A Single-group, Clinical Interventional Study on the Effect of Iron Deficiency Anemia on Blood Glucose and Insulin Resistance in Women with Type II Diabetes.

AIMS: Iron deficiency anemia (IDA) is one of the disorders recently associated with an increase in insulin resistance (IR) and, consequently, diabetes mellitus (DM) affection by causing oxidative stress. In this study, we look at how IDA may contribute to developing type II diabetes mellitus (T2DM), controlling diabetes, and reducing IR in women with T2DM. METHODS: In this single group, clinical interventional study, we enrolled 40 women with T2DM and IDA. Before and after intervention with ferrous sulfate tablets, their blood glucose (BG) levels and IR levels were evaluated. This study was approved by the Ethics Committee of Qom University of Medical Sciences (ethics code: IR.MUQ.REC.1397.031) and registered at the Iranian Center for Clinical Trials (No. IRCT20170215032587N3). A significant level was considered p <0.05. RESULT: The mean age of patients was 48.18 ± 4.6 years, with 5.3-5.8 years duration of T2DM. After the intervention, the mean fasting blood glucose (FBG) level reached 198.53 ± 48.11 to 170.93 ± 37.41, which was significant (p <0.0001). Also, hemoglobin A1C level reached from 8.49 ± 0.9 to 7.96 ± 0.58, which was significant (p <0.0001). Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) demonstrating a significant reduction of IR levels after intervention with ferrous sulfate tablets (p <0.018). CONCLUSIONS: IDA treatment in patients with T2DM can significantly reduce the BG and IR levels. To better control BG, checking iron status and its correction may provide better clinical outcomes in these patients. CLINICAL TRIAL REGISTRATION NUMBER: IRCT20170215032587N3.

Hemoglobin A1c levels and 1-year mortality in patients with ST-elevation myocardial infarction undergoing percutaneous coronary intervention.

Background: In this study, we investigated whether different levels of hemoglobin A1c (HbA1c) are associated with different short-term and 1-year mortality rates among diabetic patients undergoing percutaneous coronary intervention. Patients & methods: Clinical events including in-hospital, 1-month and 1-year mortality were compared between three groups based on HbA1c levels of patients (I: ≤5.6%, II: 5.7-6.4%, III: ≥6.5%). Results: Among 165 diabetic individuals, patients with abnormal HbA1c levels (≥6.5%) experienced significantly higher hospitalization days (7.65 ± 1.64 days) compared with those with normal HbA1c (4.94 ± 0.97 days) (p < 0.0001). In-hospital mortality was significantly higher in group III (14.5%) and II (5.5%) compared with group I (0%) (p = 0.008). Conclusion: HbA1c levels may be a reliable predictor of short-term clinical events in diabetic patients.

Utilizing the Glucose and Insulin Response Shape of an Oral Glucose Tolerance Test to Predict Dysglycemia in Children with Overweight and Obesity, Ages 8-18 Years.

Common dysglycemia measurements including fasting plasma glucose (FPG), oral glucose tolerance test (OGTT)-derived 2 h plasma glucose, and hemoglobin A1c (HbA1c) have limitations for children. Dynamic OGTT glucose and insulin responses may better reflect underlying physiology. This analysis assessed glucose and insulin curve shapes utilizing classifications-biphasic, monophasic, or monotonically increasing-and functional principal components (FPCs) to predict future dysglycemia. The prospective cohort included 671 participants with no previous diabetes diagnosis (BMI percentile ≥ 85th, 8-18 years old); 193 returned for follow-up (median 14.5 months). Blood was collected every 30 min during the 2 h OGTT. Functional data analysis was performed on curves summarizing glucose and insulin responses. FPCs described variation in curve height (FPC1), time of peak (FPC2), and oscillation (FPC3). At baseline, both glucose and insulin FPC1 were significantly correlated with BMI percentile (Spearman correlation r = 0.22 and 0.48), triglycerides (r = 0.30 and 0.39), and HbA1c (r = 0.25 and 0.17). In longitudinal logistic regression analyses, glucose and insulin FPCs predicted future dysglycemia (AUC = 0.80) better than shape classifications (AUC = 0.69), HbA1c (AUC = 0.72), or FPG (AUC = 0.50). Further research should evaluate the utility of FPCs to predict metabolic diseases.

Semaglutide Effects on Metabolic Outcomes in Diabetes Mellitus Patients - Real World Study.

Purpose: Diabetes is a public health problem that requires strategies to impact glycemic control and reduce the risk of long-term medical complications. Pharmacological management is a necessary treatment for this disease. Therefore, semaglutide is an essential tool to achieve the treatment targets. The present study aimed to evaluate the semaglutide effects on a cohort with type 2 diabetes mellitus (T2DM) in Colombia. Materials and Methods: The cohort included 49 patients with T2DM that have been treated in a specialized care center. Their glycemic outcomes, weight, renal function, and adverse events were evaluated through a 3-, 6- and 12-month follow-up. Results: Significant differences were observed in the outcome evaluation: reduction of glycated hemoglobin levels (MD -2.74 CI -1.95 to -3.52 in 6 months), fasting plasma glucose levels, body weight (MD -7.11 CI -5.97 to -8.24), and the albumin-to-creatinine ratio. The results were maintained throughout the treatment period. The adverse event rate was 16.3%, predominating gastrointestinal events. Conclusion: This real-world evidence shows the efficacy of semaglutide in achieving treatment goals in patients with T2DM.

Association Between Hemoglobin A1c and Development of Cardiovascular Disease in Canadian Men and Women Without Diabetes at Baseline: A Population-Based Study of 608 474 Adults.

BACKGROUND: We examined the association between hemoglobin A1c (HbA1c) and the development of cardiovascular disease (CVD) in men and women, without diabetes or CVD at baseline. METHODS AND RESULTS: This retrospective cohort study included adults aged 40 to <80 years in Alberta, Canada. Men and women were divided into categories based on a random HbA1c during a 3-year enrollment period. The primary outcome of CVD hospitalization and secondary outcome of combined CVD hospitalization/mortality were examined during a 5-year follow-up period until March 31, 2021. A total of 608 474 individuals (55.2% women) were included. Compared with HbA1c 5.0% to 5.4%, men with HbA1c of 5.5% to 5.9% had an increased risk of CVD hospitalization (adjusted hazard ratio [aHR], 1.12 [95% CI, 1.07-1.19]) whereas women did not (aHR, 1.01 [95% CI, 0.95-1.08]). Men and women with HbA1c of 6.0% to 6.4% had a 38% and 17% higher risk and men and women with HbA1c ≥6.5% had a 79% and 51% higher risk of CVD hospitalization, respectively. In addition, HbA1c of 6.0% to 6.4% and HbA1c ≥6.5% were associated with a higher risk (14% and 41%, respectively) of CVD hospitalization/death in men, but HbA1c ≥6.5% was associated with a 24% higher risk only among women. CONCLUSIONS: In both men and women, HbA1c ≥6.0% was associated with an increased risk of CVD and mortality outcomes. The association between CVD and HbA1c levels of 5.5% to 5.9%, considered to be in the "normal" range, highlights the importance of optimizing cardiovascular risk profiles at all levels of glycemia, especially in men.

Effect of non-surgical periodontal therapy on hemoglobin A1c in periodontitis patients without diabetes mellitus: A systematic review and meta-analysis.

OBJECTIVES: This systematic review was aimed to evaluate the effect of non-surgical periodontal therapy (NSPT) on hemoglobin A1c (HbA1c) in periodontitis patients without diabetes mellitus (DM). DATA/SOURCES: The present systematic review and meta-analysis were performed through searching the following electronic databases: EMBASE, MEDLINE, Web of Science, Cochrane Library and Open GREY. Interventional studies of periodontitis patients without DM were investigated. HbA1c changes in these patients before and after NSPT were analyzed. Subgroup analysis and sensitivity analysis were employed to identify sources of heterogeneity. STUDY SELECTION: Three reviewers independently selected the eligible studies by screening the titles and abstract. Then, a full-text analysis was performed. The reasons for excluding studies were recorded. Any disagreements were settled by discussion with a fourth reviewer. All the four reviewers extracted and crosschecked the data, and disagreements were resolved by discussion. There are 21 case-series studies (self-controlled studies) and 1 non-randomized interventional studies (NRIs) were included. RESULTS: For periodontitis patients without DM, a total of 469 individuals from 22 studies were enrolled. The pooled analysis demonstrated that it was significantly changed in HbA1c levels at 3-month follow-up (0.16 with 95% CI 0.04, 0.27; P=0.008), and 6-month follow-up (0.17% with 95% CI 0.08, 0.27; P<0.001) compared with baseline. Smoking, gender, experience of periodontal therapy and HbA1c value at baseline could be the sources of heterogeneity. CONCLUSIONS: NSPT is potentially beneficial for the management of HbA1c in periodontitis patients with high risks of DM. However, high-quality randomized controlled trials are still necessary to confirm these conclusions. CLINICAL SIGNIFICANCE: The systemic review evaluated the effect of NSPT on HbA1c in periodontitis patients without DM. The analysis may be beneficial to the management and control of the high risks of DM in periodontitis patients.

Association between variation in hemoglobin A1c levels and diabetes therapy-related quality of life in patients with diabetes.

AIMS/INTRODUCTION: We aimed to investigate the association between glycemic variability and quality of life (QOL) in patients with diabetes, which has not been studied previously. MATERIALS AND METHODS: Patients who were undergoing treatment at the Kyoto Prefectural University of Medicine Hospital and Kameoka City Hospital participated in the KAMOGAWA-DM study, and completed the diabetes therapy-related (DTR)-QOL questionnaire from January 2016 to July 2020 were included in this study. We used linear regression analyses to compare the association between DTR-QOL scores and glycemic variability. RESULTS: We included a total of 635 patients in this analysis. The hemoglobin A1c (HbA1c) levels of these patients were measured at least four times during the 9-month period, before and after answering the questionnaire. Results showed that HbA1c variability, HbA1c mean and duration of diabetes were negatively associated with the total DTR-QOL score. Conversely, the body mass index and total DTR-QOL score were positively associated with HbA1c variability. CONCLUSIONS: A small variation in HbA1c level was associated with higher total DTR-QOL scores and the scores for each factor. Reducing blood glucose variability is significant when we treat diabetes.

Progression from Prediabetes to Diabetes in a Diverse U.S. Population: A Machine Learning Model.

Objective: To date, there are no widely implemented machine learning (ML) models that predict progression from prediabetes to diabetes. Addressing this knowledge gap would aid in identifying at-risk patients within this heterogeneous population who may benefit from targeted treatment and management in order to preserve glucose metabolism and prevent adverse outcomes. The objective of this study was to utilize readily available laboratory data to train and test the performance of ML-based predictive risk models for progression from prediabetes to diabetes. Methods: The study population was composed of laboratory information services data procured from a large U.S. outpatient laboratory network. The retrospective dataset was composed of 15,029 adults over a 5-year period with initial hemoglobin A1C (A1C) values between 5.0% and 6.4%. ML models were developed using random forest survival methods. The ground truth outcome was progression to A1C values indicative of diabetes (i.e., ≥6.5%) within 5 years. Results: The prediabetes risk classifier model accurately predicted A1C ≥6.5% within 5 years and achieved an area under the receiver-operator characteristic curve of 0.87. The most important predictors of progression from prediabetes to diabetes were initial A1C, initial serum glucose, A1C slope, serum glucose slope, initial HDL, HDL slope, age, and sex. Conclusions: Leveraging readily obtainable laboratory data, our ML risk classifier accurately predicts elevation in A1C associated with progression from prediabetes to diabetes. Although prospective studies are warranted, the results support the clinical utility of the model to improve timely recognition, risk stratification, and optimal management for patients with prediabetes.

Impact of a diabetes-designed meal delivery service on changes in hemoglobin A1c and quality of life in patients with diabetes.

BACKGROUND: Over 34 million Americans have diabetes, and nutrition therapy is essential in self-management. AIMS: The primary aim of the study was to evaluate the impact of meals designed for patients with type 2 diabetes (T2D) through a meal delivery program. The primary outcome was a 3-month change in hemoglobin A1c (HbA1c). Secondary outcomes included a 3-month change in weight, blood pressure, high-density lipoprotein, low-density lipoprotein, and triglycerides. Furthermore, the study aimed to evaluate the impact of the meal delivery program on the participants' quality of life. METHODS: In this randomized crossover clinical trial, patients were allocated in a 1:1 fashion to treatment sequence AB or treatment sequence BA. In Phase 1, participants allocated to sequence AB received 10 meals per week for 3 months, followed by a 3-month washout period and a 3-month standard intervention period with no meals. Participants allocated to sequence BA received 3 months of standard intervention with no meals followed by a 3-month washout period and a 3-month period with 10 meals per week. A quality-of-life survey was obtained during weeks 0, 12, 24, and 36. RESULTS: The mean 3-month change in HbA1c (primary outcome) was nearly a half point lower with meal delivery (-0.44% [95% CI: -0.85%, -0.03%]; P = 0.037). The estimated mean 3-month change in quality of life was approximately 2 points lower (better) with meal delivery (-2.2 points [95% CI: -4.2, -0.3]; P = .027). There were no statistically significant differences in secondary outcomes with meal delivery (all P ≥ 0.15). CONCLUSIONS: A meal delivery system for patients with T2D improves glycemic control and quality of life.

Correlation between time in range and serum uric acid in Chinese patients with type-2 diabetes: an observational cross-sectional study.

BACKGROUND: At present, the relationship between serum uric acid and blood glucose is controversial, and even opposite conclusions have been reached. We aimed to investigate the relationship between time in range and serum uric acid and estimate the influence of serum uric acid on blood glucose fluctuations in Chinese patients with type-2 diabetes mellitus (T2DM). METHODS: A total of 458 hospitalized patients with T2DM were selected. According to the SUA level, patients were divided into four groups by quartile: Q1 (≤ 254.5 µmol/L), Q2 (254.5-306.0 µmol/L), Q3 (306.0-385.5 µmol/L) and Q4 (> 385.5 µmol/L). The differences in general data, TIR and other clinical indicators between the four groups were assessed. Multifactor regression was used to analyze the relationship between subgroups of SUA and TIR, TBR, TAR, MAGE, SD, ADRR, MODD and M value. Curve fitting was used to analyze the association between TIR and SUA and to identify the inflection point. RESULTS: TIR showed an overall increasing trend with increasing SUA, while HbA1c, TAR, MAGE, SD, ADRR, MODD and M value showed an overall decreasing trend with increasing SUA. Multivariate regression analysis showed that, compared with Q1, there was no correlation between SUA and TIR, TAR, ADRR, SD, or MODD in all models of Q2. In the Q3 and Q4 groups, SUA was correlated with SD, MODD, and MAGE in all models. In the Q4 group, SUA was correlated with TIR, TAR, ADRR, and the M value in all models. When SUA > 306 µmol/L (Q3 and Q4), TIR and SUA have a curve-like relationship, and the inflection point of the fitted curve was SUA = 460 mmol/L. Before the inflection point, ß was 0.1, indicating that when SUA increases by 10 mmol/L, the corresponding TIR increases by 1%. After the inflection point, there was no significant difference in the correlation between TIR and SUA (P > 0.05). CONCLUSIONS: There is a close relationship between TIR and SUA in T2DM patients, it is speculated that SUA in a certain range had a positive protective effect on blood glucose control.

Two patients with α-chain hemoglobin variant Hb Q-Iran detected by measuring hemoglobin A1c using the variant mode of the HA-8180V HPLC analyzer.

Hemoglobin variants are often discovered when hemoglobin A1c (HbA1c) levels measured with a high-performance liquid chromatography (HPLC) system in fast mode are found to be low. The HA-8180V HPLC analyzer by Arkray offers two measurement modes: fast mode (FM) and variant mode (VM). Two Japanese patients with α-chain variant Hb Q-Iran detected incidentally after analyses with the HA-8180V in VM showed an abnormal peak, are presented. The first patient was a man in his 70 s, and the second patient was a man in his 50 s. Both were non-diabetic, but their results from HbA1c measurement in VM showed an abnormal peak. The VM-HbA1c, FM-HbA1c, and HbA1c measured by enzymatic assay and glycated albumin levels of the two patients were all within the reference ranges. They were diagnosed as having Hb Q-Iran (α2-75Asp → His) by globin gene analysis. It is difficult to detect α-chain hemoglobin variants based on abnormal FM-HbA1c levels, but measuring HbA1c in VM is useful for efficiently detecting hemoglobin variants.

Association between DNA methylation levels of thioredoxin-interacting protein (TXNIP) and changes in glycemic traits: a longitudinal population-based study.

Thioredoxin-interacting protein (TXNIP) plays an important role in glucose metabolism, and its expression is regulated by DNA methylation (DNAm). Although the association between TXNIP DNAm and type 2 diabetes mellitus has been demonstrated in studies with a cross-sectional design, prospective studies are needed. We therefore examined the association between TXNIP DNAm levels and longitudinal changes in glycemic traits by conducting a longitudinal study involving 169 subjects who underwent two health checkups in 2015 and 2019. We used a pyrosequencing assay to determine TXNIP DNAm levels in leukocytes (cg19693031). Logistic regression analyses were performed to assess the associations between dichotomized TXNIP DNAm levels and marked increases in glycemic traits. At four years, the TXNIP DNA hypomethylation group had a higher percentage of changes in fasting plasma glucose (FPG) and hemoglobin A1c (HbA1c) compared to those in the hypermethylation group. The adjusted odds ratios for FPG and HbA1c levels were significantly higher in the TXNIP DNA hypomethylation group than in the hypermethylation group. We found that TXNIP DNA hypomethylation at baseline was associated with a marked increase in glycemic traits. Leukocyte TXNIP DNAm status could potentially be used as an early biomarker for impaired glucose homeostasis.

Prognostic significance of serum cystatin C in acute brainstem infarctions patients.

OBJECTIVES: Some studies show that high circulating cystatin C (CysC) may predict cardiovascular events and death after ischemic stroke onset. However, the association between serum CysC and outcome in ischemic stroke patients remains contradictory. We sought to assess the association between a specific stroke subgroup, brainstem infarction (BSI) and serum CysC. MATERIALS AND METHODS: A total of 324 acute BSI patients were included in the study. Serum CysC was used to calculate estimated glomerular filtration rate (eGFRCysC) at baseline. Modified Rankin scale score ((mRS) ≥3) six months after acute BSI indicates poor functional outcome. Patients were categorized into two groups according to mRS and eGFRCysC. Logistic regression analyses were performed to determine independent risk factors. RESULTS: Lower eGFRCysC was associated with hemoglobin A1c (HbA1c). This risk remained statistically significant after controlling for age, hypertension, initial National Institutes of Health Stroke Scale (NIHSS) score, HbA1c, fibrinogen and homocysteine. The serum eGFRCysC levels were significantly lower in the poor functional outcome group than the good functional outcome group (P<0.001). Multivariate logistic regression analyses showed that eGFRCysC level was significantly lower in the poor outcome group after adjusting for age, previous infarctions, initial NIHSS score, and HbA1c. CONCLUSIONS: Lower eGFRCysC levels were strongly associated with poor functional outcome of acute BSI patients with a higher HbA1c level. Lower eGFRCysC may be a more helpful serologic biomarker for the prediction of prognosis in BSI.

Can artificial intelligence detect type 2 diabetes in women by evaluating the pectoral muscle on tomosynthesis: diagnostic study.

OBJECTIVES: This retrospective single-center analysis aimed to evaluate whether artificial intelligence can detect type 2 diabetes mellitus by evaluating the pectoral muscle on digital breast tomosynthesis (DBT). MATERIAL METHOD: An analysis of 11,594 DBT images of 287 consecutive female patients (mean age 60, range 40-77 years) was conducted using convolutional neural networks (EfficientNetB5). The inclusion criterion was left-sided screening images with unsuspicious interpretation who also had a current glycosylated hemoglobin A1c (HBA1c) % value. The exclusion criteria were inadequate imaging, history of breast cancer, and/or diabetes mellitus. HbA1c values between 5.6 and 6.4% were categorized as prediabetic, and those with values ≥ 6.5% were categorized as diabetic. A recorded HbA1c ≤ 5.5% served as the control group. Each group was divided into 3 subgroups according to age. Images were subjected to pattern analysis parameters then cropped and resized in a format to contain only pectoral muscle. The dataset was split into 85% for training and 15% for testing the model's performance. The accuracy rate and F1-score were selected as performance indicators. RESULTS: The training process was concluded in the 15th epoch, each comprising 1000 steps, with an accuracy rate of 92% and a loss of only 0.22. The average specificity and sensitivity for all 3 groups were 95%. The F1-score was 0.95. AUC-ROC was 0.995. PPV was 94%, and NPV was 98%. CONCLUSION: Our study presented a pioneering approach, applying deep learning for the detection of diabetes mellitus status in women using pectoral muscle images and was found to function with an accuracy rate of 92%. CRITICAL RELEVANCE STATEMENT: AI can differentiate pathological changes within pectoral muscle tissue by assessing radiological images and maybe a potential diagnostic tool for detecting diabetes mellitus and other diseases that affect muscle tissues. KEY POINTS: • AI may have an opportunistic use as a screening exam for diabetes during digital breast tomosynthesis. • This technique allows for early and non-invasive detection of diabetes mellitus by AI. • AI may have broad applications in detecting pathological changes within muscle tissue.

Risk factors for suboptimal glycemic control in pediatrics with type 1 diabetes mellitus: a cross-sectional study.

The objective of this research is to analyze the influence of various factors on glycemic control in pediatrics with type 1 diabetes mellitus (T1DM). The study, a cross-sectional analysis, involved 221 T1DM patients below 18 years old who visited our clinic between 2011 and 2020, predating the COVID-19 outbreak. Out of the initial pool, 204 participants were chosen based on specific criteria. By computing odds ratios and 95% confidence intervals, we determined the correlation between these factors and achieving optimal glycemic control (HbA1c < 7.5%). Of the 204 individuals, 55.9% (113 patients) were female. The average age at diagnosis was 6.93 ± 3.9 years. Mean HbA1c (A1C) level of optimal and suboptimal groups were 6.97, 95% CI 6.84 to 7.1 and 8.86, 95% CI 8.68 to 9.03, respectively (p-value < 0.001). Fifty patients had optimal glycemic control and 154 people experienced suboptimal glycemic control during the follow-up that the prevalence of each of them was 24.51, 95% CI 18.7 to 31 and 75.49, 95% CI 68.99 to 81.22, respectively. In the assessment of risk factors associated with suboptimal glycemic control, patients aged 10-14 years had the highest likelihood of experiencing suboptimal glycemic control (crude odds ratio [COR] 3.12, 95% CI 1.04 to 9.3), followed by duration of diabetes (COR 2.85, 95% CI 1.2 to 6.8), which both were significant. By utilizing multivariable logistic regression analysis, a noteworthy finding emerged. It was revealed that patients aged 10-14 years exhibited a significant association with suboptimal glycemic control, [adjusted odds ratio (AOR) 4.85, 95% CI 1.32 to 17.7]. Additionally, a statistically significant correlation was identified between individuals with a body mass index (BMI) falling within the ≥ 95th percentile category and suboptimal glycemic control, Cramer's V = 0.21, p-value = 0.01. Our research has revealed a significant correlation between patients aged 10-14 years and obese individuals (BMI ≥ 95th) with suboptimal glycemic control. It is crucial to consider these factors as they can offer valuable insights during diagnosis, highlighting the increased risk of long-term suboptimal glycemic control.

Assessment of Hemoglobin A1c Management and Prescription Cost Due to Polypharmacy Among Patients With Diabetes in Iran Based on the STEPS Iran 2016 Survey and a Prescription Database: A Multi-level, Cross-sectional National Study.

BACKGROUND: Diabetes frequently results in the need for multiple medication therapies, known as 'Polypharmacy'. This situation can incur significant costs and increase the likelihood of medication errors. This study evaluated the prescriptions of patients with diabetes regarding polypharmacy to assess its effect on the control of hemoglobin A1c (HbA1c) levels and prescription costs. METHODS: A cross-sectional national study was conducted based on data from linking the Iranians Health Insurance Service prescriptions in 2015 and 2016 with the STEPS 2016 survey in Iran. The association of the individual and sociodemographic factors, as well as polypharmacy, as independent variables, with control of HbA1c levels and the cost of the prescriptions were assessed among diabetic patients using logistic and linear regression, respectively. RESULTS: Among 205 patients using anti-diabetic medications, 47.8% experienced polypharmacy. The HbA1c of 74 patients (36.1%) was equal to or less than 7, indicating controlled diabetes. HbA1c control showed no significant association with gender. However, prescription costs were notably lower in females (ß=0.559 [0.324‒0.964], P=0.036). No significant correlation was found between the area of residence and prescription costs, but HbA1c was significantly more controlled in urban areas (OR=2.667 [1.132‒6.282], P=0.025). Prescription costs were significantly lower in patients without polypharmacy (ß=0.211, [0.106‒0.423], P<0.001), though there was no significant association between polypharmacy and HbA1c levels. CONCLUSION: Our results demonstrated that diabetics with polypharmacy paid significantly more for their prescriptions without experiencing a positive effect on the control of HbA1c levels.

Association between Hemoglobin A1c and Renal Arteriolar Sclerosis in Subjects Presenting without any Apparent Kidney Dysfunction.

AIMS: Diabetic kidney disease is a major vascular complication in patients with diabetes mellitus (DM). However, the association between the hemoglobin (Hb)A1c levels, notably the prediabetic levels, and renal pathological changes remains unclear. We investigated the association between the HbA1c levels and renal arteriolar lesions in subjects without any apparent kidney dysfunction using a living kidney donor cohort. METHODS: Between January 2006 and May 2016, 393 living kidney donors underwent a "zero-time" biopsy at Kyushu University Hospital. The patients were divided into four groups (HbA1c levels ＜5.6%, 5.6%-5.7%, 5.8%-6.4%, and ≥ 6.5%, or diagnosed with DM [DM group]). Renal arteriolar hyalinization and wall thickening were assessed using semi-quantitative grading. We then investigated the association between the HbA1c levels and renal pathological changes. RESULTS: 158 (40.2%) patients had arteriolar hyalinization and 148 (37.6%) showed wall thickening. A significant correlation was observed between the HbA1c levels and wall thickening (p for trend ＜0.001). An elevated HbA1c level was significantly associated with wall thickening according to a multivariable logistic analysis in subjects with HbA1c levels of 5.6%-5.7% and 5.8%-6.4%, and the DM group, compared with those with HbA1c levels of ＜5.6% (odds ratio [OR], 1.91; 95% confidence interval [CI]: [1.03-3.54] for 5.6%-5.7%, OR, 1.96; 95% CI: [1.09-3.53] for 5.8%-6.4%, and OR, 2.86; 95% CI: [0.91-9.01] for the DM group), whereas arteriolar hyalinization did not increase within the nondiabetic HbA1c levels. CONCLUSIONS: Elevated high-normal HbA1c levels are considered to be independent risk factors for arteriolar wall thickening. Subclinical renal arteriolar sclerosis may develop in patients with prediabetic HbA1c levels.

Advanced Glycation Endproducts: A Marker of Long-term Exposure to Glycemia.

This article examines the importance of advanced glycation endproducts (AGEs) and summarizes the structure of AGEs, pathological changes associated with AGEs, the contribution of AGEs to metabolic memory, and the value of AGEs as a predictor of diabetic complications and cardiovascular disease in people with and without diabetes. As a practical focus, skin autofluorescence (SAF) is examined as an attractive approach for estimating AGE burden. The measurement of AGEs may be of significant value to specific individuals and groups, including Black and Hispanic/Latino Americans, as they appear to have higher concentrations of hemoglobin A1c (HbA1c) than would be predicted by other metrics of mean glycemia. We hypothesize that if the amount of glycation of HbA1c is greater than expected from measured glucose levels, and if AGEs are accumulating, then this accumulation of AGEs might account for the increased rate of complications of diabetes in populations with high rates of vascular disease and other complications. Thus, identifying and modifying the burden of AGEs based on measurement of AGEs by SAF may turn out to be a worthwhile metric to determine individuals who are at high risk for the complications of diabetes as well as others without diabetes at risk of vascular disease. We conclude that available evidence supports SAF as both a clinical measurement and as a means of evaluating interventions aimed at reducing the risks of vascular disease and diabetic complications.

Intermittently Scanned Continuous Glucose Monitoring Performance in Patients With Liver Cirrhosis.

AIM: To evaluate the use of intermittently scanned continuous glucose monitoring (isCGM) in patients with liver cirrhosis (LC). METHODS: Observational study including 30 outpatients with LC (Child-Pugh B/C): 10 without diabetes (DM) (G1), 10 with newly diagnosed DM by oral glucose tolerance test (G2), and 10 with a previous DM diagnosis (G3). isCGM (FreeStyle Libre Pro) was used for 56 days (four sensors/patient). Blood tests were performed at baseline and after 28 and 56 days. RESULTS: No differences were found in the baseline characteristics, except for higher age in G3. There were significant differences between G1, G2 and G3 in glucose management indicator (GMI) (5.28 ± 0.17, 6.03 ± 0.59, 6.86 ± 1.08%, P < .001), HbA1c (4.82 ± 0.39, 5.34 ± 1.26, 6.97 ± 1.47%, P < .001), average glucose (82.79 ± 7.06, 113.39 ± 24.32, 149.14 ± 45.31mg/dL, P < .001), time in range (TIR) (70.89 ± 9.76, 80.2 ± 13.55, 57.96 ± 17.96%, P = .006), and glucose variability (26.1 ± 5.0, 28.21 ± 5.39, 35.31 ± 6.85%, P = .004). There was discordance between GMI and HbA1c when all groups were considered together, with a mean difference of 0.35% (95% SD 0.17, 0.63). In G1, the mean difference was 0.46% (95% SD 0.19, 0.73) and in G2 0.69% (95% SD 0.45, 1.33). GMI and HbA1c were concordant in G3, with a mean difference of -0.10 % (95% SD [-0.59, 0.38]). CONCLUSION: Disagreements were found between the GMI and HbA1c levels in patients with LC. isCGM was able to detect abnormalities in glycemic control that would not be detected by monitoring with HbA1c, suggesting that isCGM can be useful in assessing glycemic control in patients with LC.

Technical Note: Comparison of Alinity c Hemoglobin A1c Immunoassay with Premier Hb9210 Automated HPLC Assay: A Preliminary Report.

OBJECTIVE: We utilized Premier Hb9210 analyzer (HPLC method; Trinity Biotech, Jamestown, NY) for measuring HBA1c in whole blood. As our laboratory is transitioning to Abbott system, we compared HbA1c values obtained by Alinity c and Premier Hb9210. METHODS: The Premier Hb9210 analyzer is based on boronate affinity high performance liquid chromatography with analytical measurement range of 3.8 to 18.5%. The Alinity c Hemoglobin A1c assay measured both total hemoglobin and HbA1c (enzymatic assay) in whole blood and then calculated %HbA1c. The analytical measurement range of this assay is 4 to 14% of HbA1c. We evaluated the analytical performance of Alinity c HbA1c by evaluating precision and also comparing 77 clinical samples with our reference HPLC method. RESULTS: Both Alinity c HbA1c and Premier HB9210 have excellent total precision. Plotting HbA1c results obtained by the Premier Hb9210 analyzer in the x-axis (currently used reference method) and the corresponding values obtained by the Alinity c assay, we observed the following regression equation: y=0.9473x+0.1548 ( n=77, r=0.99). DISCUSSION: Our result indicates that HbA1c enzymatic assay on the Alinity c analyzer showed values comparable to HPLC method. However, at the decision points (2.8% average negative bias at >6.4% and 3.3% average negative bias at 7%), HbA1c values obtained by the Alinity c analyzer were lower than the reference method. CONCLUSIONS: We conclude that HbA1c assay on the Alinity c analyzer is a viable alternative to HPLC for measuring HbA1c in clinical laboratories but values at the decision points must be interpreted with caution and if necessary should be repeated by a reference HPLC method.