Do glycemic marker levels vary by race? Differing results from a cross-sectional analysis of individuals with and without diagnosed diabetes

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

BACKGROUND

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

METHODS AND RESULTS

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

CONCLUSIONS

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

Variation in the relationship between fasting glucose and HbA1c: implications for the diagnosis of diabetes in different age and ethnic groups

INTRODUCTION

Identify non-glycemic factors affecting the relationship between fasting plasma glucose (FPG) and glycated hemoglobin (HbA1c), in order to refine diabetes diagnostic criteria.

RESEARCH DESIGN AND METHODS

Relationship between FPG-HbA1c was assessed in 12 531 individuals from 2001 to 2018 US National Health and Nutrition Examination Survey. Using a recently described method, FPG and HbA1c were used to calculate apparent glycation ratio (AGR) of red blood cells for different subgroups based on age, race, and gender.

RESULTS

At an FPG of 7 mmol/L, black individuals had a higher HbA1c (p<0.001, mean: 50.2 mmol/mol, 95% CI (49.8 to 50.4)) compared with white individuals (47.4 mmol/mol (47.2 to 47.5)). This corresponds to NGSP (National Glycohemoglobin Standardization Program) units of 6.7% and 6.5% for black versus white individuals, respectively. Similarly, individuals under 21 years had lower HbA1c (p<0.001, 47.9 mmol/mol (47.7 to 48.1), 6.5%) compared with those over 50 years (48.3 mmol/mol (48.2 to 48.5), 6.6%). Differences were also observed between women (p<0.001, 49.2 mmol/mol (49.1 to 49.3), 6.7%) and men (47.0 mmol/mol (46.8 to 47.1), 6.5%). Of note, the difference in HbA1c at FPG of 7 mmol/L in black females over 50 and white males under 21 years was 5 mmol/mol (0.46%). AGR differences according to race (p<0.001), age (p<0.001), and gender (p<0.001) explained altered glucose-HbA1c relationship in the analyzed groups.

CONCLUSIONS

FPG-HbA1c relationship is affected by non-glycemic factors leading to incorrect diagnosis of diabetes in some individuals and ethnic groups. Assessment of AGR helps understand individual-specific relationship between glucose levels and HbA1c, which has the potential to more accurately diagnose and manage diabetes.

Race, Ethnicity, and Ancestry in Clinical Pathways: A Framework for Evaluation

Clinical algorithms, or "pathways," promote the delivery of medical care that is consistent and equitable. Race, ethnicity, and/or ancestry terms are sometimes included in these types of guidelines, but it is unclear if this is appropriate for clinical decision-making. At our institution, we developed and applied a structured framework to determine whether race, ethnicity, or ancestry terms identified in our clinical pathways library should be retained, modified, or removed. First, we reviewed all text and associated reference documents for 132 institutionally-developed clinical pathways and identified 8 pathways that included race, ethnicity, or ancestry terms. Five pathways had clear evidence or a change in institutional policy that supported removal of the term. Multispecialty teams conducted additional in-depth evaluation of the 3 remaining pathways (Acute Viral Illness, Hyperbilirubinemia, and Weight Management) by applying the framework. In total, based on these reviews, race, ethnicity, or ancestry terms were removed (n = 6) or modified (n = 2) in all 8 pathways. Application of the framework established several recommended practices, including: (1) define race, ethnicity, and ancestry rigorously; (2) assess the most likely mechanisms underlying epidemiologic associations; (3) consider whether inclusion of the term is likely to mitigate or exacerbate existing inequities; and (4) exercise caution when applying population-level data to individual patient encounters. This process and framework may be useful to other institutional programs and national organizations in evaluating the inclusion of race, ethnicity, and ancestry in clinical guidelines.

Investigating family history of diabetes as a predictor of fasting insulin and fasting glucose activity in a sample of healthy weight adults

AIMS

Type 2 diabetes is a major public health problem for the global community. Having a family history of diabetes significantly increases risk for diabetes development and understanding how family history contributes to diabetes risk could lead to more effective prevention efforts for at-risk individuals. In a previous study, we showed family history of diabetes is a significant predictor of fasting insulin in healthy weight children. The present study aimed to use the National Health and Nutrition Examination Survey (NHANES 2017) to apply similar multiple regression models to a population of healthy weight adults to determine if family history is a significant predictor of fasting glucose and fasting insulin.

METHODS

Fasting glucose (mg/dL) and fasting insulin (pmol/L) were used as dependent variables in each model, respectively, with family history of diabetes as the independent variable. Covariates for each model included age, gender, race/ethnicity, waist circumference, and macronutrient intake.

RESULTS

The model significantly predicted the variance of fasting glucose [(F(11,364) = 34.80, p < 0.001, R² = 0.2342] and fasting insulin [F(11,343) = 17.58, p < 0.001, R² = 0.1162]. After adjusting for covariates, family history was a significant predicator of fasting glucose (p = 0.0193) as well as age, gender, non-Hispanic black ethnicity, waist circumference, and fat intake. Significant predictors of fasting insulin included gender and waist circumference, but not family history (p = 0.8264). In addition, fasting glucose was higher in individuals with a family history of diabetes (p = 0.033).

CONCLUSIONS

These results add to the understanding of how family history influences the biomarkers that contribute to diabetes development. Knowledge of how family history of diabetes relates to fasting insulin and fasting glucose activity in healthy weight individuals can be used to design personalized screening and early prevention strategies.

A Closer Look at Racial Differences in Diabetes Outcomes Among a Community Sample: Diabetes Distress, Self-care, and HbA1c

OBJECTIVE

Approximately 34 million people in the U.S. have diabetes. With this illness come substantial changes to psychological and physical health. However, type 2 diabetes disproportionately affects non-Hispanic Black compared with non-Hispanic White populations. The purpose of this study was to examine racial differences in psychological, behavioral, and physical health over time among individuals recently diagnosed with type 2 diabetes.

RESEARCH DESIGN AND METHODS

Data were collected from a community sample of 193 adults recently diagnosed with type 2 diabetes (44% female; 45% Black). Measures of distress, self-care behaviors, and HbA1c were taken at an initial interview (time 1) and 6 months later (time 2). Individuals wore an Actical accelerometer to assess physical activity and participated in three 24-h dietary recall interviews to assess dietary intake within 2 weeks of the initial interview.

RESULTS

From time 1 to time 2, Black women showed the highest increase in depressive symptoms. There was a greater increase in regimen and physician distress among White compared with Black participants. White men and Black women reported a decline in medication adherence over time. There were no racial differences in changes in physical activity across 6 months. However, Black individuals had higher overall calorie consumption with greater protein, saturated fat, and cholesterol intake than White individuals. There were no race or sex differences in changes in glycemic stability.

CONCLUSIONS

Initial adjustment to a diagnosis of type 2 diabetes differentially influences Black and White men and women in terms of depressive symptoms, diabetes distress, and self-care.

Glycated albumin as biomarker: Evidence and its outcomes

Glycemic control markers are important for the diagnosis and treatment of diabetes. Hemoglobin A1c (A1C) is an important marker that is mandatory in routine medical examinations; however, it is well known that it has some limitations. In this review, we focus on the limitation of A1C and introduce a relatively new marker, glycated albumin (GA), which can be used to complement A1C. First, for a better understanding of the characteristics of each marker, we sort the similarities and differences of glycemic control markers as well as the characteristics of each marker. Second, we point out the limitation of A1C, introduce GA as an alternative indicator, and discuss the limitations of GA. Finally, we summarize important evidence regarding the utility of GA. We hope that this review provides useful information that permits more effective usage of GA as well as other glycemic control markers.

Association of the extent of return to fasting state 2-hours after a glucose challenge with incident prediabetes and type 2 diabetes: The CARDIA study

AIM

To evaluate whether the extent of return to fasting state 2-hours after a glucose challenge among normoglycemic individuals is associated with lower risk of incident prediabetes/ type 2 diabetes in the Coronary Artery Risk Development in Young Adults (CARDIA) cohort study.

METHODS

We evaluated this association among 1879 normoglycemic adults who were categorized into three groups: 'Low post load' (2hPG < FPG); 'Medium post load' (2hPG ≥ FPG and < 75^th percentile of the difference); and 'High post load' (2hPG > FPG and ≥ 75^th percentile of the difference). We used Cox proportional hazards regression to evaluate the association of the difference in 2hPG and FPG with incident diabetes/prediabetes after adjustment for demographic and clinical covariates.

RESULTS

During 20 years of follow-up, 8% developed type 2 diabetes and 35% developed prediabetes. Compared to those with 'Low post load', the risk of type 2 diabetes was higher for participants with 'High post load' [HR: 1.56, 95% CI (1.03, 2.37)] and similar for participants with 'Medium post load' [HR: 0.99, 95% CI (0.64, 1.52)]. However, HRs for incident prediabetes among participants with 'High post load' [HR = 1.2, 95 %CI = (0.98, 1.46)] was not significantly different compared to participants with 'Low post load'.

CONCLUSION

Among normoglycemic individuals, a difference between 2hPG and FPG concentration > 0.9 mmol/L can be used to stratify individuals at higher risk for developing type 2 diabetes.

Associations of glycated albumin and fructosamine with glycaemic status in urban black South Africans

BACKGROUND

The associations of glycated albumin (GA) and fructosamine (FA) as alternate tests for diabetes screening in South Africans were examined to overcome shortcomings with oral glucose tolerance tests (OGTTs).

METHODS

Based on OGTTs, glycaemic status included 1) normal glucose, 2) dysglycaemia (impaired fasting glucose, impaired glucose tolerance, newly diagnosed diabetes), and 3) known diabetes.

RESULTS

Among 1092 participants, >21 years, mean GA (16.9%) and FA (230.2 μmol/l) increased significantly by age and worsening glycaemic status and were significantly higher in women vs. men and BMI (kg/m²) ≥ 30 vs. <30. For dysglycaemia, correlations of GA and FA with fasting and 2-hour glucose levels were higher in obese (0.576 to 0.688) vs. non-obese (-0.010 to 0.522). Optimal GA threshold to identify dysglycaemia was 15.35% and comparable, but with lower sensitivity (0.54) and specificity (0.55), to Asian studies. For FA, the optimal cut-point of 227.0 μmol/l approximated that described in the literature. Dysglycaemia and known diabetes were associated with GA, while only known diabetes was related to FA, in models adjusted for age, gender and obesity.

CONCLUSIONS

Potential exists for GA and/or FA as alternative measures of dysglycaemia in clinical practice in Africans, but longitudinal studies are required to clearly elucidate their utility.

HbA1c Performance in African Descent Populations in the United States With Normal Glucose Tolerance, Prediabetes, or Diabetes: A Scoping Review

Introduction

African descent populations in the United States have high rates of type 2 diabetes and are incorrectly represented as a single group. Current glycated hemoglobin A_1c (HbA_1c) cutoffs (5.7% to <6.5% for prediabetes; ≥6.5% for type 2 diabetes) may perform suboptimally in evaluating glycemic status among African descent groups. We conducted a scoping review of US-based evidence documenting HbA_1c performance to assess glycemic status among African American, Afro-Caribbean, and African people.

Methods

A PubMed, Scopus, and Cumulative Index to Nursing and Allied Health Literature (CINAHL) search (January 2020) yielded 3,238 articles published from January 2000 through January 2020. After review of titles, abstracts, and full texts, 12 met our criteria. HbA_1c results were compared with other ethnic groups or validated against the oral glucose tolerance test (OGTT), fasting plasma glucose (FPG), or previous diagnosis. We classified study results by the risk of false positives and risk of false negatives in assessing glycemic status.

Results

In 5 studies of African American people, the HbA_1c test increased risk of false positives compared with White populations, regardless of glycemic status. Three studies of African Americans found that HbA_1c of 5.7% to less than 6.5% or HbA_1c of 6.5% or higher generally increased risk of overdiagnosis compared with OGTT or previous diagnosis. In one study of Afro-Caribbean people, HbA_1c of 6.5% or higher detected fewer type 2 diabetes cases because of a greater risk of false negatives. Compared with OGTT, HbA_1c tests in 4 studies of Africans found that HbA_1c of 5.7% to less than 6.5% or HbA_1c of 6.5% or higher leads to underdiagnosis.

Conclusion

HbA_1c criteria inadequately characterizes glycemic status among heterogeneous African descent populations. Research is needed to determine optimal HbA_1c cutoffs or other test strategies that account for risk profiles unique to African American, Afro-Caribbean, and African people living in the United States.

The Need for Ethnoracial Equity in Artificial Intelligence for Diabetes Management: Review and Recommendations

There is clear evidence to suggest that diabetes does not affect all populations equally. Among adults living with diabetes, those from ethnoracial minority communities—foreign-born, immigrant, refugee, and culturally marginalized—are at increased risk of poor health outcomes. Artificial intelligence (AI) is actively being researched as a means of improving diabetes management and care; however, several factors may predispose AI to ethnoracial bias. To better understand whether diabetes AI interventions are being designed in an ethnoracially equitable manner, we conducted a secondary analysis of 141 articles included in a 2018 review by Contreras and Vehi entitled “Artificial Intelligence for Diabetes Management and Decision Support: Literature Review.” Two members of our research team independently reviewed each article and selected those reporting ethnoracial data for further analysis. Only 10 articles (7.1%) were ultimately selected for secondary analysis in our case study. Of the 131 excluded articles, 118 (90.1%) failed to mention participants’ ethnic or racial backgrounds. The included articles reported ethnoracial data under various categories, including race (n=6), ethnicity (n=2), race/ethnicity (n=3), and percentage of Caucasian participants (n=1). Among articles specifically reporting race, the average distribution was 69.5% White, 17.1% Black, and 3.7% Asian. Only 2 articles reported inclusion of Native American participants. Given the clear ethnic and racial differences in diabetes biomarkers, prevalence, and outcomes, the inclusion of ethnoracial training data is likely to improve the accuracy of predictive models. Such considerations are imperative in AI-based tools, which are predisposed to negative biases due to their black-box nature and proneness to distributional shift. Based on our findings, we propose a short questionnaire to assess ethnoracial equity in research describing AI-based diabetes interventions. At this unprecedented time in history, AI can either mitigate or exacerbate disparities in health care. Future accounts of the infancy of diabetes AI must reflect our early and decisive action to confront ethnoracial inequities before they are coded into our systems and perpetuate the very biases we aim to eliminate. If we take deliberate and meaningful steps now toward training our algorithms to be ethnoracially inclusive, we can architect innovations in diabetes care that are bound by the diverse fabric of our society.

Identifying Africans with undiagnosed diabetes: Fasting plasma glucose is similar to the hemoglobin A1C updated Atherosclerosis Risk in Communities diabetes prediction equation

AIMS

Seventy percent of Africans living with diabetes are undiagnosed. Identifying who should be referred for testing is critical. Therefore we evaluated the ability of the Atherosclerosis Risk in Communities (ARIC) diabetes prediction equation with A1C added (ARIC + A1C) to identify diabetes in 451 African-born blacks living in America (66% male; age 38 ± 10y (mean ± SD); BMI 27.5 ± 4.4 kg/m²).

METHODS

All participants denied a history of diabetes. OGTTs were performed. Diabetes diagnosis required 2-h glucose ≥200 mg/dL. The five non-invasive (Age, parent history of diabetes, waist circumference, height, systolic blood pressure) and four invasive variables (Fasting glucose (FPG), A1C, triglycerides (TG), HDL) were obtained. Four models were tested: Model-1: Full ARIC + A1C equation; Model-2: All five non-invasive variables with one invasive variable excluded at a time; Model-3: All five non-invasive variables with one invasive variable included at a time; Model-4: Each invasive variable singly. Area under the receiver operator characteristic curve (AROC) predicted diabetes. Youden Index identified optimal cut-points.

RESULTS

Diabetes occurred in 7% (30/451). Model-1, the full ARIC + A1C equation, AROC = 0.83. Model-2: With FPG excluded, AROC = 0.77 (P = 0.038), but when A1C, HDL or TG were excluded AROC remained unchanged. Model-3 with all non-invasive variables and FPG alone, AROC=0.87; but with A1C, TG or HDL included AROC declined to ≤0.76. Model-4: FPG as a single predictor, AROC = 0.87. A1C, TG, or HDL as single predictors all had AROC ≤ 0.74. Optimal cut-point for FPG was 100 mg/dL.

CONCLUSIONS

To detect diabetes, FPG performed as well as the nine-variable updated ARIC + A1C equation.

Continuous Glucose Monitoring and Use of Alternative Markers To Assess Glycemia in Chronic Kidney Disease

OBJECTIVE

In chronic kidney disease, glycated albumin and fructosamine have been postulated to be better biomarkers of glycemic control than HbA_1c. We evaluated the accuracy, variability, and covariate bias of three biomarkers (HbA_1c, glycated albumin, and fructosamine) compared with continuous glucose monitoring (CGM)-derived measurement of glycemia across estimated glomerular filtration rate (eGFR) in type 2 diabetes.

RESEARCH DESIGN AND METHODS

A prospective cohort study was conducted of 104 participants with type 2 diabetes, 80 with eGFR <60 mL/min/1.73 m² (not treated with dialysis) and 24 frequency-matched control subjects with eGFR ≥60 mL/min/1.73 m². Participants wore a blinded CGM for two 6-day periods separated by 2 weeks, with blood and urine collected at the end of each CGM period. HbA_1c, glycated albumin, and fructosamine were measured by high-performance liquid chromatographic, enzymatic, and colorimetric nitroblue tetrazolium methods, respectively.

RESULTS

Within-person biomarker values were strongly correlated between the two CGM periods (r = 0.92-0.95), although no marker fully captured the within-person variability of mean CGM glucose. All markers were similarly correlated with mean CGM glucose (r = 0.71-77). Compared with mean CGM glucose, glycated albumin and fructosamine were significantly biased by age, BMI, serum iron concentration, transferrin saturation, and albuminuria; HbA_1c was underestimated in those with albuminuria.

CONCLUSIONS

Glycated albumin and fructosamine were not less variable than HbA_1c at a given mean CGM glucose level, with several additional sources of bias. These results support measuring HbA_1c to monitor trends in glycemia among patients with eGFR <60 mL/min/1.73 m². Direct measurements of glucose are necessary to capture short-term variability.

Diabetes Screening: Detection and Application of Saliva 1,5-Anhydroglucitol by Liquid Chromatography-Mass Spectrometry

CONTEXT

Unlike other commonly used invasive blood glucose-monitoring methods, saliva detection prevents patients from suffering physical uneasiness. However, there are few studies on saliva 1,5-anhydroglucitol (1,5-AG) in patients with diabetes mellitus (DM).

OBJECTIVE

This study aimed to evaluate the effectiveness of saliva 1,5-AG in diabetes screening in a Chinese population.

DESIGN AND PARTICIPANTS

This was a population-based cross-sectional study. A total of 641 subjects without a valid diabetic history were recruited from September 2018 to June 2019. Saliva 1,5-AG was measured with liquid chromatography-mass spectrometry.

MAIN OUTCOME MEASURES

DM was defined per American Diabetes Association criteria. The efficiency of saliva 1,5-AG for diabetes screening was analyzed by receiver operating characteristic curves, and the optimal cutoff point was determined according to the Youden index.

RESULTS

Saliva 1,5-AG levels in subjects with DM were lower than those in subjects who did not have DM (both P < .05). Saliva 1,5-AG was positively correlated with serum 1,5-AG and negatively correlated with blood glucose and glycated hemoglobin (HbA1c) (all P < .05). The optimal cutoff points of saliva 1,5-AG0 and 1,5-AG120 for diabetes screening were 0.436 μg/mL (sensitivity: 63.58%, specificity: 60.61%) and 0.438 μg/mL (sensitivity: 62.25%, specificity: 60.41%), respectively. Fasting plasma glucose (FPG) combined with fasting saliva 1,5-AG reduced the proportion of people who required an oral glucose tolerance test by 47.22% compared with FPG alone.

CONCLUSION

Saliva 1,5-AG combined with FPG or HbA1c improved the efficiency of diabetes screening. Saliva 1,5-AG is robust in nonfasting measurements and a noninvasive and convenient tool for diabetes screening.

A Review of Diabetes Prediction Equations in African Descent Populations

Background: Predicting undiagnosed diabetes is a critical step toward addressing the diabetes epidemic in populations of African descent worldwide. Objective: To review characteristics of equations developed, tested, or modified to predict diabetes in African descent populations. Methods: Using PubMed, Scopus, and Embase databases, a scoping review yielded 585 research articles. After removal of duplicates (n = 205), 380 articles were reviewed. After title and abstract review 328 articles did not meet inclusion criteria and were excluded. Fifty-two articles were retained. However, full text review revealed that 44 of the 52 articles did not report findings by AROC or C-statistic in African descent populations. Therefore, eight articles remained. Results: The 8 articles reported on a total of 15 prediction equation studies. The prediction equations were of two types. Prevalence prediction equations (n = 9) detected undiagnosed diabetes and were based on non-invasive variables only. Non-invasive variables included demographics, blood pressure and measures of body size. Incidence prediction equations (n = 6) predicted risk of developing diabetes and used either non-invasive variables or both non-invasive and invasive. Invasive variables required blood tests and included fasting glucose, high density lipoprotein-cholesterol (HDL), triglycerides (TG), and A1C. Prevalence prediction studies were conducted in the United States, Africa and Europe. Incidence prediction studies were conducted only in the United States. In all these studies, the performance of diabetes prediction equations was assessed by area under the receiver operator characteristics curve (AROC) or the C-statistic. Therefore, we evaluated the efficacy of these equations based on standard criteria, specifically discrimination by either AROC or C-statistic were defined as: Poor (0.50 - 0.69); Acceptable (0.70 - 0.79); Excellent (0.80 - 0.89); or Outstanding (0.90 - 1.00). Prediction equations based only on non-invasive variables reported to have poor to acceptable detection of diabetes with AROC or C-statistic 0.64 - 0.79. In contrast, prediction equations which were based on both non-invasive and invasive variables had excellent diabetes detection with AROC or C-statistic 0.80 - 0.82. Conclusion: Equations which use a combination of non-invasive and invasive variables appear to be superior in the prediction of diabetes in African descent populations than equations that rely on non-invasive variables alone.

Increased glycated albumin and decreased esRAGE levels in serum are related to negative coronary artery remodeling in patients with type 2 diabetes: an Intravascular ultrasound study

BACKGROUND

Negative coronary artery remodeling is frequent in patients with diabetes, but its mechanism remains unclear. We here evaluated the association of serum levels of glycated albumin (GA) and endogenous secretory receptor for advanced glycation end products (esRAGE) with coronary artery remodeling in type 2 diabetic patients.

METHODS

Serum levels of GA and esRAGE were measured and intravascular ultrasound was performed in 136 consecutive diabetic patients with 143 coronary intermediate lesions. The remodeling index (RI) was calculated as the ratio between external elastic membrane (EEM) area at the lesion site and EEM area at the reference segment. Negative remodeling (NR) was defined as an RI < 0.95 and intermediate or positive remodeling as an RI ≥ 0.95.

RESULTS

Mean plaque burden at the lesion site was 70.96 ± 9.98%, and RI was 0.96 ± 0.18. Negative coronary arterial remodeling existed in 81 (56.6%) lesions. RI correlated closely with serum esRAGE level (r = 0.236, P = 0.005) and was inversely related to serum GA level (r = - 0.240, P = 0.004) and plasma low-density lipoprotein cholesterol (LDL-C) (r = - 0.206, P = 0.014) and total cholesterol levels (r = - 0.183, P = 0.028). Generalized estimating equations logistic regression analysis identified esRAGE (OR 0.037; 95% CI 0.012-0.564, P = 0.021), GA (OR 1.093; 95% CI 1.013-1.179, P = 0.018) and LDL-C (OR 1.479; 95% CI 1.072-2.835, P = 0.023) as independent predictors for negative remodeling.

CONCLUSIONS

In diabetic patients, negative coronary artery remodeling is associated with increased GA and decreased esRAGE levels in serum.

Racial disparity in HbA1c persists when fructosamine is used as a surrogate for mean blood glucose in youth with type 1 diabetes

BACKGROUND

Blacks have been reported to have higher hemoglobin A1c (HbA1c) than Whites even after adjustment for differences in blood glucose levels. Potentially glucose-independent racial disparity in HbA1c is an artifact of glucose ascertainment methods. In order to test this possibility, we examined the relationship of HbA1c with race after adjustment for concurrent fructosamine level as a surrogate for mean blood glucose (MBG).

METHODS

Youth with type 1 diabetes self-identified as either Black or White had blood drawn for HbA1c, fructosamine complete blood count, ferritin, and soluble transferrin receptor (sTfR) at a clinic visit. MBG was calculated as the average of self-monitored capillary glucoses over the preceding 30 days. The effect of race on HbA1c was evaluated in a general linear model adjusting for either MBG or fructosamine, along with other covariates.

RESULTS

Fructosamine was correlated with both HbA1c (r = 0.73, P < .0001), MBG (r = 0.46, P < .0001), red cell distribution width coefficient of variation (RDW-CV) (r = 0.31, P = .0045), Fe (r = 0.27, P = .017), and sTfR (r = 0.32, P = .0042). HbA1c was approximately 0.7% higher in Blacks than Whites after adjustment for fructosamine along with age, gender, RDW-CV, Fe, sTfR.

CONCLUSIONS

Blacks tend to have higher HbA1c than Whites even after statistical adjustment for fructosamine levels as a surrogate for MBG. Thus, HbA1c tends to overestimate corresponding MBG or fructosamine levels in Black patients. Racial differences should be taken into consideration when using HbA1c as a guide to diagnosis and therapy of diabetes in mixed-race populations.

Reference intervals for serum 1,5-anhydroglucitol in children, adolescents, adults, and pregnant women

BACKGROUND

1,5-anhydroglucitol (1,5-AG) is a validated marker of short-term glycemic control. We determined the reference intervals of 1,5-AG in different age groups and during pregnancy.

METHODS

Blood samples were collected from 2303 Euro-Brazilian healthy subjects: 580 children, 496 adolescents, 922 adults matched by age and sex, and 305 pregnant women in four gestational periods. Serum 1,5-AG was measured using an enzymatic reagent in an automated system.

RESULTS

The calculated reference intervals (nonparametric, 2.5th-97.5th) for males and females were, respectively: children, 96-302 and 89-277 μmol/l; adolescents, 84-311 and 79-277 μmol/l; and adults, 80-260 and 62-241 μmol/l. Males consistently showed significantly higher concentrations than females. 1,5-AG reference intervals in pregnant women were 56-298 μmol/l at <23 weeks gestation (n = 110), 37-166 μmol/l at 24-28 weeks gestation (n = 106), 34-155 μmol/l at 29-32 weeks gestation (n = 52), and 33-246 μmol/l at >32 weeks gestation (n = 37). No significant differences in 1,5-AG concentration were observed between non-pregnant and pregnant women at <23 weeks of gestation. A negative correlation (r = -0.287; p < .001) between 1,5-AG concentration and age was observed.

CONCLUSIONS

The reference intervals for 1,5-AG were affected by sex and age.

Haemoglobin A1c or Glycated Albumin for Diagnosis and Monitoring Diabetes: An African Perspective

Diabetes mellitus (DM) has reached epidemic proportions across the globe with the largest increases seen in sub-Saharan Africa. Those that are diagnosed are largely poorly controlled. This review summarizes the limitations of the use of glycated haemoglobin (HBA1c) in Africa and current knowledge on the utility of glycated albumin and fructosamine in African patients. The diagnosis and monitoring of DM in African patients may be compromised by associated conditions like sickle cell anaemia, chronic kidney disease and HIV infection. Glycated albumin reflects short term glycaemia and is not affected by many conditions that alter HbA1c. It can be measured enzymatically, and this review discusses methods for analysis, and discusses the advantages and limitations in specific situations with an emphasis on conditions that also affect HbA1c.

Distribution of glycated haemoglobin and its determinants in Korean youth and young adults: a nationwide population-based study

The present study aimed to describe the distribution of and to investigate the factors associated with glycated haemoglobin (HbA1c) values in Korean youth (10–19 years old) and young adults (20–29 years old). Data from the Korea Health and Nutrition Examination Survey (2011–2015) were used. A total of 6,418 participants (male 3,140 [53.2%]) aged 10–29 years were included in the analysis. Percentiles of HbA1c were calculated and HbA1c values were compared according to age, sex, and associated factors. The mean HbA1c values (% [mmol/mol]) were 5.42 ± 0.01 (35.7 ± 0.1) for youths and 5.32 ± 0.01 (34.7 ± 0.1) for young adults (P < 0.001). Male participants showed significantly higher HbA1c level than females (P < 0.001). When age was grouped into 5-year intervals, HbA1c was the highest in those aged 10–14 years and the lowest in those aged 20–24 years. After controlling for confounding variables, the HbA1c values of youths and male participants were significantly higher than those of young adults and female participants. The present study provides nationally representative data on the distribution of HbA1c values in Korean youth and young adults. There were significant differences in the level of HbA1c according to age and sex.

Undetected dysglycaemia common in primary care patients treated for hypertension and/or dyslipidaemia: on the need for a screening strategy in clinical practice. A report from EUROASPIRE IV a registry from the EuroObservational Research Programme of the European Society of Cardiology

Background

Dysglycaemia defined as type 2 diabetes (T2DM) and impaired glucose tolerance (IGT), increases the risk of cardiovascular disease (CVD). The negative impact is more apparent in the presence of hypertension and/or dyslipidaemia. Thus, it seems reasonable to screen for dysglycaemia in patients treated for hypertension and/or dyslipidaemia. A simple screening algorithm would enhance the adoption of such strategy in clinical practice.

Objectives

To test the hypotheses (1) that dysglycaemia is common in patients with hypertension and/or dyslipidaemia and (2) that initial screening with the Finnish Diabetes Risk Score (FINDRISC) will decrease the need for laboratory based tests.

Methods

2395 patients (age 18–80 years) without (i) a history of CVD or TDM2, (ii) prescribed blood pressure and/or lipid lowering drugs answered the FINDRISC questionnaire and had an oral glucose tolerance test (OGTT) and HbA1c measured.

Results

According to the OGTT 934 (39%) had previously undetected dysglycaemia (T2DM 19%, IGT 20%). Of patients, who according to FINDRISC had a low, moderate or slightly elevated risk 20, 34 and 41% and of those in the high and very high-risk category 49 and 71% had IGT or T2DM respectively. The OGTT identified 92% of patients with T2DM, FPG + HbA1c 90%, FPG 80%, 2hPG 29% and HbA1c 22%.

Conclusions

(1) The prevalence of dysglycaemia was high in patients treated for hypertension and/or dyslipidaemia. (2) Due to the high proportion of dysglycaemia in patients with low to moderate FINDRISC risk scores its initial use did not decrease the need for subsequent glucose tests. (3) FPG was the best test for detecting T2DM. Its isolated use is limited by the inability to disclose IGT. A pragmatic strategy, decreasing the demand for an OGTT, would be to screen all patients with FPG followed by OGTT in patients with IFG.

Racial Disparities in Elderly Patients Receiving Lumbar Spinal Stenosis Surgery

STUDY DESIGN

Retrospective cohort study.

OBJECTIVE

To evaluate for racial disparities in elderly patients having undergone lumbar spinal stenosis surgery.

METHODS

The US Medicare Provider Analysis and Review database (records from 2005 to 2011) was used to identify patients over the age of 65 years, diagnosed with lumbar spinal stenosis, and having undergone lumbar laminectomy or fusion surgery. Blacks were compared to Whites in both unmatched and propensity score-matched populations. The data was analyzed with univariate (χ² and Wilcoxon rank sum tests for unmatched comparison, and McNemar exact and signed rank sum tests for matched comparison) and multivariate models.

RESULTS

Query of the data resulted in a study sample of 12 807 patients; 514 (4.0%) were identified as Black and 12 293 (96%) as White. Blacks were less likely to be discharged home (42.4% vs 58.9%, P < .0001) and had lower repeat operation rates (6.81% vs 11.5%, P = .0009); both remained significant in the propensity score-matched comparison. Finally, Blacks experienced more postoperative complications, higher median Medicare costs, but lower out-of-pocket expenses (P = .0113). Blacks had higher rates of diabetes (33.7% vs 21.5%, P < .0001) and obesity (9.92% vs 6.85%, P = .0074), when compared to Whites, but these comorbidities did not significantly affect odds of 30-day complications.

CONCLUSIONS

Black patients having undergone lumbar spinal stenosis surgery were more likely to have received fusion at initial operation, had shorter pre- and postoperative follow-up intervals and displayed variances in discharge disposition. Reasons for these differences are not entirely understood; however, educational and socioeconomic factors and possibly ethnic/cultural biases may have contributed. Racial disparities in health care continue to be identified and should be further explored in order to eliminate them.

Effect of ethnicity on HbA1c levels in individuals without diabetes: Systematic review and meta-analysis

Aims/Hypothesis

Disparities in HbA1c levels have been observed among ethnic groups. Most studies were performed in patients with diabetes mellitus (DM), which may interfere with results due to the high variability of glucose levels. We conducted a systematic review and meta-analysis to investigate the effect of ethnicity on HbA1c levels in individuals without DM.

Methods

This is a systematic review with meta-analysis. We searched MEDLINE and EMBASE up to September 2016. Studies published after 1996, performed in adults without DM, reporting HbA1c results measured by certified/standardized methods were included. A random effects model was used and the effect size was presented as weighted HbA1c mean difference (95% CI) between different ethnicities as compared to White ethnicity.

Results

Twelve studies met the inclusion criteria, totalling data from 49,238 individuals. There were significant differences between HbA1c levels in Blacks [0.26% (2.8 mmol/mol); 95% CI 0.18 to 0.33 (2.0 to 3.6), p <0.001; I² = 90%, p <0.001], Asians [0.24% (2.6 mmol/mol); 95% CI 0.16 to 0.33 (1.7 to 3.6), p <0.001; I² = 80%, p = 0.0006] and Latinos [0.08% (0.9 mmol/mol); IC 95% 0.06 to 0.10 (0.7 to 1.1); p <0.001; I² = 0%; p = 0.72] when compared to Whites.

Conclusions/Interpretation

This meta-analysis shows that, in individuals without DM, HbA1c values are higher in Blacks, Asians, and Latinos when compared to White persons. Although small, these differences might have impact on the use of a sole HbA1c point to diagnose DM in all ethnic populations.