Postchallenge Glucose, A1C, and Fasting Glucose as Predictors of Type 2 Diabetes and Cardiovascular Disease: A 10-year prospective cohort study

OBJECTIVE

A1C has been proposed as a new indicator for high risk of type 2 diabetes. The long-term predictive power and comparability of elevated A1C with the currently used high-risk indicators remain unclear. We assessed A1C, impaired glucose tolerance (IGT), and impaired fasting glucose (IFG) as predictors of type 2 diabetes and cardiovascular disease (CVD) at 10 years.

RESEARCH DESIGN AND METHODS

This prospective population-based study of 593 inhabitants from northern Finland, born in 1935, was conducted between 1996 and 2008. An oral glucose tolerance test (OGTT) was conducted at baseline and follow-up, and A1C was determined at baseline. Those with a history of diabetes were excluded from the study. Elevated A1C was defined as 5.7–6.4%. Incident type 2 diabetes was confirmed by two OGTTs. Cardiovascular outcome was measured as incident CVD or CVD mortality. Multivariate log-binomial regression models were used to predict diabetes, CVD, and CVD mortality at 10 years. Receiver operating characteristic curves compared predictive values of A1C, IGT, and IFG.

RESULTS

Incidence of diabetes during the follow-up was 17.1%. Two of three of the cases of newly diagnosed diabetes were predicted by a raise in ≥1 of the markers. Elevated A1C, IGT, or IFG preceded diabetes in 32.8, 40.6, and 21.9%, respectively. CVD was predicted by an intermediate and diabetic range of 2-h glucose but only by diabetic A1C levels in women.

CONCLUSIONS

A1C predicted 10-year risk of type 2 diabetes at a range of A1C 5.7–6.4% but CVD only in women at A1C ≥6.5%.Early detection of high risk for type 2 diabetes is fundamental for prevention of diabetes and associated cardiovascular complications. Impaired fasting glucose (IFG) and impaired glucose tolerance (IGT) are currently used for diagnosis of high-risk glucose levels below the diabetic range. The International Expert Committee proposed A1C ≥6.5% as a diagnostic tool for diabetes in 2009 (1) and in January 2010 an intermediate range of A1C 5.7–6.4% (elevated A1C) was proposed by the American Diabetes Association (ADA) to detect individuals at high risk for developing type 2 diabetes (2).To date, however, limited data exist to support the use of A1C in predicting type 2 diabetes (3–8). Importantly, the long-term predictive power of elevated A1C as defined above has not yet been investigated. Previous data on the association between A1C and incident type 2 diabetes in unselected populations have relied on self-reporting, fasting glucose measurements, and use of antidiabetes medication to determine the outcomes. An oral glucose tolerance test (OGTT) has not been used to determine the outcome (3–8).Deterioration of glucose homeostasis reflects a continuum of glycemia, some of which is reversible if detected early (9,10). Importantly, the risk of cardiovascular disease is increased already before glycemia reaches the levels of diabetes, and 2-h glucose appears to be a better predictor of cardiovascular disease (CVD) than fasting glucose (11). Recently, A1C was shown to be a better predictor of CVD than fasting glucose (12).Data directly comparing 2-h glucose and A1C as long-term predictors of new-onset cardiovascular disease are scarce, and results are controversial (13,14). Therefore, we compared A1C, 2-h glucose, and fasting glucose as predictors of type 2 diabetes, CVD, and CVD mortality during a prospective population-based study with a 10-year follow-up.     

��-Cell�CMediated Signaling Predominates Over Direct ��-Cell Signaling in the Regulation of Glucagon Secretion in Humans

OBJECTIVE

Given evidence of both indirect and direct signaling, we tested the hypothesis that increased β-cell–mediated signaling of α-cells negates direct α-cell signaling in the regulation of glucagon secretion in humans.

RESEARCH DESIGN AND METHODS

We measured plasma glucagon concentrations before and after ingestion of a formula mixed meal and, on a separate occasion, ingestion of the sulfonylurea glimepiride in 24 basal insulin-infused, demonstrably β-cell–deficient patients with type 1 diabetes and 20 nondiabetic, demonstrably β-cell–sufficient individuals; the latter were infused with glucose to prevent hypoglycemia after glimepiride.

RESULTS

After the mixed meal, plasma glucagon concentrations increased from 22 ± 1 pmol/l (78 ± 4 pg/ml) to 30 ± 2 pmol/l (103 ± 7 pg/ml) in the patients with type 1 diabetes but were unchanged from 27 ± 1 pmol/l (93 ± 3 pg/ml) to 26 ± 1 pmol/l (89 ± 3 pg/ml) in the nondiabetic individuals (P < 0.0001). After glimepiride, plasma glucagon concentrations increased from 24 ± 1 pmol/l (83 ± 4 pg/ml) to 26 ± 1 pmol/l (91 ± 4 pg/ml) in the patients with type 1 diabetes and decreased from 28 ± 1 pmol/l (97 ± 5 pg/ml) to 24 ± 1 pmol/l (82 ± 4 pg/ml) in the nondiabetic individuals (P < 0.0001). Thus, in the presence of both β-cell and α-cell secretory stimuli (increased amino acid and glucose levels, a sulfonylurea) glucagon secretion was prevented when β-cell secretion was sufficient but not when β-cell secretion was deficient.

CONCLUSIONS

These data indicate that, among the array of signals, indirect reciprocal β-cell–mediated signaling predominates over direct α-cell signaling in the regulation of glucagon secretion in humans.The regulation of pancreatic islet α-cell glucagon secretion is complex (1–10). It involves direct signaling of α-cells (1) and indirect signaling of α-cells by β-cell (2–6) and δ-cell (7) secretory products, the autonomic nervous system (8,9), and gut incretins (10).Appropriate glucagon secretory responses occur from the perfused pancreas (3,5) and perifused islets (2). Low plasma glucose concentrations stimulate glucagon secretion from the transplanted (i.e., denervated) human pancreas (11) and the denervated dog pancreas (12). Therefore, we have focused on the intraislet regulation of glucagon secretion. Furthermore, because selective destruction of β-cells results in loss of the glucagon response to hypoglycemia in type 1 diabetes (13), and partial reduction of the β-cell mass in minipigs results in impaired postprandial suppression of glucagon secretion (14), we have focused on the role of β-cell–mediated signaling in the regulation of glucagon secretion.Findings from studies of the perfused rat (3,4) and human (5) pancreas, rats in vivo (6), rat islets (2), isolated rat α-cells (2), and humans (15–18) have been interpreted to indicate that a β-cell secretory product or products tonically restrains basal α-cell glucagon secretion during euglycemia and that a decrease in β-cell secretion, coupled with low glucose concentrations at the α-cells, signals an increase in glucagon secretion in response to hypoglycemia. Parenthetically, the relative roles of the candidate β-cell secretory products (insulin, zinc, γ-aminobutyric acid, and amylin, among others) (2) that normally restrain α-cell glucagon secretion remain to be determined. However, that interpretation rests, in part, on results of studies in isolated rat α-cells (2), which are debated (1), and on the evidence that the islet microcirculation flows from β-cells to α-cells to δ-cells (4), which is also debated (19). Furthermore, it does not address the plausible possibility that a decrease in intraislet δ-cell somatostatin secretion might also signal an increase in α-cell glucagon secretion during hypoglycemia (7).Given that interpretation, it follows that an increase in β-cell secretion would signal a decrease in glucagon secretion in the postprandial state (14). The concept is an interplay of indirect reciprocal β-cell–mediated signaling of α-cells and of direct α-cell signaling in the regulation of glucagon secretion.There is, in our view, compelling evidence that, among other mechanisms, both indirect reciprocal β-cell–mediated signaling of α-cells (2–6) and direct α-cell signaling (1) are involved in the regulation of glucagon secretion by nutrients, hormones, neurotransmitters, and drugs. Given that premise, we posed the question: Which of these predominates in humans? Accordingly, we tested the hypothesis that increased β-cell–mediated signaling of α-cells negates direct α-cell signaling in the regulation of glucagon secretion in humans. To do so, we measured plasma glucagon responses to ingestion of a mixed meal and, on a separate occasion, to ingestion of the sulfonylurea glimepiride in patients with type 1 diabetes and in nondiabetic individuals. We conceptualized patients with type 1 diabetes as a model of α-cells isolated from β-cells because their β-cells had been destroyed but they have functioning α-cells. (Their α-cells are not, of course, isolated from other islet cells, including δ-cells.) Increased plasma amino acid and glucose levels after a mixed meal and sulfonylureas normally stimulate β-cell secretion; increased plasma amino acid and perhaps glucose (2) levels after a mixed meal and sulfonylureas (1) stimulate α-cell secretion. Our hypothesis predicts that such factors that normally stimulate both β-cells and α-cells would stimulate glucagon secretion in patients with type 1 diabetes but not in nondiabetic individuals, i.e., in the virtual absence and the presence of β-cell function, respectively. Indeed, a mixed meal (20,21) and the secretagogues tolbutamide (22), glyburide (23), and repaglinide (23) have been reported to raise plasma glucagon concentrations in patients with type 1 diabetes, but all of those studies lacked nondiabetic control subjects.     

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.     

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.     

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.     

Elevated A1C in Adults Without a History of Diabetes in the U.S.

OBJECTIVE

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

RESEARCH DESIGN AND METHODS

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

RESULTS

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

CONCLUSIONS

A single elevated A1C level (A1C >6%) is common in the general population of adults without a history of diabetes and is highly reliable for the detection of elevated fasting glucose. Nondiabetic adults with elevated A1C are likely to have impaired fasting glucose and an array of other risk factors for type 2 diabetes and cardiovascular disease.A1C is an integrated measure of circulating glucose levels and tracks well in individuals over time. Epidemiological studies have shown that A1C values in nondiabetic adults predict incident diabetes (1–5), cardiovascular disease morbidity and mortality (6–10), and total mortality (7). In these studies, A1C values well within in the “normal” range (i.e., A1C <6%) were independently associated with clinical outcomes. There is currently renewed interest in using A1C for diagnosis and/or screening for diabetes (11); however, there have been few epidemiological investigations of A1C in nondiabetic adults. The objective of the present study was to examine the prevalence and correlates of elevated A1C in a large, nationally representative sample of U.S. adults without diagnosed diabetes who participated in the National Health and Nutrition Examination Survey (NHANES) (1999–2006). We hypothesized that 1) elevated A1C levels (e.g., A1C >6%) are common in the general population of nondiabetic adults in the U.S. and 2) A1C levels would be associated with risk factors for type 2 diabetes and its complications even in the absence of elevated glucose levels.     

Further Improvement in Postprandial Glucose Control With Addition of Exenatide or Sitagliptin to Combination Therapy With Insulin Glargine and Metformin: A proof-of-concept study

OBJECTIVE

To assess the effect of a 4-week adjunctive therapy of exenatide (EXE) (5–10 μg b.i.d.) or sitagliptin (SITA) (100 mg once daily) in response to a standardized breakfast meal challenge in 48 men or women with type 2 diabetes receiving insulin glargine (GLAR) + metformin (MET).

RESEARCH DESIGN AND METHODS

This was a single-center, randomized, open-label, active comparator–controlled study with a three-arm parallel group design, consisting of: screening, 4- to 8-week run-in period, 4-week treatment period, and follow-up. In all three groups, the GLAR dose was titrated according to an algorithm (fasting blood glucose ≤100 mg/dl).

RESULTS

The unadjusted 6-h postprandial blood glucose excursion of both GLAR + MET + EXE and GLAR + MET + SITA was statistically significantly smaller than that of GLAR + MET (606 ± 104 vs. 612 ± 133 vs. 728 ± 132 mg/dl/h; P = 0.0036 and 0.0008). A1C significantly decreased in all three groups (P < 0.0001), with the greatest reduction of −1.9 ± 0.7 under GLAR + MET + EXE (GLAR + MET + SITA −1.5 ± 0.7; GLAR + MET −1.2 ± 0.5%-points; GLAR + MET + EXE vs. GLAR + MET P = 0.0154). The American Diabetes Association A1C target of <7.0% was reached by 80.0, 87.5, and 62.5% of subjects, respectively. GLAR + MET + EXE had the highest number (47) of adverse events, mostly gastrointestinal (56%) with one dropout. GLAR + MET or GLAR + MET + SITA only had 10 and 12 adverse events, respectively, and no dropouts. Hypoglycemia (blood glucose <50 mg/dl) rates were low and comparable among groups. Weight decreased with GLAR + MET + EXE (−0.9 ± 1.7 kg; P = 0.0396) and increased slightly with GLAR + MET (0.4 ± 1.5 kg; NS; GLAR + MET + EXE vs. GLAR + MET P = 0.0377).

CONCLUSIONS

EXE or SITA added to GLAR + MET further substantially reduced postprandial blood glucose excursions. Longer-term studies in a larger population are warranted to confirm these findings.The UK Prospective Diabetes Study (UKPDS) demonstrated that good glycemic control in type 2 diabetes is associated with a reduced risk of diabetes complications (1). After lifestyle modifications (diet and exercise) and oral hypoglycemic agents (OHAs) the addition of basal insulin to OHAs is common practice (2), because this kind of regimen requires only a single injection in most cases and can improve glycemic control. Its use, however, may not adequately control postprandial hyperglycemia or may be associated with hypoglycemia and/or weight gain (3,4). Because obesity is frequently present in subjects with type 2 diabetes (5) and represents a factor contributing to insulin resistance (5) and cardiovascular risk (5), weight gain may be particularly undesirable.A significant advance in basal insulin therapy was the introduction of insulin glargine, a long-acting insulin analog with an extended duration of action of ∼24 h without exhibiting a pronounced peak (6,7). In subjects with type 2 diabetes, insulin glargine was shown to confer glycemic control at least equivalent to that of NHP insulin with a lower incidence of hypoglycemia (3,8,9). However, insulin glargine still has the drawbacks of insulin treatment such as weight gain (3,8,9) and a lower effect on postprandial glucose excursions (8) than on fasting glucose values.Exenatide is the first-in-class glucagon-like peptide 1 (GLP-1) receptor agonist (or incretin mimetic) approved in the U.S. and Europe (10). Compared with placebo, exenatide statistically reduced A1C, whereas there was no difference in A1C improvement between exenatide and insulin glargine or biphasic insulin aspart (11–14). However, postprandial glycemia as well as weight was further reduced with exenatide compared with insulin glargine or biphasic insulin, with a similar risk of hypoglycemia (12,13).Sitagliptin is an approved once-daily, potent, and highly selective dipeptidyl peptidase-4 (DPP-4) inhibitor (15). When added to metformin, sitagliptin, given at a dose of 100 mg once daily over 24 weeks, led to significant reductions in A1C, fasting, and 2-h postprandial plasma glucose and was weight-neutral (16).With this background, a therapy controlling both fasting blood glucose (FBG) and postprandial glucose excursions seems to be a promising approach for subjects with type 2 diabetes (17–21). Therefore, in the present study we investigated the influence of a 4-week adjunctive therapy of either a GLP-1 receptor agonist (exenatide) or a DPP-4 inhibitor (sitagliptin) to titrated basal insulin (insulin glargine) plus metformin versus the continuation with titrated insulin glargine plus metformin alone as active comparator in subjects with type 2 diabetes.     

Peri-Conceptional A1C and Risk of Serious Adverse Pregnancy Outcome in 933 Women With Type 1 Diabetes

OBJECTIVE

To study the association between peri-conceptional A1C and serious adverse pregnancy outcome (congenital malformations and perinatal mortality).

RESEARCH DESIGN AND METHODS

Prospective data were collected in 933 singleton pregnancies complicated by type 1 diabetes.

RESULTS

The risk of serious adverse outcome at different A1C levels was compared with the background population. The risk was significantly higher when peri-conceptional A1C exceeded 6.9%, and the risk tended to increase gradually with increasing A1C. Women with A1C exceeding 10.4% had a very high risk of 16%. Congenital malformation rate increased significantly at A1C above 10.4%, whereas perinatal mortality was increased even at A1C below 6.9%.

CONCLUSIONS

These results support recent guidelines of preconceptional A1C levels <7% in women with type 1 diabetes.Recently, guidelines for management of pregnancy in women with pregestational diabetes have recommended pregestational A1C values <7.0% (1,2) and <6.1% (3). Previous studies have reported information of early A1C including 116–691 pregnancies (4–10). We aimed to study whether there is a threshold value for peri-conceptional A1C in women with type 1 diabetes below which the risk of serious adverse pregnancy outcome (congenital malformation and perinatal mortality) is not increased.     

A Study of Dapagliflozin in Patients With Type 2 Diabetes Receiving High Doses of Insulin Plus Insulin Sensitizers: Applicability of a novel insulin-independent treatment

OBJECTIVE

To determine whether dapagliflozin, which selectively inhibits renal glucose reabsorption, lowers hyperglycemia in patients with type 2 diabetes that is poorly controlled with high insulin doses plus oral antidiabetic agents (OADs).

RESEARCH DESIGN AND METHODS

This was a randomized, double-blind, three-arm parallel-group, placebo-controlled, 26-center trial (U.S. and Canada). Based on data from an insulin dose-adjustment setting cohort (n = 4), patients in the treatment cohort (n = 71) were randomly assigned 1:1:1 to placebo, 10 mg dapagliflozin, or 20 mg dapagliflozin, plus OAD(s) and 50% of their daily insulin dose. The primary outcome was change from baseline in A1C at week 12 (dapagliflozin vs. placebo, last observation carried forward [LOCF]).

RESULTS

At week 12 (LOCF), the 10- and 20-mg dapagliflozin groups demonstrated −0.70 and −0.78% mean differences in A1C change from baseline versus placebo. In both dapagliflozin groups, 65.2% of patients achieved a decrease from baseline in A1C ≥0.5% versus 15.8% in the placebo group. Mean changes from baseline in fasting plasma glucose (FPG) were +17.8, +2.4, and −9.6 mg/dl (placebo, 10 mg dapagliflozin, and 20 mg dapagliflozin, respectively). Postprandial glucose (PPG) reductions with dapagliflozin also showed dose dependence. Mean changes in total body weight were −1.9, −4.5, and −4.3 kg (placebo, 10 mg dapagliflozin, and 20 mg dapagliflozin). Overall, adverse events were balanced across all groups, although more genital infections occurred in the 20-mg dapagliflozin group than in the placebo group.

CONCLUSIONS

In patients receiving high insulin doses plus insulin sensitizers who had their baseline insulin reduced by 50%, dapagliflozin decreased A1C, produced better FPG and PPG levels, and lowered weight more than placebo.Treatment of hyperglycemia in patients with type 2 diabetes remains a challenge, particularly in those who require insulin as the disease progresses (1,2). Various combinations of insulin with oral antidiabetic agents (OADs) have been investigated (2–8). Often, these combination therapies become less effective in controlling hyperglycemia over time, particularly as a result of weight gain and worsening insulin resistance as well as progressive failure of insulin secretion.Hypoglycemia, weight gain, and subsequent increased insulin resistance are significant factors that limit optimal titration and effectiveness of insulin (2). Weight gain with insulin therapy, used alone or with OADs (7–9), is in part a consequence of reducing glucosuria (10,11). Among commonly used OADs, thiazolidinediones (TZDs) and sulfonylureas intrinsically contribute to weight gain, whereas metformin causes weight loss and dipeptidyl peptidase-4 inhibitors are weight neutral. Overall, there is a need for novel agents that can be safely administered to help achieve glycemic targets without increasing the risks of weight gain or hypoglycemia.A novel approach to treating hyperglycemia targets receptors for renal glucose reabsorption (12). Agents that selectively block sodium-glucose cotransporter 2 (SGLT2), located in the proximal tubule of the kidney, inhibit glucose reabsorption and induce its elimination through urinary excretion (13). Preclinical models have shown that SGLT2 inhibition lowers blood glucose independently of insulin (14–17). Dapagliflozin, a highly selective inhibitor of SGLT2, has demonstrated efficacy, alone or in combination with metformin, in reducing hyperglycemia in patients with type 2 diabetes (18,19) but has not been tested in patients requiring insulin. This study was designed to determine whether dapagliflozin is effective in lowering blood glucose in patients with type 2 diabetes who have not responded adequately to insulin combined with oral therapies that act through insulin-dependent mechanisms.     

Lifestyle counseling in routine care and long-term glucose, blood pressure, and cholesterol control in patients with diabetes

OBJECTIVE

In clinical trials, diet, exercise, and weight counseling led to short-term improvements in blood glucose, blood pressure, and cholesterol levels in patients with diabetes. However, little is known about the long-term effects of lifestyle counseling on patients with diabetes in routine clinical settings.

RESEARCH DESIGN AND METHODS

This retrospective cohort study of 30,897 patients with diabetes aimed to determine whether lifestyle counseling is associated with time to A1C, blood pressure, and LDL cholesterol control in patients with diabetes. Patients were included if they had at least 2 years of follow-up with primary care practices affiliated with two teaching hospitals in eastern Massachusetts between 1 January 2000 and 1 January 2010.

RESULTS

Comparing patients with face-to-face counseling rates of once or more per month versus less than once per 6 months, median time to A1C <7.0% was 3.5 versus 22.7 months, time to blood pressure <130/85 mmHg was 3.7 weeks versus 5.6 months, and time to LDL cholesterol <100 mg/dL was 3.5 versus 24.7 months, respectively (P < 0.0001 for all). In multivariable analysis, one additional monthly face-to-face lifestyle counseling episode was associated with hazard ratios of 1.7 for A1C control (P < 0.0001), 1.3 for blood pressure control (P < 0.0001), and 1.4 for LDL cholesterol control (P = 0.0013).

CONCLUSIONS

Lifestyle counseling in the primary care setting is strongly associated with faster achievement of A1C, blood pressure, and LDL cholesterol control. These results confirm that the findings of controlled clinical trials are applicable to the routine care setting and provide evidence to support current treatment guidelines.Diabetes is increasingly common in the U.S. and worldwide (1,2). Elevated blood glucose, blood pressure, and LDL cholesterol are associated with increased risk for micro- and macrovascular complications, and their reduction decreases the risk (3–8). Nevertheless, most patients with diabetes do not have A1C, blood pressure, and LDL cholesterol under control (9,10).American and European guidelines widely recommend diet, exercise, and weight counseling with follow-up for patients with diabetes (11,12). Many short-term randomized clinical trials have shown that intensive lifestyle counseling interventions of up to 1 year in duration can lead to lower blood glucose (13–16) and blood pressure (17–21), but long-term data on the efficacy of lifestyle counseling are lacking (22–24). Furthermore, clinical trials typically involve resource-intensive interventions that may not be feasible in routine care, and the efficacy of lifestyle counseling in everyday clinical practice remains questionable (25–27). Consequently, further evidence is needed to establish that lifestyle counseling as practiced in routine care improves the outcomes of patients with diabetes.We therefore conducted a retrospective study of over 30,000 patients with diabetes and hyperglycemia, hypertension, and/or hyperlipidemia who received care in a primary care setting to test the hypothesis that higher rates of lifestyle counseling in routine care are associated with better diabetes control.     

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.     

Acute Effects of Decaffeinated Coffee and the Major Coffee Components Chlorogenic Acid and Trigonelline on Glucose Tolerance

OBJECTIVE

Coffee consumption has been associated with lower risk of type 2 diabetes. We evaluated the acute effects of decaffeinated coffee and the major coffee components chlorogenic acid and trigonelline on glucose tolerance.

RESEARCH DESIGN AND METHODS

We conducted a randomized crossover trial of the effects of 12 g decaffeinated coffee, 1 g chlorogenic acid, 500 mg trigonelline, and placebo (1 g mannitol) on glucose and insulin concentrations during a 2-h oral glucose tolerance test (OGTT) in 15 overweight men.

RESULTS

Chlorogenic acid and trigonelline ingestion significantly reduced glucose (−0.7 mmol/l, P = 0.007, and −0.5 mmol/l, P = 0.024, respectively) and insulin (−73 pmol/l, P = 0.038, and −117 pmol/l, P = 0.007) concentrations 15 min following an OGTT compared with placebo. None of the treatments affected insulin or glucose area under the curve values during the OGTT compared with placebo.

CONCLUSIONS

Chlorogenic acid and trigonelline reduced early glucose and insulin responses during an OGTT.In prospective cohort studies, higher coffee consumption has been associated with a lower risk of type 2 diabetes (1,2). Associations have been similar for caffeinated and decaffeinated coffee (1,3–5), suggesting that coffee components other than caffeine have beneficial effects on glucose homeostasis. Coffee is a major source of the phenolic compound chlorogenic acid (6) and the vitamin B3 precursor trigonelline (7), which have been shown to reduce blood glucose concentrations in animal studies (5–8). This is the first study to investigate the acute effects of chlorogenic acid and trigonelline on glucose tolerance in humans.     

Glycemic Control and Cardiovascular Disease in 7,454 Patients With Type 1 Diabetes: An observational study from the Swedish National Diabetes Register (NDR)

OBJECTIVE

We assessed the association between A1C and cardiovascular diseases (CVDs) in an observational study of patients with type 1 diabetes followed for 5 years.

RESEARCH DESIGN AND METHODS

A total of 7,454 patients were studied from the Swedish National Diabetes Register (aged 20–65 years, diabetes duration 1–35 years, followed from 2002 to 2007).

RESULTS

Hazard ratios (HRs) for fatal/nonfatal coronary heart disease (CHD) per 1% unit increase in baseline or updated mean A1C at Cox regression analysis were 1.31 and 1.34 and 1.26 and 1.32, respectively, for fatal/nonfatal CVD (all P < 0.001 after adjustment for age, sex, diabetes duration, blood pressure, total and LDL cholesterol, triglycerides, BMI, smoking, and history of CVD). HRs were only slightly lower for CHD (P = 0.002) and CVD (P = 0.002–0.007) after also adjusting for albuminuria. Adjusted 5-year event rates of CHD and CVD increased progressively with higher A1C, ranging from 5 to 12%, as well as when subgrouped by shorter (1–20 years) or longer (21–35 years) duration of diabetes. A group of 4,186 patients with A1C 5–7.9% (mean 7.2) at baseline showed risk reductions of 41% (95% confidence intervals: 15–60) (P = 0.005) for fatal/nonfatal CHD and 37% (12–55) (P = 0.008) for CVD, compared with 3,268 patients with A1C 8–11.9% (mean 9.0), fully adjusted also for albuminuria.

CONCLUSIONS

This observational study of patients in modern everyday clinical practice demonstrates progressively increasing risks for CHD and CVD with higher A1C, independently of traditional risk factors, with no J-shaped risk curves. A baseline mean A1C of 7.2% showed considerably reduced risks of CHD and CVD compared with A1C 9.0%, emphasizing A1C as a strong independent risk factor in type 1 diabetes.Patients with type 1 diabetes have long been considered to have increased risks of cardiovascular disease (CVD) and mortality (1,2), and this has recently been confirmed in two studies (3,4) from the General Practice Research Database in the U.K. Based on data from 1992 to 1999, risks of CVD and mortality were four to eight times higher in men and women with type 1 diabetes than nondiabetic individuals (3,4).While the association between glycemia and microvascular complications is established (5,6), there have been no long-term randomized clinical studies satisfactorily examining the relationship with macrovascular complications in type 1 diabetes, and epidemiological studies have shown conflicting results (7–14). The Epidemiology of Diabetes Interventions and Complications (EDIC) Study showed that patients who had previously been subjected to intensive glucose control during the Diabetes Control and Complications Trial (DCCT) had a considerably lower risk of CVD than patients receiving standard treatment (1983–1993) (7). A small study from Finland on late-onset type 1 diabetic patients without albuminuria showed increased risk of coronary heart disease (CHD) with poor glycemic control (9), but the EURODIAB Prospective Complications Study (PCS), the Pittsburgh Epidemiology of Diabetes Complications (EDC) Study, and the Wisconsin Epidemiologic Study of Diabetic Retinopathy did not demonstrate a significant relationship between glycemia and CHD after controlling for other cardiovascular risk factors (10–13). However, a recent study (14) from the Pittsburgh EDC showed that change in A1C was related to coronary artery disease, whereas baseline A1C was not.With this background, we assessed the association between A1C and CHD, stroke, and CVD in a large cohort of patients with type 1 diabetes, aged 20–65 years, treated in everyday clinical practice from 2002 to 2007. Data were used from the Swedish National Diabetes register (NDR), a quality-assurance tool in diabetes care with nationwide coverage with recently published reports regarding type 1 and type 2 diabetes (15–17).     

Physical Activity, Adiposity, and Diabetes Risk in Middle-Aged and Older Chinese Population: The Guangzhou Biobank Cohort Study

OBJECTIVE

Physical activity may modify the association of adiposity with type 2 diabetes. We investigated the independent and joint association of adiposity and physical activity with fasting plasma glucose, impaired fasting glucose, and type 2 diabetes in a Chinese population.

RESEARCH DESIGN AND METHODS

Middle-aged and older Chinese (n = 28,946, ≥50 years, 72.4%women) from the Guangzhou Biobank Cohort Study were examined in 2003–2008. Multivariable regression was used in a cross-sectional analysis.

RESULTS

BMI, waist circumference, and waist-to-hip ratio (WHR) were positively associated with type 2 diabetes after multiple adjustment, most strongly for WHR with odds ratio (OR) of 3.99 (95% CI 3.60–4.42) for highest compared with lowest tertile. Lack of moderate-to-vigorous physical activity, but not walking, was associated with diabetes with an OR of 1.29 (1.17–1.41). The association of moderate-to-vigorous activity with fasting glucose varied with WHR tertiles (P = 0.01 for interaction). Within the high WHR tertile, participants who had a lack of moderate-to-vigorous activity had an OR of 3.87 (3.22–4.65) for diabetes, whereas those who were active had an OR of 2.94 (2.41–3.59).

CONCLUSIONS

In this population, WHR was a better measure of adiposity-related diabetes risk than BMI or waist circumference. Higher moderate-to-vigorous activity was associated with lower diabetes risk, especially in abdominally obese individuals.Type 2 diabetes is a worldwide cause of morbidity and mortality. Adiposity, especially abdominal adiposity, seems to be at the core of development of hyperglycemia and type 2 diabetes (1). Increased physical activity may mitigate some of the diabetogenic impact of adiposity (2–4). Individuals who are obese but fit could even have a lower risk of mortality than those who are normal weight but unfit (5,6). However, being physically active does not completely abolish the obesity-related risk for cardiovascular disease and associated mortality (7). Adiposity is still the main risk factor for the development of type 2 diabetes (2–4,8). Although increased physical activity has been shown to be associated with reduced type 2 diabetes risk independent of adiposity, the protective effects may differ by the level of adiposity. However, the group that could benefit most from physical activity for the prevention of diabetes is still unclear (2–4,8–10).Understanding the relationship between adiposity and physical activity is important to stratify risk groups for the development of effective diabetes prevention strategies from public health and clinical perspectives. Most of the studies relate to Caucasians (2–4,8–10), whereas Asians, including Chinese and Indians, are possibly more vulnerable to insulin resistance (11). The number of Chinese adults with type 2 diabetes was estimated to be ∼28.1 million in 2000 and may double by 2030, with China being second only to India (12). The purpose of this study was to investigate the independent and joint association of adiposity and physical activity with fasting plasma glucose, impaired fasting glucose (IFG), and type 2 diabetes in 28,946 middle-aged and older Chinese participants in the Guangzhou Biobank Cohort Study.     

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.     

Comparison of near-patient capillary glucose measurement and a risk assessment questionnaire in screening for type 2 diabetes in a high-risk population in rural India

OBJECTIVE

To assess the utility of a point-of-care (POC) capillary blood glucose measurement as compared with routine clinical parameters in predicting undiagnosed diabetes in a low-resource rural India setting.

RESEARCH DESIGN AND METHODS

Nine hundred and ninety-four participants aged >30 years and stratified by age and sex were randomly selected from 20 villages in India. A clinical questionnaire, sampling for laboratory venous fasting plasma glucose (FPG), and POC capillary blood glucose assay were performed simultaneously. Diabetes diagnosis was based on the World Health Organization (WHO) definition using FPG. The capacity of the POC glucose to predict the presence of diabetes was assessed and compared with the questionnaire using area under the receiver operating characteristic curves (AUCs).

RESULTS

The AUC for POC glucose alone in predicting diabetes was 0.869 (95% CI 0.810–0.929). This was significantly better (P < 0.001 for AUC comparison) than the models based upon clinical variables alone (AUC for the best clinical model including age, BMI, hypertension, waist circumference: 0.694 [95% CI 0.621–0.766]). POC glucose appropriately reclassified the risk of up to one-third of participants ranked according to the clinical models. Adding the clinical variables to the POC glucose assay did not significantly improve the discriminatory capability beyond that achieved with the POC glucose measurement alone (all P > 0.37).

CONCLUSIONS

POC glucose testing appears to be a simple and reliable tool for identifying undiagnosed diabetes in a high-risk, resource-poor rural population. However, studies evaluating the cost effectiveness of introducing POC glucose testing are needed prior to widespread implementation.The prevalence of type 2 diabetes is rapidly increasing around the world (1). Developing countries are facing the largest increases both in absolute and relative terms (1). It is predicted that this will have devastating consequences on the economies and health systems of these countries. Successful prevention and early management of diabetes is therefore a major health priority (1,2).In many regions, up to 50% of people with diabetes remain undiagnosed (1,3,4). Failure to improve these levels of detection will mean that the opportunity to improve health outcomes with early intervention will be lost. Early treatment with successful glucose control significantly reduces the morbidity and mortality associated with diabetes (5,6). Earlier detection of diabetes also allows for the implementation of other treatments that reduce the vascular complications of diabetes (5,6).Universal screening for diabetes is not currently recommended due to a lack of good evidence for an accurate test. However, targeted screening is advocated in certain ethnic groups deemed at increased risk of diabetes (2). For some ethnic groups, implementation of targeted screening may require the entire population to be screened. This applies for instance to Asian Indian populations, which are at greater risk of developing diabetes (7) and have a high prevalence of diabetes both in urban (4) and rural settings (3). However to successfully apply screening to such populations requires accurate, safe, and low-cost diagnostic strategies that are easy to implement (8).In resource-poor settings, clinical variables–based risk assessment questionnaires or point-of-care (POC) glucose analysis may be reasonable screening tools (9). Both require little expertise and allow an individual''s risk of having undiagnosed diabetes to be immediately determined so that only those at high risk require a confirmatory diagnostic test. However, the value of risk assessment questionnaires (9–13) and POC glucose analysis (14–16) in resource-poor settings remains unclear. Additionally the performance of these different screening methods has not been compared in rural Asian Indian populations.The aim of this study was to quantify and compare the accuracy of strategies based on POC glucose, clinical variables, and the combination of both in predicting undiagnosed diabetes in an asymptomatic, resource-poor rural Asian Indian population.     

Screening for Diabetes and Pre-Diabetes With Proposed A1C-Based Diagnostic Criteria

OBJECTIVE

An International Expert Committee (IEC) and the American Diabetes Association (ADA) proposed diagnostic criteria for diabetes and pre-diabetes based on A1C levels. We hypothesized that screening for diabetes and pre-diabetes with A1C measurements would differ from using oral glucose tolerance tests (OGTT).

RESEARCH DESIGN AND METHODS

We compared pre-diabetes, dysglycemia (diabetes or pre-diabetes), and diabetes identified by the proposed criteria (A1C ≥6.5% for diabetes and 6.0–6.4% [IEC] or 5.7–6.4% [ADA] for high risk/pre-diabetes) with standard OGTT diagnoses in three datasets. Non-Hispanic white or black adults without known diabetes who had A1C and 75-g OGTT measurements were included from the prospective Screening for Impaired Glucose Tolerance study (n = 1,581), and from the National Health and Nutrition Examination Survey (NHANES) III (n = 2014), and NHANES 2005–2006 (n = 1,111).

RESULTS

OGTTs revealed pre-diabetes in 35.8% and diabetes in 5.2% of combined study subjects. A1C provided receiver operating characteristic (ROC) curve areas for diabetes of 0.79–0.83, but ROC curve areas were ≤0.70 for dysglycemia or pre-diabetes. The proposed criteria missed 70% of individuals with diabetes, 71–84% with dysglycemia, and 82–94% with pre-diabetes. Compared with the IEC criteria, the ADA criteria for pre-diabetes resulted in fewer false-negative and more false-positive result. There were also racial differences, with false-positive results being more common in black subjects and false-negative results being more common in white subjects. With use of NHANES 2005–2006 data, ∼5.9 million non-Hispanic U.S. adults with unrecognized diabetes and 43–52 million with pre-diabetes would be missed by screening with A1C.

CONCLUSIONS

The proposed A1C diagnostic criteria are insensitive and racially discrepant for screening, missing most Americans with undiagnosed diabetes and pre-diabetes.Diabetes affects >21 million American adults (1,2), with a lifetime risk ranging from 20 to 50+%, depending on sex and race (3). Identification of diabetes and its precursor, pre-diabetes, can permit management to prevent complications or delay progression from pre-diabetes to diabetes. Because most U.S. health care systems do not have systematic screening programs, many Americans have undiagnosed diabetes and pre-diabetes, and, therefore, these individuals are not initiating programs targeted at prevention (2).An International Expert Committee (IEC) recently proposed new diagnostic criteria based on measurement of A1C, with A1C ≥6.5% for diabetes and 6.0–6.4% for “high risk” of progression to diabetes (4). The American Diabetes Association (ADA) subsequently proposed A1C ≥6.5% for the diagnosis of diabetes and 5.7–6.4% for the highest risk to progress to diabetes (5).Because A1C testing is readily available in the U.S., is relatively well standardized, exhibits low intraindividual variation, and does not require fasting or restriction to certain times of the day (6), many clinicians might wish to use A1C measurements to screen for diabetes and pre-diabetes. However, the proposed diagnostic criteria were based largely on identification of diabetic retinopathy, and use of the proposed criteria as a screening test is not understood. The IEC A1C criteria have recently been compared with testing with fasting glucose or oral glucose tolerance tests (OGTTs) in various populations to diagnose diabetes (7–13) and high-risk/pre-diabetes (10,11,13), but the ADA A1C criteria have not been studied.We hypothesized that A1C diagnostic criteria would fail to identify many subjects with unrecognized diabetes or pre-diabetes. We evaluated the proposed criteria as screening tests in three populations, compared with the OGTT as a “gold standard” used for identification of diabetes and pre-diabetes around the world (14).     

Randomized Comparison of Pramlintide or Mealtime Insulin Added to Basal Insulin Treatment for Patients With Type 2 Diabetes

OBJECTIVE

To compare the efficacy and safety of adding mealtime pramlintide or rapid-acting insulin analogs (RAIAs) to basal insulin for patients with inadequately controlled type 2 diabetes.

RESEARCH DESIGN AND METHODS

In a 24-week open-label, multicenter study, 113 patients were randomly assigned 1:1 to addition of mealtime pramlintide (120 μg) or a titrated RAIA to basal insulin and prior oral antihyperglycemic drugs (OADs). At screening, patients were insulin naive or had been receiving <50 units/day basal insulin for <6 months. The basal insulin dosage was titrated from day 1, seeking fasting plasma glucose (FPG) ≥70–<100 mg/dl. Pramlintide and an RAIA were initiated on day 1 and week 4, respectively. The proportion of patients achieving A1C ≤7.0% without weight gain or severe hypoglycemia at week 24 was the primary end point.

RESULTS

More pramlintide- than RAIA-treated patients achieved the primary end point (30 vs. 11%, P = 0.018) with a similar dose of basal insulin. Pramlintide and an RAIA yielded similar mean ± SEM values for FPG and A1C at 24 weeks (122 ± 7 vs. 123 ± 5 mg/dl and 7.2 ± 0.2 vs. 7.0 ± 0.1%, respectively) and similar least squares mean reductions from baseline to end point (−31 ± 6 vs. −34 ± 6 mg/dl and −1.1 ± 0.2 vs. −1.3 ± 0.2%, respectively). RAIAs but not pramlintide caused weight gain (+4.7 ± 0.7 vs. +0.0 ± 0.7 kg, P < 0.0001). Fewer patients reported mild to moderate hypoglycemia with pramlintide than with the RAIA (55 vs. 82%), but more patients reported nausea (21 vs. 0%). No severe hypoglycemia occurred in either group.

CONCLUSIONS

In patients taking basal insulin and OADs, premeal fixed-dose pramlintide improved glycemic control as effectively as titrated RAIAs. The pramlintide regimen sometimes caused nausea but no weight gain and less hypoglycemia.Adding basal insulin therapy to oral agents improves glycemic control for many patients with type 2 diabetes, but up to 50% of patients continue to have A1C values >7% (1,2,3,4,5). Persistent after-meal hyperglycemia is generally observed in such patients (6). The usual next step in treatment is addition of mealtime insulin injections, but this approach increases risks of weight gain and hypoglycemia (4,6).Previous studies have shown that defects in addition to insulin deficiency contribute to after-meal hyperglycemia. Both insulin and amylin are secreted by β-cells, and, in individuals with abnormal β-cell function, glucose- and mixed meal–stimulated secretion of both hormones is delayed and reduced (7,8,9). Insulin deficiency impairs suppression of hepatic glucose production and enhancement of glucose uptake by tissues that normally limit postmeal hyperglycemia. Amylin deficiency accelerates gastric emptying, increases glucagon secretion, and alters satiety mechanisms (10,11).Pramlintide, an injectable synthetic analog of amylin, slows gastric emptying, attenuates postprandial glucagon secretion, enhances satiety, and reduces food intake (12,13,14). Pramlintide is approved as adjunctive treatment for patients with diabetes who use mealtime insulin with or without oral antihyperglycemic drugs (OADs) and have not achieved desired glucose control. Recently, a 16-week, double-blind, placebo-controlled study of patients with type 2 diabetes showed that pramlintide reduces A1C and weight without increasing insulin-induced hypoglycemia when added to basal insulin ± OADs without mealtime insulin (15).Pramlintide may offer an additional therapeutic option for mealtime use by patients with type 2 diabetes already using basal insulin. Rapid-acting insulin analogs (RAIAs) and pramlintide have different mechanisms of action and different patterns of desired and unwanted effects. Although both can limit after-meal hyperglycemia, RAIAs often cause weight gain and hypoglycemia (6), whereas pramlintide is associated with weight loss and nausea (15,16). This study was designed to compare the efficacy and side effects of pramlintide versus RAIAs when added to basal insulin to intensify treatment of type 2 diabetes.     

Closed-Loop Insulin Delivery Using a Subcutaneous Glucose Sensor and Intraperitoneal Insulin Delivery: Feasibility study testing a new model for the artificial pancreas

OBJECTIVE

Attempts to build an artificial pancreas by using subcutaneous insulin delivery from a portable pump guided by an subcutaneous glucose sensor have encountered delays and variability of insulin absorption. We tested closed-loop intraperitoneal insulin infusion from an implanted pump driven by an subcutaneous glucose sensor via a proportional-integral-derivative (PID) algorithm.

RESEARCH DESIGN AND METHODS

Two-day closed-loop therapy (except for a 15-min premeal manual bolus) was compared with a 1-day control phase with intraperitoneal open-loop insulin delivery, according to randomized order, in a hospital setting in eight type 1 diabetic patients treated by implanted pumps. The percentage of time spent with blood glucose in the 4.4–6.6 mmol/l range was the primary end point.

RESULTS

During the closed-loop phases, the mean ± SEM percentage of time spent with blood glucose in the 4.4–6.6 mmol/l range was significantly higher (39.1 ± 4.5 vs. 27.7 ± 6.2%, P = 0.05), and overall dispersion of blood glucose values was reduced among patients. Better closed-loop glucose control came from the time periods excluding the two early postprandial hours with a higher percentage of time in the 4.4–6.6 mmol/l range (46.3 ± 5.3 vs. 28.6 ± 7.4, P = 0.025) and lower mean blood glucose levels (6.9 ± 0.3 vs. 7.9 ± 0.6 mmol/l, P = 0.036). Time spent with blood glucose <3.3 mmol/l was low and similar for both investigational phases.

CONCLUSIONS

Our results demonstrate the feasibility of intraperitoneal insulin delivery for an artificial β-cell and support the need for further study. Moreover, according to a semiautomated mode, the features of the premeal bolus in terms of timing and amount warrant further research.In patients with type 1 diabetes, the near-normal glucose control required to prevent long-term complications (1,2) remains difficult to achieve (3). Indeed, the incidence of hypoglycemia increases when glucose control approaches normal glucose levels (4). For this reason the development of an “artificial pancreas” has been a goal for >30 years (5,6).An artificial β-cell requires three elements: a continuous insulin delivery device, a continuous glucose monitoring system, and a control algorithm linking insulin delivery to glucose measurements (3,7,8). The recent development of better performing continuous glucose sensors renewed the potential feasibility of closed-loop insulin delivery (9–11). Short-term initiatives in the clinical research setting were reported in recent years but showed some limitations (12–14). Key limiting factors were, first, delays in the modulation of insulin action related to subcutaneous infusion and, second, time lags in glucose detection due to either the placement of the sensors in the interstitial compartment of subcutaneous tissue or the internal structure of implanted intravenous sensors (15). To reduce glucose deviations at mealtimes, a hybrid option of closed-loop insulin delivery includes a manual priming bolus (16).Reported benefits of intraperitoneal insulin infusion from implantable pumps include fast insulin action and low basal plasma insulin levels, resulting in tight glucose control and a low incidence of hypoglycemic events (17). The feasibility of automated closed-loop insulin delivery from implantable pumps has been demonstrated in clinical trials performed with the Long-Term Sensor System, which coupled these devices with an intravenous glucose sensor (18).Our approach to optimize closed-loop glucose control includes the use of closer to physiological intraperitoneal insulin delivery, subcutaneous glucose sensing, and a proportional-integral-derivative (PID) algorithm with a manual premeal bolus, resulting in a hybrid PID (HyPID) system. The objective of this study was to test the feasibility of such an approach. We investigated patients in the same controlled hospital setting while testing the HyPID system and when following their usual self-management. This approach marks a difference from the previously reported closed-loop trials, which considered home-use periods for comparison with in-clinic closed-loop studies (13,16).     

Real-Time Continuous Glucose Monitoring in Critically Ill Patients: A prospective randomized trial

OBJECTIVE

To evaluate the impact of real-time continuous glucose monitoring (CGM) on glycemic control and risk of hypoglycemia in critically ill patients.

RESEARCH DESIGN AND METHODS

A total 124 patients receiving mechanical ventilation were randomly assigned to the real-time CGM group (n = 63; glucose values given every 5 min) or to the control group (n = 61; selective arterial glucose measurements according to an algorithm; simultaneously blinded CGM) for 72 h. Insulin infusion rates were guided according to the same algorithm in both groups. The primary end point was percentage of time at a glucose level <110 mg/dl. Secondary end points were mean glucose levels and rate of severe hypoglycemia (<40 mg/dl).

RESULTS

Percentage of time at a glucose level <110 mg/dl (59.0 ± 20 vs. 55.0 ± 18% in the control group, P = 0.245) and the mean glucose level (106 ± 18 vs. 111 ± 10 mg/dl in the control group, P = 0.076) could not be improved using real-time CGM. The rate of severe hypoglycemia was lower in the real-time CGM group (1.6 vs. 11.5% in the control group, P = 0.031). CGM reduced the absolute risk of severe hypoglycemia by 9.9% (95% CI 1.2–18.6) with a number needed to treat of 10.1 (95% CI 5.4–83.3).

CONCLUSIONS

In critically ill patients, real-time CGM reduces hypoglycemic events but does not improve glycemic control compared with intensive insulin therapy guided by an algorithm.Hyperglycemia, a frequent finding in up to 90% of all critically ill patients, is associated with increased morbidity and mortality (1,2). In three monocentric studies, intensive insulin therapy to achieve and maintain normoglycemia resulted in decreased morbidity and mortality (3–5). However, in two subsequent multicenter studies, normoglycemia was not adequately reached, and the studies were stopped prematurely because of safety reasons with increased rates of severe hypoglycemia (6,7). However, in a recent trial, intensive insulin therapy resulted in improved short-term outcome in pediatric intensive care; another recent trial demonstrated increased mortality among adults under intensive glucose control (5,8). An updated meta-analysis of 26 randomized trials including 13,567 patients reported that intensive insulin therapy had no effect on the overall risk of death but simultaneously resulted in a sixfold increased risk of severe hypoglycemia. Currently, there is still an intense and conflicting discussion on the difficulty of obtaining near-normoglycemia and thereby avoiding the risk of severe hypoglycemia (9). In critically ill patients, accurate real-time continuous glucose monitoring (CGM) might be the best way to minimize a consistently reported increased rate of severe hypoglycemia associated with intensive insulin therapy and to increase effectiveness and safety of tight glucose control.Numerous studies in diabetic patients tested CGM devices and demonstrated high accuracy of the CGM-derived glucose values compared with blood glucose measurements (10–12). In particular, these devices were highly sensitive in detecting rapid glucose excursions (12). Recently, these CGM techniques have also been evaluated in critically ill patients and have yielded similar positive results (13–17). Mainly, subcutaneous CGM devices have been intensely investigated (13–17). Accuracy and reliability of a subcutaneous CGM device could be demonstrated both in critically ill patients with and without circulatory shock (16). Subcutaneous CGM worked equally in patients without and with norepinephrine therapy. Validity of the subcutaneous CGM under norepinephrine therapy was furthermore independent of levels of blood glucose values, severity of illness, and patients'' BMI (16). With use of this subcutaneous CGM device, ∼99% of all measured sensor glucose values were within the acceptable treatment zone according to an insulin titration grid analysis (16). Based on these underlying data, we hypothesized that subcutaneous real-time CGM improves glucose control, simultaneously reducing the risk of hypoglycemia.