The combination of fasting plasma glucose and glycosylated hemoglobin predicts type 2 diabetes in Japanese workers

The combination of body mass index and fasting plasma glucose is associated with type 2 diabetes mellitus in Japan: a secondary retrospective analysis

Background

Body mass index (BMI) and fasting plasma glucose (FPG) are known risk factors for type 2 diabetes mellitus (T2DM), but data on the prospective association of the combination of BMI and FPG with T2DM are limited. This study sought to characterize the association of the combination of BMI and FPG (ByG) with T2DM.

Methods

The current study used the NAGALA database. We categorized participants by tertiles of ByG. The association of ByG with T2DM was expressed with hazard ratios (HRs) with 95% confidence intervals (CIs) after adjustment for potential risk factors.

Results

During a median follow-up of 6.19 years in the normoglycemia cohort and 5.58 years in the prediabetes cohort, the incidence of T2DM was 0.75% and 7.79%, respectively. Following multivariable adjustments, there were stepwise increases in T2DM with increasing tertiles of ByG. After a similar multivariable adjustment, the risk of T2DM was 2.57 (95% CI 2.26 - 2.92), 1.97 (95% CI 1.53 - 2.54) and 1.50 (95% CI 1.30 - 1.74) for a per-SD change in ByG in all populations, the normoglycemia cohort and the prediabetes cohort, respectively.

Conclusion

ByG was associated with an increased risk of T2DM in Japan. The result reinforced the importance of the combination of BMI and FPG in assessing T2DM risk.

Dynamic Detection of HbA1c Using a Silicon Nanowire Field Effect Tube Biosensor

As an emerging diabetes diagnostic indicator and a dynamic change index, HbA1c can not only reflect the average blood glucose level over a period of time but can also well predict the incidence of related microvascular complications. It is important to develop a detection method that can dynamically characterize HbA1c. Silicon nanowire (SiNW) devices were mass-produced using top-down sputtering technology, and a microdialyzer was installed in a SiNW field effect tube biosensor detection system. Finally, the detection system was used to detect HbA1c levels quantitatively and dynamically in experimental rabbits. Various measurements showed that mass-produced SiNW devices have ideal dimensions, stable structures, and good performance. A series of microscopy results showed that the SiNW surface can be functionalized for intermolecular interactions. The addition of a dialysis device can effectively overcome Debye shielding, making the blood test similar to the pure standard test. Finally, the dynamic detection of HbA1c within 40 h was realized. SiNW biosensors are capable of the dynamic detection of biomolecules, and dynamic observation of the interaction between blood glucose and HbA1c provides new ideas for the diagnosis and treatment of patients with diabetes. Therefore, the SiNW biosensor can reflect the dynamic changes in HbA1c in a shorter time, which has a certain potential value in the clinical treatment of diabetes.

Dental Treatment Effect on Blood Glucose Level Fluctuation in Type 1 Balanced Diabetic Children

Introduction

Pediatric dentists, while treating diabetic patients, have a major concern about the occurrence of hypo- or hyperglycemia complications. So far, no dental care protocol is elaborated to help practitioners in creating a safe environment for their patients. This study aims to evaluate the blood glucose level (BGL) fluctuation in type 1 diabetic children according to the type of the delivered treatment and its duration, to outline guidance for predicting the occurrence of a hypo- or hyperglycemia complication.

Materials and methods

A cross-sectional approach was conducted on 70 balanced diabetic children aged between 7 years and 12 years old (32 females and 38 males) in the Department of Pediatric Dentistry at the Lebanese University in Beirut. Only the patients having a BGL between 70 mg/dL and 300 mg/dL could undergo dental treatment. The gender, the duration of the dental session (≤30 or >30 minutes), the BGLs at the baseline and the end of the session were noted. The types of the performed dental treatment were classified as simple, and unpleasant acts.

Results

For the female group, only eight sessions lasted ≤30 minutes. The results of simple and unpleasant interventions >30 minutes showed that BGLs before and after treatment were almost identical (p > 0.05). In the male group, for the simple acts >30 minutes, the BGL showed a significant fluctuation (p = 0.02).

Conclusion

Dentists must be aware of signs of discomfort in balanced type 1 diabetic children to avoid severe complications. This study highlights a new range of BGLs (70–300 mg/dL) that allows safe dental treatment.

How to cite this article

Nassif N, Noueiri B. Dental Treatment Effect on Blood Glucose Level Fluctuation in Type 1 Balanced Diabetic Children. Int J Clin Pediatr Dent 2021;14(2):212–216.

Prediction of Type 2 Diabetes Based on Machine Learning Algorithm

Prediction of type 2 diabetes (T2D) occurrence allows a person at risk to take actions that can prevent onset or delay the progression of the disease. In this study, we developed a machine learning (ML) model to predict T2D occurrence in the following year (Y + 1) using variables in the current year (Y). The dataset for this study was collected at a private medical institute as electronic health records from 2013 to 2018. To construct the prediction model, key features were first selected using ANOVA tests, chi-squared tests, and recursive feature elimination methods. The resultant features were fasting plasma glucose (FPG), HbA1c, triglycerides, BMI, gamma-GTP, age, uric acid, sex, smoking, drinking, physical activity, and family history. We then employed logistic regression, random forest, support vector machine, XGBoost, and ensemble machine learning algorithms based on these variables to predict the outcome as normal (non-diabetic), prediabetes, or diabetes. Based on the experimental results, the performance of the prediction model proved to be reasonably good at forecasting the occurrence of T2D in the Korean population. The model can provide clinicians and patients with valuable predictive information on the likelihood of developing T2D. The cross-validation (CV) results showed that the ensemble models had a superior performance to that of the single models. The CV performance of the prediction models was improved by incorporating more medical history from the dataset.

Repetition of Prediabetes Enhances the Risk of Developing Diabetes

We attempted to clarify the severity of the risk of diabetes mellitus (DM) in the individuals who repeatedly fulfill the criteria for prediabetes in both fasting plasma glucose (FPG) and hemoglobin A1c (HbA1c). The subjects were 2347 individuals who underwent annual health checkup at our hospital. They were classified as normal glucose tolerance or prediabetes as their yearly status of glucose tolerance for three years; furthermore, the individuals classified as prediabetes were subclassified into 3 groups. Among them, we focused the individuals who fulfilled the criteria for prediabetes in both FPG and HbA1c, and this group was named as PD3. Similarly, all subjects were categorized into 4 groups by the frequency of the status of PD3 during three years. Moreover, all subjects were categorized into 8 patterns when PD3 status was positive. Then, we surveyed the development of diabetes for 5 years, and the incidence rates (IRs) and the age- and sex-adjusted odds ratios (ORs) were obtained. A total of 188 subjects developed diabetes. The individuals in the group of PD3 showed the highest IR of DM (33.6%). The values of ORs were 11.5, 20.0, and 63.5 when the frequencies of PD3 were one, two, and three, respectively. In the group whose frequency of PD3 was two, the individuals who had repeated the status of PD3 twice then moved to the status other than PD3 showed smaller risk of DM than the others in the same group. In conclusion, individuals who fulfill the criteria for prediabetes in both FPG and HbA1c were at a high risk of developing DM, and the risk was enhanced by repeating this status. On the other hand, changing the status from PD3 to others might reduce the risk of DM.

Associations of HbA1c and fasting plasma glucose with incident diabetes: Implications for pre-diabetes thresholds in a Japanese population

AIMS

This study assessed pre-diabetes (pre-DM) cutoffs for HbA1c and fasting plasma glucose (FPG) that were associated with an increased risk of incident DM.

METHODS

We evaluated 2267 non-diabetic Japanese health-check examinees (HbA1c: <6.5% [<48mmol/mol] and FPG: <7.0mmol/L) who were 30-79 years old and were followed-up for 5 years. Incident DM was defined as HbA1c of ≥6.5% (≥48mmol/mol), FPG of ≥7.0mmol/L, or physician-diagnosed DM.

RESULTS

During 11047 person-years, we identified 99 incident DM cases (4.3%). The incidence of DM increased with increasing baseline HbA1c or FPG levels, and the change points (95% confidence intervals) were 5.7% (5.6-5.7%; 39mmol/mol [38-39mmol/mol]) for HbA1c and 5.5mmol/L (5.5-5.6mmol/L) for FPG. The adjusted hazard ratios (HRs) for incident DM per one standard deviation-increase in HbA1c and FPG were 5.5 (4.4-6.8) and 4.0 (3.2-4.8), respectively. The adjusted HRs for incident DM were significantly higher at HbA1c of 5.7-6.4% (39-46mmol/mol) or FPG of 5.5-6.9mmol/L, compared to HbA1c of <5.7% (<39mmol/mol) or FPG of <5.5mmol/L.

CONCLUSION

The lower cut-offs for pre-DM may be 5.7% (39mmol/mol) for HbA1c and 5.5mmol/L for FPG in this Japanese population.

Update on pre-diabetes: Focus on diagnostic criteria and cardiovascular risk

Pre-diabetes, which is typically defined as blood glucose concentrations higher than normal but lower than the diabetes threshold, is a high-risk state for diabetes and cardiovascular disease development. As such, it represents three groups of individuals: Those with impaired fasting glucose (IFG), those with impaired glucose tolerance (IGT) and those with a glycated haemoglobin (HbA_1c) between 39-46 mmol/mol. Several clinical trials have shown the important role of IFG, IGT and HbA_1c-pre-diabetes as predictive tools for the risk of developing type 2 diabetes. Moreover, with regard to cardiovascular disease, pre-diabetes is associated with more advanced vascular damage compared with normoglycaemia, independently of confounding factors. In view of these observations, diagnosis of pre-diabetes is mandatory to prevent or delay the development of the disease and its complications; however, a number of previous studies reported that the concordance between pre-diabetes diagnoses made by IFG, IGT or HbA_1c is scarce and there are conflicting data as to which of these methods best predicts cardiovascular disease. This review highlights recent studies and current controversies in the field. In consideration of the expected increased use of HbA_1c as a screening tool to identify individuals with alteration of glycaemic homeostasis, we focused on the evidence regarding the ability of HbA_1c as a diagnostic tool for pre-diabetes and as a useful marker in identifying patients who have an increased risk for cardiovascular disease. Finally, we reviewed the current evidence regarding non-traditional glycaemic biomarkers and their use as alternatives to or additions to traditional ones.

Interleukin-6 is associated with chronic hyperglycemia and insulin resistance in patients after acute pancreatitis

BACKGROUND

Diabetes is a pervasive disease, with a mounting prevalence and burden on health care systems. Under this collective term of diabetes falls diabetes after diseases of the exocrine pancreas, a condition which was previously under-recognised and often mislabeled as type 2 diabetes mellitus and is now increasingly acknowledged as a stand-alone entity. However, there is a paucity of clinical studies investigating the underlying pathophysiology of diabetes after acute pancreatitis, the most frequent disease of the pancreas. This study aimed to investigate the role of adipocytokines in glucose metabolism after acute pancreatitis.

METHODS

This was a cross-sectional follow-up study of a patient cohort diagnosed with acute pancreatitis. Fasting venous blood samples were collected to analyse markers of glucose metabolism (fasting blood glucose, haemoglobin A1c, homeostasis model assessment (HOMA-IR) as a measure of insulin resistance) and adypocytokines (adiponectin, interleukin-6, leptin, monocyte chemoattractant protein-1, retinol binding protein-4, resistin, and tumor necrosis factor-α). Participants were categorized into two groups: normoglycemia after acute pancreatitis and chronic hyperglycemia after acute pancreatitis (CHAP). Binary logistic regression and linear regression analyses were used to investigate the association between each of the adipocytokines and markers of glucose metabolism. Potential confounders were adjusted for in multivariate analyses.

RESULTS

A total of 83 patients with acute pancreatitis were included, of whom 19 developed CHAP. Interleukin-6 was significantly associated with CHAP in both unadjusted and adjusted models (p = 0.030 and p = 0.018, respectively). Further, it was also significantly associated with HOMA-IR in both unadjusted and adjusted models (p = 0.029 and p = 0.037, respectively). Other adipocytokines were not significantly associated with markers of glucose metabolism.

CONCLUSION

Interleukin-6 appears to be implicated in the development of chronic hyperglycemia and insulin resistance in patients after acute pancreatitis. It may become a potential target in the prevention and early treatment of diabetes after diseases of the exocrine pancreas.

The changing relationship between HbA1c and FPG according to different FPG ranges

PURPOSE

Since the American Diabetes Association included hemoglobin A1c (HbA1c) in the diagnostic criteria for diabetes in 2010, the clinical use of HbA1c has remained controversial. We explored the use of HbA1c for diagnosing diabetes and intermediate hyperglycemia in comparison with fasting plasma glucose (FPG).

METHODS

We screened 3710 adult subjects (mean age = 55.24 years) comprising 1704 males and 2006 females. We drew an receiver operating characteristic (ROC) curve to evaluate the ability of HbA1c to diagnose diabetes and intermediate hyperglycemia according to FPG. We used Kappa coefficient and Pearson's correlation coefficient to evaluate the relationship between HbA1c and FPG in different FPG ranges.

RESULTS

The areas under ROC curve to diagnose diabetes and intermediate hyperglycemia were 0.859 (95 % CI 0.827-0.892) and 0.633 (95 % CI 0.615-0.651). The kappa coefficients between FPG and HbA1c for diagnosis of diabetes and intermediate hyperglycemia were 0.601 (P < 0.001) and 0.104 (P < 0.001). The Pearson's correlation coefficient of FPG and HbA1c was 0.640 (P < 0.001), but when we classified FPG as normal, intermediate hyperglycemia and diabetes, the coefficients became 0.07 (P = 0.002), 0.185 (P < 0.001) and 0.760 (P < 0.001), respectively.

CONCLUSIONS

The relationship between HbA1c and FPG changed according to the different FPG ranges. When FPG was higher, the relationship was stronger. HbA1c and FPG were highly consistent in diagnosing diabetes, but they were not in predicting intermediate hyperglycemia.

Glycaemic Control and Associated Self-Management Behaviours in Diabetic Outpatients: A Hospital Based Observation Study in Lusaka, Zambia

BACKGROUND

The control of diabetes mellitus depends on several factors that also include individual lifestyles. We assessed glycaemic control status and self-management behaviours that may influence glycaemic control among diabetic outpatients.

METHODS

This cross-sectional study among 198 consenting randomly selected patients was conducted at the University Teaching Hospital diabetic clinic between September and December 2013 in Lusaka, Zambia. A structured interview schedule was used to collect data on demographic characteristics, self-management behaviours, and laboratory measurements. Binary logistic regression analysis using IBM SPSS for Windows version 20.0 was carried out to predict behaviours that were associated with glycaemic control status.

RESULTS

The proportion of patients that had good glycaemic control status (HbA1c≤ 48 mmol/mol) was 38.7% compared to 61.3% that had poor glycaemic control status (HbA1c≥ 49 mmol/mol). Adherence to antidiabetic treatment and fasting plasma glucose predicted glycaemic control status of the patients. However, self-blood glucose monitoring, self-blood glucose monitoring means and exercise did not predict glycaemic control status of the patients.

CONCLUSION

We find evidence of poor glycaemic control status among most diabetic patients suggesting that health promotion messages need to take into account both individual and community factors to promote behaviours likely to reduce nonadherence.

Optimal Hemoglobin A1c Levels for Screening of Diabetes and Prediabetes in the Japanese Population

The aim of this study was to evaluate the utility of hemoglobin A1c (HbA1c) to identify individuals with diabetes and prediabetes in the Japanese population. A total of 1372 individuals without known diabetes were selected for this study. A 75 g oral glucose tolerance test (OGTT) was used to diagnose diabetes and prediabetes. The ability of HbA1c to detect diabetes and prediabetes was investigated using receiver operating characteristic (ROC) analysis. The kappa (κ) coefficient was used to test the agreement between HbA1c categorization and OGTT-based diagnosis. ROC analysis demonstrated that HbA1c was a good test to identify diabetes and prediabetes, with areas under the curve of 0.918 and 0.714, respectively. Optimal HbA1c cutoffs for diagnosing diabetes and prediabetes were 6.0% (sensitivity 83.7%, specificity 87.6%) and 5.7% (sensitivity 60.6%, specificity 72.1%), respectively, although the cutoff for prediabetes showed low accuracy (67.6%) and a high false-negative rate (39.4%). Agreement between HbA1c categorization and OGTT-based diagnosis was low in diabetes (κ = 0.399) and prediabetes (κ = 0.324). In Japanese subjects, the HbA1c cutoff of 6.0% had appropriate sensitivity and specificity for diabetes screening, whereas the cutoff of 5.7% had modest sensitivity and specificity in identifying prediabetes. Thus, HbA1c may be inadequate as a screening tool for prediabetes.

Glycaemic control in diabetic patients in Zambia

INTRODUCTION

The glycaemic control status of diabetic patients affects the management of their disorder. We examined the glycaemic control and clinical factors that may influence the achievement of the glycaemic control targets among diabetic out-patients.

METHODS

This was a hospital based cross-sectional study carried out at the University Teaching Hospital diabetic clinic in Lusaka, Zambia. A simple random sample of 198 consenting participants was selected from diabetic out-patients between September and December 2013. A structured interview schedule was used to capture socio-demographic data as well as needed clinical data from clients' medical records and laboratory results. Multivariate binary logistic regression analysis was carried out to examine factors that may be associated with the glycaemic control status of these diabetic patients.

RESULTS

Overall (n = 198), mean (SD) age was 53.19 ± 13.32 years. Majority (61.3%) of the patients had poor glycaemic control status (HbA1c ≥ 49 mmol/mol). Insulin treatment (OR 0.13, 95% CI: 0.01 - 1.41), systolic blood pressure (OR 1.04, CI: 1.00 - 1.08) and fasting plasma glucose (previous; OR 0.81, CI: 0.72 - 0.90 and current; OR 0.85, CI: 0.78 - 0.93) were statistically significantly associated with glycaemic control. The poor glycaemic control observed in this study is similar to that reported in other published studies.

CONCLUSION

We found evidence of poor glycaemic control in the study population suggesting need to explore the reasons for this. Association of Insulin, systolic blood pressure and fasting plasma glucose with glycaemic control further suggests the efficiency of traditional basic monitoring parameters which should be exploited in sharpening primary preventive strategies especially those that support lifestyle modification. Such efforts should also be integrated in all information, education and communication strategies that target but not limited to hospital based patients too.

Pretransplant HbA1c Is a Useful Predictor for the Development of New-Onset Diabetes in Renal Transplant Recipients Receiving No or Low-Dose Erythropoietin

Aims. To evaluate the predictive power of pretransplant HbA1c for new-onset diabetes after transplantation (NODAT) in kidney transplant candidates, who had several predispositions for fluctuated HbA1c levels. Methods. We performed a retrospective study of 119 patients without diabetes who received kidney transplantation between March 2000 and January 2012. Univariate and multivariate logistic regression analyses were used to investigate the association of several parameters with NODAT. Predictive discrimination of HbA1c was assessed using a receiver-operating characteristic curve. Results. Seventeen patients (14.3%) developed NODAT within 1 year of transplantation. Univariate logistic regression analysis revealed that recipient age, gender, and HbA1c were predictors of NODAT. In the multivariate analysis, the association between pretransplant HbA1c and NODAT development did not reach statistical significance (P = 0.07). To avoid the strong influence of high-dose erythropoietin on HbA1c levels, we performed subgroup analyses on 85 patients receiving no or low-dose (≤6000 IU/week) erythropoietin. HbA1c was again an independent predictor for NODAT. Receiver-operating characteristic analysis revealed a cut-off value of 5.2% with an optimal sensitivity of 64% and specificity of 78% for predicting NODAT. Conclusions. Our results reveal that the pretransplant HbA1c level is a useful predictor for NODAT in patients receiving no or low-dose erythropoietin.

Use of high-normal levels of haemoglobin A(1C) and fasting plasma glucose for diabetes screening and for prediction: a meta-analysis

BACKGROUND

Using high-normal levels of haemoglobin A1C (Abnormal-A1C ) or fasting plasma glucose (FPG) (Abnormal-FPG) for diabetes screening are expected to improve the ability to detect persons with or at high risk of diabetes. We assessed the diagnostic and predictive capacity for diabetes of Abnormal-A1C and Abnormal-FPG. We compared these to the combined use of the two measures to the single use of either measurement.

METHODS

We analysed 31 eligible cross-sectional or cohort studies that assessed diagnostic or predictive ability, respectively, by using lower A1C and FPG cutoff values than recommended by current diabetes criteria. Positive and negative likelihood ratios (LR+ and LR-) were calculated to assess the ability to confirm or exclude diabetes, respectively, on the basis of a bivariate random-effects model.

RESULTS

With both Abnormal-A1C and Abnormal-FPG, the pooled LR+ was above 4 for diagnosing diabetes and above 3 for predicting diabetes. However, the pooled LR- for predicting diabetes was higher with Abnormal-A1C (0.48) and Abnormal-FPG (0.49) in comparison with that for diagnosing diabetes (0.27, Abnormal-A1C ; 0.28, Abnormal-FPG). In eight studies that assessed the predictive ability of the combination of A1C and FPG, using either Abnormal-A1C or Abnormal-FPG could lower LR- to 0.17 from 0.43 for only Abnormal-A1C and from 0.38 for only Abnormal-FPG. Accordingly, LR+ was also lowered to 2.37 from 3.36 for only Abnormal-A1C and from 3.84 for only-Abnormal-FPG.

CONCLUSION

The use of the two blood glucose tests had insufficient capacity to identify subjects at high risk for diabetes but had considerable capacity to identify undiagnosed diabetes.

Incidence of type 2 diabetes in Japan: a systematic review and meta-analysis

BACKGROUND

The definition of incident type 2 diabetes varies across studies; hence, the actual incidence of type 2 diabetes in Japan is unclear. Here, we reviewed the various definitions of incident type 2 diabetes used in previous epidemiologic studies and estimated the diabetes incidence rate in Japan.

METHODS

We searched for related literature in the MEDLINE, EMBASE, and Ichushi databases through September 2012. Two reviewers selected studies that evaluated incident type 2 diabetes in the Japanese population.

RESULTS

From 1824 relevant articles, we included 33 studies with 386,803 participants. The follow-up period ranged from 2.3 to 14 years and the studies were initiated between 1980 and 2003. The random-effects model indicated that the pooled incidence rate of diabetes was 8.8 (95% confidence interval, 7.4-10.4) per 1000 person-years. We observed a high degree of heterogeneity in the results (I(2) = 99.2%; p < 0.001), with incidence rates ranging from 2.3 to 52.6 per 1000 person-years. Three studies based their definition of incident type 2 diabetes on self-reports only, 10 on laboratory data only, and 20 on self-reports and laboratory data. Compared with studies defining diabetes using laboratory data (n = 30; pooled incidence rate = 9.6; 95% confidence interval = 8.3-11.1), studies based on self-reports alone tended to show a lower incidence rate (n = 3; pooled incidence rate = 4.0; 95% confidence interval = 3.2-5.0; p for interaction < 0.001). However, stratified analyses could not entirely explain the heterogeneity in the results.

CONCLUSIONS

Our systematic review and meta-analysis indicated the presence of a high degree of heterogeneity, which suggests that there is a considerable amount of uncertainty regarding the incidence of type 2 diabetes in Japan. They also suggested that laboratory data may be important for the accurate estimation of the incidence of type 2 diabetes.

Optimal hemoglobin A1C Cutoff Value for Diagnosing type 2 diabetes mellitus in Korean adults

Commonly used tests for the diagnosis of diabetes include measurements of fasting plasma glucose levels and the oral glucose tolerance test (OGTT). Recently, a hemoglobin A1C (A1C) level of 6.5% has been included as a criterion for diabetes diagnosis by the American Diabetes Association. We aimed to determine appropriate A1C cutoff values for identifying patients with diabetes or prediabetes, including impaired glucose tolerance and impaired fasting glucose among Korean adults and to determine whether these cutoffs vary according to age. We recruited 4616 adults without a history of diabetes from 10 university hospitals. A 75-g OGTT and A1C sampling were performed in all examinees. Pointwise area under the receiver operating characteristic curve was used to evaluate the diagnostic accuracy of the A1C cutoff. An A1C threshold of 6.1% proved to be the optimal limit for diagnosing diabetes, with 63.8% sensitivity and 88.1% specificity. The cutoff value increased with age (5.9% in 18-39 years, 6.2% in 40-64 years, and 6.4% in older than 65 years) and were similar for men and women. An A1C cutoff of 5.7% had reasonable sensitivity (48.6%) and specificity (65.7%) for the identification of prediabetes. Further prospective studies should be carried out to determine whether the application of age-specific diagnostic criteria is appropriate.

Incidence of type 2 diabetes by HbA1c and OGTT: the Isfahan Diabetes Prevention Study

The aim of this study was to estimate the incidence of type 2 diabetes using newly proposed hemoglobin A(1C) (HbA(1c)) and current oral glucose tolerance test (OGTT) definition in an Iranian non-diabetic population. A total of 923 non-diabetic first-degree relatives (FDRs) of patients with type 2 diabetes 30-70 years old in 2003-2005 were followed through 2009 for the occurrence of type 2 diabetes. At baseline and through follow-ups, participants underwent a standard 75 g 2-h OGTT and HbA(1c) measurements. Prediction of progression to type 2 diabetes by OGTT-defined or HbA(1c)-defined diabetes was assessed with area under the receiver operating characteristic (ROC) curves based upon measurement of fasting plasma glucose, 2-h post-load glucose values, and HbA(1c). The prevalence of type 2 diabetes was 9.2% (95% CI: 8.2, 10.2) by OGTT-defined diabetes and 7.9% (95% CI: 6.9, 9.0) by HbA(1c) ≥ 6.5. The incidence of type 2 diabetes was 2.0% (95% CI: 1.6, 2.4) (1.8% men and 2.1% women) per year by the current OGTT definition, whereas the incidence rates were 1.7% (95% CI: 1.3, 2.0) (1.6% men and 1.7% women) per year by HbA(1c) ≥ 6.5%. Of those diagnosed with type 2 diabetes by OGTT, 69.6% had HbA(1c) <6.5% and therefore would not have been classified as having type 2 diabetes. The incidence and prevalence of diabetes using newly proposed HbA(1c) threshold in this FDRs of patients with type 2 diabetes were slightly lower than using current OGTT definition.

Assessment of HbA1c as a diagnostic tool in diabetes and prediabetes

To evaluate HbA1c as a diagnostic tool in prediabetes-impaired fasting glucose (IFG) and impaired glucose tolerance (IGT), and newly detected diabetes (NDD), defined by plasma glucose and OGTT. 2,231 subjects, of mean age 50.3 ± 13.9 years and mean BMI 29.5 ± 6.2 kg/m(2), underwent an OGTT. HbA1c performance was assessed using the area under the receiver operating characteristics curve (AUC-ROC). HbA1c was significantly higher in all groups with altered glucose tolerance-5.72 ± 0.61% in IFG, 5.84 ± 0.63% in IGT, and 7.5 ± 1.69% in NDD when compared to normal glucose tolerance-5.23 ± 0.65% (P < 0.0001). HbA1c of both prediabetic groups was significantly lower in comparison with NDD (P < 0.0001); in IGT being significantly higher than in IFG (P = 0.02). ROC analysis demonstrated good performance of HbA1c for diagnosing diabetes-AUC-ROC 0.958 (95% CI: 0.946-0.970), as well as prediabetes-AUC-ROC 0.729 (95% CI: 0.702-0.755). The optimal cut-off level of HbA1c for diagnosing diabetes was 6.1% (sensitivity 86%, specificity 92%) and for undiagnosed prediabetes-5.5% (sensitivity 71%, specificity 64%). HbA(1c) appears to be a useful, convenient, and reliable tool for identifying subjects with prediabetes and diabetes and should be considered in the development of diagnostic strategies.

Use of HbA(1C) testing to diagnose pre-diabetes in high risk African American children: a comparison with fasting glucose and HOMA-IR

OBJECTIVE

This study aimed to compare the discriminating power of HbA(1C) with other pre-diabetes diagnostic tests specifically in high-risk African American children.

RESEARCH DESIGN AND METHODS

A cross-sectional analysis was performed on a sample of 172 children (70 boys and 102 girls) aged 9-11 years with BMI's above the 85th percentile. Fasting glucose, insulin and HbA(1C) were analyzed from the plasma samples.

RESULTS

Of the 172 participants included in this analysis, 21 (12.2%) had HbA(1C) concentrations above the cutoff of 5.7 used to identify pre-diabetes. None (0%) of these 21 participants, however, were observed to have a glucose concentration above the pre-diabetes cutoff of 110 mg/dl, and only 13 of 21 participants had HOMA-IR above the pre-diabetes cutoff of 2.5. When compared to the previously identified glucose cutoff of 110 mg/dl and HOMA-IR cutoff of 2.5 for pre-diabetes, HbA(1C) showed high specificity (88 and 93%, respectively) but very low sensitivity (0 and 21%, respectively). Glucose, insulin and HOMA-IR were significantly interrelated, but HbA(1C) was not significantly correlated with these biochemical prediabetes assessment variables, nor with anthropometric (BMIz, WC) risk factors.

CONCLUSION

Our results suggest that HbA(1C) had poor discrimination power to identify prediabetes in overweight and obese 9- to 11-year-old African American children. Future studies are recommended to compare the feasibility, sensitivity and predictive power of different screening tests currently recommended to avoid inadequacy when screening for prediabetes and diabetes.

Persistent fasting hyperglycaemia is more predictive of type 2 diabetes than transient fasting hyperglycaemia

AIMS

We investigated the value of persistent fasting hyperglycaemia as assessed by repeated elevated fasting plasma glucose in predicting the progression to diabetes.

METHODS

A retrospective cohort study was conducted from 1998 to 2006 inclusive among 7929 persons (37,742 person-years), with a mean age of 53.0 years at baseline. The cumulative incidence of diabetes was measured. A baseline and follow-up fasting plasma glucose were categorized as normal fasting glucose (< 5.56 mmol/l), or impaired fasting glucose (5.56-6.94 mmol/l).

RESULTS

The cumulative incidence and incidence density of diabetes were 3.5% (275 cases) and 7.3 per 1000 person-years over a mean follow-up period of 4.8 years. The cumulative incidence of diabetes among subjects with impaired fasting glucose at both previous examinations (persistent impaired fasting glucose) was 30.4% (222/1518) compared with 0.6% (15/5063) of those with normal fasting glucose at both baseline and initial follow-up. The hazard ratios to develop diabetes, adjusted for possible confounders, was 37.10 (95% CI, 21.6-63.7) for persistent impaired fasting glucose versus persistent normal fasting glucose. Persistent impaired fasting glucose predicted diabetes at 80.7% (222/275) sensitivity and 83.1% (6358/7654) specificity, whereas first baseline impaired fasting glucose only predicted diabetes at 86.9% (239/275) sensitivity and 74.9% (5730/7654) specificity. The model using both previous fasting plasma glucose levels had a greater AUROC (area under receiver operating characteristic) than that using first baseline fasting plasma glucose only (0.92 vs. 0.88; P < 0.001).

CONCLUSIONS

Repeated measurements of fasting plasma glucose better predicts incidence of diabetes than a single test. In particular, persistent fasting hyperglycaemia adds more substantial precision to the prediction of future diabetes than transient impaired fasting glucose. This combination is cost efficient and may be practical for early detection of high-risk individuals.

Haemoglobin A1c cut-off point to identify a high risk group of future diabetes: results from the Omiya MA Cohort Study

AIMS

Using the HbA(1c) level to define diabetes has several advantages and these advantages also apply to define a high-risk group. However, the risk of diabetes increases as HbA(1c) increases and a certain degree of arbitrariness in the cut-off for the high risk group is unavoidable. The aim of this study was to determine the HbA(1c) cut-off for defining a high-risk group that corresponds to the fasting plasma glucose cut-off by comparing the risk of diabetes against the fasting plasma glucose and HbA(1c) levels in the Japanese population.

METHODS

A retrospective cohort study was conducted using data from annual health examinations performed in Omiya city. A total of 11,271 subjects between the ages of 40 and 79 years without diabetes at baseline were followed for up to 7 years. According to the new diagnostic criteria, diabetes was defined as an fasting plasma glucose level ≥ 7 mmol/l or an HbA(1c) level ≥ 48 mmol/mol (≥ 6.5%) or a self-report. The HbA(1c) cut-off corresponding to the fasting plasma glucose cut-off was determined using the incidence, hazard ratio, and a receiver operating characteristic analysis.

RESULTS

Eight hundred and sixty subjects developed diabetes. The incidence, hazard ratio, and receiver operating characteristic analysis all indicated that an HbA(1c) cut-off of 39 mmol/mol (5.7%) corresponded to an fasting plasma glucose level of 5.6 mmol/l.

CONCLUSIONS

Our results suggested that the HbA(1c) cut-off for high-risk of diabetes should be 39 mmol/mol (5.7%), consistent with the American Diabetes Association recommendation. Further research is needed to determine whether our results are applicable to other populations.

The Heritability of HbA1c and Fasting Blood Glucose in Different Measurement Settings

In an extended twin study we estimated the heritability of fasting HbA1c and blood glucose levels. Blood glucose was assessed in different settings (at home and in the clinic). We tested whether the genetic factors influencing fasting blood glucose levels overlapped with those influencing HbA1c and whether the same genetic factors were expressed across different settings. Fasting blood glucose was measured at home and during two visits to the clinic in 77 healthy families with same-sex twins and siblings, aged 20 to 45 years. HbA1c was measured during the first clinic visit. A 4-variate genetic structural equation model was used that estimated the heritability of each trait and the genetic correlations among traits. Heritability explained 75% of the variance in HbA1c. The heritability of fasting blood glucose was estimated at 66% at home and lower in the clinic (57% and 38%). Fasting blood glucose levels were significantly correlated across settings (0.34 <r< 0.54), mostly due to a common set of genes that explained between 53% and 95% of these correlations. Correlations between HbA1c and fasting blood glucoses were low (0.11 <r< 0.23) and genetic factors influencing HbA1c and fasting glucose were uncorrelated. These results suggest that in healthy adults the genes influencing HbA1c and fasting blood glucose reflect different aspects of the glucose metabolism. As a consequence these two glycemic parameters can not be used interchangeably in diagnostic procedures or in studies attempting to find genes for diabetes. Both contribute unique (genetic) information.

Haemoglobin A1c is superior to fasting glucose in predicting the incidence of diabetes over 8 years among Chinese

Baseline haemoglobin A1c had a higher standardized hazard ratio, and more optimal sensitivity and specificity than fasting glucose in predicting the 8-year incidence of diabetes among 530 non-diabetic Chinese from the population-based Hong Kong Cardiovascular Risk Factor Prevalence Study.

Insufficient sensitivity of hemoglobin A(₁C) determination in diagnosis or screening of early diabetic states

An International Expert Committee made recommendations for using the hemoglobin A(₁C) (A1C) assay as the preferred method for the diagnosis of diabetes in nonpregnant individuals. A concentration of at least 6.5% was considered as diagnostic. It is the aim of this study to compare the sensitivity of A1C with that of plasma glucose concentrations in subjects with early diabetes or impaired glucose tolerance (IGT). We chose 2 groups of subjects who had A1C not exceeding 6.4%. The first group of 89 subjects had family histories of diabetes (MODY or type 2 diabetes mellitus) and had oral glucose tolerance test (OGTT) and A1C determinations. They included 36 subjects with diabetes or IGT and 53 with normal OGTT. The second group of 58 subjects was screened for diabetes in our Diabetes Clinic by fasting plasma glucose, 2-hour plasma glucose, or OGTT and A1C; and similar comparisons were made. Subjects with diabetes or IGT, including those with fasting hyperglycemia, had A1C ranging from 5.0% to 6.4% (mean, 5.8%). The subjects with normal OGTT had A1C of 4.2% to 6.3% (mean, 5.4%), or 5.5% for the 2 groups. The A1C may be in the normal range in subjects with diabetes or IGT, including those with fasting hyperglycemia. Approximately one third of subjects with early diabetes and IGT have A1C less than 5.7%, the cut point that the American Diabetes Association recommends as indicating the onset of risk of developing diabetes in the future. The results of our study are similar to those obtained by a large Dutch epidemiologic study. If our aim is to recognize early diabetic states to apply effective prophylactic procedures to prevent or delay progression to more severe diabetes, A1C is not sufficiently sensitive or reliable for diagnosis of diabetes or IGT. A combination of A1C and plasma glucose determinations, where necessary, is recommended for diagnosis or screening of diabetes or IGT.

A1C level and future risk of diabetes: a systematic review

We examined ranges of A1C useful for identifying persons at high risk for diabetes prior to preventive intervention by conducting a systematic review. From 16 included studies, we found that annualized diabetes incidence ranged from 0.1% at A1C <5.0% to 54.1% at A1C >or=6.1%. Findings from 7 studies that examined incident diabetes across a broad range of A1C categories showed 1) risk of incident diabetes increased steeply with A1C across the range of 5.0 to 6.5%; 2) the A1C range of 6.0 to 6.5% was associated with a highly increased risk of incident diabetes, 25 to 50% incidence over 5 years; 3) the A1C range of 5.5 to 6.0% was associated with a moderately increased relative risk, 9 to 25% incidence over 5 years; and 4) the A1C range of 5.0 to 5.5% was associated with an increased incidence relative to those with A1C <5%, but the absolute incidence of diabetes was less than 9% over 5 years. Our systematic review demonstrated that A1C values between 5.5 and 6.5% were associated with a substantially increased risk for developing diabetes.

Impaired glucose tolerance in sleep disorders

BACKGROUND

Recent epidemiological and experimental data suggest a negative influence of shortened or disturbed night sleep on glucose tolerance. Due to the high prevalence of sleep disorders this might be a major health issue. However, no comparative studies of carbohydrate metabolism have been conducted in clinical sleep disorders.

METHODOLOGY/PRINCIPAL FINDINGS

We performed oral glucose tolerance tests (OGTT) and assessed additional parameters of carbohydrate metabolism in patients suffering from obstructive sleep apnea syndrome (OSAS, N = 25), restless legs syndrome (RLS, N = 18) or primary insomnia (N = 21), and in healthy controls (N = 33). Compared to controls, increased rates of impaired glucose tolerance were found in OSAS (OR: 4.9) and RLS (OR: 4.7) patients, but not in primary insomnia patients (OR: 1.6). In addition, HbA1c values were significantly increased in the same two patient groups. Significant positive correlations were found between 2-h plasma glucose values measured during the OGTT and the apnea-arousal-index in OSAS (r = 0.56; p<0.05) and the periodic leg movement-arousal-index in RLS (r = 0.56, p<0.05), respectively. Sleep duration and other quantitative aspects of sleep were similar between patient groups.

CONCLUSIONS/SIGNIFICANCE

Our findings suggest that some, but not all sleep disorders considerably compromise glucose metabolism. Repeated arousals during sleep might be a pivotal causative factor deserving further experimental investigations to reveal potential novel targets for the prevention of metabolic diseases.

Diabetes progression from "high-normal" glucose in school teachers

OBJECTIVE

High-normal, the intermediate category between normal fasting glucose (NFG) and impaired fasting glucose (IFG), was introduced in the criteria of the disordered glucose metabolism in 2008. The aim of this study was to investigate the risk for future incidence of type 2 diabetes of the subjects with high-normal and to examine how other metabolic variables could be useful for their risk stratification.

METHODS

A historical cohort study was conducted from 2001 to 2008, inclusive, in 4,165 non-diabetic employees at public schools (2,229 men and 1,936 women; age 45.8+/-5.9 years, range 25-55 years). They were classified at baseline as NFG with fasting plasma glucose (FPG)<100 mg/dL, high-normal with FPG 100-109 mg/dL, and IFG with FPG 110-125 mg/dL. The incidence of type 2 diabetes (defined either by FPG > or = 126 mg/dL or by receiving treatments) was measured.

RESULTS

The cumulative incidence during a mean follow-up of 5.1 years were 16/3,364 (0.5%), 40/613 (6.5%), and 53/188 (28.2%) in subjects with NFG, high-normal, and IFG, respectively. Multivariate-adjusted odds ratios for the incidence were still significant both in high-normal and IFG compared to NFG. Body mass index (BMI) and alanine aminotransaminase (ALT) were associated with the incidence of type 2 diabetes independently of FPG categories (p<0.05).

CONCLUSION

The future incidence of type 2 diabetes in subjects with high-normal was significantly higher than in those with NFG in this population. BMI and ALT can improve risk stratification in high-normal subjects.

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.

HbA1c is associated with severity of obstructive sleep apnea hypopnea syndrome in nondiabetic men

The aim of this study was to examine the potential correlation of sleep characteristics with glucose metabolism in nondiabetic men with obstructive sleep apnea syndrome (OSAS). Included were 31 male patients (mean age 46.7 ±11 years), recently diagnosed with OSAS by full polysomnography. There was a significant correlation of fasting glucose and glycosylated hemoglobin (HbA_1c) levels with arousal index (P = 0.047 and P =0.014, respectively). Moreover, HbA_1c levels were correlated with apnea hypopnea index (P =0.009), a widely accepted marker of the severity of OSAS, and with percentage of sleep time with saturation of hemoglobin with oxygen as measured by pulse oximetry (SpO₂) < 90% (t < 90%) ( P =0.010). Finally, glucose and HbA_1c levels showed a significant negative correlation with average SpO₂ (P =0.013 and P = 0.012, respectively) and, additionally, glucose levels with minimum SpO ₂ (P =0.027) during sleep. In conclusion, severity of OSAS among nondiabetic men is associated with increased HbA_1c levels and increased fasting glucose. Thus, severity of OSAS may be an additional marker of cardiovascular risk, as well as of future diabetes, in these subjects. However, further work is needed to confirm the clinical significance of these observations.

Elevated A1C in adults without a history of diabetes in the U.S

OBJECTIVE

The purpose of this study was to examine the prevalence and correlates of elevated A1C in a large, nationally representative sample of adults without diabetes in the U.S.

RESEARCH DESIGN AND METHODS

We analyzed data from 15,934 participants aged >or=20 years without diagnosed diabetes who had A1C measurements in the 1999-2006 National Health and Nutrition Examination Survey, a cross-sectional and nationally representative sample of the U.S. population.

RESULTS

The overall prevalence of A1C >6% was 3.8%, corresponding to 7.1 million adults without diabetes in the U.S. population. Approximately 90% of these individuals had fasting glucose >or=100 mg/dl. Older age, male sex, non-Hispanic black race/ethnicity, hypercholesterolemia, higher BMI, and lower attained education were significantly associated with having a higher A1C level even among individuals with normal fasting glucose (<100 mg/dl) and after multivariable adjustment.

CONCLUSIONS

A single elevated A1C level (A1C >6%) is common in the general population of adults without a history of diabetes and is highly reliable for the detection of elevated fasting glucose. Nondiabetic adults with elevated A1C are likely to have impaired fasting glucose and an array of other risk factors for type 2 diabetes and cardiovascular disease.

Fasting plasma glucose and HbA1c as risk factors for Type 2 diabetes

AIMS

We examined the value of combining fasting plasma glucose (FPG) and glycated haemoglobin (HbA(1c)) as a predictor of diabetes, using the new American Diabetes Association (ADA) criteria of FPG and lower cut-off point of HbA(1c).

METHODS

A retrospective cohort study was conducted from 1998 to 2006, inclusive, in 10 042 persons (55 884 person-years), with a mean age of 53.0 years at baseline. The cumulative incidence of diabetes (defined either as an FPG > or = 7.0 mmol/l or as clinically diagnosed diabetes) was measured.

RESULTS

The cumulative incidence and incidence density of diabetes were 3.7% (368 cases) and 6.6/1000 person-years over a mean follow-up period of 5.5 years. The cumulative incidence of diabetes in subjects with impaired fasting glucose (IFG) and HbA(1c) 5.5-6.4% was 24.8% (172/694 persons) compared with 0.4% (25/6698 persons), 2.5% (15/605 persons), 7.6% (156/2045 persons) in those with normal fasting glucose (NFG) and HbA(1c) < 5.5%, NFG and HbA(1c) 5.5-6.4% and IFG and HbA(1c) < 5.5%, respectively. The hazard ratio for diabetes, adjusted for possible confounders, was 7.4 (95% confidence interval, 4.70 to 11.74) for those with NFG and HbA(1c) 5.5-6.4%, 14.4 (11.93 to 27.79) for those with IFG and HbA(1c) < 5.5% and 38.4 (24.63 to 59.88) for those with IFG and HbA(1c) 5.5-6.4%.

CONCLUSIONS

The combination of FPG and HbA(1c) identifies individuals who are at risk of progression to Type 2 diabetes at the new ADA criteria of FPG and a lower cut-off point of HbA(1c) than previous studies.

A new look at screening and diagnosing diabetes mellitus

OBJECTIVE

Diabetes is underdiagnosed. About one third of people with diabetes do not know they have it, and the average lag between onset and diagnosis is 7 yr. This report reconsiders the criteria for diagnosing diabetes and recommends screening criteria to make case finding easier for clinicians and patients.

PARTICIPANTS

R.M.B. invited experts in the area of diagnosis, monitoring, and management of diabetes to form a panel to review the literature and develop consensus regarding the screening and diagnosis of diabetes with particular reference to the use of hemoglobin A1c (HbA1c). Participants met in open session and by E-mail thereafter. Metrika, Inc. sponsored the meeting.

EVIDENCE

A literature search was performed using standard search engines.

CONSENSUS PROCESS

The panel heard each member's discussion of the issues, reviewing evidence prior to drafting conclusions. Principal conclusions were agreed on, and then specific cut points were discussed in an iterative consensus process.

CONCLUSIONS

The main factors in support of using HbA1c as a screening and diagnostic test include: 1) HbA1c does not require patients to be fasting; 2) HbA1c reflects longer-term glycemia than does plasma glucose; 3) HbA1c laboratory methods are now well standardized and reliable; and 4) errors caused by nonglycemic factors affecting HbA1c such as hemoglobinopathies are infrequent and can be minimized by confirming the diagnosis of diabetes with a plasma glucose (PG)-specific test. Specific recommendations include: 1) screening standards should be established that prompt further testing and closer follow-up, including fasting PG of 100 mg/dl or greater, random PG of 130 mg/dl or greater, or HbA1c greater than 6.0%; 2) HbA1c of 6.5-6.9% or greater, confirmed by a PG-specific test (fasting plasma glucose or oral glucose tolerance test), should establish the diagnosis of diabetes; and 3) HbA1c of 7% or greater, confirmed by another HbA1c- or a PG-specific test (fasting plasma glucose or oral glucose tolerance test) should establish the diagnosis of diabetes. The recommendations are offered for consideration of the clinical community and interested associations and societies.