Minimal Contribution of Fasting Hyperglycemia to the Incidence of Type 2 Diabetes in Subjects With Normal 2-h Plasma Glucose

OBJECTIVE

To assess the relative contribution of increased fasting and postload plasma glucose concentrations to the incidence of type 2 diabetes in subjects with a normal 2-h plasma glucose concentration.

RESEARCH DESIGN AND METHODS

A total of 3,450 subjects with 2-h plasma glucose concentration <140 mg/dl at baseline were followed up in the San Antonio Heart Study (SAHS) and the Botnia Study for 7–8 years. The incidence of type 2 diabetes at follow-up was related to the fasting, 1-h, and 2-h plasma glucose concentrations.

RESULTS

In subjects with 2-h plasma glucose <140 mg/dl, the incidence of type 2 diabetes increased with increasing fasting plasma glucose (FPG) and 1-h and 2-h plasma glucose concentrations. In a multivariate logistic analysis, after adjustment for all diabetes risk factors, the FPG concentration was a strong predictor of type 2 diabetes in both the SAHS and the Botnia Study (P < 0.0001). However, when the 1-h plasma glucose, but not 2-h plasma glucose, concentration was added to the model, FPG concentration was no longer a significant predictor of type 2 diabetes in both studies (NS). When subjects were matched for the level of 1-h plasma glucose concentration, the incidence of type 2 diabetes markedly increased with the increase in 1-h plasma glucose, but the increase in FPG was not associated with a significant increase in the incidence of type 2 diabetes.

CONCLUSIONS

An increase in postload glycemia in the normal range is associated with an increase in the incidence of type 2 diabetes. After controlling for 1-h plasma glucose concentration, the increase in FPG concentration is not associated with an increase in the incidence of type 2 diabetes.Impaired fasting glucose (IFG) was introduced in 1997 by the American Diabetes Association (ADA) (1), and, analogous with impaired glucose tolerance (IGT), it was meant to represent an intermediate stage in the transition from normal glucose tolerance (NGT) to overt type 2 diabetes. Both IFG and IGT indicate an increased risk for future type 2 diabetes (2–4). Previously (5–7), we have shown that the 1-h plasma glucose concentration has better predictive power than either fasting plasma glucose (FPG) or 2-h plasma glucose, suggesting that the 1-h plasma glucose concentration may have greater utility in identifying subjects at increased risk for type 2 diabetes in routine clinical practice.Previous studies have reported that IFG and IGT represent separate clinical entities, which are characterized by distinct metabolic abnormalities (8–13). Subjects with IGT manifest insulin resistance in skeletal muscle (9–12) and impaired β-cell function (both early and late phases of insulin secretion) (10,14–16), whereas subjects with IFG are characterized by increased hepatic insulin resistance (9,16), impaired early insulin response (12), and decreased non–insulin-dependent glucose clearance (15). Because of the prominent role of progressive β-cell failure in the development of hyperglycemia (17), the impairment in β-cell function in subjects with IGT represents a major pathogenic factor for their increased risk for future type 2 diabetes. Although the increase in fasting plasma glucose is associated with a decrease in first-phase insulin secretion (11–13,18), subjects with IFG have robust second-phase insulin secretion, and, when related to their prevailing level of insulin resistance, they have second-phase insulin secretion comparable with that of subjects with NGT (12,13). Thus, impaired β-cell function cannot fully explain the increased incidence of type 2 diabetes associated with the increase in FPG concentration, e.g., in subjects with isolated IFG.Previously we have shown a strong correlation between insulin resistance in skeletal muscle and liver (16). Thus, a strong correlation between FPG and postload plasma glucose concentrations is anticipated. Therefore, we hypothesized that the increased type 2 diabetes risk associated with the increase in FPG, at least in part, is due to the increased postprandial plasma glucose concentration associated with the increase in FPG and is not due to the increase in FPG per se. The aim of this study was to test this hypothesis.     

Cardiovascular Disease Mortality in Europeans in Relation to Fasting and 2-h Plasma Glucose Levels Within a Normoglycemic Range

OBJECTIVE

To study mortality in relation to fasting plasma glucose (FPG) and 2-h plasma glucose levels within the normoglycemic range.

RESEARCH DESIGN AND METHODS

Data from 19 European cohorts comprising 12,566 men and 10,874 women who had FPG <6.1 mmol/l and 2-h plasma glucose <7.8 mmol/l at baseline examination were analyzed. Multivariate-adjusted hazard ratios (HRs) and 95% CIs for deaths from cardiovascular disease (CVD), non-CVD, and all causes were estimated for individuals whose 2-h plasma glucose > FPG (group II) compared with those whose 2-h plasma glucose ≤ FPG (group I).

RESULTS

A total of 827 (246) CVD and 611 (351) non-CVD and 1,438 (597) all-cause deaths occurred in men (women). Group II was older and had higher BMI, blood pressure, and fasting insulin than group I. The multivariate-adjusted HRs (95% CIs) for CVD, non-CVD, and all-cause mortality were 1.22 (1.05–1.41), 1.09 (0.92–1.29), and 1.16 (1.04–1.30) in men and 1.40 (1.03–1.89), 0.99 (0.79–1.25), and 1.13 (0.94–1.35) in women, respectively, for group II as compared with group I. HRs were 1.25 (1.05–1.50), 1.09 (0.89–1.34), and 1.18 (1.03–1.35) in men and 1.60 (1.03–2.48), 1.05 (0.78–1.42), and 1.18 (0.93–1.51) in women, respectively, after additional adjustment for fasting insulin in a subgroup of individuals.

CONCLUSIONS

In individuals with both FPG and 2-h plasma glucose within the normoglycemic range, high 2-h plasma glucose was associated with insulin resistance and increased CVD mortality.It is well known that type 2 diabetes (1,2) and nondiabetic hyperglycemia such as impaired glucose tolerance are risk factors for cardiovascular disease (CVD) mortality (3–5). The relations of fasting plasma glucose (FPG) and 2-h plasma glucose with CVD mortality and morbidity have been extensively investigated during the last few decades (6–9). Evidence has shown that 2-h plasma glucose is a stronger risk predictor than FPG for incident coronary heart disease (6) and CVD mortality (7), but little is known about the impact of FPG versus 2-h plasma glucose in the normoglycemic range. It has been suggested that individuals with normoglycemia, whose 2-h plasma glucose did not return to the FPG levels during an oral glucose tolerance test (OGTT) had a significantly higher risk of developing type 2 diabetes (10) and a worse cardiovascular risk factor profile (11) than individuals whose 2-h plasma glucose returned to the FPG levels. In the current study, based on the data of the Diabetes Epidemiology: Collaborative Analysis of Diagnostic Criteria in Europe (DECODE) study, we compared CVD mortality in individuals whose 2-h plasma glucose was higher than FPG with those whose 2-h plasma glucose was equal to or lower than FPG.     

A1C Between 5.7 and 6.4% as a Marker for Identifying Pre-Diabetes, Insulin Sensitivity and Secretion, and Cardiovascular Risk Factors: The Insulin Resistance Atherosclerosis Study (IRAS)

OBJECTIVE

A1C is an optional method for diagnosing diabetes and also for detecting individuals at increased risk of the disease. However, how A1C compares with fasting (FPG) and 2-h plasma glucose for detecting at-risk individuals is not well known.

RESEARCH DESIGN AND METHODS

A 2-h glucose tolerance test, frequently sampled intravenous glucose tolerance test, and A1C were obtained at the follow-up examination in 855 participants in the Insulin Resistance Atherosclerosis Study (IRAS). For this report, 385 individuals were at increased risk of diabetes as defined by A1C between 5.7 and 6.4%, impaired glucose tolerance (IGT), and/or impaired fasting glucose (IFG).

RESULTS

IFG and IGT identified 69.1 and 59.5% of all individuals at increased risk of diabetes, respectively. A1C 5.7–6.4% detected 23.6% of all at-risk individuals, although more African Americans (31.4%) and Hispanics (35.2%) than non-Hispanic whites (9.9%). Relative to A1C, FPG was more strongly related to fasting insulin (r = 0.38 vs. 0.26; P < 0.01), acute insulin response (r = – 0.20 vs. – 0.09; P < 0.01), and waist circumference (r = 0.43 vs. 0.25; P < 0.001) by the Spearman correlation test. Similarly, 2-h plasma glucose was more strongly related to Si (r = – 0.40 vs. – 0.27; P < 0.01) and triglycerides (r = 0.30 vs. 0.08; P < 0.001).

CONCLUSIONS

A1C 5.7–6.4% is less sensitive for detecting at-risk individuals than IFG and IGT, particularly among non-Hispanic whites. Single determinations of FPG and 2-h plasma glucose seem to be more precise correlates of insulin resistance and secretion than A1C and, in general, better for other metabolic disorders.A1C has been proposed by the American Diabetes Association (ADA) as an optional assay for diagnosing diabetes and also for detecting individuals at increased risk of the disease (1). A1C has been shown to predict future onset of diabetes (2–4) and is better than fasting plasma glucose (FPG) for predicting microvascular complications (1). A1C may be superior to FPG in predicting mortality and cardiovascular risk in nondiabetic individuals (5) but inferior to 2-h glucose concentration (2-h plasma glucose) in most studies (6–8), albeit not all (9). The A1C assay has advantages over the measurement of plasma glucose including convenience (not requiring fasting samples) and superior technical attributes (1). Conversely, the number of individuals diagnosed with diabetes by the 6.5% A1C threshold is significantly smaller than the number of those diagnosed by the 2003 American Diabetes Association (ADA) criteria (10–13). A1C, FPG, and 2-h plasma glucose assess different aspects of glucose metabolism (1), but differences in the relation of these three glycemic measures to insulin resistance, insulin secretion, and other metabolic abnormalities have not been described.A1C between 5.7 and 6.4% (A1C 5.7–6.4%) is now considered a category of increased risk for diabetes in addition to impaired fasting glucose (IFG) and impaired glucose tolerance (IGT) (1). However, studies that compare A1C 5.7–6.4% with IFG and IGT are lacking. Therefore, our aim was twofold: 1) to analyze A1C, FPG, and 2-h plasma glucose for their ability to identify individuals at increased risk of diabetes; and 2) to examine the relation of these glycemic measures to other metabolic abnormalities, particularly measured insulin resistance and secretion in nondiabetic subjects.     

Inflammatory, Hemostatic, and Other Novel Biomarkers for Diabetic Retinopathy: The Multi-Ethnic Study of Atherosclerosis

OBJECTIVE

There are conflicting data regarding relationships of systemic biomarkers of inflammation, hemostasis, and homocysteine with diabetic retinopathy. We examined these relationships in the Multi-Ethnic Study of Atherosclerosis.

RESEARCH DESIGN AND METHODS

A total of 921 participants with diabetes were included. Diabetic retinopathy was graded from retinal photographs. We defined two outcomes: any diabetic retinopathy and vision-threatening diabetic retinopathy (severe nonproliferative diabetic retinopathy or worse). Systemic markers analyzed were C-reactive protein, homocysteine, fibrinogen, plasmin-α₂-antiplasmin complex (PAP), interleukin-6, d-dimer, factor VIII, serum creatinine, and urinary albumin-to-creatinine (UAC) ratio.

RESULTS

Prevalence of diabetic retinopathy was 33.2% and vision-threatening diabetic retinopathy 7.1%. After adjusting for established risk factors (diabetes duration, A1C, systolic blood pressure, waist-to-hip ratio, and use of diabetes medications), fibrinogen (odds ratio 1.14 [95% CI 1.01–1.32], P = 0.05) and PAP (1.25 [1.05–1.50], P = 0.01) were associated with any diabetic retinopathy, while PAP (1.54 [1.13–2.11], P = 0.007) and homocysteine (1.57 [1.16–2.11], P = 0.003) were associated with vision-threatening diabetic retinopathy. Only PAP remained significant after additional adjustment for serum creatinine and UAC ratio. Area under receiver-operator characteristic curve (AUROC) for diabetic retinopathy was constructed for established and novel risk factors. Established risk factors accounted for a 39.2% increase of the AUROC, whereas novel markers (fibrinogen, PAP, homocysteine, serum creatinine, and UAC ratio) only accounted for an additional 2.2%.

CONCLUSIONS

There were few associations of novel markers of inflammation, hemostasis, and homocysteine with diabetic retinopathy after controlling for established risk factors. These data suggest that there is limited clinical use of these biomarkers for prediction of diabetic retinopathy.Diabetic retinopathy is the leading cause of blindness in working-age individuals (1). There is increasing evidence that established risk factors for diabetic retinopathy (2,3), including duration of diabetes, hyperglycemia, and hypertension, only explain a limited amount of the variance in the risk of diabetic retinopathy (1). Furthermore, the underlying pathogenesis of diabetic retinopathy remains inadequately understood (4). This has resulted in examination of the relation of novel risk markers such as inflammation (e.g., C-reactive protein [CRP]), markers of hemostatic disturbances (e.g., fibrinogen levels), and hyperhomocysteinemia to diabetic retinopathy. However, to date, the relations of these factors to diabetic retinopathy have not been consistent (5–17). The reasons for these inconsistencies may be due, in part, to differences in study sample and definitions of diabetic retinopathy (e.g., clinical versus photograph grading) and failure in some studies to make adequate adjustments for traditional risk factors such as glycemic control and hypertension. Thus, it remains unclear if there is a role for the use of these systemic markers as additional clinical tests to identify individuals at high risk of diabetic retinopathy. In this study, we evaluated the relationship of a range of inflammatory, hemostatic, and novel vascular markers with diabetic retinopathy, while controlling for traditional risk factors, in a large multiethnic population.     

Associations between media consumption habits, physical activity, socioeconomic status, and glycemic control in children, adolescents, and young adults with type 1 diabetes

OBJECTIVE

To evaluate the relationship between media consumption habits, physical activity, socioeconomic status, and glycemic control in youths with type 1 diabetes.

RESEARCH DESIGN AND METHODS

In the cross-sectional study, self-report questionnaires were used to assess media consumption habits, physical activity, and socioeconomic status in 296 children, adolescents, and young adults with type 1 diabetes. Clinical data and HbA_1c levels were collected. Risk factors were analyzed by multiple regression.

RESULTS

Youths with type 1 diabetes (aged 13.7 ± 4.1 years, HbA_1c 8.7 ± 1.6%, diabetes duration 6.1 ± 3.3 years) spent 2.9 ± 1.8 h per day watching television and using computers. Weekly physical activity was 5.1 ± 4.5 h. Multiple regression analysis identified diabetes duration, socioeconomic status, and daily media consumption time as significant risk factors for glycemic control.

CONCLUSIONS

Diabetes duration, socioeconomic status, and daily media consumption time, but not physical activity, were significant risk factors for glycemic control in youths with type 1 diabetes.The pivotal Diabetes Control and Complications Trial (DCCT) and Epidemiology of Diabetes Interventions and Complications (EDIC) study demonstrate that poor glycemic control is associated with an increased risk of developing complications in type 1 diabetes (1). Various factors contributing to glycemic control have been identified (2). Immutable parameters such as age, sex, diabetes duration, and socioeconomic status have a major effect on metabolic control (2–6). Lower socioeconomic status is an important determinant for poor glycemic control (4,5). Modifiable factors influencing metabolic control are diabetes-related knowledge, frequency of blood glucose monitoring, and daily insulin dose (3,4,6,7). Lastly, psychosocial parameters are important in achieving good glycemic control (3–5,8–10). The influence of physical activity on metabolic control is unclear (9,11,12).Recent research addresses the influence of modern life habits on general health. Youths spend more and more time watching television and using computers. Many studies suggest that sedentary behaviors such as watching television lead to obesity in children (13,14). In one study in youths with type 1 diabetes, Margeirsdottir et al. (15) showed that poor metabolic control was associated with extensive television watching. However, the authors did not examine other covariables, such as socioeconomic status, which is associated with both glycemic control and media consumption (4,5,16,17). Hence, the aim of this study was to examine the impact of media consumption habits, physical activity, and socioeconomic status on glycemic control in youths with type 1 diabetes.     

Relationship between A1C and fasting plasma glucose in dysglycemia or type 2 diabetes: an analysis of baseline data from the ORIGIN trial

OBJECTIVE

A1C measurement has advantages over measures of plasma glucose. Few studies have evaluated the A1C–fasting plasma glucose (FPG) relationship and whether oral antidiabetes drugs (OADs) and ethnic or geographic variations affect the relationship. Baseline A1C and FPG data from the Outcome Reduction with Initial Glargine Intervention (ORIGIN) trial participants were analyzed to 1) elucidate the relationship between A1C and FPG in people with moderate dysglycemia (A1C 5.6–9.0% [38–75 mmol/mol]) and additional risk factors for cardiovascular disease, 2) determine whether this relationship is altered by use of an OAD, and 3) study whether geographic and ethnic differences exist.

RESEARCH DESIGN AND METHODS

Analysis was performed of 12,527 participants with dysglycemia or early type 2 diabetes recruited in North America, South America, Europe, Australia, and Asia who comprised white, Latin American, Asian, black, and other ethnicities. The A1C-FPG relationships were analyzed using cubic B spline curves in all participants and in subgroups not using an OAD or using an OAD and comprising persons of different ethnic or geographic origin.

RESULTS

A strong relationship between FPG in the range of 5.6–9.0 mmol/L and the corresponding A1C was seen across different geographic regions and ethnic groups. A smaller increase in A1C per unit increase in FPG occurred for persons taking an OAD versus those not taking an OAD.

CONCLUSIONS

The strong relationship between A1C and FPG in moderate dysglycemia is not significantly affected by ethnic or geographic differences. Use of an OAD alters the relationship and should be considered when interpreting A1C level.A1C is widely used in the management of diabetes both as a measure of long-term glycemic control and as a risk factor for diabetes complications (1–3). Many studies have demonstrated that A1C is correlated with and reflects other measures of glycemic control including FPG and 2-h plasma glucose (4,5). A1C has several advantages over direct measures of plasma glucose including greater reproducibility and sample stability, less intrapersonal variation, and measurability in random versus fasting or postprandial blood samples (6,7). Limitations of A1C as a measure of glycemic control include genetically determined variations of hemoglobin structure that may alter the rate of glycation of the molecule or the lifespan of erythrocytes, thus altering the relationship between glucose and A1C. These observations, together with known ethnic and regional variations of dietary habits, suggest that A1C and glucose levels may differ by ethnicity (8–10) or geographic location (11). However, little is known about the relationship between A1C and glucose levels in different populations. Furthermore, few studies have evaluated whether the relationship between A1C and glucose levels is affected by the use of glucose-lowering agents (4,8,12).The Outcome Reduction with Initial Glargine Intervention (ORIGIN) trial is a global trial testing whether targeting normal FPG levels with basal insulin glargine reduces cardiovascular outcomes compared with standard care in people taking 0 or 1 oral antidiabetes drugs (OADs) (13). Baseline A1C and FPG data collected from participants were analyzed in order to 1) elucidate the relationship between A1C and FPG in persons with moderate dysglycemia (A1C 5.6–9.0% [38–75 mmol/mol]) and additional risk factors for cardiovascular disease, 2) determine whether this relationship is altered by use of an OAD, and 3) study whether the relationship differs in persons from different geographic regions or of different ethnicity.     

Rates of Progression in Diabetic Retinopathy During Different Time Periods: A systematic review and meta-analysis

OBJECTIVE

This meta-analysis reviews rates of progression of diabetic retinopathy to proliferative diabetic retinopathy (PDR) and/or severe visual loss (SVL) and temporal trends.

RESEARCH DESIGN AND METHODS

This systematic literature review and meta-analysis of prospective studies assesses progression of retinopathy among diabetic patients without treatment for retinopathy at baseline. Studies published between 1975 to February 2008 were identified. Outcomes of interest were rates of progression to PDR and/or SVL. Pooled baseline characteristics and outcome measures were summarized using weighted averages of counts and means. Baseline characteristics and outcomes were compared between two periods: 1975–1985 and 1986–2008.

RESULTS

A total of 28 studies comprising 27,120 diabetic patients (mean age 49.8 years) were included. After 4 years, pooled incidence rates for PDR and SVL were 11.0 and 7.2%, respectively. Rates were lower among participants in 1986–2008 than in 1975–1985. After 10 years, similar patterns were observed. Participants in 1986–2008 studies had lower proportions of PDR and non-PDR at all time points than participants in 1975–1985 studies.

CONCLUSIONS

Since 1985, diabetic patients have lower rates of progression to PDR and SVL. These findings may reflect an increased awareness of retinopathy risk factors; earlier identification and initiation of care for patients with retinopathy; and improved medical management of glucose, blood pressure, and serum lipids. Differences in baseline characteristics, particularly in the prevalence and severity of retinopathy, could also have contributed to these temporal differences.Diabetes affects more than 170 million individuals worldwide (1,2), and diabetic retinopathy is the most frequent cause of visual impairment among working-age individuals (3,4). In the last 3 decades, a relative decline in rates of diabetic retinopathy has been suggested by some studies, (5–8) possibly reflecting improved patient and physician awareness, screening, and prevention, as well as better management of diabetes (9). In 1985, the Early Treatment Diabetic Retinopathy Study (ETDRS) demonstrated the effectiveness of laser photocoagulation (10,11). Systemic control of both hyperglycemia and hypertension was shown to be important in the Diabetes Control and Complications Trial (DCCT) and the UK Prospective Diabetes Study (UKPDS) in the 1990s (12,13). Findings from these trials, other studies, and clinical practice guidelines may have led to increased public awareness to diabetes risk factors and a shorter time from onset to diagnosis, potentially altering the rates of diabetic retinopathy progression (9,14).Understanding the natural history of diabetic retinopathy is also important for estimating sample size for testing new interventions in clinical trials. Already, inadequate sample size estimations may have resulted in underpowered trials (15). Traditionally, progression rates from the ETDRS and the Wisconsin Epidemiologic Study of Diabetic Retinopathy (WESDR) were used for sample size calculations (16–22). However, these studies were conducted almost 30 years ago. Contemporary estimates for diabetic retinopathy progression are clearly needed, some of which may, in part, be provided by more recent studies, such as the Daily-Dose Consensus Interferon and Ribavirin: Efficacy of Combined Therapy (DIRECT) trial (23,24).In this systematic review and meta-analysis, we summarized the best available evidence to provide contemporary data on the clinical course of diabetic retinopathy and to examine potential differences in rates of diabetic retinopathy progression over time.     

Long-Term Changes in Adiposity and Glycemic Control Are Associated With Past Adenovirus Infection

OBJECTIVE

Ad36, a human adenovirus, increases adiposity but improves glycemic control in animal models. Similarly, natural Ad36 infection is cross-sectionally associated with greater adiposity and better glycemic control in humans. This study compared longitudinal observations in indices of adiposity (BMI and body fat percentage) and glycemic control (fasting glucose and insulin) in Ad36-infected versus uninfected adults.

RESEARCH DESIGN AND METHODS

Baseline sera from Hispanic men and women (n = 1,400) were screened post hoc for the presence of Ad36-specific antibodies. Indices of adiposity and glycemic control at baseline and at ∼10 years past the baseline were compared between seropositive and seronegative subjects, with adjustment for age and sex. In addition to age and sex, indices of glycemic control were adjusted for baseline BMI and were analyzed only for nondiabetic subjects.

RESULTS

Seropositive subjects (14.5%) had greater adiposity at baseline, compared with seronegative subjects. Longitudinally, seropositive subjects showed greater adiposity indices but lower fasting insulin levels. Subgroup analyses revealed that Ad36-seropositivity was associated with better baseline glycemic control and lower fasting insulin levels over time in the normal-weight group (BMI ≤25 kg/m²) and longitudinally, with greater adiposity in the overweight (BMI 25–30 kg/m²) and obese (BMI >30 kg/m²) men. Statistically, the differences between seropositive and seronegative individuals were modest in light of the multiple tests performed.

CONCLUSIONS

This study strengthens the plausibility that in humans, Ad36 increases adiposity and attenuates deterioration of glycemic control. Panoptically, the study raises the possibility that certain infections may modulate obesity or diabetes risk. A comprehensive understanding of these under-recognized factors is needed to effectively combat such metabolic disorders.A deeper understanding of the factors that modulate adiposity or glycemic control may aid in the development of more effective treatment and prevention strategies for combating obesity or diabetes. Although the contribution of various behavioral and physiological risk factors for obesity or diabetes is extensively investigated, that of several putative factors remains under-investigated (1). Ad36, a human adenovirus, is one such putative factor originally described for its adipogenic property (2). Subsequent data indicated that Ad36 is likely to modulate both adiposity and glycemic control. In various animal models, experimental Ad36 infection significantly increases adiposity (3–7) and yet, seemingly paradoxically, improves glycemic control (6,7). In vitro and ex vivo mechanistic studies indicate that Ad36 expands adipose tissue by recruiting adipocyte progenitors and increasing their commitment, differentiation, and lipid accumulation (8–12). In agreement with these findings, fat cells of humans harboring Ad36 DNA in adipose tissue have greater adipogenic ability compared with fat cells of those without Ad36 DNA (10). In addition, Ad36 increases cellular glucose uptake in adipose tissue and skeletal (13,14), reduces hepatic lipid accumulation and glucose release from hepatocytes (7,15), and upregulates adiponectin, an insulin-sensitizing adipocytokine (7,16), which may collectively contribute to systemic glycemic control improved by Ad36 (6,7). An improvement in glycemic control via the expansion of adipose tissue has been recently documented in several animal models (17–19) and has been suggested in humans receiving some antidiabetic agents (20). Similarly, Ad36 may mediate its effect on glycemic control by increasing adiposity.In humans, Ad36 infection is prevalent globally (21), with a prevalence of ∼15% in United States adults (7,22). Because of the substantial prevalence, if Ad36 influences adiposity or glycemic control in humans, then the potential impact could be considerable. However, ethical considerations preclude experimental infection of humans to determine a causal role of Ad36 in modulating adiposity or glycemic control. Several cross-sectional studies show that natural Ad36 infection in humans is associated with greater adiposity but better glycemic control. Association of Ad36 infection with greater BMI or greater prevalence of obesity is reported in adults from the United States (22), Italy (23), and Korea (24), and in children from the United States (25) and Korea (26,27). Ad36 infected human twins are significantly heavier compared with their uninfected counterparts (22). However, two studies did not find an association of Ad36 with obesity in military recruits or Scandinavian subjects (2). In four cohorts totaling >1,500 white, black, and Hispanic men, women, and children from the United States, Ad36 infection significantly predicted better indices of glycemic control that were independent of race, sex, age, and adiposity (7). Other smaller studies also showed significantly lower HbA1c levels and higher adiponectin in Ad36-infected adults (13,16). In addition, Ad36 infection is associated with lower hepatic lipid levels in United States and Italian adults and children (7,28).Similar to the phenotype induced by Ad36 in experimentally infected animals, overall human cross-sectional studies show an association of Ad36 infection with greater adiposity, better glycemic control, and lower hepatic lipid levels. This congruence of data from animal and human studies supports a similar role for Ad36 in humans. However, causality cannot be established unequivocally because of the observational nature of these studies. A prospective approach could help elucidate the long-term association of Ad36 infection with adiposity and glycemic control within a person over time, and could markedly strengthen causal inferences by assessing temporality. Such determination may advance our understanding of multifactorial nature of obesity or diabetes, and may lead to novel prevention or treatment strategies.This study screened baseline serum samples of Hispanic adults enrolled in San Antonio Family Heart Study for a history of natural Ad36 infection, as indicated by neutralizing antibodies. Data on obesity and glycemic control were collected for ∼10 years past baseline, which allowed the comparison of changes in indices of adiposity (BMI and body fat percentage) and glycemic control (fasting glucose and insulin) in Ad36-seropositive vs. Ad36-seronegative individuals.     

Active Care Management Supported by Home Telemonitoring in Veterans With Type 2 Diabetes: The DiaTel randomized controlled trial

OBJECTIVE

We compared the short-term efficacy of home telemonitoring coupled with active medication management by a nurse practitioner with a monthly care coordination telephone call on glycemic control in veterans with type 2 diabetes and entry A1C ≥7.5%.

RESEARCH DESIGN AND METHODS

Veterans who received primary care at the VA Pittsburgh Healthcare System from June 2004 to December 2005, who were taking oral hypoglycemic agents and/or insulin for ≥1 year, and who had A1C ≥7.5% at enrollment were randomly assigned to either active care management with home telemonitoring (ACM+HT group, n = 73) or a monthly care coordination telephone call (CC group, n = 77). Both groups received monthly calls for diabetes education and self-management review. ACM+HT group participants transmitted blood glucose, blood pressure, and weight to a nurse practitioner using the Viterion 100 TeleHealth Monitor; the nurse practitioner adjusted medications for glucose, blood pressure, and lipid control based on established American Diabetes Association targets. Measures were obtained at baseline, 3-month, and 6-month visits.

RESULTS

Baseline characteristics were similar in both groups, with mean A1C of 9.4% (CC group) and 9.6% (ACM+HT group). Compared with the CC group, the ACM+HT group demonstrated significantly larger decreases in A1C at 3 months (1.7 vs. 0.7%) and 6 months (1.7 vs. 0.8%; P < 0.001 for each), with most improvement occurring by 3 months.

CONCLUSIONS

Compared with the CC group, the ACM+HT group demonstrated significantly greater reductions in A1C by 3 and 6 months. However, both interventions improved glycemic control in primary care patients with previously inadequate control.Within the Veterans Health Administration, ∼500,000 veterans receive care for diabetes annually; diabetes is a leading cause of morbidity and mortality and a major contributor to health care cost (1,2). Sampling data from 2009 indicate that ∼28% of veterans nationally have suboptimal glycemic control with A1C ≥8% (3). Increases in A1C levels above the normal range in patients with diabetes are associated with progressive increases in morbidity and mortality due to micro- and macrovascular disease (4). Intensive glycemic control can reduce microvascular complications in both type 1 and type 2 diabetes (5,6). However, recent studies have not demonstrated that intensive glycemic control for 3–6 years with achieved A1C targets from 6.4 to 6.9% reduces macrovascular complications in patients with long-standing type 2 diabetes (7–9). In contrast, intensive glycemic control initiated early in the course of either type 1 or type 2 diabetes appears to reduce the risk of subsequent macrovascular complications significantly even when glycemic control later deteriorates (10,11).Home-based telemedicine has been examined as a tool for management of chronic diseases (12), including diabetes (13–19). This approach can obviate geographic barriers; provide automated education, feedback, and data transmission; and facilitate provider-to-patient communication (12). However, outcomes with home telemonitoring in diabetes and other chronic diseases have been variable (12). Of several randomized controlled trials (RCTs) using home telemonitoring in diabetes care (13–19), only two have reported significant improvement in A1C (17,18). Neither of these trials included active medication management by a provider in response to real-time transmission of self-monitored blood glucose (SMBG) data or have specifically targeted patients not meeting glycemic control goals in response to pharmacological therapy under conditions of usual care.The present study compared the efficacy of home telemonitoring coupled with active medication management by a nurse practitioner (ACM+HT intervention) with a lower-intensity care coordination intervention (CC intervention) consisting of monthly telephone contact with a diabetes nurse educator. Our study specifically targeted veterans with A1C levels ≥8% after ≥1 year receiving pharmacological therapy under conditions of usual care.     

Effect of Ranolazine on A1C and Glucose Levels in Hyperglycemic Patients With Non-ST Elevation Acute Coronary Syndrome

OBJECTIVE

We determined the relationships between glycemia at randomization, concurrent antidiabetic therapy, and change in A1C and fasting plasma glucose (FPG) in patients with diabetes receiving standard treatment for diabetes and randomized to ranolazine or placebo within the MERLIN-TIMI-36 (MERLIN) study. Ranolazine is a novel first-in-class drug approved for treating angina pectoris.

RESEARCH DESIGN AND METHODS

Randomization and 4-month glycemic and antidiabetes drug usage data from MERLIN were analyzed using Spotfire and SAS version 9.1 software.

RESULTS

In patients with diabetes and A1C of ≥8–10% at randomization (n = 171), there was an absolute A1C reduction in the ranolazine group of 1.2% (95% CI −1.4 to −1.0), and the placebo-adjusted (n = 182) decrease in A1C by ranolazine was 0.59% (95% CI −0.99 to −0.20, P < 0.001). In patients with FPG of 150–400 mg/dl at randomization, ranolazine (n = 131) compared with placebo (n = 147) reduced FPG by 25.7 mg/dl (95% CI −43.3 to −8.1, P = 0.001). When changes in either A1C or FPG were correlated to A1C or FPG at randomization, the slopes were significantly steeper for ranolazine than placebo (A1C, P = 0.046; FPG, P < 0.001), indicating that lowering of A1C and FPG by ranolazine is related to hyperglycemia at randomization. Ranolazine, compared with placebo, was not associated with serious hypoglycemic events, associated with significant changes in concurrent antidiabetic therapy, or dependent on a history of angina.

CONCLUSIONS

Ranolazine, when added to concurrent antidiabetes treatment, lowers FPG and A1C in patients with cardiovascular disease and poorly controlled diabetes.Diabetes is an established risk factor for cardiovascular disease, and the risk of cardiovascular disease increases with worsening hyperglycemia (1–3). Furthermore, coronary artery disease is the most common cause of death in patients with diabetes (4). Patients with coronary artery disease and a recent myocardial infarction or acute coronary syndrome (ACS) have an increased incidence of impaired fasting plasma glucose (FPG) and new-onset diabetes (5–7). Management of diabetes in patients with cardiovascular disease is complicated by the fact that the cardiovascular safety of some oral glucose–lowering agents has been questioned, and outcome data are lacking (8).Ranolazine is a first-in-class anti-anginal drug with cardioprotective properties without effects on heart rate or blood pressure (9). The drug inhibits the cardiac late sodium current (10,11). The late sodium current is enhanced during ischemia and in the failing heart and contributes to the Na+-dependent cellular calcium overload associated with these pathological conditions (10,11). Ranolazine has been shown effective in treating chronic angina both as a monotherapy (MARISA trial) and in combination with commonly prescribed cardiovascular drugs (CARISA and ERICA trials) (12–14), with no increase in mortality in patients with established coronary artery disease, including those with diabetes (15,16).Post hoc analysis of data from the CARISA study demonstrated that ranolazine lowered A1C, a long-term biomarker of glucose control, in patients with chronic angina and diabetes, in a dose-dependent manner (17). While the mechanism of glycemic improvement remains incompletely understood, preliminary studies using isolated rat and human pancreatic islets suggest ranolazine may promote glucose-stimulated insulin secretion (18).In the MERLIN-TIMI-36 (MERLIN) study, the effects of ranolazine to lower A1C and glucose were confirmed using prespecified glycemic end points (16). In this study, patients with diabetes were receiving standard of care treatment for diabetes with mean A1C levels of 7.5% at randomization. Despite the relatively low mean A1C at randomization, ranolazine was found to significantly reduce A1C in patients with diabetes and to reduce the incidence of newly elevated A1C in initially normoglycemic patients (16). The mean placebo-corrected reductions in A1C with ranolazine treatment at 4 months were 0.42% (P < 0.001) and 0.18% (P < 0.001) for patients with and without diabetes, respectively. There were no differences in the reported incidence of hypoglycemia between placebo and ranolazine.The glucose-lowering response to multiple antidiabetic therapies is greater in patients with higher baseline A1C and glucose values (19). Therefore, the current analysis of the MERLIN data was undertaken to evaluate the effects of ranolazine on FPG and A1C in diabetic patients with moderate or severe hyperglycemia, defined as an A1C of 6 to <8% or ≥8–10%, or FPG <150 or ≥150–400 mg/dl, respectively, at randomization. Additionally, MERLIN data were assessed as to whether effects of ranolazine on glycemia were influenced by concurrent antidiabetic therapy.     

Gestational Diabetes Mellitus: Simplifying the International Association of Diabetes and Pregnancy diagnostic algorithm using fasting plasma glucose

OBJECTIVE

To determine the impact of the International Association of Diabetes and Pregnancy Study Group (IADPSG) criteria on 1) gestational diabetes mellitus (GDM) diagnosis compared with the American Diabetes Association (ADA) criteria and 2) the fasting plasma glucose (FPG) to predict GDM.

RESEARCH DESIGN AND METHODS

In 10,283 pregnant women undergoing a 75-g oral glucose tolerance test (OGTT) for universal screening of GDM, two FPG thresholds (of the OGTT) were used to rule in and to rule out GDM.

RESULTS

The IADPSG and ADA criteria identified GDM in 3,875 (37.7%) women and 1,328 (12.9%) women, respectively (P < 0.0005). FPG thresholds of ≥5.1 mmol/l ruled in GDM in 2,975 (28.9%) women with 100% specificity, while <4.4 mmol/l ruled out GDM in 2,228 (21.7%) women with 95.4% sensitivity. FPG independently could have avoided the OGTT in 5,203 (50.6%) women.

CONCLUSIONS

The IADPSG criteria increased GDM prevalence nearly threefold. By circumventing a significant number of OGTTs, an initial FPG can greatly simplify the IADPSG diagnostic algorithm.The scourge of gestational diabetes mellitus (GDM) is the lack of an international agreement on the screening and diagnosis among the pre-eminent diabetes, obstetric, and health care organizations (1). Therefore, without a globally accepted guideline, the diagnosis of GDM causes a great deal of clinical confusion (2). In March 2010, the International Association of Diabetes and Pregnancy Study Group (IADPSG) issued consensus guidelines to potentially attain a single approach for GDM diagnosis worldwide (3).The inconsistency in GDM diagnosis is evident in the United Arab Emirates (UAE), which has the second highest prevalence of type 2 diabetes (18.7%) in the world (4). GDM in the UAE varies from 7.9 to 24.9%, depending on which of the six well-accepted criteria are used for diagnosis (2). The popular American Diabetes Association (ADA) criteria (5) demonstrates a prevalence of 10.6–14.7% (2,6–8). In this population, multiple studies have confirmed that the initial fasting plasma glucose (FPG) result of the oral glucose tolerance test (OGTT) is excellent in determining the need to continue with the OGTT (6,9–10); however, its efficiency depends on the criteria used for GDM diagnosis (6). The aim of this study was to determine, in this high-risk population, the impact of the new IADPSG criteria on 1) the diagnosis of GDM compared with the ADA criteria and 2) the FPG to predict GDM in order to decide whether to proceed with the OGTT.     

Long-Term Cardiovascular Risk in Type 2 Diabetic Compared With Nondiabetic First Acute Myocardial Infarction Patients: A population-based cohort study in southern Europe

OBJECTIVE

The aim of this study was to determine whether long-term cardiovascular risk differs in type 2 diabetic patients compared with first acute myocardial infarction patients in a Mediterranean region, considering therapy, diabetes duration, and glycemic control.

RESEARCH DESIGN AND METHODS

A prospective population-based cohort study with 10-year follow-up was performed in 4,410 patients aged 30–74 years: 2,260 with type 2 diabetes without coronary heart disease recruited in 53 primary health care centers and 2,150 with first acute myocardial infarction without diabetes recruited in 10 hospitals. We compared coronary heart disease incidence and cardiovascular mortality rates in myocardial infarction patients and diabetic patients, including subgroups by diabetes treatment, duration, and A1C.

RESULTS

The adjusted hazard ratios (HRs) for 10-year coronary heart disease incidence and for cardiovascular mortality were significantly lower in men and women with diabetes than in myocardial infarction patients: HR 0.54 (95% CI 0.45–0.66) and 0.28 (0.21–0.37) and 0.26 (0.19–0.36) and 0.16 (0.10–0.26), respectively. All diabetic patient subgroups had significantly fewer events than myocardial infarction patients: the HR of cardiovascular mortality ranged from 0.15 (0.09–0.26) to 0.36 (0.24–0.54) and that of coronary heart disease incidence ranged from 0.34 (0.26–0.46) to 0.56 (0.43–0.72).

CONCLUSIONS

Lower long-term cardiovascular risk was found in type 2 diabetic and all subgroups analyzed compared with myocardial infarction patients. These results do not support equivalence in coronary disease risk for diabetic and myocardial infarction patients.The prevalence of diabetes is reaching epidemic proportions in developed countries (1). For example, the U.S. has 18 million diabetic patients, Spain has >2 million diabetic patients, and management of the disease costs >$132 and >$3.3 billion per year, respectively (2).Some studies (3–5), several of them with great influence on important guidelines for cardiovascular prevention (3), suggest that the cardiovascular risk of diabetic patients is similar to that of coronary heart disease secondary prevention patients. Other reports, however, do not confirm these observations (6–10).Part of the discrepancy may stem from differences in the duration of diabetes, type of treatment, and baseline glucose control of diabetic patients included in the studies (3–5). These limit comparability, given the fact that time of evolution and treatment required to attain appropriate glycemic control are key determinants of prognosis (10–16).Among population-based cohort studies that compared the prognosis of diabetic patients with that of myocardial infarction patients without diabetes (3–10), only two analyzed the role of diabetes duration (11,12). Even these studies did not include unstable angina among the end points and risk was not stratified by type of treatment. To our knowledge, the effect of type 2 diabetes on coronary heart disease incidence has barely been studied in southern Europe, a region known for low cardiovascular mortality (17). The aim of this study was to determine whether long-term cardiovascular risk differed between type 2 diabetic patients and first acute myocardial infarction patients and to assess the influence of diabetes duration, type of treatment, and glycemic control at baseline.     

High prevalence of microvascular complications in adults with type 1 diabetes and newly diagnosed celiac disease

OBJECTIVE

The implications of celiac disease (CD) in adult patients with type 1 diabetes are unknown, with respect to diabetes-related outcomes including glycemic control, lipids, microvascular complications, quality of life, and the effect of a gluten-free diet (GFD). We identified CD in adults with type 1 diabetes and investigated the effect of a GFD on diabetes-related complications.

RESEARCH DESIGN AND METHODS

This was a case-control study conducted at a U.K. teaching hospital. Patients with type 1 diabetes aged >16 years (n = 1,000) were assessed for CD. HbA_1c, lipid profile, quality of life, retinopathy stage, nephropathy stage, and degree of neuropathy before and after 1 year on a GFD were assessed.

RESULTS

The prevalence of CD was 33 per 1,000 subjects (3.3% [95% CI 2.3–4.6]). At diagnosis of CD, adult type 1 diabetic patients had worse glycemic control (8.2 vs. 7.5%, P = 0.05), lower total cholesterol (4.1 vs. 4.9, P = 0.014), lower HDL cholesterol (1.1 vs. 1.6, P = 0.017), and a higher prevalence of retinopathy (58.3 vs. 25%, P = 0.02), nephropathy (41.6 vs. 4.2%, P = 0.009), and peripheral neuropathy (41.6 vs. 16.6%, P = 0.11). There was no difference in quality of life (P > 0.1). After 1 year on a GFD, only the lipid profile improved overall, but in adherent individuals HbA_1c and markers for nephropathy improved.

CONCLUSIONS

Adults with undetected CD and type 1 diabetes have worse glycemic control and a higher prevalence of retinopathy and nephropathy. Treatment with a GFD for 1 year is safe in adults with type 1 diabetes and does not have a negative impact on the quality of life.Long-term microvascular and neurologic complications are responsible for major morbidity and mortality in type 1 diabetes (1). Intensive glycemic control reduces these complications and improves quality of life (1). Even patients with good glycemic control have complications, suggesting that other factors increase the risk (2). Coexisting medical problems may be a confounding factor when managing glycemic control (2). The association between celiac disease (CD) and type 1 diabetes was recognized over 30 years ago, particularly by pediatricians. The prevalence of CD in patients with adult type 1 diabetes has been reported as 1.8–8.4% (3–6). Despite a large number of prevalence studies, other important clinical factors have not been well investigated, including glycemic control, quality of life, microvascular complications, cardiac risk factors, and bone mineral density.Investigations of the effect of CD on glycemic control have been conflicting, with some studies showing improvement (7) and some deterioration (4,8) and others showing no effect (9). The difficulty in interpreting these studies is that most involve pediatric populations and are small, retrospective, and uncontrolled, leaving this question unanswered. There have been no quality-of-life assessments before and after the diagnosis of CD to assess the impact of the diagnosis and a subsequent gluten-free diet (GFD) (3). Adapting to a GFD with the restrictions of a diabetic diet may negatively impact quality of life.Peripheral neuropathy affects up to 30% of patients with adult type 1 diabetes and is a major cause of morbidity (1). Neuropathy is associated with both type 1 diabetes and CD; therefore, patients with both conditions may have a higher prevalence (10,11). In gluten-sensitive neuropathy, the pathophysiological changes lie in the humoral immune response, and a GFD seems to be beneficial (12,13). There are no studies examining neuropathy in patients with type 1 diabetes and CD or the effect of a GFD. One study examined whether CD may contribute to autonomic neuropathy in a cohort of patients with type 1 diabetes. They found no difference in the prevalence of positive antibodies in patients with and without autonomic neuropathy (14).Two previous studies have examined the effect of CD on diabetic nephropathy but were conflicting (15,16). There are currently no studies examining the prevalence of retinopathy in individuals with both type 1 diabetes and CD.Recent data in nondiabetic CD cohorts have shown a reduced risk of ischemic heart disease, possibly attributed to lower cholesterol levels and a lower prevalence of hypertension (17). Reduced bone mineral density has been associated with both CD and type 1 diabetes, but there are little data on people with both conditions (18). The aim of our study was to identify undetected CD in adult patients with type 1 diabetes and investigate the effect on diabetes-related complications before and after a GFD.     

Declining ��-Cell Function Relative to Insulin Sensitivity With Increasing Fasting Glucose Levels in the Nondiabetic Range in Children

OBJECTIVE

In adults, higher fasting plasma glucose (FPG) levels, even within the normoglycemic range, are associated with increased diabetes risk. This investigation tested the hypothesis that β-cell function relative to insulin sensitivity decreases with increasing FPG in youth.

RESEARCH DESIGN AND METHODS

A total of 223 youth with FPG <126 mg/dl underwent evaluation of first- and second-phase insulin secretion during a 2-h hyperglycemic (∼225 mg/dl) clamp, insulin sensitivity during a 3-h hyperinsulinemic-euglycemic clamp, body composition, and abdominal adiposity with dual-energy X-ray absorptiometry and computed tomographic scan. β-Cell function relative to insulin sensitivity was calculated as the product of first-phase insulin and insulin sensitivity, i.e., glucose disposition index (GDI). The subjects were divided into three FPG categories: ≤90, >90–<100, and ≥100–<126 mg/dl.

RESULTS

GDI decreased significantly across the three categories as FPG increased (1,086 ± 192 vs. 814 ± 67 and 454 ± 57 mg/kg/min, P = 0.002). This decline remained significant after adjustment for race, sex, BMI, and percent body fat or visceral fat. Within each FPG category, GDI declined with increasing BMI percentiles.

CONCLUSIONS

The impairment in β-cell function relative to insulin sensitivity is apparent even within the nondiabetic FPG range in children. At the current cutoff of 100 mg/dl for impaired fasting glucose (IFG), there is an ∼49% decline in the GDI independent of obesity and race. This observation may reflect a heightened risk of β-cell dysfunction and progression to diabetes in these children. Considering the near doubling of IFG prevalence among youth between National Health and Nutrition Examination Survey 1999–2000 and 2005–2006, our findings have important public health implications.Higher fasting plasma glucose (FPG) levels within the currently accepted normoglycemic range seem to have an impact on diabetes risk in adults (1–3). FPG levels >125 mg/dl indicate a provisional diagnosis of diabetes (4). FPG levels below this cutoff but above normal increase the risk of developing diabetes (5) and are associated with a higher cardiovascular disease risk (6,7). The American Diabetes Association classifies this intermediate state of FPG as impaired fasting glucose (IFG) (4) and initially defined it as fasting glucose of 110–125 mg/dl (8), which was lowered to 100 mg/dl in 2003 to better identify subjects at risk of diabetes development (9). Several studies in adults suggested that future diabetes risk increases continually with increasing FPG even below this lower cutoff for normoglycemia (1,2). In adults, fasting glucose levels of 90–94 mg/dl conferred a 49% greater risk of developing diabetes compared with levels <85 mg/dl (2). FPG levels in the top quintiles (95–99 mg/dl) of the normoglycemic range constituted an independent risk factor for type 2 diabetes among young men in the Israeli army after adjustment for several risk factors (1). In a Mauritius population-based study, parameters related to diabetes and cardiovascular disease such as higher BMI, cholesterol, triglycerides, and hypertension were positively correlated with higher FPG values in an approximately linear relationship (3). In addition, a meta-analysis of prospective studies showed a continuous relationship between baseline fasting glucose and subsequent cardiovascular risk (10). These observations raise a fundamental question: are insulin secretion and sensitivity impaired at higher levels of FPG but within the normal range? Few studies in adults have investigated this question, and results are conflicting (11–13). However, none of these studies used robust methodologies of assessing in vivo insulin secretion and sensitivity to derive a glucose disposition index (GDI), which is accepted to be the best indicator of β-cell dysfunction (14). Currently there are no published data assessing the relationship between high-normal fasting glucose levels and insulin sensitivity and secretion in children. The pre-diabetes cutoff levels for FPG in pediatrics are based on adult data and not on data generated in pediatric populations.In this study, we investigated the relationship between levels of fasting glucose and insulin secretion relative to insulin sensitivity, i.e., GDI, in children. Based on adult observations we hypothesized that β-cell function relative to insulin sensitivity decreases as FPG concentrations increase within the currently accepted nondiabetic range in children.     

Effects of a Diet Higher in Carbohydrate/Lower in Fat Versus Lower in Carbohydrate/Higher in Monounsaturated Fat on Postmeal Triglyceride Concentrations and Other Cardiovascular Risk Factors in Type 1 Diabetes

OBJECTIVE

To compare the effects of a eucaloric diet higher in carbohydrate/lower in fat versus lower in carbohydrate/higher in monounsaturated fat on postmeal triglyceride (TG) concentrations and other cardiovascular disease risk factors in nonobese subjects with type 1 diabetes and in good glycemic control.

RESEARCH DESIGN AND METHODS

In a parallel group design study, 30 subjects were randomly assigned and completed one of the two eucaloric diets. Assessments included: BMI, blood pressure, A1C, plasma lipids, and markers of oxidation, thrombosis, and inflammation. At 6 months, subjects were hospitalized for 24 h to measure plasma TG excursions.

RESULTS

There were no significant differences between groups other than decreased plasminogen activator inhibitor 1 (PAI-1) levels and weight gain in the lower-carbohydrate/higher–monounsaturated fat group. During the 24-h testing, the lower-carbohydrate/higher–monounsaturated fat group had a lower plasma TG profile.

CONCLUSIONS

A diet lower in carbohydrate/higher in monounsaturated fat could offer an appropriate choice for nonobese type 1 diabetic individuals with good metabolic and weight control.The optimal macronutrient composition of the diet in diabetes has not yet been established. Dietary recommendations for carbohydrates range from 45–60% of energy intake and 25–35% for fat (1–2); the amount of carbohydrates is usually inversely associated with amount of fat. On the one hand, higher amounts of carbohydrates are directly associated with increases in plasma triglyceride (TG) levels and postprandial glycemic levels (3), risk factors in the development of micro- and macrovascular complications in diabetes (4–5). On the other hand, higher-fat diets have the potential to increase fasting and postprandial TG levels, independent risk factors for macroangiopathy (5). Thus, nutrition therapy needs to address the effects of diet on both fasting and postprandial TG and glycemic levels.In type 2 diabetes, replacing carbohydrates with monounsaturated fats in eucaloric diets was associated with lower TG levels and improved glycemic control (6–7); however, results are contradictory in type 1 diabetes (8–9). Therefore, our objective was to compare the effects of a eucaloric diet, higher in carbohydrate/lower in fat versus lower in carbohydrate/higher in monounsaturated fat, on 24-h TG and glycemic excursions and other cardiovascular risk factors in type 1 diabetes. We expected that: 1) the lower carbohydrate content of the higher–monounsaturated fat diet would reduce VLDL-TG production, resulting in lower fasting TG levels and 24-h TG area under the curve, in line with type 2 diabetes studies (6–7); and, 2) the higher monounsaturated fat intake would positively affect LDL oxidation, adhesion molecules, and markers of thrombosis and inflammation (10–12).     

Retinal Vascular Fractal Dimension and Risk of Early Diabetic Retinopathy: A prospective study of children and adolescents with type 1 diabetes

OBJECTIVE

To examine the prospective association of retinal vascular fractal dimension with diabetic retinopathy risk in young people with type 1 diabetes.

RESEARCH DESIGN AND METHODS

This was a hospital-based prospective study of 590 patients aged 12–20 years with type 1 diabetes free of retinopathy at baseline. All patients had seven-field retinal photographs taken of both eyes. Incident retinopathy was ascertained from retinal photographs taken at follow-up visits. Fractal dimension was measured from baseline photographs using a computer-based program following a standardized protocol.

RESULTS

Over a mean ± SD follow-up period of 2.9 ± 2.0 years, 262 participants developed mild nonproliferative diabetic retinopathy (15.0 per 100 person-years). After adjusting for age, sex, diabetes duration, A1C, and other risk factors, we found no association between retinal vascular fractal dimension and incident retinopathy.

CONCLUSIONS

Retinal vascular fractal dimension was not associated with incident early diabetic retinopathy in this sample of children and adolescents with type 1 diabetes.Fractal objects are self-similar structures that retain a similar level of complexity across all scales. For example, blood vessels repeatedly subdivide downstream into smaller blood vessels with similar network patterns. Fractal dimension (D_f) quantifies the degree of complexity into a single value and is particularly useful for quantifying non-Euclidean geometric shapes such as vascular networks. The retinal circulation is a fractal object (1–3), and fractal analysis has been used to study the embryological development of the retinal vasculature (2) and vascular changes associated with diabetic retinopathy (3–7). Variations in retinal vascular D_f may reflect geometric alterations in the vascular network in response to hypoxia (2,7).Earlier case-control studies showed that retinal vascular D_f was associated with proliferative diabetic retinopathy (5,6), suggesting that neovascularization increases the complexity of the retinal vascular branching pattern. More recently, using a computer-based program to reliably measure D_f of the retinal vasculature (8), we reported that retinal vascular D_f was cross-sectionally associated with the prevalence of early retinopathy in patients with type 1 diabetes (9). However, prospective data are needed to elucidate the significance of this interesting finding. We therefore aimed to determine whether retinal vascular D_f measured from baseline photographs of eyes without retinopathy is associated with subsequent risk of retinopathy development in a cohort of type 1 diabetic subjects.     

Assessing Glycemic Control in Maintenance Hemodialysis Patients With Type 2 Diabetes

OBJECTIVE

Optimizing glycemic control in diabetic patients undergoing maintenance hemodialysis requires accurate assessment. We hypothesize that 1) 48-h continuous glucose monitoring (CGM) provides additional, clinically relevant, information to that provided by the A1C measurement and 2) glycemic profiles differ significantly between day on and day off dialysis.

RESEARCH DESIGN AND METHODS

With the use of GlucoDay S, 48-h CGM was performed in 19 type 2 diabetic subjects undergoing hemodialysis to capture consecutive 24-h periods on and off dialysis. Energy intake was calculated using food diaries. A1C was assayed by a high-performance liquid chromatography method.

RESULTS

CGM data were available for 17 subjects (13 male) with a mean (range) age of 61.5 years (42–79 years) and diabetes duration of 18.8 years (4–30 years). The 24-h CGM area under the glucose curve and 24-h mean glucose values were significantly higher during the day off dialysis than on dialysis (5,932.1 ± 2,673.6 vs. 4,694 ± 1,988.0 mmol · 3 min⁻¹ · l⁻¹, P = 0.022, and 12.6 ± 5.6 vs. 9.8 ± 3.8 mmol/l, P = 0.013, respectively), independent of energy intake. Asymptomatic hypoglycemia occurred in 4 subjects, 3 within 24 h of dialysis, and the glucose nadir in 14 subjects occurred within 24 h of dialysis.

CONCLUSIONS

Glucose values are significantly lower on dialysis days than on nondialysis days despite similar energy intake. The risk of asymptomatic hypoglycemia was highest within 24 h of dialysis. Physicians caring for patients undergoing hemodialysis need to be aware of this phenomenon and consider enhanced glycemic monitoring after a hemodialysis session. CGM provides glycemic information in addition to A1C, which is potentially relevant to clinical management.Diabetic nephropathy is the leading cause of end-stage renal failure (ESRF) (1), representing 30–45% of the U.K. and U.S. (2) populations undergoing long-term maintenance hemodialysis. The patients typically are elderly type 2 diabetic patients with established micro- and macrovascular disease (3). Hypoglycemia is common because of impaired renal gluconeogenesis, malnutrition, and the increased half-life of insulin and hypoglycemic agents (4). The annual mortality among diabetic patients undergoing hemodialysis is high and is predominately due to cardiovascular disease (CVD) (2).Intensive glycemic management delays progression of microvascular disease (5–8) and improves malnutrition (9); however, large randomized controlled trials show no mortality benefit in high-risk groups with CVD (7),(10). Hypoglycemic events increase with intensive treatment and in the presence of CVD can cause fatal dysrhythmia (11). U.K. diabetes guidelines advise against intensive treatment aimed to lower A1C levels <6.5% (12), whereas American guidelines caution against values <7% (13). No evidence-based guidelines for the glycemic targets for diabetic patients with ESRF undergoing long-term maintenance hemodialysis are available.In patients without ESRF, the A1C value is routinely used to assess long-term glycemic control, and assays are standardized to those used in the Diabetes Control and Complications Trial (14). There is a strong correlation between A1C values and the weighted mean glucose values of the preceding 2–3 months (14).The validity of the A1C measurement in patients with ESRF undergoing hemodialysis depends on the methodology (15). A number of factors may influence the assay including altered red blood cell (RBC) life span and metabolic and mechanical factors (16). Potential metabolic factors are interference from carbamylated hemoglobin formed in uremia and acetylated hemoglobin formed from long-term aspirin use (17).A limitation of the A1C value in patients undergoing hemodialysis is that it is not informative regarding glycemic control on the days on and off dialysis. In the U.K., maintenance hemodialysis is typically given in a hospital setting three times a week, with sessions lasting 4–5½ h. The CGM devices that measure glucose every 3 min using a biosensor and a subcutaneous microbore cannula are, in contrast, ideally suited to examine the effect of dialysis on glucose profiles over a 48-h period. Thus, in the present study we test the hypotheses 1) that 48-h CGM provides additional, clinically relevant, information to that provided by the A1C measurement in patients undergoing hemodialysis and 2) that 24-h glucose profiles are different on the day that includes a dialysis session compared with those on a day that does not.     

Assessing Progress in Retinopathy Outcomes in Type 1 Diabetes: Comparing findings from the Wisconsin Diabetes Registry Study and the Wisconsin Epidemiologic Study of Diabetic Retinopathy

OBJECTIVE

The Wisconsin Diabetes Registry Study (WDRS) cohort consisted of patients diagnosed with type 1 diabetes in the same geographic region as, but 8–34 years later than the Wisconsin Epidemiologic Study of Diabetic Retinopathy (WESDR) cohort, providing a unique opportunity to assess changes in complications. We estimated the current prevalence and severity of diabetic retinopathy at 20 years of diabetes duration, compared these between eras, and evaluated the influence of diabetes management.

RESEARCH DESIGN AND METHODS

Twenty-year examinations, including fundus photographs, were completed on 305 WDRS subjects during 2007–2011. A subgroup of the WESDR cohort participated in one of four study visits during 1980–1996, at similar diabetes duration (n = 583). Adjusted ordinal logistic regression with three retinopathy severity categories was used to estimate odds ratios (ORs) of more severe retinopathy with diagnosis during an earlier era.

RESULTS

Mean hemoglobin A_1c (HbA_1c) was lower in WDRS than in WESDR (8.0% vs. 9.3% [P < 0.001], and 93.4% vs. 21.3% [P < 0.001]) used ≥3 daily insulin injections or an insulin pump. In WDRS, 18% had vision-threatening levels of retinopathy vs. 43% in WESDR. The adjusted OR of more severe retinopathy in the earlier era (OR 3.0 [95% CI 2.2–4.0]) was reduced by including 20-year HbA_1c in the model (OR 2.2 [1.6–3.0]).

CONCLUSIONS

Retinopathy severity at a diabetes duration of 20 years is lower in the more recent era of type 1 diabetes. Updated projections should be used when informing newly diagnosed individuals of prognosis and for health care cost assessments. Current glycemic control explained a limited amount of the difference.The burden of type 1 diabetes mellitus is high. Because type 1 diabetes onset is typically in childhood and adolescence, the effort to manage the disease and its sequelae lasts a lifetime. The majority of the morbidity and mortality associated with type 1 diabetes comes from chronic microvascular and macrovascular complications (1,2), including diabetic retinopathy (DR), a leading cause of preventable blindness in adults (3). Previously, some evidence of DR was present in most individuals by 15–20 years of diabetes duration (4,5). Recent reports, however, suggest less or less severe DR in the current era of diabetes care, not only at early durations (6,7) but perhaps even in long-standing type 1 diabetes (8–11). Studies report a decline in the incidence of severe DR across those diagnosed during the 1960s, 1970s, and early 1980s (8–10), but they may still overestimate the current level of retinopathy at 20 years of the disease (12). “Glycemic memory” (13) implies that individuals practicing intensive diabetes management starting at early diabetes duration may have much lower rates or lesser severity of retinopathy today. Antihypertensive and lipid-lowering therapies now implemented earlier in the course of the disease could also impact the current level of retinopathy (8,14). The current course of retinopathy clearly has implications for individuals with type 1 diabetes as well as the health care system (15). Contemporary estimates on DR, DR severity, and diabetes self-management practices from population-based studies of individuals with type 1 diabetes in the U.S. are needed (12,15).Differences in methods of identifying DR complicate the evaluation of time trends in retinopathy (16,17). In our two studies, protocols for data collection included the same gold standard methods for objectively measuring retinopathy. The Wisconsin Diabetes Registry Study (WDRS) has followed a population-based cohort of individuals comprehensively since diagnosis of type 1 diabetes (6,18). This cohort was enrolled from a geographically defined region overlapping the study area of the landmark and also population-based Wisconsin Epidemiologic Study of Diabetic Retinopathy (WESDR) (4). We sought to capitalize on the unique opportunity presented by these two cohorts to investigate change in the course of DR. Specifically, we aimed to do the following: 1) provide contemporary estimates of the prevalence and severity of DR and diabetes self-management in the population after type 1 diabetes duration of 20 years, 2) compare retinopathy severity between time periods, and 3) evaluate whether changes in glycemic control and related diabetes management factors explained the differences seen in retinopathy between these time periods.     

Glycemic Control, Coping, and Internalizing and Externalizing Symptoms in Adolescents With Type 1 Diabetes: A cross-lagged longitudinal approach

OBJECTIVE

This study examines how active coping and withdrawal, psychological (internalizing and externalizing) symptoms, and glycemic control (A1C values) influence each other across time in adolescents with type 1 diabetes.

RESEARCH DESIGN AND METHODS

One hundred and nine adolescents participated in a four-wave longitudinal study spanning four years (mean age at Time 1 was 13.77). Patients were visited at home and completed questionnaires measuring coping and psychological symptoms. The treating physicians were contacted to obtain A1C values. Cross-lagged path analysis from a structural equation modeling approach was used for data analysis.

RESULTS

Clinically meaningful pathways between coping and glycemic control were found across time. Active coping prospectively predicted lower A1C levels, which, in turn, predicted active coping. Higher A1C levels and higher psychological symptoms consistently predicted avoidance coping across time. Finally, psychological symptomatology constituted an important link in the observed longitudinal chain of effects. More specifically, higher A1C values and symptomatology at Time 1 positively predicted withdrawal at Time 2, which, in turn, positively predicted symptomatology at Time 3. Next, symptomatology at Time 3 positively predicted higher A1C values at Time 4, thus coming full circle.

CONCLUSIONS

Coping with everyday stress, psychological symptoms, and glycemic control were interrelated across time. Evidence was obtained for reciprocal pathways and mutually reinforcing mechanisms, indicating the need to monitor coping strategies and psychological symptoms along with glycemic control in optimizing clinical care in adolescents with type 1 diabetes.Adolescence can be a challenging time when individuals have to deal with several developmental tasks such as growing independent from parents and developing mature peer relationships. Having type 1 diabetes imposes multiple additional demands on the adolescent, invading every aspect of his or her life. Diabetes management requires a great deal of self-discipline and is perceived as being highly stressful (1). Consequently, several studies suggest that adolescents with diabetes are at a greater risk than their healthy peers for developing psychological symptoms (such as internalizing and externalizing symptoms, which are both being assessed in this study) or even psychiatric disorders (e.g., depressive disorder) (2–4). However, other studies did not find increased levels of psychological symptoms in these adolescents (5,6), which could signal their increased competence in managing their illness and coping with age-specific developmental tasks. Psychological symptoms (such as internalizing or, more specifically, depressive symptoms) can negatively influence glycemic control through physiological channels and/or through behavioral pathways thereby reducing treatment adherence (4,7). In turn, such symptoms can also be a consequence of poorly controlled diabetes (e.g., due to repeated stressful episodes of severe diabetic ketoacidosis and diabetic microvascular complications such as retinopathy) (3,8–10). As such, the relationship between psychological symptoms and glycemic control is hypothesized to be a reciprocal one.Several studies have shown that many adolescents have difficulty coping with various illness-specific and everyday stressors, show low adherence with their prescribed treatment, and/or poor glycemic control (11,12). Seiffge-Krenke et al. (13,14) distinguished between functional and dysfunctional coping. Functional coping refers to efforts to manage a problem by actively seeking support, taking concrete actions, or reflecting on possible solutions. Dysfunctional coping includes efforts to withdraw from or deny the existence of the stressor and to avoid seeking solutions and, as such, risk exacerbating the effects of stress (11). Adolescents using active coping skills were less likely to show a worsening in their glycemic control, implying that their coping competencies had a protective effect (15). The consistent use of withdrawal or avoidance coping has been linked to increases in psychological symptoms in community samples (16). In sum, adolescents with diabetes who use withdrawal coping may be at risk for psychological symptoms and poor glycemic control. Some have suggested that these relationships may be reciprocal (1).     

Large Pre- and Postexercise Rapid-Acting Insulin Reductions Preserve Glycemia and Prevent Early- but Not Late-Onset Hypoglycemia in Patients With Type 1 Diabetes

OBJECTIVE

To examine the acute and 24-h glycemic responses to reductions in postexercise rapid-acting insulin dose in type 1 diabetic patients.

RESEARCH DESIGN AND METHODS

After preliminary testing, 11 male patients (24 ± 2 years, HbA_1c 7.7 ± 0.3%; 61 ± 3.4 mmol/mol) attended the laboratory on three mornings. Patients consumed a standardized breakfast (1 g carbohydrate ⋅ kg⁻¹ BM; 380 ± 10 kcal) and self-administered a 25% rapid-acting insulin dose 60 min prior to performing 45 min of treadmill running at 72.5 ± 0.9% VO_2peak. At 60 min postexercise, patients ingested a meal (1 g carbohydrate ⋅ kg⁻¹ BM; 660 ± 21 kcal) and administered a Full, 75%, or 50% rapid-acting insulin dose. Blood glucose concentrations were measured for 3 h postmeal. Interstitial glucose was recorded for 20 h after leaving the laboratory using a continuous glucose monitoring system.

RESULTS

All glycemic responses were similar across conditions up to 60 min postexercise. After the postexercise meal, blood glucose was preserved under 50%, but declined under Full and 75%. Thence at 3 h, blood glucose was highest under 50% (50% [10.4 ± 1.2] vs. Full [6.2 ± 0.7] and 75% [7.6 ± 1.2 mmol ⋅ L⁻¹], P = 0.029); throughout this period, all patients were protected against hypoglycemia under 50% (blood glucose ≤3.9; Full, n = 5; 75%, n = 2; 50%, n = 0). Fifty percent continued to protect patients against hypoglycemia for a further 4 h under free-living conditions. However, late-evening and nocturnal glycemia were similar; as a consequence, late-onset hypoglycemia was experienced under all conditions.

CONCLUSIONS

A 25% pre-exercise and 50% postexercise rapid-acting insulin dose preserves glycemia and protects patients against early-onset hypoglycemia (≤8 h). However, this strategy does not protect against late-onset postexercise hypoglycemia.Patients with type 1 diabetes are encouraged to engage in regular exercise as part of a healthy lifestyle (1,2). However, engaging in exercise is not without its difficulties (1). Defective glucose regulation presents a significant challenge in preventing hypoglycemia during, and particularly after, exercise (3,4). Exercise-induced hypoglycemia is both a frequent (5) and dangerous occurrence (6) and remains a major obstacle to patients who wish to engage in exercise (7).Much of the literature has focused on providing strategies to help combat hypoglycemia during, and early after, exercise (8–17), with investigations focusing on altering exercise modality (14,18), carbohydrate consumption (12,16,17), and reductions to pre-exercise, rapid-acting insulin dose (10–12,17,19). Prior to moderate-intensity, continuous, aerobic exercise, it is recommended that patients should reduce their prandial rapid-acting insulin dose by ∼75% to prevent hypoglycemia during exercise (10–12). However, despite best preserving blood glucose, it has been shown that this strategy is not fully protective against postexercise hypoglycemia (11,12). This has, in part, been attributed to iatrogenic causes (11), whereby patients administer their usual doses of rapid-acting insulin in a heightened insulin-sensitive state, potentially leading to unexpected falls in blood glucose and, consequently, hypoglycemia (11).A potential strategy to help minimize the risk of developing hypoglycemia after exercise could be to reduce the dose of rapid-acting insulin administered with the postexercise meal (20). Exercise increases the sensitivity of the body to insulin for many hours after exercise (3) and patients could be faced with a window of particularly high sensitivity around the postexercise meal, whereby greater rates of glucose uptake could occur to supplement the high metabolic priority of replenishing muscle glycogen (21). Thus, the meal consumed after exercise is important. With this in mind, it would be intuitive to reduce the amount of insulin administered with the meal consumed at this time; this may preserve glycemia and prevent postexercise hypoglycemia. Conversely, severe reductions in rapid-acting insulin dose may incur prolonged postexercise hyperglycemia, even more so if the pre-exercise dose is also reduced. However, there is a lack of data to confirm or refute these hypotheses. In addition, it would be prudent to examine the extent to which rapid-acting insulin dose adjustments may help combat late falls in glycemia after exercise, considering type 1 diabetic patients are susceptible to late-onset, postexercise hypoglycemia (3), suggested to be due to a biphasic response in glucose uptake occurring early and also late after exercise (22). Therefore, the aim of this study was to examine the acute and 24-h postexercise glycemic responses to reducing the postexercise rapid-acting insulin dose, when using the recommended pre-exercise insulin reductions, in type 1 diabetic patients.