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1.  The future of care for type 1 diabetes 
PMCID: PMC3589303  PMID: 23359043
2.  Glucose Levels and Risk of Dementia 
The New England journal of medicine  2013;369(6):540-548.
Diabetes is a risk factor for dementia. It is unknown whether higher glucose levels increase the risk of dementia in people without diabetes.
We used 35,264 clinical measurements of glucose levels and 10,208 measurements of glycated hemoglobin levels from 2067 participants without dementia to examine the relationship between glucose levels and the risk of dementia. Participants were from the Adult Changes in Thought study and included 839 men and 1228 women whose mean age at baseline was 76 years; 232 participants had diabetes, and 1835 did not. We fit Cox regression models, stratified according to diabetes status and adjusted for age, sex, study cohort, educational level, level of exercise, blood pressure, and status with respect to coronary and cerebrovascular diseases, atrial fibrillation, smoking, and treatment for hypertension.
During a median follow-up of 6.8 years, dementia developed in 524 participants (74 with diabetes and 450 without). Among participants without diabetes, higher average glucose levels within the preceding 5 years were related to an increased risk of dementia (P = 0.01); with a glucose level of 115 mg per deciliter (6.4 mmol per liter) as compared with 100 mg per deciliter (5.5 mmol per liter), the adjusted hazard ratio for dementia was 1.18 (95% confidence interval [CI], 1.04 to 1.33). Among participants with diabetes, higher average glucose levels were also related to an increased risk of dementia (P = 0.002); with a glucose level of 190 mg per deciliter (10.5 mmol per liter) as compared with 160 mg per deciliter (8.9 mmol per liter), the adjusted hazard ratio was 1.40 (95% CI, 1.12 to 1.76).
Our results suggest that higher glucose levels may be a risk factor for dementia, even among persons without diabetes. (Funded by the National Institutes of Health.)
PMCID: PMC3955123  PMID: 23924004
3.  Glycated Albumin and Direct Low Density Lipoprotein Cholesterol Levels in Type 2 Diabetes Mellitus 
Diabetes mellitus is a major risk factor for coronary heart disease (CHD), renal failure, retinopathy, and neuropathy. Lowering glycosylated hemoglobin (HbA1c) as well as low-density lipoprotein-cholesterol (LDL-C) has been associated with a decreased risk of these complications. We evaluated the utility of glycated albumin (GA) and direct LDL-C, 2 novel assays, as compared to HbA1c and calculated LDL-C, in evaluating diabetes control and lipid in a heterogeneous population and in specific subgroups of patients with type 2 diabetes mellitus.
We obtained fasting blood samples and measured HbA1c, GA, and direct LDL-C, as well as other parameters, in a multi-ethnic population of 616 male and female patients with type 2 diabetes and 895 non-diabetic controls.
HbA1c and GA levels, which measure different periods of glycemia, had a correlation of r=0.70 (p<0.001), and mean values in patients were 38.7% and 43.4% higher, respectively, than controls in men, and 41.1% and 40.1% higher, respectively, than controls, in women (both p<0.001). Calculated and direct LDL-C values correlated very highly (r=0.96, p<0.001). The correlations between HbA1c and GA, and between calculated and direct LDL-C were similar for subgroups defined by gender, race, age, and other factors.
Calculated LDL-C provides an accurate assessment of fasting LDL-C compared with a direct measurement in most subjects, except for those with hypertriglyceridemia, and GA correlates with HbA1c in diabetic and non-diabetic subjects and may serve as a reasonable marker of short term diabetic control.
PMCID: PMC3927411  PMID: 19465013
glycated albumin; low density lipoprotein cholesterol; type 2 diabetes
4.  A Comparative Effectiveness Analysis of Three Continuous Glucose Monitors 
Diabetes Care  2013;36(2):251-259.
To compare three continuous glucose monitoring (CGM) devices in subjects with type 1 diabetes under closed-loop blood glucose (BG) control.
Six subjects with type 1 diabetes (age 52 ± 14 years, diabetes duration 32 ± 14 years) each participated in two 51-h closed-loop BG control experiments in the hospital. Venous plasma glucose (PG) measurements (GlucoScout, International Biomedical) obtained every 15 min (2,360 values) were paired in time with corresponding CGM glucose (CGMG) measurements obtained from three CGM devices, the Navigator (Abbott Diabetes Care), the Seven Plus (DexCom), and the Guardian (Medtronic), worn simultaneously by each subject. Errors in paired PG–CGMG measurements and data reporting percentages were obtained for each CGM device.
The Navigator had the best overall accuracy, with an aggregate mean absolute relative difference (MARD) of all paired points of 11.8 ± 11.1% and an average MARD across all 12 experiments of 11.8 ± 3.8%. The Seven Plus and Guardian produced aggregate MARDs of all paired points of 16.5 ± 17.8% and 20.3 ± 18.0%, respectively, and average MARDs across all 12 experiments of 16.5 ± 6.7% and 20.2 ± 6.8%, respectively. Data reporting percentages, a measure of reliability, were 76% for the Seven Plus and nearly 100% for the Navigator and Guardian.
A comprehensive head-to-head-to-head comparison of three CGM devices for BG values from 36 to 563 mg/dL revealed marked differences in performance characteristics that include accuracy, precision, and reliability. The Navigator outperformed the other two in these areas.
PMCID: PMC3554299  PMID: 23275350
5.  The effect of excess weight gain with intensive diabetes treatment on cardiovascular disease risk factors and atherosclerosis in type 1 diabetes: Results from the Diabetes Control and Complications Trial / Epidemiology of Diabetes Interventions and Complications Study (DCCT/EDIC) study 
Circulation  2012;127(2):10.1161/CIRCULATIONAHA.111.077487.
Intensive diabetes therapy of type 1 diabetes (T1DM) reduces diabetes complications but can be associated with excess weight gain, central obesity, and dyslipidemia.
The purpose of this study was to determine if excessive weight gain with diabetes therapy of T1DM is prospectively associated with atherosclerotic disease.
Methods and Results
Subjects with T1DM (97% Caucasian, 45% female, mean age 35 years) randomly assigned to intensive (INT) or conventional (CONV) diabetes treatment during the Diabetes Control and Complications Trial (DCCT) underwent intima-media thickness (IMT) (n=1015) and coronary artery calcium (CAC) score (n=925) measurements during follow-up in the Epidemiology of Diabetes Interventions and Complications (EDIC) Study. INT subjects were classified by quartile of BMI change during the DCCT. Excess gainers (4th quartile, including CONV subjects meeting this threshold) maintained greater BMI and waist circumference (WC), needed more insulin, had greater IMT (+5%, P<0.001 EDIC year 1, P=0.003 EDIC year 6), and trended towards greater CAC scores (OR 1.55, CI 0.97 – 2.49, P=0.07) than minimal gainers. DCCT subjects meeting metabolic syndrome criteria for WC and blood pressure had greater IMT in both EDIC years (P =0.02 to <0.001); those meeting HDL criteria had greater CAC scores (OR 1.6 and CI 1.1 – 2.4, P=0.01) during follow-up. Increasing frequency of a family history of diabetes, hypertension, and hyperlipidemia was associated with greater IMT thickness with INT but not CONV.
Excess weight gain in DCCT is associated with sustained increases in central obesity, insulin resistance, dyslipidemia and blood pressure, as well as more extensive atherosclerosis during EDIC.
PMCID: PMC3819101  PMID: 23212717
diabetes mellitus; carotid intima media thickness; coronary artery calcium; imaging; obesity
6.  Pretreatment, Psychological, and Behavioral Predictors of Weight Outcomes Among Lifestyle Intervention Participants in the Diabetes Prevention Program (DPP) 
Diabetes Care  2012;36(1):34-40.
To identify the most important pretreatment characteristics and changes in psychological and behavioral factors that predict weight outcomes in the Diabetes Prevention Program (DPP).
Approximately 25% of DPP lifestyle intervention participants (n = 274) completed questionnaires to assess weight history and psychological and behavioral factors at baseline and 6 months after completion of the 16-session core curriculum. The change in variables from baseline to 6 months was assessed with t tests. Multivariate models using hierarchical logistic regression assessed the association of weight outcomes at end of study with each demographic, weight loss history, psychological, and behavioral factor.
At end of study, 40.5% had achieved the DPP 7% weight loss goal. Several baseline measures (older age, race, older age when first overweight, fewer self-implemented weight loss attempts, greater exercise self-efficacy, greater dietary restraint, fewer fat-related dietary behaviors, more sedentary activity level) were independent predictors of successful end-of-study weight loss with the DPP lifestyle program. The DPP core curriculum resulted in significant improvements in many psychological and behavioral targets. Changes in low-fat diet self-efficacy and dietary restraint skills predicted better long-term weight loss, and the association of low-fat diet self-efficacy with weight outcomes was explained by dietary behaviors.
Health care providers who translate the DPP lifestyle intervention should be aware of pretreatment characteristics that may hamper or enhance weight loss, consider prioritizing strategies to improve low-fat diet self-efficacy and dietary restraint skills, and examine whether taking these actions improves weight loss outcomes.
PMCID: PMC3526204  PMID: 23129133
7.  How Doctors Choose Medications to Treat Type 2 Diabetes 
Diabetes care  2007;30(6):10.2337/dc06-2499.
Glycemic control remains suboptimal despite the wide range of available medications. More effective medication prescription might result in better control. However, the process by which physicians choose glucose-lowering medicines is poorly understood. We sought to study the means by which physicians choose medications for type 2 diabetic patients.
We surveyed 886 physician members of either the Society of General Internal Medicine (academic generalists, response rate 30%) or the American Diabetes Association (specialists, response rate 23%) currently managing patients with type 2 diabetes. Respondents weighed the importance of 15 patient, physician, and nonclinical factors when deciding which medications to prescribe for type 2 diabetic subjects at each of three management stages (initiation, use of second-line oral agents, and insulin).
Respondents reported using a median of five major considerations (interquartile range 4–6) at each stage. Frequently cited major considerations included overall assessment of the patient’s health/comorbidity, A1C level, and patient’s adherence behavior but not expert guidelines/hospital algorithms or patient age. For insulin initiation, academic generalists placed greater emphasis on patient adherence (76 vs. 60% of specialists, P < 0.001). These generalists also identified patient fear of injections (68%) and patient desire to prolong noninsulin therapy (68%) as major insulin barriers. Overall, qualitative factors (e.g., adherence, motivation, overall health assessment) were somewhat more highly considered than quantitative factors (e.g., A1C, age, weight) with mean aggregate scores of 7.3 vs. 6.9 on a scale of 0–10, P < 0.001.
The physicians in our survey considered a wide range of qualitative and quantitative factors when making medication choices for hyperglycemia management. The apparent complexity of the medication choice process contrasts with current evidence-based treatment guidelines.
PMCID: PMC3829641  PMID: 17337497
8.  Blood Glucose Control in Type 1 Diabetes With a Bihormonal Bionic Endocrine Pancreas 
Diabetes Care  2012;35(11):2148-2155.
To test whether safe and effective glycemic control could be achieved in type 1 diabetes using a bihormonal bionic endocrine pancreas driven by a continuous glucose monitor in experiments lasting more than two days and including six high-carbohydrate meals and exercise as challenges to glycemic control.
Six subjects with type 1 diabetes and no endogenous insulin secretion participated in two 51-h experiments. Blood glucose was managed with a bionic endocrine pancreas controlling subcutaneous delivery of insulin and glucagon with insulin pumps. A partial meal-priming bolus of insulin (0.035 units/kg/meal, then 0.05 units/kg/meal in repeat experiments) was administered at the beginning of each meal (on average 78 ± 12 g of carbohydrates per meal were consumed). Plasma glucose (PG) control was evaluated with a reference quality measurement on venous blood every 15 min.
The overall mean PG was 158 mg/dL, with 68% of PG values in the range of 70–180 mg/dL. There were no significant differences in mean PG between larger and smaller meal-priming bolus experiments. Hypoglycemia (PG <70 mg/dL) was rare, with eight incidents during 576 h of closed-loop control (0.7% of total time). During 192 h of nighttime control, mean PG was 123 mg/dL, with 93% of PG values in the range of 70–180 mg/dL and only one episode of mild hypoglycemia (minimum PG 62 mg/dL).
A bihormonal bionic endocrine pancreas achieved excellent glycemic control with minimal hypoglycemia over the course of two days of continuous use despite high-carbohydrate meals and exercise. A trial testing a wearable version of the system under free-living conditions is justified.
PMCID: PMC3476884  PMID: 22923666
9.  Impact of inpatient diabetes management, education, and improved discharge transition on glycemic control 12 months after discharge 
To determine whether inpatient diabetes management and education with improved transition to outpatient care (IDMET) improves glycemic control after hospital discharge in patients with uncontrolled type 2 diabetes (T2DM).
Adult inpatients with T2DM and HbA1c≥7.5% (11 mmol/mol) admitted for reasons other than diabetes to an academic medical center were randomly assigned to IDMET vs. usual care (UC). Linear mixed models estimated treatment-dependent differences in the change in HbA1c (measured at 3, 6, and 12 months) from baseline to 1 year follow-up.
Thirty-one subjects had mean age 55 ± 12.6 years, with mean HbA1c of 9.7 ± 1.6% (82 ± 18 mmol/mol). Mean inpatient glucose was lower in the IDMET than in the UC group (176 ± 66 vs. 195 ± 74 mg/dl [9.7 vs. 10.8 mmol/l]), p=0.001. In the year after discharge, the average HbA1c reduction was greater in the IDMET compared to the UC group by 0.6% (SE 0.5%, [7 (SE 5) mmol/mol], p=0.3). Among patients newly discharged on insulin, the average HbA1c reduction was greater in the in the IDMET than in the UC group by 2.4% (SE 1.0%, [25 (SE 11) mmol/mol] p=0.04).
Inpatient diabetes management (IDMET) substantially improved glycemic control one year after discharge in patients newly discharged on insulin; patients previously treated with insulin did not benefit.
PMCID: PMC3514591  PMID: 23036785
inpatient diabetes management; diabetes care management strategy; inpatient to outpatient transitions in care
10.  Midcourse correction to a clinical trial when the event rate is underestimated: the Look AHEAD (Action for Health in Diabetes) Study 
The Look AHEAD (Action for Health in Diabetes) Study is a long-term clinical trial that aims to determine the cardiovascular disease (CVD) benefits of an intensive lifestyle intervention (ILI) in obese adults with type 2 diabetes. The study was designed to have 90% statistical power to detect an 18% reduction in the CVD event rate in the ILI Group compared to the Diabetes Support and Education (DSE) Group over 10.5 years of follow-up.
The original power calculations were based on an expected CVD rate of 3.125% per year in the DSE group; however, a much lower-than-expected rate in the first 2 years of follow-up prompted the Data and Safety Monitoring Board (DSMB) to recommend that the Steering Committee undertake a formal blinded evaluation of these design considerations. The Steering Committee created an Endpoint Working Group (EPWG) that consisted of individuals masked to study data to examine relevant issues.
The EPWG considered two primary options: (1) expanding the definition of the primary endpoint and (2) extending follow-up of participants. Ultimately, the EPWG recommended that the Look AHEAD Steering Committee approve both strategies. The DSMB accepted these modifications, rather than recommending that the trial continue with inadequate statistical power.
Trialists sometimes need to modify endpoints after launch. This decision should be well justified and should be made by individuals who are fully masked to interim results that could introduce bias. This article describes this process in the Look AHEAD study and places it in the context of recent articles on endpoint modification and recent trials that reported endpoint modification.
PMCID: PMC3790961  PMID: 22334468
11.  Effect of Hospital Admission on Glycemic Control One Year after Discharge 
We assessed the effect of hospital admission on glycemic control in patients with diabetes up to 1 year after discharge.
We retrospectively studied 826 adults with diabetes admitted to a tertiary care medical center and with available hemoglobin A1c (A1C) values prior to admission and 1 year after discharge. We compared them to 826 age-, sex-, race-, co-morbidity- and baseline A1C-matched non-hospitalized adults with diabetes. We determined change in A1C relative to hospitalization and baseline A1C using multivariate random effects models for repeated measures. Logistic regression was used to determine predictors of achieving recommended A1C levels at 1 year.
Patients with baseline A1C≥9% (adjusted mean A1C 9.90% [95% CI 9.25, 10.55]) had an adjusted change in A1C of −0.10% per month ([95% CI −0.18, −0.022], p<0.01) over the course of 1 year without differences between hospitalized and non-hospitalized patients in the mean rate of change. However, hospitalized patients were less likely to achieve an A1C ≤7% at one year (OR 0.68 [95% CI 0.55, 0.86], p<0.01) or A1C <8% at one year (OR 0.62 [95% CI 0.48, 0.81], p<0.01) compared to non-hospitalized patients.
Despite an overall trend towards improved glycemia over time, hospitalized patients with uncontrolled diabetes were less likely to achieve glycemic targets at 1 year compared to matched non-hospitalized patients. These results suggest a missed opportunity to improve long-term glycemic control in hospitalized patients with diabetes.
PMCID: PMC3746561  PMID: 22805110
hemoglobin A1c; hospitalization; glycemic control
12.  Plasma 25-Hydroxyvitamin D and Progression to Diabetes in Patients at Risk for Diabetes 
Diabetes Care  2012;35(3):565-573.
To investigate the association between vitamin D status, assessed by plasma 25-hydroxyvitamin D, and risk of incident diabetes.
Prospective observational study with a mean follow-up of 2.7 years in the Diabetes Prevention Program (DPP), a multicenter trial comparing different strategies for prevention of diabetes in patients with prediabetes. We assessed the association between plasma 25-hydroxyvitamin D, measured repeatedly during follow-up, and incident diabetes in the combined placebo (n = 1,022) and intensive lifestyle (n = 1,017) randomized arms of the DPP. Variables measured at multiple study time points (25-hydroxyvitamin D, BMI, and physical activity) entered the analyses as time-varying “lagged” covariates, as the mean of the previous and current visits at which diabetes status was assessed.
After multivariate adjustment, including for the DPP intervention, participants in the highest tertile of 25-hydroxyvitamin D (median concentration, 30.1 ng/mL) had a hazard ratio of 0.72 (95% CI 0.56–0.90) for developing diabetes compared with participants in the lowest tertile (median concentration, 12.8 ng/mL). The association was in the same direction in placebo (0.70; 0.52–0.94) versus lifestyle arm (0.80; 0.54–1.17).
Higher plasma 25-hydroxyvitamin D, assessed repeatedly, was associated with lower risk of incident diabetes in high-risk patients, after adjusting for lifestyle interventions (dietary changes, increased physical activity, and weight loss) known to decrease diabetes risk. Because of the observational nature of the study, the potential association between vitamin D and diabetes needs to be confirmed in intervention studies.
PMCID: PMC3322702  PMID: 22323410
13.  Myocardial Structure, Function and Scar in Patients with Type 1 Diabetes 
Circulation  2011;124(16):1737-1746.
We report relationships of cardiovascular disease (CVD) risk factors with myocardial structure, function and scar in patients with type 1 diabetes in the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) study.
Cardiac magnetic resonance (CMR) was obtained in 1017 patients with type 1 diabetes. Gadolinium CMR was also obtained in 741 patients. The mean age was 49 ± 7 years, 52% were men, and mean diabetes duration was 28± 5 years. Associations of CVD risk factors with CMR parameters were examined using linear and logistic regression models. History of macroalbuminuria was positively associated with LV mass (by +14.8 g) leading to a significantly higher LV mass/EDV ratio (by 8%). Mean hemoglobin A1c (HbA1c) levels over the preceding 22 years were inversely associated with end-diastolic volume (−3.0 ml per unit mean HbA1c %) and stroke volume (−2.3 ml per unit mean HbA1c %) and positively related to elevated LV mass/EDV ratio (0.02 g/ml per unit). The overall prevalence of myocardial scar was 4.3% by CMR and 1.4% by clinical adjudication of myocardial infarction. Both mean HbA1c (Odds ratio (O.R.) 1.5 [1.0–2.2] per unit) and macroalbuminuria (OR 3.5 [1.2–9.9]) were significantly associated with myocardial scar as well as traditional CVD risk factors.
In addition to traditional CVD risk factors, elevated mean HbA1c and macroalbuminuria were significantly associated with alterations in LV structure and function. The prevalence of myocardial scar was 4.3% in this subcohort of DCCT/EDIC participants with relatively preserved renal function.
PMCID: PMC3215589  PMID: 21947298
Myocardial function; myocardial scar; type 1 diabetes; delayed enhancement; CMR
14.  Efficacy Determinants of Subcutaneous Microdose Glucagon during Closed-Loop Control 
During a previous clinical trial of a closed-loop blood glucose (BG) control system that administered insulin and microdose glucagon subcutaneously, glucagon was not uniformly effective in preventing hypoglycemia (BG <70 mg/dl). After a global adjustment of control algorithm parameters used to model insulin absorption and clearance to more closely match insulin pharmacokinetic (PK) parameters observed in the study cohort, administration of glucagon by the control system was more effective in preventing hypoglycemia. We evaluated the role of plasma insulin and plasma glucagon levels in determining whether glucagon was effective in preventing hypoglycemia.
We identified and analyzed 36 episodes during which glucagon was given and categorized them as either successful or unsuccessful in preventing hypoglycemia.
In 20 of the 36 episodes, glucagon administration prevented hypoglycemia. In the remaining 16, BG fell below 70 mg/dl (12 of the 16 occurred during experiments performed before PK parameters were adjusted). The (dimensionless) levels of plasma insulin (normalized relative to each subject’s baseline insulin level) were significantly higher during episodes ending in hypoglycemia (5.2 versus 3.7 times the baseline insulin level, p = .01). The relative error in the control algorithm’s online estimate of the instantaneous plasma insulin level was also higher during episodes ending in hypoglycemia (50 versus 30%, p = .003), as were the peak plasma glucagon levels (183 versus 116 pg/ml, p = .007, normal range 50–150 pg/ml) and mean plasma glucagon levels (142 versus 75 pg/ml, p = .02). Relative to mean plasma insulin levels, mean plasma glucagon levels tended to be 59% higher during episodes ending in hypoglycemia, although this result was not found to be statistically significant (p = .14). The rate of BG descent was also significantly greater during episodes ending in hypoglycemia (1.5 versus 1.0 mg/dl/min, p = .02).
Microdose glucagon administration was relatively ineffective in preventing hypoglycemia when plasma insulin levels exceeded the controller’s online estimate by >60%. After the algorithm PK parameters were globally adjusted, insulin dosing was more conservative and microdose glucagon administration was very effective in reducing hypoglycemia while maintaining normal plasma glucagon levels. Improvements in the accuracy of the controller’s online estimate of plasma insulin levels could be achieved if ultrarapid-acting insulin formulations could be developed with faster absorption and less intra- and intersubject variability than the current insulin analogs available today.
PMCID: PMC3005038  PMID: 21129323
artificial endocrine pancreas; bihormonal; blood glucose; counterregulatory hormone; hypoglycemia; insulin pump; type 1 diabetes
15.  TCF7L2 Polymorphisms and Progression to Diabetes in the Diabetes Prevention Program 
The New England journal of medicine  2006;355(3):241-250.
Common polymorphisms of the transcription factor 7–like 2 gene (TCF7L2) have recently been associated with type 2 diabetes. We examined whether the two most strongly associated variants (rs12255372 and rs7903146) predict the progression to diabetes in persons with impaired glucose tolerance who were enrolled in the Diabetes Prevention Program, in which lifestyle intervention or treatment with metformin was compared with placebo.
We genotyped these variants in 3548 participants and performed Cox regression analysis using genotype, intervention, and their interactions as predictors. We assessed the effect of genotype on measures of insulin secretion and insulin sensitivity at baseline and at one year.
Over an average period of three years, participants with the risk-conferring TT genotype at rs7903146 were more likely to have progression from impaired glucose tolerance to diabetes than were CC homozygotes (hazard ratio, 1.55; 95 percent confidence interval, 1.20 to 2.01; P<0.001). The effect of genotype was stronger in the placebo group (hazard ratio, 1.81; 95 percent confidence interval, 1.21 to 2.70; P = 0.004) than in the metformin and lifestyle-intervention groups (hazard ratios, 1.62 and 1.15, respectively; P for the interaction between genotype and intervention not significant). The TT genotype was associated with decreased insulin secretion but not increased insulin resistance at baseline. Similar results were obtained for rs12255372.
Common variants in TCF7L2 seem to be associated with an increased risk of diabetes among persons with impaired glucose tolerance. The risk-conferring genotypes in TCF7L2 are associated with impaired beta-cell function but not with insulin resistance. ( number, NCT00004992.)
PMCID: PMC1762036  PMID: 16855264
16.  Does Glucose Variability Influence the Relationship Between Mean Plasma Glucose and HbA1c Levels in Type 1 and Type 2 Diabetic Patients? 
Diabetes Care  2011;34(8):1843-1847.
The A1C-Derived Average Glucose (ADAG) study demonstrated a linear relationship between HbA1c and mean plasma glucose (MPG). As glucose variability (GV) may contribute to glycation, we examined the association of several glucose variability indices and the MPG-HbA1c relationship.
Analyses included 268 patients with type 1 diabetes and 159 with type 2 diabetes. MPG during 3 months was calculated from 7-point self-monitored plasma glucose and continuous glucose monitoring. We calculated three different measures of GV and used a multiple-step regression model to determine the contribution of the respective GV measures to the MPG-HbA1c relationship.
GV, as reflected by SD and continuous overlapping net glycemic action, had a significant effect on the MPG-HbA1c relationship in type 1 diabetic patients so that high GV led to a higher HbA1c level for the same MPG. In type 1 diabetes, the impact of confounding and effect modification of a low versus high SD at an MPG level of 160 mg/dL on the HbA1c level is 7.02 vs. 7.43 and 6.96 vs. 7.41. All GV measures showed the same tendency.
In only type 1 diabetic patients, GV shows a significant interaction with MPG in the association with HbA1c. This effect is more pronounced at higher HbA1c levels. However, the impact of GV on the HbA1c level in type 1 diabetes is modest, particularly when HbA1c is close to the treatment target of 7%.
PMCID: PMC3142023  PMID: 21700921
17.  Using A Multi-Level B-Spline Model to Analyze and Compare Patient Glucose Profiles Based on Continuous Monitoring Data 
We show how continuous glucose monitoring (CGM) data can be analyzed using a three-level B-spline model, facilitating the estimation of inter-patient variability, within-patient inter-day variability, and measurement error. We propose methods for statistical comparison of glucose profiles among patient groups.
We applied a three-level random effects model using quadratic B-spline functions to analyze inter-patient and within-patient inter-day variations of the glucose trend. The estimated SD values of the glucose curves are time-dependent and were averaged over a 24-h period. We analyzed CGM data from 322 patients with type 1 diabetes, 223 patients with type 2 diabetes, and 86 subjects without diabetes using interstitial glucose levels measured every 5 min, for approximately 8 days per patient. We compared group-wide glucose profiles from the insulin pump–treated (n = 124) and multiple daily injection (MDI)–treated (n = 144) patients with type 1 diabetes.
The average inter-patient SD values were 49 mg/dL, 43 mg/dL, and 15 mg/dL for type 1 diabetes patients, type 2 diabetes patients, and subjects without diabetes, respectively. The average within-patient, inter-day SD values were 67 mg/dL, 41 mg/dL, and 18 mg/dL, respectively. The residual SD values were 19 mg/dL, 14 mg/dL, and 8 mg/dL, respectively. We identified a statistically significant difference in glucose profiles during the morning between insulin pump–treated and MDI-treated type 1 diabetes patients.
B-spline models facilitate the analysis of CGM data and show that type 1 diabetes is associated with higher inter-day glucose variation than type 2 diabetes or being without diabetes. Pump therapy and MDI have different effects on glucose control during specific time periods.
PMCID: PMC3101946  PMID: 21488799
18.  Guidelines and Recommendations for Laboratory Analysis in the Diagnosis and Management of Diabetes Mellitus 
Diabetes Care  2011;34(6):e61-e99.
Multiple laboratory tests are used to diagnose and manage patients with diabetes mellitus. The quality of the scientific evidence supporting the use of these tests varies substantially.
An expert committee compiled evidence-based recommendations for the use of laboratory testing for patients with diabetes. A new system was developed to grade the overall quality of the evidence and the strength of the recommendations. Draft guidelines were posted on the Internet and presented at the 2007 Arnold O. Beckman Conference. The document was modified in response to oral and written comments, and a revised draft was posted in 2010 and again modified in response to written comments. The National Academy of Clinical Biochemistry and the Evidence-Based Laboratory Medicine Committee of the American Association for Clinical Chemistry jointly reviewed the guidelines, which were accepted after revisions by the Professional Practice Committee and subsequently approved by the Executive Committee of the American Diabetes Association.
In addition to long-standing criteria based on measurement of plasma glucose, diabetes can be diagnosed by demonstrating increased blood hemoglobin A1c (HbA1c) concentrations. Monitoring of glycemic control is performed by self-monitoring of plasma or blood glucose with meters and by laboratory analysis of HbA1c. The potential roles of noninvasive glucose monitoring, genetic testing, and measurement of autoantibodies, urine albumin, insulin, proinsulin, C-peptide, and other analytes are addressed.
The guidelines provide specific recommendations that are based on published data or derived from expert consensus. Several analytes have minimal clinical value at present, and their measurement is not recommended.
PMCID: PMC3114322  PMID: 21617108
19.  Obesity and Type 2 Diabetes: What Can Be Unified and What Needs to Be Individualized? 
Diabetes Care  2011;34(6):1424-1430.
This report examines what is known about the relationship between obesity and type 2 diabetes and how future research in these areas might be directed to benefit prevention, interventions, and overall patient care.
An international working group of 32 experts in the pathophysiology, genetics, clinical trials, and clinical care of obesity and/or type 2 diabetes participated in a conference held on 6–7 January 2011 and cosponsored by The Endocrine Society, the American Diabetes Association, and the European Association for the Study of Diabetes. A writing group comprising eight participants subsequently prepared this summary and recommendations. Participants reviewed and discussed published literature and their own unpublished data.
The writing group unanimously supported the summary and recommendations as representing the working group's majority or unanimous opinions.
The major questions linking obesity to type 2 diabetes that need to be addressed by combined basic, clinical, and population-based scientific approaches include the following: 1) Why do not all patients with obesity develop type 2 diabetes? 2) Through what mechanisms do obesity and insulin resistance contribute to β-cell decompensation, and if/when obesity prevention ensues, how much reduction in type 2 diabetes incidence will follow? 3) How does the duration of type 2 diabetes relate to the benefits of weight reduction by lifestyle, weight-loss drugs, and/or bariatric surgery on β-cell function and glycemia? 4) What is necessary for regulatory approval of medications and possibly surgical approaches for preventing type 2 diabetes in patients with obesity? Improved understanding of how obesity relates to type 2 diabetes may help advance effective and cost-effective interventions for both conditions, including more tailored therapy. To expedite this process, we recommend further investigation into the pathogenesis of these coexistent conditions and innovative approaches to their pharmacological and surgical management.
PMCID: PMC3114323  PMID: 21602431
20.  Position Statement Executive Summary: Guidelines and Recommendations for Laboratory Analysis in the Diagnosis and Management of Diabetes Mellitus 
Diabetes Care  2011;34(6):1419-1423.
Multiple laboratory tests are used in the diagnosis and management of patients with diabetes mellitus. The quality of the scientific evidence supporting the use of these assays varies substantially.
An expert committee compiled evidence-based recommendations for the use of laboratory analysis in patients with diabetes. A new system was developed to grade the overall quality of the evidence and the strength of the recommendations. A draft of the guidelines was posted on the Internet, and the document was modified in response to comments. The guidelines were reviewed by the joint Evidence-Based Laboratory Medicine Committee of the AACC and the National Academy of Clinical Biochemistry and were accepted after revisions by the Professional Practice Committee and subsequent approval by the Executive Committee of the American Diabetes Association.
In addition to the long-standing criteria based on measurement of venous plasma glucose, diabetes can be diagnosed by demonstrating increased hemoglobin A1c (HbA1c) concentrations in the blood. Monitoring of glycemic control is performed by the patients measuring their own plasma or blood glucose with meters and by laboratory analysis of HbA1c. The potential roles of noninvasive glucose monitoring, genetic testing, and measurement of autoantibodies, urine albumin, insulin, proinsulin, C-peptide, and other analytes are addressed.
The guidelines provide specific recommendations based on published data or derived from expert consensus. Several analytes are found to have minimal clinical value at the present time, and measurement of them is not recommended.
PMCID: PMC3114347  PMID: 21617111
21.  Levels of Oxidized LDL and Advanced Glycation End Products–Modified LDL in Circulating Immune Complexes Are Strongly Associated With Increased Levels of Carotid Intima-Media Thickness and Its Progression in Type 1 Diabetes 
Diabetes  2011;60(2):582-589.
High cholesterol levels in circulating immune complexes (IC), surrogate markers of modified LDL, are associated with increased carotid intima-media thickness (IMT) and cardiovascular events in type 1 diabetes. Different modifications of LDL are involved in IC formation, but which of these are predictive of vascular events is not known. Therefore, we measured oxidized LDL (oxLDL), advanced glycation end products–modified LDL (AGE-LDL), and malondialdehyde-modified LDL (MDA-LDL) in IC and determined their relationship with increased carotid IMT and compared the strength of the association with that observed with conventional risk factors.
Levels of oxLDL, AGE-LDL, and MDA-LDL were measured in circulating IC isolated from sera of 479 patients of the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) cohort, collected at baseline. Internal and common carotid IMT were measured 8 and 14 years later by DCCT/EDIC.
OxLDL, AGE-LDL, and MDA-LDL levels in circulating IC were significantly correlated with diabetes duration, BMI, and lipid and blood pressure, but not with age. Multivariate logistic regression models indicated that individuals in the highest versus lowest quartile of oxLDL and AGE-LDL in IC had a 6.11-fold [confidence interval (CI) 2.51–14.8] and a 6.4-fold (CI 2.53–16.2) increase in the odds of having high carotid IMT, respectively, after adjusting for conventional risk factors. Parallel analyses resulted in odds ratios of 2.62 (CI 1.24, 5.55) for LDL-C, 1.45 (CI 0.69, 3.03) for diastolic blood pressure, and 2.33 (CI 1.09, 4.99) for A1C.
OxLDL and AGE-LDL in circulating IC were significantly associated with progression and increased levels of carotid IMT in type 1 diabetes.
PMCID: PMC3028359  PMID: 20980456
22.  Progression of Carotid Artery Intima-Media Thickness During 12 Years in the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) Study 
Diabetes  2011;60(2):607-613.
This study investigated the long-term effects of intensive diabetic treatment on the progression of atherosclerosis, measured as common carotid artery intima-media thickness (IMT).
A total of 1,116 participants (52% men) in the Epidemiology of Diabetes Interventions and Complications (EDIC) trial, a long-term follow-up of the Diabetes Control and Complications Trial (DCCT), had carotid IMT measurements at EDIC years 1, 6, and 12. Mean age was 46 years, with diabetes duration of 24.5 years at EDIC year 12. Differences in IMT progression between DCCT intensive and conventional treatment groups were examined, controlling for clinical characteristics, IMT reader, and imaging device.
Common carotid IMT progression from EDIC years 1 to 6 was 0.019 mm less in intensive than in conventional (P < 0.0001), and from years 1 to 12 was 0.014 mm less (P = 0.048); but change from years 6 to 12 was similar (intensive − conventional = 0.005 mm, P = 0.379). Mean A1C levels during DCCT and DCCT/EDIC were strongly associated with progression of IMT, explaining most of the differences in IMT progression between DCCT treatment groups. Albuminuria, older age, male sex, smoking, and higher systolic blood pressure were significant predictors of IMT progression.
Intensive treatment slowed IMT progression for 6 years after the end of DCCT but did not affect IMT progression thereafter (6–12 years). A beneficial effect of prior intensive treatment was still evident 13 years after DCCT ended. These differences were attenuated but not negated after adjusting for blood pressure. These results support the early initiation and continued maintenance of intensive diabetes management in type 1 diabetes to retard atherosclerosis.
PMCID: PMC3028362  PMID: 21270271
23.  Associations Between Features of Glucose Exposure and A1C 
Diabetes  2010;59(7):1585-1590.
Various methods are used to quantify postprandial glycemia or glucose variability, but few have been compared and none are standardized. Our objective was to examine the relationship among common indexes of postprandial glycemia, overall hyperglycemia, glucose variability, and A1C using detailed glucose measures obtained during everyday life and to study which blood glucose values of the day provide the strongest prediction of A1C.
In the A1C-Derived Average Glucose (ADAG) study, glucose levels were monitored in 507 participants (268 type 1 diabetic, 159 type 2 diabetic, and 80 nondiabetic subjects) with continuous glucose monitoring (CGM) and frequent self-monitoring of blood glucose (SMBG) during 16 weeks. We calculated several indexes of glycemia and analyzed their intercorrelations. The association between glucose measurements at different times of the day (pre- and postprandial) and A1C was examined using multiple linear regression.
Indexes of glucose variability showed strong intercorrelation. Among postprandial indexes, the area under the glucose curve calculated from CGM 2 h after a meal correlated well with the 90-min SMBG postprandial measurements. Fasting blood glucose (FBG) levels were only moderately correlated with indexes of hyperglycemia and average or postprandial glucose levels. Indexes derived with SMBG strongly correlated with those from CGM. Some SMBG time points had a stronger association with A1C than others. Overall, preprandial glucose values had a stronger association with A1C than postprandial values for both diabetes types, particularly for type 2 diabetes.
Indexes of glucose variability and average and postprandial glycemia intercorrelate strongly within each category. Variability indexes are weakly correlated with the other categories, indicating that these measures convey different information. FBG is not a clear indicator of general glycemia. Preprandial glucose values have a larger impact on A1C levels than postprandial values.
PMCID: PMC2889756  PMID: 20424232
24.  Adipocytokines, Obesity, and Insulin Resistance During Combined Androgen Blockade for Prostate Cancer: Evidence for a Distinct Hypogonadal Metabolic Syndrome? 
Urology  2008;71(2):318-322.
Gonadotropin-releasing hormone agonists increase fat mass, decrease insulin sensitivity, and increase serum triglycerides–changes suggestive of the classic metabolic syndrome. These analyses were designed to assess the effects of gonadotropin-releasing hormone agonist treatment on other markers of the metabolic syndrome including adiponectin, resistin, and plasminogen activator inhibitor type 1 (PAI-1) levels and to evaluate relationships between changes in adipocytokines, body composition, and insulin sensitivity.
In this prospective 12-week study, 25 nondiabetic men with locally advanced or recurrent prostate cancer and no radiographic evidence of metastases were treated with leuprolide depot and bicalutamide. Outcomes included changes from baseline to week 12 in body composition, insulin sensitivity, and levels of adiponectin, resistin, and PAI-1.
Mean (± SE) percentage fat body mass increased by 4.3 ± 1.3% from baseline to week 12 (P=0.002). Insulin sensitivity index decreased by 12.9 ± 7.6% (P=0.02). Serum adiponectin levels increased by 37.4 ± 7.2% from baseline to week 12 (P<0.001). In contrast, serum resistin levels did not change significantly. Changes in adiponectin were associated with changes lean mass (r=0.448; P=0.02) and fat mass (r=−0.383; P=0.06) but not changes in insulin sensitivity.
Combined androgen blockade with leuprolide and bicalutamide significantly increased serum adiponectin levels but did not alter PAI-1 or resistin levels. This pattern of metabolic changes appears distinct from the classic metabolic syndrome.
PMCID: PMC2614378  PMID: 18308111
prostate cancer; GnRH agonist; obesity; insulin resistance; adiponectin; resistin
25.  Rapid Identification of Myocardial Infarction Risk Associated With Diabetes Medications Using Electronic Medical Records 
Diabetes Care  2009;33(3):526-531.
To assess the ability to identify potential association(s) of diabetes medications with myocardial infarction using usual care clinical data obtained from the electronic medical record.
We defined a retrospective cohort of patients (n = 34,253) treated with a sulfonylurea, metformin, rosiglitazone, or pioglitazone in a single academic health care network. All patients were aged >18 years with at least one prescription for one of the medications between 1 January 2000 and 31 December 2006. The study outcome was acute myocardial infarction requiring hospitalization. We used a cumulative temporal approach to ascertain the calendar date for earliest identifiable risk associated with rosiglitazone compared with that for other therapies.
Sulfonylurea, metformin, rosiglitazone, or pioglitazone therapy was prescribed for 11,200, 12,490, 1,879, and 806 patients, respectively. A total of 1,343 myocardial infarctions were identified. After adjustment for potential myocardial infarction risk factors, the relative risk for myocardial infarction with rosiglitazone was 1.3 (95% CI 1.1–1.6) compared with sulfonylurea, 2.2 (1.6–3.1) compared with metformin, and 2.2 (1.5–3.4) compared with pioglitazone. Prospective surveillance using these data would have identified increased risk for myocardial infarction with rosiglitazone compared with metformin within 18 months of its introduction with a risk ratio of 2.1 (95% CI 1.2–3.8).
Our results are consistent with a relative adverse cardiovascular risk profile for rosiglitazone. Our use of usual care electronic data sources from a large hospital network represents an innovative approach to rapid safety signal detection that may enable more effective postmarketing drug surveillance.
PMCID: PMC2827502  PMID: 20009093

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