Hemoglobin A1c as a diagnostic tool for diabetes screening and new-onset diabetes prediction: a 6-year community-based prospective study

Accounting for time-varying exposures and covariates in the relationship between obesity and diabetes: analysis using parametric g-formula

BACKGROUND

Previous studies investigating the association between obesity and diabetes often did not consider the role of time-varying covariates affected by previous obesity status. This study quantified the association between obesity and diabetes using parametric g-formula.

METHODS

We included 8924 participants without diabetes from the Korean Genome and Epidemiology Study-Ansan and Ansung study(2001-2002)-with up to the seventh biennial follow-up data from 2015 to 2016. Obesity status was categorised as normal (body mass index (BMI) <23.5 kg/m2), overweight (23.5-24.9 kg/m2), obese 1 (25.0-27.4 kg/m2) and obese 2 (≥27.5 kg/m2). Hazard ratios (HRs) comparing baseline or time-varying obesity status were estimated using Cox models, whereas risk ratio (RR) was estimated using g-formula.

RESULTS

The Cox model for baseline obesity status demonstrated an increased risk of diabetes in overweight (HR 1.85; 95% CI=1.48-2.31), obese 1 (2.40; 1.97-2.93) and obese 2 (3.65; 2.98-4.47) statuses than that in normal weight status. Obesity as a time-varying exposure with time-varying covariates had HRs of 1.31 (1.07-1.60), 1.55 (1.29-1.86) and 2.58 (2.14-3.12) for overweight, obese 1 and obese 2 statuses. Parametric g-formula comparing if everyone had been in each obesity category versus normal over 15 years showed increased associations of RRs of 1.37 (1.34-1.40), 1.78 (1.76-1.80) and 2.42 (2.34-2.50).

CONCLUSIONS

Higher BMI classification category was associated with increased risk of diabetes after accounting for time-varying covariates using g-formula. The results from g-formula were smaller than when considering baseline obesity status only but comparable with the results from time-varying Cox model.

Doubly robust evaluation of high-dimensional surrogate markers

When evaluating the effectiveness of a treatment, policy, or intervention, the desired measure of efficacy may be expensive to collect, not routinely available, or may take a long time to occur. In these cases, it is sometimes possible to identify a surrogate outcome that can more easily, quickly, or cheaply capture the effect of interest. Theory and methods for evaluating the strength of surrogate markers have been well studied in the context of a single surrogate marker measured in the course of a randomized clinical study. However, methods are lacking for quantifying the utility of surrogate markers when the dimension of the surrogate grows. We propose a robust and efficient method for evaluating a set of surrogate markers that may be high-dimensional. Our method does not require treatment to be randomized and may be used in observational studies. Our approach draws on a connection between quantifying the utility of a surrogate marker and the most fundamental tools of causal inference-namely, methods for robust estimation of the average treatment effect. This connection facilitates the use of modern methods for estimating treatment effects, using machine learning to estimate nuisance functions and relaxing the dependence on model specification. We demonstrate that our proposed approach performs well, demonstrate connections between our approach and certain mediation effects, and illustrate it by evaluating whether gene expression can be used as a surrogate for immune activation in an Ebola study.

Machine learning for predicting diabetes risk in western China adults

OBJECTIVE

Diabetes mellitus is a global epidemic disease. Long-time exposure of patients to hyperglycemia can lead to various type of chronic tissue damage. Early diagnosis of and screening for diabetes are crucial to population health.

METHODS

We collected the national physical examination data in Xinjiang, China, in 2020 (a total of more than 4 million people). Three types of physical examination indices were analyzed: questionnaire, routine physical examination and laboratory values. Integrated learning, deep learning and logistic regression methods were used to establish a risk model for type-2 diabetes mellitus. In addition, to improve the convenience and flexibility of the model, a diabetes risk score card was established based on logistic regression to assess the risk of the population.

RESULTS

An XGBoost-based risk prediction model outperformed the other five risk assessment algorithms. The AUC of the model was 0.9122. Based on the feature importance ranking map, we found that hypertension, fasting blood glucose, age, coronary heart disease, ethnicity, parental diabetes mellitus, triglycerides, waist circumference, total cholesterol, and body mass index were the most important features of the risk prediction model for type-2 diabetes.

CONCLUSIONS

This study established a diabetes risk assessment model based on multiple ethnicities, a large sample and many indices, and classified the diabetes risk of the population, thus providing a new forecast tool for the screening of patients and providing information on diabetes prevention for healthy populations.

Association between Nighttime Work and HbA1c Levels in South Korea

Background: As the world has become a 24 h society, people’s demands have generated various work schedules, leading to an increase in workers’ health problems. The study aimed to investigate the association between nighttime work and HbA1c levels among South Korean adults over the age of 30. Methods: Participants were selected from the 2016−2019 Korea National Health and Nutrition Survey; those diagnosed with diabetes were excluded. The dependent variable was the HbA1c level reported in the KNHANES health examination report. The main independent variable was the participant’s work schedule. Work schedules were classified into three categories based on the participant’s report: (1) day; (2) night and overnight, and (3) other. Generalized multiple linear regression was used, and the significance level was defined as p < 0.05. Results: The participants comprised 4773 men and 4818 women. Those engaged in the “day” schedule served as the reference group. Among the male participants, the “night and overnight” group had significantly larger HbA1c (%) levels than the “day” group (β = 0.061, p = 0.0085). Among these nighttime male workers, HbA1c (%) levels were particularly higher in the people who were physically inactive (β = 0.094, p = 0.0031), slept less than 7 h (β = 0.108, p = 0.0009), and skipped meals (β = 0.064, p = 0.0401). Conclusion: Our results revealed an association of nighttime work with increased HbA1c levels in male participants. High-risk groups for HbA1c levels require careful observation of physical activity, sleeping time, and eating habits.

Genetic Variants Relate to Fasting Plasma Glucose, 2-Hour Postprandial Glucose, Glycosylated Hemoglobin, and BMI in Prediabetes

Diabetes mellitus (DM) is a chronic disease that seriously threatens human health. Prediabetes is a stage in the progression of DM. The level of clinical indicators including fasting plasma glucose (FPG), 2-h postprandial glucose (2hPG), and glycosylated hemoglobin (HbA1C) are the diagnostic markers of diabetes. In this genome-wide association study (GWAS), we aimed to investigate the association of genetic variants with these phenotypes in Hainan prediabetes. In this study, we recruited 451 prediabetes patients from the residents aged ≥18 years who participated in the National Diabetes Prevalence Survey of the Chinese Medical Association in 2017. The GWAS of FPG, 2hPG, HbA1C, and body mass index (BMI) in prediabetes was analyzed with a linear model using an additive genetic model with adjustment for age and sex. We identified that rs13052524 in MRPS6 and rs62212118 in SLC5A3 were associated with 2hPG in Hainan prediabetes (p = 4.35 × 10^-6, p = 4.05 × 10^-6, respectively). Another six variants in the four genes (LINC01648, MATN1, CRAT37, and SLCO3A1) were related to HbA1C. Moreover, rs11142842, rs1891298, rs1891299, and rs11142843 in TRPM3/TMEM2 and rs78432036 in MLYCD/OSGIN1 were correlated to BMI (all p < 5 × 10^-6). This study is the first to determine the genome-wide association of FPG, 2hPG, and HbA1C, which emphasizes the importance of in-depth understanding of the phenotypes of high-value susceptibility gene markers in the diagnosis of prediabetes.

Diagnostic accuracy of tests for type 2 diabetes and prediabetes: A systematic review and meta-analysis

AIM

This systematic review aimed to ascertain the diagnostic accuracy (sensitivity and specificity) of screening tests for early detection of type 2 diabetes and prediabetes in previously undiagnosed adults.

METHODS

This systematic review included published studies that included one or more index tests (random and fasting tests, HbA1c) for glucose detection, with 75-gram Oral Glucose Tolerance Test (or 2-hour post load glucose) as a reference standard (PROSPERO ID CRD42018102477). Seven databases were searched electronically (from their inception up to March 9, 2020) accompanied with bibliographic and website searches. Records were manually screened and full text were selected based on inclusion and exclusion criteria. Subsequently, data extraction was done using standardized form and quality assessment of studies using QUADAS-2 tool. Meta-analysis was done using bivariate model using Stata 14.0. Optimal cut offs in terms of sensitivity and specificity for the tests were analysed using R software.

RESULTS

Of 7,151 records assessed by title and abstract, a total of 37 peer reviewed articles were included in this systematic review. The pooled sensitivity, specificity, positive (LR+) and negative likelihood ratio (LR-) for diagnosing diabetes with HbA1c (6.5%; venous sample; n = 17 studies) were 50% (95% CI: 42-59%), 97.3% (95% CI: 95.3-98.4), 18.32 (95% CI: 11.06-30.53) and 0.51 (95% CI: 0.43-0.60), respectively. However, the optimal cut-off for diagnosing diabetes in previously undiagnosed adults with HbA1c was estimated as 6.03% with pooled sensitivity of 73.9% (95% CI: 68-79.1%) and specificity of 87.2% (95% CI: 82-91%). The optimal cut-off for Fasting Plasma Glucose (FPG) was estimated as 104 milligram/dL (mg/dL) with a sensitivity of 82.3% (95% CI: 74.6-88.1%) and specificity of 89.4% (95% CI: 85.2-92.5%).

CONCLUSION

Our findings suggest that at present recommended threshold of 6.5%, HbA1c is more specific and less sensitive in diagnosing the newly detected diabetes in undiagnosed population from community settings. Lowering of thresholds for HbA1c and FPG to 6.03% and 104 mg/dL for early detection in previously undiagnosed persons for screening purposes may be considered.

Use and performance of machine learning models for type 2 diabetes prediction in community settings: A systematic review and meta-analysis

OBJECTIVE

We aimed to identify machine learning (ML) models for type 2 diabetes (T2DM) prediction in community settings and determine their predictive performance.

METHOD

Systematic review of ML predictive modelling studies in 13 databases since 2009 was conducted. Primary outcomes included metrics of discrimination, calibration, and classification. Secondary outcomes included important variables, level of validation, and intended use of models. Meta-analysis of c-indices, subgroup analyses, meta-regression, publication bias assessments and sensitivity analyses were conducted.

RESULTS

Twenty-three studies (40 prediction models) were included. Studies with high-, moderate-, and low- risk of bias were 3, 14, and 6 respectively. All studies conducted internal validation whereas none conducted external validation of their models. Twenty studies provided classification metrics to varying extents whereas only 7 studies performed model calibration. Eighteen studies reported information on both the variables used for model development and the feature importance. Twelve studies highlighted potential applicability of their models for T2DM screening. Meta-analysis produced a good pooled c-index (0.812). Sources of heterogeneity were identified through subgroup analyses and meta-regression. Issues pertaining to methodological quality and reporting were observed.

CONCLUSIONS

We found evidence of good performance of ML models for T2DM prediction in the community. Improvements to methodology, reporting and validation are needed before they can be used at scale.

Detection of diabetes and prediabetes using glycosylated hemoglobin in Chinese adults living in Shanghai: A prospective analysis

BACKGROUND

This study aimed to evaluate the discriminative abilities of glycosylated hemoglobin (HbA1c) and to examine the optimal HbA1c cutoff values for diabetes and prediabetes in Chinese adults.

METHODS

Data of a population-based cohort of Chinese adults aged ≥40 years living in Jiading District in Shanghai were used. At baseline, 9389 and 7241 participants were included to identify the optimal HbA1c cutoff values for diabetes and prediabetes, respectively using the 1999 World Health Organization criteria as reference. In addition, the follow-up data on incident diabetes of 4538 participants were used to determine the HbA1c cutoff value for prediabetes using the development of diabetes as reference. The discriminative abilities of HbA1c were evaluated using receiver operating characteristic (ROC) curves, and the optimal cutoff values were determined by Youden's index.

RESULTS

The areas under the ROC curves were 0.849 for diabetes, 0.614 for prediabetes using baseline data, and 0.648 for prediabetes using follow-up data. An HbA1c cutoff value of 6.0% had the largest Youden's index to diagnose diabetes with a sensitivity of 70.2% and a specificity of 87.4%. An HbA1c cutoff value of 5.6% was indicated for prediabetes using both baseline and follow-up data. However, the sensitivity and specificity were both low (55.4% and 61.1% using an oral glucose tolerance test as reference, 64.6% and 57.1% using incident diabetes as reference).

CONCLUSIONS

An HbA1c value ≥6.0% could be used to detect diabetes in Chinese adults aged ≥40 years. However, although an HbA1c value of 5.6% to 5.9% was indicated in this study, the overall discrimination of HbA1c for prediabetes was poor.

Glycated hemoglobin (HbA1c) as diagnostic criteria for diabetes: the optimal cut-off points values for the Pakistani population; a study from second National Diabetes Survey of Pakistan (NDSP) 2016-2017

AIM

Glycated hemoglobin (HbA1c) cut-off values as diagnostic tool in diabetes and prediabetes with its concordance to oral glucose tolerance test (OGTT) in Pakistani population.

METHODOLOGY

Data for this substudy was obtained from second National Diabetes Survey of Pakistan (NDSP) 2016-2017. With this survey, 10 834 individuals were recruited and after excluding known subjects with diabetes, 6836 participants fulfilled inclusion criteria for this study. Demographic, anthropometric and biochemical parameters were obtained. OGTT was used as standard diagnostic tool to screen population and HbA1c for optimal cut-off values. Participants were categorized into normal glucose tolerance (NGT), newly diagnosed diabetes (NDD) and prediabetes.

RESULTS

Out of 6836 participants, 4690 (68.6%) had NGT, 1333 (19.5%) had prediabetes and 813 (11.9%) had NDD by OGTT criteria with median (IQR) age of 40 (31-50) years. Optimal HbA1c cut-off point for identification of diabetes and prediabetes was observed as 5.7% ((AUC (95% CI)=0.776 (0.757 to 0.795), p<0.0001)) and 5.1% ((AUC (95% CI)=0.607 (0.590 to 0.624), p<0.0001)), respectively. However, out of 68.6% NGT subjects identified through OGTT, 24.1% and 9.3% participants were found to have prediabetes and NDD, respectively by using HbA1c criteria. By using both OGTT and HbA1c criteria, only 7.9% and 7.3% were observed as prediabetes and diabetes, respectively.

CONCLUSION

Findings from second NDSP demonstrated disagreement between findings of OGTT and HbA1c as diagnostic tool for Pakistani population. As compared with international guidelines, HbA1c threshold for prediabetes and NDD were lower in this part of world. HbA1c as diagnostic tool might require ethnic or regional-based modification in cut-off points, validated by relevant community-based epidemiological surveys.

Value-based healthcare delivery through metabolomics-based personalized health platform

Type 2 diabetes is routinely identified in clinical practice by tests that rely on a hyperglycemic index. However, people at risk for developing type 2 diabetes may not present with hyperglycemia. We identified several underlying risks for type 2 diabetes, insulin resistance, and associated co-morbidities, using a liquid chromatography mass spectrometry-based analysis of blood metabolites, in participants with normoglycemia and no clinical symptoms. Personalized lifestyle recommendations, including diet, exercise, and nutritional supplement recommendations, were conveyed to these participants by a web-based platform, and after 100 days of following their recommendations, these participants reported reductions in the health risks associated with type 2 diabetes and associated diseases. Our comprehensive metabolite-based assay can be used for type 2 diabetes risk stratification, and our personalized lifestyle recommendation system could be deployed as a preventative treatment option to improve health outcomes, reduce the incidence of chronic disease, and live healthier lives in an evidence-based way.

Developing new TB biomarkers, are miRNA the answer?

Efforts to reduce the global TB burden are hindered by the lack of simple, reliable non-sputum based diagnostics. To date studies investigating the biomarker potential of circulating host proteins and mRNA have not shown sufficient diagnostic utility. Recently, there has been increasing interest in circulating miRNA as a biomarker of TB disease. This review examined all published miRNA-TB biomarker studies to determine if a reproducible miRNA signature of TB disease could be elucidated. From 15 miRNA profiling studies, 894 miRNA differentially expressed between TB patients and healthy controls were identified in at least one study. Of these, 143 miRNA were validated by qPCR with 53 differentially expressed between TB patients and controls. Interestingly, only 8 of these miRNA were identified in 2 or more studies, and no consensus on a reproducible miRNA signature for identification of TB disease could be identified. TB disease is clearly associated with a wide breadth of differentially expressed miRNA. This review highlights our recent progress and the multiple factors, including environment, source of tissue, ethnicity and extent of TB disease that may influence miRNA expression. Coordinated efforts are required to validate identified targets in multiple populations to progress miRNA biomarker development.

Genome-wide Association Study of Change in Fasting Glucose over time in 13,807 non-diabetic European Ancestry Individuals

Type 2 diabetes (T2D) affects the health of millions of people worldwide. The identification of genetic determinants associated with changes in glycemia over time might illuminate biological features that precede the development of T2D. Here we conducted a genome-wide association study of longitudinal fasting glucose changes in up to 13,807 non-diabetic individuals of European descent from nine cohorts. Fasting glucose change over time was defined as the slope of the line defined by multiple fasting glucose measurements obtained over up to 14 years of observation. We tested for associations of genetic variants with inverse-normal transformed fasting glucose change over time adjusting for age at baseline, sex, and principal components of genetic variation. We found no genome-wide significant association (P < 5 × 10^-8) with fasting glucose change over time. Seven loci previously associated with T2D, fasting glucose or HbA1c were nominally (P < 0.05) associated with fasting glucose change over time. Limited power influences unambiguous interpretation, but these data suggest that genetic effects on fasting glucose change over time are likely to be small. A public version of the data provides a genomic resource to combine with future studies to evaluate shared genetic links with T2D and other metabolic risk traits.

Detection of Secondary Metabolites as Biomarkers for the Early Diagnosis and Prevention of Type 2 Diabetes

BACKGROUND

Type 2 diabetes, or T2D, is a metabolic disease that results in insulin resistance. In the present study, we hypothesize that metabolomic analysis in blood samples of T2D patients sharing the same ethnic background can recover new metabolic biomarkers and pathways that elucidate early diagnosis and predict the incidence of T2D.

METHODS

The study included 34 T2D patients and 33 healthy volunteers recruited between the years 2012 and 2013; the secondary metabolites were extracted from blood samples and analyzed using HPLC.

RESULTS

Principal coordinate analysis and hierarchical clustering patterns for the uncharacterized negatively and positively charged metabolites indicated that samples from healthy individuals and T2D patients were largely separated with only a few exceptions. The inspection of the top 10% secondary metabolites indicated an increase in fucose, tryptophan and choline levels in the T2D patients, while there was a reduction in carnitine, homoserine, allothreonine, serine and betaine as compared to healthy individuals. These metabolites participate mainly in three cross-talking pathways, namely "glucagon signaling", "glycine, serine and threonine" and "bile secretion". Reduced level of carnitine in T2D patients is known to participate in the impaired insulin-stimulated glucose utilization, while reduced betaine level in T2D patients is known as a common feature of this metabolic syndrome and can result in the reduced glycine production and the occurrence of insulin resistance. However, reduced levels of serine, homoserine and allothrionine, substrates for glycine production, indicate the depletion of glycine, thus possibly impair insulin sensitivity in T2D patients of the present study.

CONCLUSION

We introduce serine, homoserine and allothrionine as new potential biomarkers of T2D.

Development of type 2 diabetes mellitus in people with intermediate hyperglycaemia

BACKGROUND

Intermediate hyperglycaemia (IH) is characterised by one or more measurements of elevated blood glucose concentrations, such as impaired fasting glucose (IFG), impaired glucose tolerance (IGT) and elevated glycosylated haemoglobin A1c (HbA1c). These levels are higher than normal but below the diagnostic threshold for type 2 diabetes mellitus (T2DM). The reduced threshold of 5.6 mmol/L (100 mg/dL) fasting plasma glucose (FPG) for defining IFG, introduced by the American Diabetes Association (ADA) in 2003, substantially increased the prevalence of IFG. Likewise, the lowering of the HbA1c threshold from 6.0% to 5.7% by the ADA in 2010 could potentially have significant medical, public health and socioeconomic impacts.

OBJECTIVES

To assess the overall prognosis of people with IH for developing T2DM, regression from IH to normoglycaemia and the difference in T2DM incidence in people with IH versus people with normoglycaemia.

SEARCH METHODS

We searched MEDLINE, Embase, ClincialTrials.gov and the International Clinical Trials Registry Platform (ICTRP) Search Portal up to December 2016 and updated the MEDLINE search in February 2018. We used several complementary search methods in addition to a Boolean search based on analytical text mining.

SELECTION CRITERIA

We included prospective cohort studies investigating the development of T2DM in people with IH. We used standard definitions of IH as described by the ADA or World Health Organization (WHO). We excluded intervention trials and studies on cohorts with additional comorbidities at baseline, studies with missing data on the transition from IH to T2DM, and studies where T2DM incidence was evaluated by documents or self-report only.

DATA COLLECTION AND ANALYSIS

One review author extracted study characteristics, and a second author checked the extracted data. We used a tailored version of the Quality In Prognosis Studies (QUIPS) tool for assessing risk of bias. We pooled incidence and incidence rate ratios (IRR) using a random-effects model to account for between-study heterogeneity. To meta-analyse incidence data, we used a method for pooling proportions. For hazard ratios (HR) and odds ratios (OR) of IH versus normoglycaemia, reported with 95% confidence intervals (CI), we obtained standard errors from these CIs and performed random-effects meta-analyses using the generic inverse-variance method. We used multivariable HRs and the model with the greatest number of covariates. We evaluated the certainty of the evidence with an adapted version of the GRADE framework.

MAIN RESULTS

We included 103 prospective cohort studies. The studies mainly defined IH by IFG5.6 (FPG mmol/L 5.6 to 6.9 mmol/L or 100 mg/dL to 125 mg/dL), IFG6.1 (FPG 6.1 mmol/L to 6.9 mmol/L or 110 mg/dL to 125 mg/dL), IGT (plasma glucose 7.8 mmol/L to 11.1 mmol/L or 140 mg/dL to 199 mg/dL two hours after a 75 g glucose load on the oral glucose tolerance test, combined IFG and IGT (IFG/IGT), and elevated HbA1c (HbA1c5.7: HbA1c 5.7% to 6.4% or 39 mmol/mol to 46 mmol/mol; HbA1c6.0: HbA1c 6.0% to 6.4% or 42 mmol/mol to 46 mmol/mol). The follow-up period ranged from 1 to 24 years. Ninety-three studies evaluated the overall prognosis of people with IH measured by cumulative T2DM incidence, and 52 studies evaluated glycaemic status as a prognostic factor for T2DM by comparing a cohort with IH to a cohort with normoglycaemia. Participants were of Australian, European or North American origin in 41 studies; Latin American in 7; Asian or Middle Eastern in 50; and Islanders or American Indians in 5. Six studies included children and/or adolescents.Cumulative incidence of T2DM associated with IFG5.6, IFG6.1, IGT and the combination of IFG/IGT increased with length of follow-up. Cumulative incidence was highest with IFG/IGT, followed by IGT, IFG6.1 and IFG5.6. Limited data showed a higher T2DM incidence associated with HbA1c6.0 compared to HbA1c5.7. We rated the evidence for overall prognosis as of moderate certainty because of imprecision (wide CIs in most studies). In the 47 studies reporting restitution of normoglycaemia, regression ranged from 33% to 59% within one to five years follow-up, and from 17% to 42% for 6 to 11 years of follow-up (moderate-certainty evidence).Studies evaluating the prognostic effect of IH versus normoglycaemia reported different effect measures (HRs, IRRs and ORs). Overall, the effect measures all indicated an elevated risk of T2DM at 1 to 24 years of follow-up. Taking into account the long-term follow-up of cohort studies, estimation of HRs for time-dependent events like T2DM incidence appeared most reliable. The pooled HR and the number of studies and participants for different IH definitions as compared to normoglycaemia were: IFG5.6: HR 4.32 (95% CI 2.61 to 7.12), 8 studies, 9017 participants; IFG6.1: HR 5.47 (95% CI 3.50 to 8.54), 9 studies, 2818 participants; IGT: HR 3.61 (95% CI 2.31 to 5.64), 5 studies, 4010 participants; IFG and IGT: HR 6.90 (95% CI 4.15 to 11.45), 5 studies, 1038 participants; HbA1c5.7: HR 5.55 (95% CI 2.77 to 11.12), 4 studies, 5223 participants; HbA1c6.0: HR 10.10 (95% CI 3.59 to 28.43), 6 studies, 4532 participants. In subgroup analyses, there was no clear pattern of differences between geographic regions. We downgraded the evidence for the prognostic effect of IH versus normoglycaemia to low-certainty evidence due to study limitations because many studies did not adequately adjust for confounders. Imprecision and inconsistency required further downgrading due to wide 95% CIs and wide 95% prediction intervals (sometimes ranging from negative to positive prognostic factor to outcome associations), respectively.This evidence is up to date as of 26 February 2018.

AUTHORS' CONCLUSIONS

Overall prognosis of people with IH worsened over time. T2DM cumulative incidence generally increased over the course of follow-up but varied with IH definition. Regression from IH to normoglycaemia decreased over time but was observed even after 11 years of follow-up. The risk of developing T2DM when comparing IH with normoglycaemia at baseline varied by IH definition. Taking into consideration the uncertainty of the available evidence, as well as the fluctuating stages of normoglycaemia, IH and T2DM, which may transition from one stage to another in both directions even after years of follow-up, practitioners should be careful about the potential implications of any active intervention for people 'diagnosed' with IH.

Metabolomics insights into early type 2 diabetes pathogenesis and detection in individuals with normal fasting glucose

AIMS/HYPOTHESIS

Identifying the metabolite profile of individuals with normal fasting glucose (NFG [<5.55 mmol/l]) who progressed to type 2 diabetes may give novel insights into early type 2 diabetes disease interception and detection.

METHODS

We conducted a population-based prospective study among 1150 Framingham Heart Study Offspring cohort participants, age 40-65 years, with NFG. Plasma metabolites were profiled by LC-MS/MS. Penalised regression models were used to select measured metabolites for type 2 diabetes incidence classification (training dataset) and to internally validate the discriminatory capability of selected metabolites beyond conventional type 2 diabetes risk factors (testing dataset).

RESULTS

Over a follow-up period of 20 years, 95 individuals with NFG developed type 2 diabetes. Nineteen metabolites were selected repeatedly in the training dataset for type 2 diabetes incidence classification and were found to improve type 2 diabetes risk prediction beyond conventional type 2 diabetes risk factors (AUC was 0.81 for risk factors vs 0.90 for risk factors + metabolites, p = 1.1 × 10-4). Using pathway enrichment analysis, the nitrogen metabolism pathway, which includes three prioritised metabolites (glycine, taurine and phenylalanine), was significantly enriched for association with type 2 diabetes risk at the false discovery rate of 5% (p = 0.047). In adjusted Cox proportional hazard models, the type 2 diabetes risk per 1 SD increase in glycine, taurine and phenylalanine was 0.65 (95% CI 0.54, 0.78), 0.73 (95% CI 0.59, 0.9) and 1.35 (95% CI 1.11, 1.65), respectively. Mendelian randomisation demonstrated a similar relationship for type 2 diabetes risk per 1 SD genetically increased glycine (OR 0.89 [95% CI 0.8, 0.99]) and phenylalanine (OR 1.6 [95% CI 1.08, 2.4]).

CONCLUSIONS/INTERPRETATION

In individuals with NFG, information from a discrete set of 19 metabolites improved prediction of type 2 diabetes beyond conventional risk factors. In addition, the nitrogen metabolism pathway and its components emerged as a potential effector of earliest stages of type 2 diabetes pathophysiology.

Re-examining the sensitivity of HbA1c to screen for diabetes mellitus

BACKGROUND

One of the laboratory tests recommended by the American Diabetes Association (ADA) to screen for diabetes mellitus (DM) is HbA1c, and it is particularly suitable for segments of the population that cannot or are unwilling to fast for a screening test. The aim of this study was to determine whether HbA1c would be a useful tool to screen for DM in a real-world setting if ADA guidelines for repeat testing to confirm the diagnosis of DM are strictly adhered to.

METHODS

A retrospective database study was performed by extracting demographic and laboratory data from a chronic disease registry that collects data on adults from three tertiary hospitals and nine large primary care clinics in Singapore. Data were extracted and analyzed for adults not previously known to have DM whose data was captured in the registry between 2005 and 2016 with HbA1c and at least two diagnostic tests for DM (fasting plasma glucose or 2-h plasma glucose) performed within 4 weeks after HbA1c determination.

RESULTS

In all, 3928 adults were included in this study. The sensitivity, specificity, and area under the receiver operating characteristic curve for HbA1c at a threshold of 6.5% were 85.2%, 82.3%, and 0.914, respectively. A higher sensitivity was found in female adults, younger adults, and those of non-Chinese ethnicity.

CONCLUSIONS

The sensitivity of HbA1c as a screening test for DM in this study was significantly higher than that reported previously. This work provides additional evidence supporting the inclusion of HbA1c as one of the screening tests for DM.

The simultaneous assessment of glycosylated hemoglobin, fasting plasma glucose and oral glucose tolerance test does not improve the detection of type 2 diabetes mellitus in Colombian adults

INTRODUCTION

Guidelines recommend early detection of type 2 diabetes mellitus (DM2). The objective of the present study was to evaluate the capacity to identify DM2 in subjects that were screened for DM2 simultaneously with all three of the tests recommended-fasting plasma glucose (FPG), glycosylated hemoglobin (HbA1c) and a 2-hour post 75-g oral glucose tolerance test (OGTT).

METHODS AND RESULTS

The present analysis of an anonymous database of 1113 adults from a reference clinical laboratory in Bucaramanga, Colombia, was an observational, descriptive, cross-sectional secondary source study. 259 individuals met at least one of the criteria for DM2: FPG ≥ 126mg/dL (7.0mmol/L), HbA1c ≥ 6.5% (48mmol/mol) and OGTT ≥ 200mg/dL (11.1mmol/L). 30 subjects (2.7%) were diabetic according to FPG, 56 subjects (5.0%) by HbA1c and 250 subjects (22.5%) by OGTT. In total 259 subjects (23.3% [IC 95%: 20.7%- 25.8%] were diabetic either by FPG, OGTT or HbA1c.

DISCUSSION

The largest number of patients were identified as diabetic with the OGTT. The combination of two or three tests did not increase the detection of new cases of DM2. Our findings suggest that routinely requesting FPG, OGTT and HbA1c at the same time may be inappropriate in at risk individuals, as this approach does not significantly improve the diagnostic capacity compared to using FPG+OGTT and substantially increases the financial burden on the health system, insurers or individual.

The influence of prehypertension, hypertension, and glycated hemoglobin on the development of type 2 diabetes mellitus in prediabetes: the Korean Genome and Epidemiology Study (KoGES)

BACKGROUND

It has been reported that elevated blood pressure (BP) was significantly associated with the increased risk for type 2 diabetes mellitus (T2DM). However, there is still limited information about the influence of BP on the risk for T2DM across the level of glycated hemoglobin (HbA1c).

METHOD

In a cohort of the Korean Genome and Epidemiology Study (KoGES), 2830 non-diabetic Korean adults with prediabetes defined by HbA1c level of 5.7-6.4% were followed-up for 10 years. Multivariate cox proportional hazards assumption was used to assess the risk for T2DM according to the baseline BP categories (normal, prehypertension and hypertension) and HbA1c level (low: 5.7-5.9% and high: 6.0-6.4%).

RESULTS

The risk for T2DM significantly increased proportionally to BP categories (adjusted HR; reference in normal BP, 1.32 [1.10-1.59] in prehypertension and 1.61 [1.35-1.92] in hypertension). Subgroup analysis indicated that individuals with high HbA1c had the higher risk for T2DM than individuals with low HbA1c regardless of BP. Additionally, combined presence of hypertension and high HbA1c had the highest risk for T2DM (adjusted HR: 3.82 [3.00-4.87]). In each systolic and diastolic BP level, the risk for T2DM significantly increased from systolic BP ≥ 130 mmHg (adjusted HRs: 1.39 ([1.15-1.71]) and diastolic BP ≥ 80 mmHg (adjusted HRs: 1.30 ([1.07-1.58]).

CONCLUSION

BP and HbA1c may be useful tools in identifying individuals with prediabetes more potentially predisposed to T2DM. Prospective studies should be considered to examine whether controlling BP actually lowers the risk for T2DM.

HbA1c Cutoff Point of 5.9% Better Identifies High Risk of Progression to Diabetes among Chinese Adults: Results from a Retrospective Cohort Study

AIMS

This article performed a retrospective cohort study to estimate the annual incidence rates of diabetes and to assess the utility of HbA1c as a predictor for progression to diabetes in Chinese community adults aged 40 years or older.

METHODS

In all, 2778 nondiabetic subjects (including 1901 women) underwent HbA1c testing and oral glucose tolerance test (OGTT) measurements at baseline and after 3 years. Diabetes and prediabetes were defined using the WHO criteria. The HbA1c cutoff points were evaluated to predict the future risks of diabetes. Relative risk (RR) was calculated using the chi-square test. The area under the receiver operating characteristic (ROC) curve (AUC) was used to evaluate the predictive efficiency of fasting plasma glucose (FPG), 2 hr postprandial plasma glucose (2hPG), and HbA1c for progression to diabetes. A superior cutoff point was defined as the point on the ROC curve with a larger Youden index.

RESULTS

Overall, 7.5% (210/2778) of the subjects progressed to diabetes, yielding an annual 2.5% diabetes incidence rate. Additionally, 4.5% (100/2227) of the subjects with normal glucose tolerance (NGT) and 19.6% (110/561) of the subjects with prediabetes progressed to diabetes, and the relative risk of progression to diabetes was 5.188 times higher in subjects with prediabetes than in subjects with NGT (p < 0.001). Compared to subjects with HbA1c values ≤ 5.6%, the RRs of progression to diabetes in subjects whose HbA1c ranged from 5.7 to 5.8%, 5.9 to 6.2%, 6.3 to 6.4%, and ≥6.5% were 1.165, 2.582, 5.732, and 16.619, respectively. However, the RRs for subjects with HbA1c ranging from 5.7 to 5.8% and those with HbA1c ≤ 5.6% did not differ significantly (p = 0.615). The AUCs for predicting diabetes after 3 years by FPG, 2hPG, and HbA1c were 0.752 (95% confidence interval 0.718-0.787), 0.710 (95% confidence interval 0.671-0.748), and 0.756 (95% confidence interval 0.720-0.793), respectively. The HbA1c cutoff point of 5.9% (sensitivity of 0.771 and specificity of 0.580) may better identify individuals at high risk of progression to diabetes than the 5.7% value (sensitivity of 0.862 and specificity of 0.371) due to the former's larger Youden index of 0.351, which exceeded the indices for FPG and 2hPG.

CONCLUSIONS

The use of HbA1c values ≥ 5.9% may provide greater accuracy in evaluating the risk of progression to diabetes and identify individuals with prediabetes with greater reliability among Chinese adults.

Prediction of Type 2 Diabetes by Hemoglobin A1c in Two Community-Based Cohorts

OBJECTIVE

Hemoglobin A_1c (HbA_1c) can be used to assess type 2 diabetes (T2D) risk. We asked whether HbA_1c was associated with T2D risk in four scenarios of clinical information availability: 1) HbA_1c alone, 2) fasting laboratory tests, 3) clinic data, and 4) fasting laboratory tests and clinic data.

RESEARCH DESIGN AND METHODS

We studied a prospective cohort of white (N = 11,244) and black (N = 2,294) middle-aged participants without diabetes in the Framingham Heart Study and Atherosclerosis Risk in Communities study. Association of HbA_1c with incident T2D (defined by medication use or fasting glucose [FG] ≥126 mg/dL) was evaluated in regression models adjusted for 1) age and sex (demographics); 2) demographics, FG, HDL, and triglycerides; 3) demographics, BMI, blood pressure, and T2D family history; or 4) all preceding covariates. We combined results from cohort and race analyses by random-effects meta-analyses. Subsidiary analyses tested the association of HbA_1c with developing T2D within 8 years or only after 8 years.

RESULTS

Over 20 years, 3,315 individuals developed T2D. With adjustment for demographics, the odds of T2D increased fourfold for each percentage-unit increase in HbA_1c. The odds ratio (OR) was 4.00 (95% CI 3.14, 5.10) for blacks and 4.73 (3.10, 7.21) for whites, resulting in a combined OR of 4.50 (3.35, 6.03). After adjustment for fasting laboratory tests and clinic data, the combined OR was 2.68 (2.15, 3.34) over 20 years, 5.79 (2.51, 13.36) within 8 years, and 2.23 (1.94, 2.57) after 8 years.

CONCLUSIONS

HbA_1c predicts T2D in different common scenarios and is useful for identifying individuals with elevated T2D risk in both the short- and long-term.

Prediabetes in Colombia: Expert Consensus

The prevalence of Prediabetes in Colombia is high, and despite being recognized and categorized in the main Medical Guidelines and included in the International Classification of Diseases in Colombia, knowledge and awareness of it is limited amongst healthcare professionals and in the community. Our expert group recommends that educational programs emphasize a global approach to risk which includes a recognition of the importance of prediabetes and its evaluation along with and other risk factors such as a family history of DM2, overweight and obesity, dislipidemia and hypertension. Studies conducted in Colombia demonstrate the value of the FINDRIS questionnaire as a tool to identify subjects at risk of prediabetes and DM2, and we recommend that it should be systematic applied throughout the country as part of government policy. Prediabetes progresses to DM2 at an annual rate of 10%, but it has also been shown that prediabetes is an independent risk factor for cardiovascular outcomes. On this basis, the Committee recommends that once prediabetes is detected and diagnosed, immediate management of the disease begins through lifestyle changes, with follow up assessments performed at 3 and 6 months. If the patient does not respond with a weight loss of at least 5% and if the HbA1C values ​​are not normalized, pharmacological management should be initiated with a metformin dose of 500 mg / day, increasing up to 1,500 - 1,700 mg / day, according to tolerance.

The influence of physical activity on risk of cardiovascular disease in people who are obese but metabolically healthy

The metabolic outcomes of metabolically healthy obesity (MHO) remain controversial. The aim of the present study was to determine the effect of physical activity on the cardiovascular disease (CVD) outcomes of MHO. The study included participants who were followed for 10 years and recruited from the Korean Genome and Epidemiology Study (KoGES), a population-based cohort study. Participants with previously recorded CVDs or cancer, or who had received steroids or anticoagulants at baseline were excluded. A total of 8144 participants (3,942 men and 4,202 women) fulfilled inclusion criteria. In a multivariate Cox regression model adjusted for age and sex, MHO participants were not at elevated risk of CVD compared with their metabolically healthy non-obese (MHNO) counterparts (HR, 1.28; 95% CI, 0.96–1.71), although both the non-obese (HR, 1.50; 95% CI, 1.19–1.90) and obese (HR, 1.85; 95% CI, 1.48–2.30) participants with metabolic abnormalities were at elevated risk. However, in the subgroup analysis by physical activity, physically inactive MHO participants had a significantly higher HR for CVD events compared to active MHNO participants (HR, 1.54; 95% CI, 1.03–2.30), while active MHO participants were not at elevated risk (HR, 1.15; 95% CI, 0.70–1.89). Physically inactive MHO participants had significantly increased risk of CVD compared to physically active MHNO participants whereas physically active MHO participants did not.

Mitochondrial DNA copy number augments performance of A1C and oral glucose tolerance testing in the prediction of type 2 diabetes

Here, we tested the performance of the mitochondrial DNA copy number (mtDNA-CN) in predicting future type 2 diabetes (n = 1108). We used the baseline clinical data (age, sex, body mass index, waist-to-hip ratio, systolic and diastolic blood pressure) and the mtDNA-CN, hemoglobin A1c (A1C) levels and results of oral glucose tolerance test (OGTT) including fasting plasma glucose, 1-hour glucose, and 2-hour glucose levels, to predict future diabetes. We built a prediction model using the baseline data and the diabetes status at biannual follow-up of 8 years. The mean area under curve (AUC) for all follow-ups of the full model including all variables was 0.92 ± 0.04 (mean ± standard deviation), while that of the model excluding the mtDNA-CN was 0.90 ± 0.03. The sensitivity of the f4ull model was much greater than that of the model not including mtDNA-CN: the mean sensitivities of the model with and without mtDNA-CN were 0.60 ± 0.06 and 0.53 ± 0.04, respectively. We found that the mtDNA-CN of peripheral leukocytes is a biomarker that augments the predictive power for future diabetes of A1C and OGTT. We believe that these results could provide invaluable information for developing strategies for the management of diabetes.

Patterns of diabetes care in Slovenia, Croatia, Serbia, Bulgaria and Romania : An observational, non-interventional, cross-sectional study

BACKGROUND

National guidelines for treating type 2 diabetes in the Balkans generally follow European guidelines. The current study was undertaken to estimate the rate of glycated hemoglobin (HbA1c) measurements and level of HbA1c control in diabetic patients treated in regular clinical practice settings in the Balkans and to evaluate if providing HbA1c measurements improves adherence to treatment guidelines.

METHODS

This cross-sectional study enrolled type 2 diabetic patients treated by 79 primary care physicians and 102 specialists. The participants were provided with HbA1c measuring devices to measure HbA1c during regular office visits and a physician survey evaluated HbA1c the results feedback. Relevant clinical, demographic, drug treatment and specialist referral data were extracted from patient charts. Descriptive statistics and stepwise multivariate regression analysis were used.

RESULTS

Among 1853 patients included (average age 63.5 ± 10.7 years, 51% male) the average diabetes duration was 8.9 ± 7.1 years, 40% of patients had HbA1c measured every 6 months and 34% every 12 months (or less frequently). The rate of 6‑month measurement was higher among specialists (43%) vs. primary care physicians (32%, p < 0.01). The average HbA1c was 7.3 ± 1.5 and 35% of patients achieved the target HbA1c level of < 6.5%. Metformin monotherapy was prescribed to 28% of patients and metformin + sulphonylurea to 23%, 55% of patients on metformin monotherapy and 32% of patients on dual therapy metformin + sulphonylurea achieved the target HbA1c < 6.5%. Treatment remained unchanged in 91% and was stepped up in only 7.2% of patients. Physicians were not surprised (in 79% of patients) or were pleasantly surprised (in 11%) by the HbA1c results at the time of visit. Average diabetes duration and patient use of home glucometers were associated with the level of disease control.

CONCLUSIONS

The rates of HbA1c measurements remain low in the Balkans, although higher among specialists. Over 60% of patients, mostly treated with traditional oral antidiabetics did not achieve disease control. Providing convenient HbA1c measurement devices was not associated with a marked change in diabetes management. Future research is needed to evaluate the impact of these treatment patterns on long-term outcomes and costs to society.

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.

PERFORMANCE OF A1C VERSUS OGTT FOR THE DIAGNOSIS OF PREDIABETES IN A COMMUNITY-BASED SCREENING

OBJECTIVE

Reliable identification of individuals at risk for developing diabetes is critical to instituting preventative strategies. Studies suggest that the accuracy of using hemoglobin A1c as a sole diagnostic criterion for diabetes may be variable across different ethnic groups. We postulate that there will be lack of concordance between A1c and the oral glucose tolerance test (OGTT) for diagnosing prediabetes across Hispanic and non-Hispanic white (NHW) populations.

METHODS

A total of 218 asymptomatic adults at risk for type 2 diabetes (T2D) were assessed with A1c and OGTT for the diagnosis of prediabetes. Glucose homeostasis status was assigned as no diabetes (A1c <5.7% [39 mmol/mol]), prediabetes (A1c 5.7 to 6.4% [46 mmol/mol]), and T2D (A1c >6.4% [46 mmol/mol]). Inclusion criteria were age >18 years and at least one of the following: a family history of diabetes, a history of gestational diabetes, Hispanic ethnicity, non-Caucasian race, or obesity. Subjects received a fasting 75-g OGTT and A1c on the same day. Bowker's test of symmetry was employed to determine agreement between the tests.

RESULTS

Data from 99 Hispanic patients and 79 NHW patients were analyzed. There was no concordance between A1c and OGTT for Hispanic (P = .002) or NHW individuals (P = .003) with prediabetes.

CONCLUSION

A1c is discordant with OGTT among Hispanic and NHW subjects for the diagnosis of prediabetes. Sole use of A1c to designate glycemic status will result in a greater prevalence of prediabetes among Hispanic and NHW New Mexicans.

ABBREVIATIONS

A1c = hemoglobin A1c BMI = body mass index CDC = Centers for Disease Control CI = confidence interval FPG = fasting plasma glucose NHW = non-Hispanic white OGTT = oral glucose tolerance test T2D = type 2 diabetes WHO = World Health Organization.

Type 2 Diabetes Prevention: Implications of Hemoglobin A1c Genetics

Hemoglobin A1c (HbA1c) is a biomarker used for population-level screening of type 2 diabetes (T2D) and risk stratification. Large-scale, genome-wide association studies have identified multiple genomic loci influencing HbA1c. We discuss the challenges of classifying these genomic loci as influencing HbA1c through glycemic or nonglycemic pathways, based on their probable biology and pleiotropic associations with erythrocyte traits. We show that putative nonglycemic genetic variants have a measurable, albeit small, impact on the classification of T2D status by HbA1c in white and Asian populations. Accounting for their effect on HbA1c may be relevant when screening populations with higher frequencies of nonglycemic HbA1c-altering alleles. As carriers of such HbA1c-altering alleles have HbA1c levels that may not accurately reflect overall glycemia, we describe how accounting for genotype may improve the performance of HbA1c in T2D prediction models and risk stratification, allowing for lifestyle intervention strategies to be directed towards those who are truly at elevated risk for developing T2D. In a Mendelian randomization framework, genetic variants can be used as instrumental variables to estimate causal relationships between HbA1c and T2D-related complications. This approach may help to support or refute HbA1c as an appropriate biomarker for long-term health outcomes in the general population.

Led Astray by Hemoglobin A1c: A Case of Misdiagnosis of Diabetes by Falsely Elevated Hemoglobin A1c

Hemoglobin A1c (A1c) is used frequently to diagnose and treat diabetes mellitus. Therefore, it is important be aware of factors that may interfere with the accuracy of A1c measurements. This is a case of a rare hemoglobin variant that falsely elevated a nondiabetic patient’s A1c level and led to a misdiagnosis of diabetes. A 67-year-old male presented to endocrine clinic for further management after he was diagnosed with diabetes based on an elevated A1c of 10.7%, which is approximately equivalent to an average blood glucose of 260 mg/dL. Multiple repeat A1c levels remained >10%, but his home fasting and random glucose monitoring ranged from 92 to 130 mg/dL. Hemoglobin electrophoresis and subsequent genetic analysis diagnosed the patient with hemoglobin Wayne, a rare hemoglobin variant. This variant falsely elevates A1c levels when A1c is measured using cation-exchange high-performance liquid chromatography. When the boronate affinity method was applied instead, the patient’s A1c level was actually 4.7%. Though hemoglobin Wayne is clinically silent, this patient was erroneously diagnosed with diabetes and started on an antiglycemic medication. Due to this misdiagnosis, the patient was at risk of escalation in his “diabetes management” and hypoglycemia. Therefore, it is important that providers are aware of factors that may result in hemoglobin A1c inaccuracy including hemoglobin variants.

Performance of HbA1c for the prediction of diabetes in a rural community in Korea

AIM

To investigate the performance of HbA1c in predicting incident diabetes among Korean adults with normal fasting glucose and impaired fasting glucose levels.

METHODS

This study used data from the Korean Genome Epidemiology Study-Kangwha Study. A prospective analysis was carried out on 2079 people (820 men and 1259 women) who completed follow-up examinations up until 2013. Diabetes was defined as fasting blood glucose level ≥ 7.0 mmol/l, HbA1c level ≥ 48 mmol/mol (6.5%), or current treatment for diabetes. Areas under the receiver-operating characteristic curves were used to assess the different performances of HbA1c , glucose and insulin in predicting diabetes.

RESULTS

The median follow-up time was 3.97 years, during which 7.7% of men and 6.3% of women developed incident diabetes. The areas under the receiver-operating curves (95% CI) for diabetes prediction were 0.740 (0.692-0.787) for HbA1c , 0.716 (0.667-0.764) for glucose and 0.598 (0.549-0.648) for insulin. HbA1c showed better predictive power in people with impaired fasting glucose (area under the curve 0.753, 95% CI 0.685-0.821) than in those with normal glucose (area under the curve 0.648, 95% CI 0.577-0.719). An HbA1c threshold of 40 mmol/mol (5.8%) was found to have the highest predictive value for diabetes, with a relative risk of 6.30 (95% CI 3.49-11.35) in men and 3.52 (95% CI 2.06-6.03) in women after adjusting for age, waist circumference, triglycerides, hypertension, family history of diabetes, smoking, alcohol intake, exercise and baseline glucose level.

CONCLUSIONS

HbA1c can be used to identify people at high risk for the development of diabetes, especially in those with impaired fasting glucose levels.

Association of Exposure to Radio-Frequency Electromagnetic Field Radiation (RF-EMFR) Generated by Mobile Phone Base Stations with Glycated Hemoglobin (HbA1c) and Risk of Type 2 Diabetes Mellitus

Installation of mobile phone base stations in residential areas has initiated public debate about possible adverse effects on human health. This study aimed to determine the association of exposure to radio frequency electromagnetic field radiation (RF-EMFR) generated by mobile phone base stations with glycated hemoglobin (HbA1c) and occurrence of type 2 diabetes mellitus. For this study, two different elementary schools (school-1 and school-2) were selected. We recruited 159 students in total; 96 male students from school-1, with age range 12–16 years, and 63 male students with age range 12–17 years from school-2. Mobile phone base stations with towers existed about 200 m away from the school buildings. RF-EMFR was measured inside both schools. In school-1, RF-EMFR was 9.601 nW/cm² at frequency of 925 MHz, and students had been exposed to RF-EMFR for a duration of 6 h daily, five days in a week. In school-2, RF-EMFR was 1.909 nW/cm² at frequency of 925 MHz and students had been exposed for 6 h daily, five days in a week. 5–6 mL blood was collected from all the students and HbA1c was measured by using a Dimension Xpand Plus Integrated Chemistry System, Siemens. The mean HbA1c for the students who were exposed to high RF-EMFR was significantly higher (5.44 ± 0.22) than the mean HbA1c for the students who were exposed to low RF-EMFR (5.32 ± 0.34) (p = 0.007). Moreover, students who were exposed to high RF-EMFR generated by MPBS had a significantly higher risk of type 2 diabetes mellitus (p = 0.016) relative to their counterparts who were exposed to low RF-EMFR. It is concluded that exposure to high RF-EMFR generated by MPBS is associated with elevated levels of HbA1c and risk of type 2 diabetes mellitus.

Cardiovascular disease incidence, mortality and case fatality related to diabetes and metabolic syndrome: A community-based prospective study (Ansung-Ansan cohort 2001-12)

BACKGROUND

We evaluated the separate and combined effect of metabolic syndrome (MS) and diabetes on incident cardiovascular disease (CVD), CVD mortality and case fatality risk (CFR).

METHODS

8898 subjects were categorized into four groups on the basis of the presence of MS and diabetes (with MS, with diabetes, with both or without either). We compared the development of CVD events, mortality and CFR.

RESULTS

Over a mean follow-up of 8.0 years, 690 subjects developed CVD. There were 434 deaths, of which 101 were from CVD. The presence of diabetes alone, MS alone, or both was associated with an increased risk for incident CVD and CVD mortality. Compared with the MS only group, the adjusted hazard ratio (HR) for CVD events and CVD mortality in the diabetes only group was 1.07 (95% confidence interval [CI] 0.77-1.48) and 2.02 (95% CI 0.99-1.72), respectively. Among individuals with diabetes, the presence of MS did not significantly increase CVD risk and CVD mortality. The adjusted odds ratio for CVD CFR, including adjustment for the presence of MS, in subjects with diabetes versus without diabetes was 2.11 (95% CI 1.34-3.31).

CONCLUSIONS

There was no difference in the risk of incident CVD between individuals with diabetes alone and MS alone, whereas CVD mortality was much higher in individuals with diabetes only. The presence of MS did not exhibit an additive effect on CVD risk and mortality in individuals with diabetes. Individuals with diabetes had a higher CVD case fatality regardless of the presence of MS.

Systematic Review and Meta-Analysis of Response Rates and Diagnostic Yield of Screening for Type 2 Diabetes and Those at High Risk of Diabetes

Background

Screening for type 2 diabetes (T2DM) and individuals at risk of diabetes has been advocated, yet information on the response rate and diagnostic yield of different screening strategies are lacking.

Methods

Studies (from 1998 to March/2015) were identified through Medline, Embase and the Cochrane library and included if they used oral glucose tolerance test (OGTT) and WHO-1998 diagnostic criteria for screening in a community setting. Studies were one-step strategy if participants were invited directly for OGTT and two, three/four step if participants were screened at one or more levels prior to invitation to OGTT. The response rate and diagnostic yield were pooled using Bayesian random-effect meta-analyses.

Findings

47 studies (422754 participants); 29 one-step, 11 two-step and seven three/four-step were identified. Pooled response rate (95% Credible Interval) for invitation to OGTT was 65.5% (53.7, 75.6), 63.1% (44.0, 76.8), and 85.4% (76.4, 93.3) in one, two and three/four-step studies respectively. T2DM yield was 6.6% (5.3, 7.8), 13.1% (4.3, 30.9) and 27.9% (8.6, 66.3) for one, two and three/four-step strategies respectively. The number needed to invite to the OGTT to detect one case of T2DM was 15, 7.6 and 3.6 in one, two, and three/four-step strategies. In two step strategies, there was no difference between the response or yield rates whether the first step was blood test or risk-score. There was evidence of substantial heterogeneity in rates across study populations but this was not explained by the method of invitation, study location (rural versus urban) and developmental index of the country in which the study was performed.

Conclusions

Irrespective of the invitation method, developmental status of the countries and or rural/urban location, using a multi-step strategy increases the initial response rate to the invitation to screening for diabetes and reduces the number needed to have the final diagnostic test (OGTT in this study) for a definite diagnosis.

Effects of diabetes definition on global surveillance of diabetes prevalence and diagnosis: a pooled analysis of 96 population-based studies with 331,288 participants

BACKGROUND

Diabetes has been defined on the basis of different biomarkers, including fasting plasma glucose (FPG), 2-h plasma glucose in an oral glucose tolerance test (2hOGTT), and HbA1c. We assessed the effect of different diagnostic definitions on both the population prevalence of diabetes and the classification of previously undiagnosed individuals as having diabetes versus not having diabetes in a pooled analysis of data from population-based health examination surveys in different regions.

METHODS

We used data from 96 population-based health examination surveys that had measured at least two of the biomarkers used for defining diabetes. Diabetes was defined using HbA1c (HbA1c ≥6·5% or history of diabetes diagnosis or using insulin or oral hypoglycaemic drugs) compared with either FPG only or FPG-or-2hOGTT definitions (FPG ≥7·0 mmol/L or 2hOGTT ≥11·1 mmol/L or history of diabetes or using insulin or oral hypoglycaemic drugs). We calculated diabetes prevalence, taking into account complex survey design and survey sample weights. We compared the prevalences of diabetes using different definitions graphically and by regression analyses. We calculated sensitivity and specificity of diabetes diagnosis based on HbA1c compared with diagnosis based on glucose among previously undiagnosed individuals (ie, excluding those with history of diabetes or using insulin or oral hypoglycaemic drugs). We calculated sensitivity and specificity in each survey, and then pooled results using a random-effects model. We assessed the sources of heterogeneity of sensitivity by meta-regressions for study characteristics selected a priori.

FINDINGS

Population prevalence of diabetes based on FPG-or-2hOGTT was correlated with prevalence based on FPG alone (r=0·98), but was higher by 2-6 percentage points at different prevalence levels. Prevalence based on HbA1c was lower than prevalence based on FPG in 42·8% of age-sex-survey groups and higher in another 41·6%; in the other 15·6%, the two definitions provided similar prevalence estimates. The variation across studies in the relation between glucose-based and HbA1c-based prevalences was partly related to participants' age, followed by natural logarithm of per person gross domestic product, the year of survey, mean BMI, and whether the survey population was national, subnational, or from specific communities. Diabetes defined as HbA1c 6·5% or more had a pooled sensitivity of 52·8% (95% CI 51·3-54·3%) and a pooled specificity of 99·74% (99·71-99·78%) compared with FPG 7·0 mmol/L or more for diagnosing previously undiagnosed participants; sensitivity compared with diabetes defined based on FPG-or-2hOGTT was 30·5% (28·7-32·3%). None of the preselected study-level characteristics explained the heterogeneity in the sensitivity of HbA1c versus FPG.

INTERPRETATION

Different biomarkers and definitions for diabetes can provide different estimates of population prevalence of diabetes, and differentially identify people without previous diagnosis as having diabetes. Using an HbA1c-based definition alone in health surveys will not identify a substantial proportion of previously undiagnosed people who would be considered as having diabetes using a glucose-based test.

FUNDING

Wellcome Trust, US National Institutes of Health.

Do body mass index trajectories affect the risk of type 2 diabetes? A case-control study

Background

Although obesity is a well-studied risk factor for diabetes, there remains an interest in whether “increasing body mass index (BMI),” “high BMI per se,” or both are the actual risk factors for diabetes. The present study aimed to retrospectively compare BMI trajectories of individuals with and without diabetes in a case–control design and to assess whether increasing BMI alone would be a risk factor.

Methods

Using comprehensive health check-up data measured over ten years, we conducted a case–control study and graphically drew the trajectories of BMIs among diabetic patients and healthy subjects, based on coefficients in fitted linear mixed-effects models. Patient group was matched with healthy control group at the onset of diabetes with an optimal matching method in a 1:10 ratio. Simple fixed-effects models assessed the differences in increasing BMIs over 10 years between patient and control groups.

Results

At the time of matching, the mean ages in male patients and controls were 59.3 years [standard deviation (SD) = 9.2] and 57.7 years (SD = 11.2), whereas the mean BMIs were 25.0 kg/m² (SD = 3.1) and 25.2 kg/m² (SD = 2.9), respectively. In female patients and controls, the mean ages were 61.4 years (SD = 7.9) and 60.1 years (SD = 9.6), whereas the mean BMIs were 24.8 kg/m² (SD = 3.5) and 24.9 kg/m² (SD = 3.4), respectively. The simple fixed-effects models detected no statistical significance for the differences of increasing BMIs between patient and control groups in males (P = 0.19) and females (P = 0.67). Sudden increases in BMI were observed in both male and female patients when compared with BMIs 1 year prior to diabetes onset.

Conclusions

The present study suggested that the pace of increasing BMIs is similar between Japanese diabetic patients and healthy individuals. The increasing BMI was not detected to independently affect the onset of type 2 diabetes.

Prevalence of Prediabetes and Undiagnosed Diabetes in Canada (2007-2011) According to Fasting Plasma Glucose and HbA1c Screening Criteria

OBJECTIVE

To provide the first population-based estimates of prediabetes and undiagnosed type 2 diabetes prevalence in Canada.

RESEARCH DESIGN AND METHODS

We combined two fasting subsamples of the Canadian Health Measures Survey, which were restricted to nonpregnant adults ≥20 years of age (N = 3,494). Undiagnosed diabetes was defined as not having self-reported type 2 diabetes but having blood glucose measures that met Canadian guidelines (i.e., fasting plasma glucose [FPG] level of ≥7.0 mmol/L or hemoglobin A1c [HbA1c] level of ≥6.5% [≥48 mmol/mol]). Prediabetes was defined as an FPG level of ≥6.1 and <7.0 mmol/L or an HbA1c level of ≥6.0% and <6.5% (≥42 and <48 mmol/mol). All estimates were weighted using survey sampling weights. CIs were calculated with the bootstrap method.

RESULTS

According to FPG levels, the prevalence of undiagnosed type 2 diabetes in Canadian adults was 1.13% (95% CI 0.79, 1.62), contributing to ∼20% of total type 2 diabetes prevalence (5.62 [95% CI 4.52, 6.95]). Compared with FPG levels, the undiagnosed prevalence was greater using HbA1c level as a criterion (3.09% [95% CI 1.97, 4.81]), ∼41% of the total number of cases of diabetes (7.55 [95% CI 5.98, 9.49]). The HbA1c-only criterion resulted in a threefold increase in prediabetes prevalence overall and a sixfold increase among females (FPG 2.22%, HbA1c 13.31%). Screening based on FPG only identified older undiagnosed case patients, with a mean age of 58.7 years (95% CI 59.9, 63.4). Similarly, using HbA1c identified younger individuals with prediabetes, with reduced BMI and waist circumference compared with FPG levels.

CONCLUSIONS

In this first study of a nationally representative sample with biospecimen measures, we found that the prevalence of undiagnosed type 2 diabetes and prediabetes was significantly higher using HbA1c levels compared with FPG levels. Further evaluation is needed to fully assess the impact of using the HbA1c criterion.

HbA1c Predicts Time to Diagnosis of Type 1 Diabetes in Children at Risk

Prediction of type 1 diabetes is based on the detection of multiple islet autoantibodies in subjects who are at increased genetic risk. Prediction of the timing of diagnosis is challenging, however. We assessed the utility of HbA1c levels in predicting the clinical disease in genetically predisposed children with multiple autoantibodies. Cord blood samples from 168,055 newborn infants were screened for class II HLA genotypes in Finland, and 14,876 children with increased genetic risk for type 1 diabetes were invited to participate in regular follow-ups, including screening for diabetes-associated autoantibodies. When two or more autoantibodies were detected, HbA1c levels were analyzed at each visit. During follow-up, multiple (two or more) autoantibodies developed in 466 children; type 1 diabetes was diagnosed in 201 of these children (43%, progressors), while 265 children remained disease free (nonprogressors) by December 2011. A 10% increase in HbA1c levels in samples obtained 3-12 months apart predicted the diagnosis of clinical disease (hazard ratio [HR] 5.7 [95% CI 4.1-7.9]) after a median time of 1.1 years (interquartile range [IQR] 0.6-3.1 years) from the observed rise of HbA1c. If the HbA1c level was ≥5.9% (41 mmol/mol) in two consecutive samples, the median time to diagnosis was 0.9 years (IQR 0.3-1.5, HR 11.9 [95% CI 8.8-16.0]). In conclusion, HbA1c is a useful biochemical marker when predicting the time to diagnosis of type 1 diabetes in children with multiple autoantibodies.

Comparison of fasting plasma glucose and glycated hemoglobin for diagnosing diabetes in a Taiwanese population

BACKGROUND

The purposes of this study were to examine the impact of using glycated hemoglobin (HbA1c) as a diagnostic criterion for (pre)diabetes and to determine the appropriate HbA1c cutoff value in a Taiwanese population.

METHODS

We used a dataset from the Clinical Informatics Research & Development Center of Taichung Veteran General Hospital. Fasting plasma glucose (FPG) and HbA1c test results were obtained from outpatient laboratory reports produced from January 1, 2011, to April 30, 2012. A total of 4920 blood tests were analyzed. For each potential HbA1c cutoff value, the sensitivity, specificity, positive and negative predictive values, and area under the receiver operator characteristic curve (AUC) were calculated at FPG levels of 100 and 126 mg/dL. Two-sample t- and chi-sqaured tests were used to compare differences in characteristics between individuals matching the definitions of diabetes set by the American Diabetes Association (ADA) in 2009 and 2010.

RESULTS

Among the 4920 study subjects, 580 people had an FPG value < 126 mg/dL and an HbA1c ≥ 6.5%. After the diagnostic criterion of HbA1c percentage was applied, the numbers of patients with normoglycemia and prediabetes decreased, whereas the number of diabetic patients increased. For FPG levels of 100 and 126 mg/dL, the HbA1c cutoff points were 5.95% and 6.35%, respectively.

CONCLUSIONS

More patients were diagnosed with diabetes when HbA1c was added as a diagnostic criterion. HbA1c thresholds of 5.95% and 6.35% were highly specific for prediabetes and diabetes, respectively, in Taiwanese adults.

Sex factors in the metabolic syndrome as a predictor of cardiovascular disease

BACKGROUND

Metabolic syndrome (MetS) is a condition characterized by a cluster of metabolic disorders and is associated with increased risk of cardiovascular disease (CVD). This study analyzed data from the Korean Health and Genome Study to examine the impact of MetS on CVD.

METHODS

A total of 8,898 subjects (4,241 males and 4,657 females), 40 to 69 years of age, were enrolled and evaluated for the development of new onset CVD from 2001 to 2012 (median 8.1 years of follow-up).

RESULTS

The prevalence of MetS at baseline was 22.0% (932/4,241) and 29.7% (1,383/4,657) in males and females, respectively. MetS was associated with increased risk of coronary heart disease (CHD; hazard ratio [HR], 1.818; 95% confidence interval [CI], 1.312 to 2.520 in males; HR, 1.789; 95% CI, 1.332 to 2.404 in females) and CVD (HR, 1.689; 95% CI, 1.295 to 2.204 in males; HR, 1.686; 95% CI, 1.007 to 2.192 in females). Specifically, MetS was associated with risk of future stroke in females only (HR, 1.486; 95% CI, 1.007 to 2.192). Among MetS components, abdominal obesity and hypertension were independent predictors of both CHD and CVD. In addition, a higher number of MetS components correlated with higher CVD risk.

CONCLUSION

MetS is a significant risk factor for the development of CVD although its impact varies between sexes.

Diabetes burden and prevention in Korea and the Western Pacific Region

Diabetes burden in the Western Pacific Region (WPR) is more problematic than in any other part of the world. In 2013, the International Diabetes Federation reported >382 million people are living with diabetes around the world. About 36%, approximately 138 million people with diabetes, are living in the WPR. In addition, in the WPR, from 2012 to 2013, 6 million diabetes mellitus cases were newly diagnosed, accounting for 54.5% of all type 2 diabetes mellitus (T2DM) cases diagnosed in the world during the same period. South Korea is no exception, and the prevalence of diabetes is estimated to be as high as 5 million people. The prevalence of T2DM in Korea increased from <1% in 1960 to >10% by early 2000. According to the Ansung-Ansan Cohort study, from 2001 to 2011, T2DM increased 54% and 60% in the 50(th) and 60(th) age groups, respectively. The main reason for the rapid increase in the prevalence of diabetes in Korea was the sudden growth in the economy, resulting in rapid urbanization. Moreover, scientific evidence suggests the dramatic increase in T2DM incidence and prevalence in Korea is related to the influence of economic development, health policy, urbanization, westernized diet, decreased physical activity, as well as an individual's health behavior changes. However, diabetes management response rate was low in the newly onset groups with <20%, but gradually increased up to around 90%, then declined to <80% after 16-20 year of developing T2DM, showing an "M" management pattern. The study results revealed that despite the successful implementation of the universal health insurance system in Korea beginning in 1987, people diagnosed with T2DM were not properly managing T2DM. Most developing countries in the WPR are emulating the Korean experiences. There is clear evidence that utilization of BED (Behavioral change, Exercise, and proper Diet) could be the best vector to fight against the diabetes tsunami in the WPR. From the Korean experiences the WPR, at high risk for T2DM, could learn to prevent, intervene, and properly manage T2DM in order to reduce diabetes-related morbidity and mortality.

Glycated Hemoglobin Value for Fasting Plasma Glucose of 126 mg/dL in Korean: The 2011 Korea National Health and Nutrition Examination Survey

We aimed to estimate the cutoff value of glycated hemoglobin (HbA1c, A1c) for fasting plasma glucose (FPG) of 126 mg/dL in the Korean adult population, using the 2011 Korea National Health and Nutrition Examination Survey. A total of 5,421 participants without a history of diabetes and over 19 years of age were included in the analysis. A point-wise area under the receiver operating characteristic curve was used to estimate the optimal A1c cutoff value. A1c threshold of 6.1% produced the highest sum of sensitivity (85.2%) and specificity (90.5%) for FPG of 126 mg/dL (area under the curve, 0.941, P<0.001). A1c of 6.5% produced a sensitivity of 67.7% and specificity of 98.0% for FPG of 126 mg/dL. Considering A1c as one of three criteria for the diagnosis of diabetes and the specificity of an A1c cutoff of 6.5%, the current diagnostic criteria of A1c≥6.5% might be acceptable in the Korean adult population.

Subclinical hypothyroidism in addition to common risk scores for prediction of cardiovascular disease: a 10-year community-based cohort study

OBJECTIVE

This study was carried out to determine whether serum TSH levels improve the prediction of cardiovascular risk in addition to common clinical risk scores, given the association between subclinical hypothyroidism (SCH) and cardiovascular disease (CVD).

DESIGN

We carried out an observational study in a prospective cohort.

METHODS

The study included a total of 344 SCH and 2624 euthyroid participants aged over 40 years and who were without previously recorded CVDs were included in this study analysis. We measured thyroid function and traditional risk factors at baseline and estimated the 10-year cumulative incidence of CVD in a gender-stratified analysis.

RESULTS

During 10 years of follow-up, 251 incident cardiovascular events were recorded. The elevation of serum TSH levels significantly increased the CV risk independent of conventional risk factors in men. In the atherosclerotic CVD (ASCVD) risk score or the Reynolds risk score (RRS) model, the addition of serum TSH levels had no effect on model discrimination as measured by the area under the curve in either women or men. Adding serum TSH did not improve the net reclassification improvement in either women (3.48% (P=0.29) in the ASCVD, -0.89% (P=0.75) in the RRS, respectively) or men (-1.12% (P=0.69), 3.45% (P=0.20), respectively) and only mildly affected the integrated discrimination Improvement in the ASCVD-adjusted model (0.30% in women and 0.42% in men, both P=0.05).

CONCLUSIONS

In the context of common risk scoring models, the additional assessment of serum TSH levels provided little incremental benefit for the prediction of CV risk.

Correlation of Plasma Lipid Profile with Salivary Oxidative Stress Markers in Type II Diabetes Mellitus Patients

INTRODUCTION

Diabetes is known to be associated with greater production of reactive oxygen species (ROS) like malondialdehyde (MDA) and decreased antioxidants like total thiols and its estimation in plasma is used in monitoring the redox status. The aim of this study was to analyse the association between plasma lipid profile parameters like HDL and LDL with salivary MDA and thiols in diabetic patients.

MATERIALS AND METHODS

Sixty subjects between the age group 35- 70 years who were diagnosed with type II diabetes mellitus based on fasting blood glucose and glycated haemoglobin levels who attended the dental OPD at Kasturba Medical College and Hospital, Manipal consented to participate in this study. Plasma glucose, HDL and LDL were estimated in Cobas autoanalyser by hexokinase method, homogenous enzymatic colorimetric assay and Friedwald's formula respectively. Assessment of glycated hemoglobin was by ion exchange chromatography, MDA by thiobarbituric acid as a substrate and thiols by Ellmann's manual method in plasma and saliva.

RESULTS

The association of plasma LDL with salivary MDA was found to be positive and significant and that with salivary thiols was negative and significant. Also, the association of plasma HDL with salivary MDA was found to be negative and significant and that with salivary thiols was positive and significant.

CONCLUSION

RESULTS indicate the potential of saliva as a tool to monitor prognosis of diabetes.

Glycated hemoglobin for the diagnosis of diabetes and prediabetes: Diagnostic impact on obese and lean subjects, and phenotypic characterization

Aims/Introduction

Measurement of glycated hemoglobin (HbA1c) has been recommended for the diagnosis of diabetes and prediabetes. However, epidemiological studies have shown significant discordance between HbA1c and glucose-based tests. Of the factors that could influence agreement between HbA1c and the oral glucose tolerance test (OGTT), bodyweight has not been fully evaluated. The aims of the present study were to evaluate the impact of HbA1c criteria to diagnose diabetes and prediabetes compared with OGTT, and to examine HbA1c in relation to body mass index.

Materials and Methods

Two cohorts were studied, one from an obesity clinic (n = 592) and one from subjects undergoing screening for diabetes (n = 462). All underwent OGTT and HbA1c measurement.

Results

In the obese cohort, HbA1c ≥6.5% (≥48 mmol/mol) showed a sensitivity of 69.3% for diabetes, whereas HbA1c 5.7–6.4% (39–46 mmol/mol) did not identify prediabetes well (sensitivity 39.1%). In the diabetes screening cohort, HbA1c had low sensitivities for both diabetes (39.2%) and prediabetes (53.3%). When participants were stratified according to body mass index class I–III, HbA1c agreement with the OGTT for diabetes was much higher (80%, P < 0.005) in class I obesity compared with class II–III obesity; whereas for prediabetes, HbA1c had a low sensitivity in all obesity classes.

Conclusions

The agreement between HbA1c, fasting plasma glucose and 2-h glucose post-OGTT for the diagnosis of prediabetes was poor in our Italian population; whereas HbA1c ≥6.5% showed a relatively good agreement with OGTT for the diagnosis of diabetes. For the first time, we have shown that obesity class influences the diagnostic performance of HbA1c.

Optimal HbA1c cutoff for detecting diabetic retinopathy

The associations between high glucose levels and diabetic retinopathy have been the basis for the diagnosis of diabetes. We aimed to provide updated data on the relationship between HbA1c and diabetic retinopathy, and to assess the diagnostic accuracy of the proposed HbA1c cutoff for detecting diabetic retinopathy. This cross-sectional study included 3,403 adults from the 2009 to 2010 Ansung Cohort Study. Retinopathy was assessed with single-field nonmydriatic fundus photography and graded according to the International Clinical Diabetic Retinopathy Disease Severity Scale. HbA1c was measured by standardized assay using high performance liquid chromatography. Based on deciles distribution, the prevalence of retinopathy was very low until the HbA1c range of 48-51 mmol/mol (6.5-6.8 %). The optimal HbA1c cutoff for detecting any diabetic retinopathy was 49 mmol/mol (6.6 %), moderate or severer retinopathy was 52 mmol/mol (6.9 %) from receiver operating characteristic curve analysis. The proposed HbA1c threshold of 48 mmol/mol (6.5 %) from American Diabetes Association produced comparable accuracy for identifying both any and moderate/severer retinopathy. This study confirmed that the proposed HbA1c threshold of 48 mmol/mol (6.5 %) allowed the proper detection of diabetic retinopathy. Our data support the judicious use of HbA1c for the diagnosis of diabetes and detecting diabetic retinopathy as well.

Usefulness of a novel system for measuring glucose area under the curve while screening for glucose intolerance in outpatients

AIMS/INTRODUCTION

To realize the effectiveness of a novel system for measuring glucose area under the curve (AUC) using minimally invasive interstitial fluid extraction technology (MIET), outpatients undergoing oral glucose tolerance tests (OGTT) were investigated for the efficacy of screening for glucose intolerance using this system.

MATERIALS AND METHODS

Fifty outpatients scheduled to undergo a 75-g OGTT for medical reasons were recruited to the study. An area of skin on the forearm was pretreated with microneedle arrays before the application of hydrogels for interstitial fluid extraction. Plasma glucose (PG) levels were measured every 30 min for 2 h to calculate reference (actual) AUC. The AUC was predicted by MIET on the basis of glucose extracted by the hydrogel using sodium ion levels as the internal standard.

RESULTS

Good correlation between MIET-predicted and reference AUCs obtained using PG levels was confirmed for a wide AUC range. By introducing a threshold level for AUC to separate glucose intolerance with peak glucose ≥180 mg/dL from normal glucose tolerance, the system was demonstrated to provide better screening accuracy compared with conventional methods that use HbA1c and fasting PG levels. The results of a questionnaire-based survey administered to the subjects suggested that this system was readily accepted by the majority as a painless monitoring method.

CONCLUSIONS

The findings suggest that our glucose AUC measurement system using MIET would be useful for screening of glucose intolerance. In the future, this system may prove to be a useful aid as a screen for glucose intolerance before performing an OGTT for diagnosis.

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.