, respectively. GA (p < 0.001), C-peptide (p = 0.001), and TSH (p = 0.03) showed significant differences in patients with high LDH levels compared with those in patients with low LDH levels.

CONCLUSION

In conclusion, we suggested that LDH level was independent of long-term but associated with short-term blood glucose monitoring. The results indicated that changes in serum GA induced cell damage and the abnormal elevation of the serum level of LDH may occur simultaneously with glycemic variability. It has been reported that many biomarkers are being used to observe glucose variability in T2DM. However, LDH could provide a more convenient and faster evaluation of glycemic variability in T2DM.

Glycaemic management in diabetes: old and new approaches

HbA_1c is the most used parameter to assess glycaemic control. However, evidence suggests that the concept of hyperglycaemia has profoundly changed and that different facets of hyperglycaemia must be considered. A modern approach to glycaemic control should focus not only on reaching and maintaining optimal HbA_1c concentrations as early as possible, but to also do so by reducing postprandial hyperglycaemia, glycaemic variability, and to extend as much as possible the time in range in near-normoglycaemia. These goals should be achieved while avoiding hypoglycaemia, which, should it occur, should be reverted to normoglycaemia. Modern technology, such as intermittently scanned glucose monitoring and continuous glucose monitoring, together with new drug therapies (eg, ultra-fast insulins, SGLT2 inhibitors, and GLP-1 receptor agonists), could help to change the landscape of glycaemia management based on HbA_1c in favour of a more holistic approach that considers all the different aspects of this commonly oversimplified pathophysiological feature of diabetes.