Japanese standard reference material JDS Lot 2 for haemoglobin A1c. II: Present state of standardization of haemoglobin A1c in Japan using the new reference material in routine clinical assays

Glycated albumin and hemoglobin A1c levels and cause-specific mortality by patients' conditions among hemodialysis patients with diabetes: a 3-year nationwide cohort study

INTRODUCTION

Differences in mortality and cause-specific mortality rates according to glycated albumin (GA) and hemoglobin A1c (HbA1c) levels among dialysis patients with diabetes based on hypoglycemic agent use and malnutrition status remain unclear. Here, we examine these associations using a nationwide cohort.

RESEARCH DESIGN AND METHODS

We examined 40 417 dialysis patients with diabetes who met our inclusion criteria (female, 30.8%; mean age, 67.3±11.2 years; mean dialysis duration, 5.4±4.6 years). The Global Leadership Initiative on Malnutrition criteria were used to assess malnutrition. Adjusted HRs and 95% confidence limits were calculated for 3-year mortality after adjustment for 18 potential confounders. HRs and subdistribution HRs were used to explore cause-specific mortality.

RESULTS

We found a linear association between 3-year mortality and GA levels only in patients with GA ≥18% and not in patients with low GA levels, with a U-shaped association between HbA1c levels and the lowest morality at an HbA1c 6.0%-6.3%. This association differed based on patient conditions and hypoglycemic agent use. If patients using hypoglycemic agents were malnourished, mortality was increased with GA ≥24% and HbA1c ≥8%. In addition, patients with GA ≥22% and HbA1c ≥7.6% had significantly higher infectious or cardiovascular mortality rates. On the other hand, an inverse association was found between GA or HbA1c levels and cancer mortality. Patients with GA ≤15.8% had a higher risk of cancer mortality, especially those not using hypoglycemic agents (HR 1.63 (1.00-2.66)).

CONCLUSIONS

Target GA and HbA1c levels in dialysis patients may differ according to hypoglycemic agent use, nutritional status, and the presence of cancer. The levels may be higher in malnourished patients than in other patients, and a very low GA level in dialysis patients not taking hypoglycemic agents may be associated with a risk of cancer.

TRIAL REGISTRATION NUMBER

UMIN000018641.

Glycated albumin versus hemoglobin A1c and mortality in diabetic hemodialysis patients: a cohort study

Background

For glycemic control in diabetic patients on dialysis it was unclear what level of glycated albumin (GA) was associated with the lowest mortality and GA's utility. Accordingly, we examined the difference in association between GA and hemoglobin A1c (HbA1c) with 1-year mortality in a cohort of the Japanese Society for Dialysis Therapy.

Methods

We examined 84 282 patients with prevalent diabetes who were on maintenance hemodialysis (HD) (female 30.3%; mean age 67.3 ± 11.2 years; mean dialysis vintage 6.4 ± 4.5 years). Of them, 22 441 had both GA and HbA1c. We followed these for a year, 2013-14, using Cox regression to calculate adjusted hazard ratios (HRs) and 95% confidence limits for 1-year mortality after adjusting for potential confounders such as baseline age, sex, smoking and diabetes type.

Results

One-year mortality was lowest in diabetic HD patients who had GA levels of 15.6-18.2% and HbA1c levels of 5.8-6.3%. The associations were linear or J-shaped for GA and U-shaped for HbA1c. Adjusted HRs were significantly higher in patients with GA <12.5% and GA ≥22.9%. This trend flattened in elderly patients, those with higher hemoglobin or those with prior cardiovascular disease. In addition, the C-statistics, Harrell's C and category-free net reclassification improvement to predict 1-year mortality were better when GA was added to the model than when HbA1c was added.

Conclusions

There was a linear or J-shaped association between GA and 1-year mortality, with the lowest mortality at GA 15.6-18.2%. Furthermore, our analyses suggest the potential superiority of GA over HbA1c in predicting mortality.

A Method for Deriving Quasi-healthy Cohorts From Clinical Data

We evaluated quasi-healthy cohorts (model cohorts), derived from clinical data, to determine how well they simulated control cohorts. Control cohorts comprised individuals extracted from a public checkup database in Japan, under the condition that their values for 3 basic laboratory tests fall within specific reference ranges (3Ts condition). Model cohorts comprised outpatients, extracted from a clinical database at a hospital, under the 3Ts condition or under the condition that their values for 4 laboratory tests fall within specific reference ranges (4Ts condition). Because even a patient with a serious illness, such as cancer, may present with normal values on basic laboratory tests, one additional condition was added: the duration (1 or 3 months; 1M or 3M) during which patients were not hospitalized after their first laboratory test. For evaluations, cohorts were specified by age and sex. The 4Ts + 3M condition was the most effective condition, under which model cohorts were used to successfully simulate age-dependent changes and sex differences in laboratory test values for control cohorts. Therefore, by properly setting the conditions for extracting quasi-healthy individuals, we can derive cohorts from clinical data to simulate various types of cohorts. Although some issues with the proposed method remain to be solved, this approach presents new possibilities for using clinical data for cohort studies.

Evaluation of glycated albumin (GA) and GA/HbA1c ratio for diagnosis of diabetes and glycemic control: A comprehensive review

Diabetes Mellitus (DM) is a group of metabolic diseases characterized by chronic high blood glucose concentrations (hyperglycemia). When it is left untreated or improperly managed, it can lead to acute complications including diabetic ketoacidosis and non-ketotic hyperosmolar coma. In addition, possible long-term complications include impotence, nerve damage, stroke, chronic kidney failure, cardiovascular disease, foot ulcers, and retinopathy. Historically, universal methods to measure glycemic control for the diagnosis of diabetes included fasting plasma glucose level (FPG), 2-h plasma glucose (2HP), and random plasma glucose. However, these measurements did not provide information about glycemic control over a long period of time. To address this problem, there has been a switch in the past decade to diagnosing diabetes and its severity through measurement of blood glycated proteins such as Hemoglobin A1c (HbA1c) and glycated albumin (GA). Diagnosis and evaluation of diabetes using glycated proteins has many advantages including high accuracy of glycemic control over a period of time. Currently, common laboratory methods used to measure glycated proteins are high-performance liquid chromatography (HPLC), immunoassay, and electrophoresis. HbA1c is one of the most important diagnostic factors for diabetes. However, some reports indicate that HbA1c is not a suitable marker to determine glycemic control in all diabetic patients. GA, which is not influenced by changes in the lifespan of erythrocytes, is thought to be a good alternative indicator of glycemic control in diabetic patients. Here, we review the literature that has investigated the suitability of HbA1c, GA and GA:HbA1c as indicators of long-term glycemic control and demonstrate the importance of selecting the appropriate glycated protein based on the patient's health status in order to provide useful and modern point-of-care monitoring and treatment.

Distinct glucose-lowering properties in good responders treated with sitagliptin and alogliptin

BACKGROUND AND OBJECTIVES

All dipeptidyl peptidase 4 (DPP-4) inhibitors display similar glycemic efficacies, although they differ greatly in their chemical structures and pharmacological properties. This may be due to the inclusions of non- or poor-responders in the analysis, thereby masking the real effects of these drugs. The aim of this study was to identify any differences in diabetic parameters only in good responders treated with sitagliptin and alogliptin.

METHODS

Treatment naïve subjects with type 2 diabetes mellitus were assigned to either sitagliptin 25-50 mg/day (n = 69) or alogliptin 12.5-25 mg/day monotherapy (n = 62) for 3 months. Only those who showed good response selected by a novel parameter called A1c index were further analysed (n = 24 for sitagliptin and n = 21 for alogliptin).

RESULTS

At baseline, FBG and BMI were significantly higher and CPR-index was significantly lower in alogliptin good responders. At 3 months, while similar reductions of HbA1c were observed in these two groups, decreases of fasting blood glucose (FBG) were significantly higher in alogliptin good responders. Homeostasis model assessment (HOMA)-R significantly decreased only in alogliptin good responders, while HOMA-B similarly and significantly increased in these two groups. BMI significantly increased only in sitagliptin good responders. Significant negative correlations were observed between A1c index and changes (Δ) of HOMA-B in both groups. By contrast, significant positive and negative correlations were observed between ΔFBG and ΔHOMA-R, and between ΔFBG and ΔHOMA-B, respectively, only in alogliptin good responders.

CONCLUSIONS

These results implicate that the effects on diabetic parameters and the glucose-lowering mechanisms of these two drugs might be different in those who have good response with these drugs. Accordingly, the choice of these drugs may be dependent on the characteristics of the patients.

Alogliptin: a new dipeptidyl peptidase-4 inhibitor with potential anti-atherogenic properties

OBJECTIVES

The aim of this study is to evaluate the effects of alogliptin on metabolic profiles in relation to those of glycemic control.

PATIENTS AND METHODS

Treatment naïve subjects with type 2 diabetes received 12.5-25 mg/d alogliptin monotherapy (n = 59). A novel parameter called A1c index was used to assess the glycemic efficacy. The subjects were divided into three groups according to this index; super-responders, average responders and poor-responders. At 3 months, levels of the metabolic parameters were compared with those at baseline between super-responders (n = 20) and poor-responders (n = 21).

RESULTS

At baseline, total cholesterol, non-high density lipoprotein cholesterol and atherogenic index were significantly higher in super-responders than poor-responders. At 3 months, significant increases of beta-cell function (HOMA-B) and decreases of insulin resistance (HOMA-R) or these atherogenic lipids were observed in super-responders, while significant increases of HOMA-R were observed in poor-responders. Significant correlations were observed between A1c index and the changes of these atherogenic lipids. In super-responders, significant correlations were observed between the changes (Δ) of glycemic parameters (A1c index or fasting blood sugar) and ΔHOMA-R and/or ΔHOMA-B, while in poor-responders, significant correlations were observed between ΔHOMA-R and ΔHOMA-B. Lean subjects gained weight and the changes of body mass index had significant negative correlations with A1c index.

CONCLUSIONS

These results indicate that (1) glucose lowering efficacy of alogliptin is closely linked to atherogenic lipids. (2) alogliptin can down-regulate atherogenic lipids. (3) glycemic efficacy of alogliptin appears to be determined by the balance of its capacity in modulating insulin resistance and beta-cell function.

Replacement of neutral protamine Hagedorn insulin with the long-acting insulin analogue, detemir, improves glycemic control without weight gain in basal-bolus insulin therapy in Japanese patients with type 1 diabetes

Aims/Introduction:  The aim of the present study was to evaluate the efficacy of replacing neutral protamine Hagedorn insulin (NPH) with the long‐acting insulin analogue, detemir, in clinical practice.

Materials and Methods:  We carried out a retrospective study to compare the effects of replacing NPH with detemir in basal–bolus insulin therapy in Japanese patients with type 1 diabetes. A total of 19 patients were enrolled in the study, and changes in hemoglobin A_1c (HbA_1c), insulin dose, bodyweight, fasting blood glucose levels (FBG), within‐patient variability in FBG and prevalence in hypoglycemia were monitored for 12 weeks before replacement and during three periods after replacement; 1–12 weeks (period 1), 13–24 weeks (period 2) and 25–36 weeks (period 3).

Results:  HbA_1c values improved significantly in periods 2 and 3. Despite the total insulin dose remaining unchanged throughout the study, the basal insulin dose increased from 0.24 to 0.27 IU/kg/day in period 2 and 0.28 IU/kg/day in period 3. Bodyweight decreased from 61.8 to 60.8 kg in period 1, whereas FBG improved throughout the study. Within‐patient variability in FBG was lower with detemir treatment than with NPH, despite the number of hypoglycemic episodes increasing significantly after replacement.

Conclusions:  These findings show that the weight loss observed in patients was independent of the reduction in calorie intake resulting from less frequent hypoglycemic attacks. In Japanese patients with diabetes who received NPH, replacing NPH with detemir led to improvements in glycemic control without any weight gain. (J Diabetes Invest, doi: 10.1111/j.2040‐1124.2010.00066.x, 2010)

Effect of Pioglitazone on Serum Uric Acid Levels in Newly Diagnosed, Drug-Naïve Patients with Type 2 Diabetes

OBJECTIVES

The aim of this study was to investigate the effect of pioglitazone on serum uric acid (UA) levels and several diabetic parameters in drug-naïve subjects with type 2 diabetes mellitus (T2DM).

PATIENTS AND METHODS

The patients (n = 68) received 7.5-30 mg/day pioglitazone monotherapy. They were divided into three groups based on their baseline UA levels (low, medium, and high). These parameters were followed for 12 weeks.

RESULTS

At baseline, HbA1c and fasting blood glucose (FBG) levels were in negative proportion to those of UA, while homeostasis model assessment-beta (HOMA-B) levels were in proportion to those of UA. Insulin, homeostasis model assessment-R (HOMA-R), and body mass index (BMI) levels had a tendency to be in proportion to those of UA. While similar glycemic effects were observed in all the groups, UA levels significantly decreased in the high UA group while they insignificantly increased in the low UA group. Multiple regression analysis revealed that the baseline UA level and age were the significant determinants for the changes of UA levels. In the high UA group, significant decreases of insulin and HOMA-R levels were observed, and their changes (Δ) were significantly correlated with those of UA. Other parameters including insulin, HOMA-R, HOMA-B, and BMI were also differentially regulated between these groups.

CONCLUSIONS

These results indicate that (1) while similar glycemic effects were observed, distinct regulations of UA and other diabetic parameters were observed with pioglitazone depending on the baseline UA levels; (2) pioglitazone downregulated hyperuricemia by possibly relieving insulin resistance; and (3) the level of UA together with other parameters might provide some diabetic characteristics of the subjects.

Association of the cardioankle vascular index and ankle-brachial index with carotid artery intima media thickness in hemodialysis patients

The objectives of the present study are (1) to compare the cardioankle vascular index (CAVI), ankle-brachial index (ABI), and carotid artery intima-media thickness (CA-IMT) between HD patients with and without type 2 diabetes (T2D) or prevalence of cardiovascular (CV) disease and (2) also to evaluate the relationship of these indices with CA-IMT in these patients according to ABI levels. This study consisted of 132 HD patients with T2D and the same number of patients without T2D. The patients with diabetes or prevalence of CV disease had significantly higher CA-IMT and lower ABI values than those without diabetes or prevalence of CV disease, respectively. Although diabetic patients had higher CAVI than those without diabetes, CAVI did not differ between patients with or without prevalence of CV disease. In univariate analysis, CA-IMT was more strongly correlated with ABI than CAVI. However, the opposite was true in patients with an ABI value of more than 0.95. Both indices were significantly correlated with CA-IMT although ABI was a powerful determinant than CAVI. It appears that both indices are associated with CA-IMT in HD patients, especially with an ABI value of more than 0.95.

Absorption spectroscopy for the estimation of glycated hemoglobin (HbA1c) for the diagnosis and management of diabetes mellitus: a pilot study

OBJECTIVE

The purpose of this study was to explore the possibility of using absorption spectroscopy technique for the estimation of glycated hemoglobin HbA1c (%).

BACKGROUND DATA

Glycated hemoglobin (HbA1c) is an important marker in the diagnosis and management of diabetes mellitus. Different assay techniques have been employed for the estimation of glycated hemoglobin, including ion exchange high performance liquid chromatography (HPLC), electrophoresis, affinity chromatography, immunoturbidimetric assay and colorimetric assays, which measure different glycated products and report using different units. Spectroscopic measurements have been shown to be very sensitive and nondestructive, and require very little quantity of material for analysis. In the present study, we have employed absorption spectroscopy technique for the estimation of glycated hemoglobin in hemolysate samples of diabetic patients.

MATERIALS AND METHODS

The blood samples of individuals with normal glycemic status and confirmed diabetic patients were collected from the Clinical Biochemistry Laboratory, Kasturba Hospital, Manipal. The absorption spectra of glycated hemoglobin (HbA1c) samples were recorded in the spectral range 200-850 nm using an optic fiber based Ocean Optics CHEMUSB4-UV-VIS single beam spectrophotometer. The parameter "area under the curve" of each baseline corrected absorption spectrum was used for the estimation of HbA1c (%). The glycated hemoglobin values obtained by this spectroscopic method were compared with the values reported by the standard ion exchange HPLC method.

RESULTS

A total of 30 absorption spectra were recorded from hemolysate samples with HbA1c (%) in the range 4-10.5%. A good correlation was observed between the glycated hemoglobin values obtained by the spectroscopic method and those obtained by the standard HPLC method.

CONCLUSIONS

It appears that the direct absorption spectroscopy of hemolysate samples, therefore, may be utilized as a supplementary technique for the estimation of HbA1c (%), even at the primary healthcare centers.

Glycohemoglobin not as predictive as fasting glucose as a measure of prediabetes in predicting proteinuria

BACKGROUND

There is little data on the assessment of prediabetes with proteinuria.

METHODS

This is a cross-sectional cohort study assessing prediabetes with proteinuria in a large Japanese population. Using a nationwide health checkup database of 228 778 Japanese aged ≥20 years (median 66 years; 39.3% were men; none had pre-existing cardiovascular disease), we examined the association between prediabetes and proteinuria (≥1+ on dipstick) separately in prediabetes subjects diagnosed with the new hemoglobin A1c (HbA1c) criterion only (PD-A1c), the impaired fasting plasma glucose only (PD-IFG) and fulfilling both criteria (PD-Both).

RESULTS

According to the American Diabetes Association's (ADA's) criterion of 5.7-6.4% HbA1c and/or 100-125 mg/dL fasting plasma glucose, 43.8% of the subjects were judged as having prediabetes. Prediabetes subjects were divided into subclasses of PD-A1c (53.7%), PD-IFG (21.7%) and PD-Both (24.5%), respectively. Therefore, 21.7% of prediabetes subjects were missed using the new HbA1c criterion only. Compared with subjects with normal glucose tolerance (as a reference), the odds ratio (OR) [95% confidence interval (95% CI)] for the increased risk of proteinuria (≥1+) in diabetes itself was 2.191 (2.081-2.307) and in whole prediabetes was 1.093 (1.046-1.142); when prediabetes was subdivided, the OR for proteinuria in PD-IFG was 1.217 (1.140-1.300) and that in PD-Both was 1.249 (1.174-1.329), but that in PD-A1c was not significant, even after adjustment for significant covariates, such as age, sex, body mass index, systolic blood pressure, antihypertensive medication, eGFR, lifestyle and lipid profile.

CONCLUSIONS

Prediabetes is a significant risk factor for proteinuria compared with completely normal glucose level, and subjects with prediabetes defined using IFG are at significantly higher risk for proteinuria than those defined by HbA1c only.

The lack of long-range negative correlations in glucose dynamics is associated with worse glucose control in patients with diabetes mellitus

Glucose dynamics measured in ambulatory settings are fluid in nature and exhibit substantial complexity. We recently showed that a long-range negative correlation of glucose dynamics, which is considered to reflect blood glucose controllability over a substantial period, is absent in patients with diabetes mellitus. This was demonstrated using detrended fluctuation analysis (DFA), a modified random-walk analysis method for the detection of long-range correlations. In the present study, we further assessed the relationships between the established clinical indices of glycemic or insulinogenic control of hemoglobin A(1c) (HbA(1c)), glycated albumin (GA), 1,5-anhydroglucitol, and urine C-peptide immunoreactivity and the recently proposed DFA-based indices obtained from continuous glucose monitoring in 104 Japanese diabetic patients. Significant correlations between the following parameters were observed: (1) HbA(1c) and the long-range scaling exponent α(2) (r = 0.236, P < .05), (2) GA and α(2) (r = 0.254, P < .05), (3) GA and the short-range scaling exponent α(1) (r = 0.233, P < .05), and (4) urine C-peptide immunoreactivity and the mean glucose fluctuations (r = -0.294, P < .01). Therefore, we concluded that increases in the long-range DFA scaling exponent, which are indicative of the lack of a long-range negative correlation in glucose dynamics, reflected abnormalities in average glycemic control as clinically determined using HbA(1c) and GA parameters.

Association of glycated albumin, but not glycated hemoglobin, with calcaneus quantitative ultrasound in male hemodialysis patients with type 2 diabetes mellitus

Sustained high glucose impairs bone metabolism in patients with type 2 diabetes mellitus (T2DM). In this study, the relationship between glycemic control and bone metabolism was examined in male hemodialysis (HD) patients with T2DM. To avoid the effect of menstruation and the menstrual cycle, obesity, and glycosuria-induced hypercalciuria on bone metabolism, male anuric nonobese HD patients with T2DM (n = 42) were enrolled. Calcaneus stiffness index (SI) was determined using ultrasound after HD session. Casual plasma glucose (PG), glycated hemoglobin (HbA(1c)), and glycated albumin (GA) were measured before the HD session. In simple regression analysis, log PG (r = -0.333, P < .05) and log GA (r = -0.350, P < .05), but not log HbA(1c) (r = -0.134, P = .3985), exhibited significant and negative correlations with calcaneus SI. In multiple regression analysis including log BMI, log cCa x Pi product, and log PG, log PG was associated significantly in a negative manner with calcaneus SI, in addition to log cCa x Pi product. When log PG was replaced with log GA or log HbA(1c), log GA, but not log HbA(1c), emerged as a significant factor associated. The mechanism as to why HbA(1c) failed to associate could be explained by its false reduction by erythropoietin injection. The present study supported the notion of GA as an appropriate indicator for glycemic control in HD patients with T2DM. Furthermore, it is suggested that poor glycemic control might be a significant factor toward decreasing calcaneus SI in T2DM HD patients.

Hemoglobin A1c in predicting progression to diabetes

The predictive value of hemoglobin A1c (HbA1c) in comparison to fasting plasma glucose (FPG) is evaluated for 5-year incident diabetes (DM), as HbA1c may be more practical than FPG in the screening for DM in the future. Of 1189 non-DM subjects aged 35-89 years old from the Funagata Study, 57 subjects (4.8%) had developed DM on the WHO criteria at 5-year follow-up. The odds ratio (95% confidence interval: CI) for a one standard deviation increase in FPG/HbA1c was 3.40 (2.44-4.74)/3.49 (2.42-5.02). The area under the receiver operating characteristic curve for FPG/HbA1c was 0.786 (95% CI: 0.719-0.853)/0.785 (0.714-0.855). The HbA1c corresponding to FPG 5.56 mmol/l was HbA1c 5.3%. There was no statistical difference in sensitivity between FPG 5.56 mmol/l and HbA1c 5.3% (61.4% vs. 56.1%), while specificity was higher in HbA1c 5.3% than FPG 5.56 mmol/l (87.8% vs. 82.5%, p-value<0.001). The fraction of incident case from those with baseline IGT was similar between the groups, however the fraction of people above the cut-off was significantly lower in HbA1c 5.3% than FPG 5.56 mmol/l (14.3% vs. 19.6%, p-value<0.001). HbA1c is similar to FPG to evaluate DM risk, and HbA1c could be practical and efficient to select subjects for intervention.

Significant correlation of glycated albumin, but not glycated haemoglobin, with arterial stiffening in haemodialysis patients with type 2 diabetes

OBJECTIVE

We recently reported that glycated albumin (GA) is a better indicator of glycaemic control compared with glycated haemoglobin (HbA1c) in haemodialysis (HD) patients with type 2 diabetes. As poor glycaemic control is considered an independent risk factor for atherosclerosis in diabetes, the relationship between GA, HbA1c and arterial stiffening was examined in HD patients with type 2 diabetes.

PATIENTS AND METHODS

The present study comprised 134 HD patients with type 2 diabetes, and 158 patients without diabetes. Brachial-ankle pulse wave velocity (baPWV) was measured in all patients using a waveform analyser.

RESULTS

The mean plasma glucose (PG), GA and HbA1c levels were 7.49 +/- 2.28 mmol/l, 20.8 +/- 5.57% and 5.62 +/- 1.26%, respectively, in HD patients with diabetes (n = 134), which were significantly greater than the respective values of 5.77 +/- 1.89 mmol/l, 15.6 +/- 2.34% and 4.98 +/- 0.80% in those without diabetes (n = 158) (P < 0.0001). BaPWV was 21.69 +/- 6.90 m/s in HD patients with diabetes, which was significantly greater than the value of 18.74 +/- 4.89 m/s in those without diabetes (P < 0.0001). When the analysis was performed in a combined population of those patients with and without diabetes, the mean PG (r = 0.155, P < 0.05) and GA (r = 0.117, P < 0.05), but not HbA1c (r = 0.092, P = 0.125), exhibited significant correlations with baPWV. Multivariate regression analysis, which included age, gender, mean blood pressure, and serum levels of albumin, creatinine and LDL cholesterol, to evaluate the independent association of each marker for glycaemic control with baPWV values in HD patients demonstrated that GA, but not HbA1c or PG, was an independent factor that was significantly associated in a positive manner with baPWV in HD patients.

CONCLUSION

It was suggested that poor glycaemic control, as reflected by increased GA values, might be associated with increased arterial stiffening in HD patients.

Haemoglobin A1c analysis in the management of patients with diabetes: from chaos to harmony: Table 1

Effective management of patients with diabetes mellitus requires accurate assessments of blood glucose control. The best characterised marker of long term glycaemic control is whole blood haemoglobin A1c (HbA1c). Published clinical trials have identified quantitative and direct relationships between the HbA1c concentration and risks of diabetic microvascular complications. However, in order to practice evidence-based medicine, assays used to measure patient samples should ideally produce values comparable to the assays used in these trials. Numerous assays using chromatographic and immunological detection methods are used around the world. This paper briefly reviews the scientific evolution of HbA1c and its analysis, discusses the reasons why HbA1c assay standardisation is a challenge, describes the approaches that have been adopted to harmonise HbA1c assays, and addresses the current initiatives to standardise HbA1c globally. These efforts have established HbA1c as an essential component in the management of patients with diabetes mellitus and are likely to lead to the use of HbA1c in the screening/diagnosis of diabetes.

Association of glycated albumin, but not glycated hemoglobin, with peripheral vascular calcification in hemodialysis patients with type 2 diabetes

AIMS

Elevated HbA(1C) is a predictor of mortality as well as peripheral vascular calcification in hemodialysis (HD) patients with diabetes. However, improved glycemic control as reflected by reduction in HbA(1C) may dismiss the relationship between HbA(1C) and mortality in those patients, due possibly to the underestimation of HbA(1C) by erythropoietin use. This study was to establish the significance of glycated albumin (GA) as a useful marker of peripheral vascular calcification in diabetic HD patients, in comparison with HbA(1C).

MAIN METHODS

We examined 49 HD patients with type 2 diabetes (37 men and 12 women). Peripheral vascular calcification at hand arteries was checked on a simple X-ray photograph. GA and HbA(1C) were determined just before HD session.

KEY FINDINGS

The prevalence of peripheral vascular calcification was significantly higher in diabetic patients (65.3%) than in non-diabetic patients (27.0%). Multiple regression analyses in diabetic patients showed that both HD duration and GA were significantly associated with the presence of peripheral vascular calcification. When GA was replaced by HbA(1C) in the same model, HbA(1C) failed to show a significant association. However, when a weekly dose of erythropoietin was simultaneously included in addition to HD duration and HbA(1C), both HbA(1C) as well as HD duration emerged as a significant factor associated with the presence of peripheral vascular calcification.

SIGNIFICANCE

The present study suggested that GA might be a better indicator of glycemic control, and raise the possibility that improvement of glycemic control might prevent against the development of peripheral vascular calcification in diabetic HD patients.

Glycated albumin as an improved indicator of glycemic control in hemodialysis patients with type 2 diabetes based on fasting plasma glucose and oral glucose tolerance test

AIMS

To compare glycated albumin (GA) with glycated hemoglobin (HbA1c) as an indicator of glycemic control in hemodialysis patients with diabetes mellitus (DM), based on relationships with plasma glucose (PG) after overnight fasting and during 75 g oral glucose tolerance test (OGTT).

METHODS

GA, HbA1c, plasma glucose during 75 g OGTT, and serum pentosidine were determined in DM hemodialysis patients (n=23, male/female 9/14).

RESULTS

Significant positive correlations were found for GA and HbA1c with fasting PG (GA, r=.660, p=0.0006; HbAlc r=0.665, p=0.0004), and with PG at 30, 60 and 120 min after initiation of 75 g OGTT (GA, r=0.584, p=0.0035; r=0.624, p=0.0015; r=0.510, p=0.0129, respectively; HbA1c, r=0.669, p=0.0004; r=0.624, p=0.0011; r=0.509, p=0.0112, respectively). The area under the curve for PG during 75 g OGTT showed strong correlations with GA (r=0.625, p=0.0008) and HbA1c (r=0.671, p=0.0003). GA and HbA1c also correlated positively with serum pentosidine, demonstrating that GA provides a no less significant assay than HbA1c as a reflection of glycemic control in DM hemodialysis patients. However, HbA1c was apparently reduced in DM hemodialysis patients, as reflected by an increase in the GA/HbA1c ratio to 3.58+/-0.62 (mean+/-SD), suggesting underestimation of glycemic control by HbA1c.

CONCLUSION

GA and HbA1c exhibited similar correlations with PG during a 75 g OGTT. The dependence of GA, in contrast to HbA1c, on PG does not differ in DM hemodialysis patients from that reported for subjects with normal renal function, suggesting GA as a better marker of glycemic control in DM hemodialysis patients.

Glycated albumin is a better glycemic indicator than glycated hemoglobin values in hemodialysis patients with diabetes: effect of anemia and erythropoietin injection

The significance of glycated albumin (GA), compared with casual plasma glucose (PG) and glycated hemoglobin (HbA(1c)), was evaluated as an indicator of the glycemic control state in hemodialysis (HD) patients with diabetes. The mean PG, GA, and HbA(1c) levels were 164.5 +/- 55.7 mg/dl, 22.5 +/- 7.5%, and 5.85 +/- 1.26%, respectively, in HD patients with diabetes (n = 538), which were increased by 51.5, 31.6, and 17.7%, respectively, compared with HD patients without diabetes (n = 828). HbA(1c) levels were significantly lower than simultaneous PG and GA values in those patients in comparison with the relationship among the three parameters in patients who had diabetes without renal dysfunction (n = 365), as reflected by the significantly more shallow slope of regression line between HbA(1c) and PG or GA. A significant negative correlation was found between GA and serum albumin (r = -0.131, P = 0.002) in HD patients with diabetes, whereas HbA(1c) correlated positively and negatively with hemoglobin (r = 0.090, P = 0.036) and weekly dose of erythropoietin injection (r = -0.159, P < 0.001), respectively. Although PG and GA did not differ significantly between HD patients with diabetes and with and without erythropoietin injection, HbA(1c) levels were significantly higher in patients without erythropoietin. Categorization of glycemic control into arbitrary quartile by HbA(1c) level led to better glycemic control in a significantly higher proportions of HD patients with diabetes than those assessed by GA. Multiple regression analysis demonstrated that the weekly dose of erythropoietin, in addition to PG, emerged as an independent factor associated with HbA(1c) in HD patients with diabetes, although PG but not albumin was an independent factor associated with GA. In summary, it is suggested that GA provides a significantly better measure to estimate glycemic control in HD patients with diabetes and that the assessment of glycemic control by HbA(1c) in these patients might lead to underestimation likely as a result of the increasing proportion of young erythrocyte by the use of erythropoietin.