Prevalence and risk factors for diabetic retinopathy at diagnosis of type 2 diabetes: an observational study of 77 681 patients from the Swedish National Diabetes Registry.

INTRODUCTION: To assess the prevalence of diabetic retinopathy (DR) in persons with newly diagnosed type 2 diabetes (T2D) to understand the potential need for intensified screening for early detection of T2D. RESEARCH DESIGN AND METHODS: Individuals from the Swedish National Diabetes Registry with a retinal photo <2 years after diagnosis of T2D were included. The proportion of patients with retinopathy (simplex or worse) was assessed. Patient characteristics and risk factors at diagnosis were analyzed in relation to DR with logistic regression. RESULTS: In total, 77 681 individuals with newly diagnosed T2D, mean age 62.6 years, 41.1% females were included. Of these, 13 329 (17.2%) had DR.DR was more common in older persons (adjusted OR 1.03 per 10-year increase, 95% CI 1.01 to 1.05) and men compared with women, OR 1.10 (1.05 to 1.14). Other variables associated with DR were OR (95% CI): lower education 1.08 (1.02 to 1.14); previous stroke 1.18 (1.07 to 1.30); chronic kidney disease 1.29 (1.07 to 1.56); treatment with acetylsalicylic acid 1.14 (1.07 to 1.21); ACE inhibitors 1.12 (1.05 to 1.19); and alpha blockers 1.41 (1.15 to 1.73). DR was more common in individuals born in Asia (OR 1.16, 95% CI 1.08 to 1.25) and European countries other than those born in Sweden (OR 1.11, 95% CI 1.05 to 1.18). CONCLUSIONS: Intensified focus on screening of T2D may be needed in Sweden in clinical practice since nearly one-fifth of persons have retinopathy at diagnosis of T2D. The prevalence of DR was higher in men, birthplace outside of Sweden, and those with a history of stroke, kidney disease, and hypertension.

Performance of Dexcom G5 and FreeStyle Libre sensors tested simultaneously in people with type 1 or 2 diabetes and advanced chronic kidney disease.

BACKGROUND: Advanced chronic kidney disease (CKD) is a common complication for people with type 1 and 2 diabetes and can often lead to glucose instability. Continuous glucose monitoring (CGM) helps users monitor and stabilize their glucose levels. To date, CGM and intermittent scanning CGM are only approved for people with diabetes but not for those with advanced CKD. AIM: To compare the performance of Dexcom G5 and FreeStyle Libre sensors in adults with type 1 or 2 diabetes and advanced CKD. METHODS: This was a non-randomized clinical trial that took place in two outpatient clinics in western Sweden. All patients with type 1 or 2 diabetes and an estimated glomerular filtration rate (eGFR) of < 30 mL/min per 1.73 m2 were invited to participate. Forty patients (full analysis set = 33) carried the Dexcom G5 sensor for 7 d and FreeStyle Libre sensor for 14 d simultaneously. For referencing capillary blood glucose (SMBG) was measured with a high accuracy glucose meter (HemoCue®) during the study period. At the end of the study, all patients were asked to answer a questionnaire on their experience using the sensors. RESULTS: The mean age was 64.1 (range 41-77) years, hemoglobin A1c was 7.0% [standard deviation (SD) 3.2], and diabetes duration was 28.5 (SD 14.7) years. A total of 27.5% of the study population was on hemodialysis and 22.5% on peritoneal dialysis. The mean absolute relative difference for Dexcom G5 vs SMBG was significantly lower than that for FreeStyle Libre vs SMBG [15.2% (SD 12.2) vs 20.9% (SD 8.6)], with a mean difference of 5.72 [95% confidence interval (CI): 2.11-9.32; P = 0.0036]. The mean absolute difference was also significantly lower for Dexcom G5 than for FreeStyle Libre, 1.21 mmol/L (SD 0.78) and 1.76 mmol/L (SD 0.78), with a mean diffrenec of 0.55 (95%CI: 0.27-0.83; P = 0.0004).The mean difference (MD) was -0.107 mmol/L and -1.10 mmol/L (P = 0.0002), respectively. In all, 66% of FreeStyle Libre values were in the no risk zone on the surveillance error grid compared to 82% of Dexcom G5 values. CONCLUSION: Dexcom G5 produces more accurate sensor values than FreeStyle Libre in people with diabetes and advanced CKD and is likely safe to be used by those with advanced CKD.

Evaluation of Reference Metrics for Continuous Glucose Monitoring in Persons Without Diabetes and Prediabetes.

BACKGROUND: Recent guidelines have been developed for continuous glucose monitoring (CGM) metrics in persons with diabetes. To understand what glucose profiles should be judged as normal in clinical practice and glucose-lowering trials, we examined the glucose profile of healthy individuals using CGM. METHODS: Persons without diabetes or prediabetes were included after passing a normal oral glucose tolerance test, two-hour value <8.9 mmol/L (160 mg/dL), fasting glucose <6.1 mmol/L (110 mg/dL), and HbA1c <6.0% (<42 mmol/mol). CGM metrics were evaluated using the Dexcom G4 Platinum. RESULTS: In total, 60 persons were included, mean age was 43.0 years, 70.0% were women, mean HbA1c was 5.3% (34 mmol/mol), and mean body mass index was 25.7 kg/m2. Median and mean percent times in hypoglycemia <3.9 mmol/L (70 mg/dL) were 1.6% (IQR 0.6-3.2), and 3.2% (95% CI 2.0; 4.3), respectively. For glucose levels <3.0 mmol/L (54 mg/dL), the corresponding estimates were 0.0% (IQR 0.0-0.4) and 0.5% (95% CI 0.2; 0.8). Median and mean time-in-range (3.9-10.0 mmol/L [70-180 mg/dL]) was 97.3% (IQR 95.4-98.7) and 95.4% (95% CI 94.0; 96.8), respectively. Median and mean standard deviations were 1.04 mmol/L (IQR 0.92-1.29) and 1.15 mmol/L (95% CI 1.05; 1.24), respectively. Measures of glycemic variability (standard deviation, coefficient of variation, mean amplitude of glycemic excursions) were significantly greater during daytime compared with nighttime, whereas others did not differ. CONCLUSIONS: People without prediabetes or diabetes show a non-negligible % time in hypoglycemia, median 1.6% and mean 3.2%, which needs to be accounted for in clinical practice and glucose-lowering trials. Glycemic variability measures differ day and night in this population.

Characteristics of Continuous Glucose Monitoring Metrics in Persons with Type 1 and Type 2 Diabetes Treated with Multiple Daily Insulin Injections.

Background: Although guidelines advocate similar continuous glucose monitoring (CGM) targets for insulin-treated persons with type 1 diabetes (T1D) and type 2 diabetes (T2D), it is unclear how these persons differ with respect to hypoglycemia, glucose variability, and other CGM metrics in clinical practice. Methods: We used data from 2 multicenter randomized-controlled trials (GOLD and MDI-Liraglutide) where 161 persons with T1D and 124 persons with T2D treated with multiple daily injections were included and monitored with masked CGM. Results: Persons from both cohorts had similar mean glucose levels, 10.9 mmol/L (196 mg/dL) in persons with T1D and 10.8 mmol/L (194 mg/dL) in persons with T2D. Time in hypoglycemia (<3.9 mmol/L [70 mg/dL]) was 5.1% and 1.0% for persons with T1D and T2D, respectively (P < 0.001). Corresponding estimates for the standard deviations of mean glucose levels were 4.4 mmol/L (79 mg/dL) versus 3.0 (54 mg/dL) (P < 0.001), for coefficient of variation 41% versus 28% (P < 0.001), and for time in range 38.2% versus 45.3%, respectively (P = 0.004). Mean C-peptide levels were 0.05 nmol/L and 0.67 nmol/L (P < 0.001) for persons with T1D and T2D, respectively. Conclusions: Persons with T1D compared with persons with T2D treated with multiple daily insulin injections spend considerably more time in hypoglycemia, have higher glucose variability, and less "time in range." This needs to be taken into account in daily clinical care and in recommended targets for CGM metrics.

Effect of Liraglutide on Times in Glycaemic Ranges as Assessed by CGM for Type 2 Diabetes Patients Treated With Multiple Daily Insulin Injections.

INTRODUCTION: The effects of the GLP-1 analogue liraglutide on time in hypoglycaemia, time in hyperglycaemia, and time in range for type 2 diabetes patients initially treated with multiple daily insulin injections (MDI) were investigated. Variables associated with hypoglycaemia in the current population were also identified. METHODS: Analyses were based on data from a previously performed double-blind, placebo-controlled trial in which 124 MDI-treated patients with type 2 diabetes were randomized to liraglutide or placebo. Masked continuous glucose monitoring (CGM) was performed at baseline and week 24 in 99 participants. RESULTS: The mean time in hypoglycaemia was similar for participants receiving liraglutide and those receiving placebo after 24 weeks of treatment. Mean time in target was greater in the liraglutide group than in the placebo group: 430 versus 244 min/24 h (p < 0.001) and 960 versus 695 min/24 h (p < 0.001) for the two glycaemic ranges considered, 4-7 mmol/l and 4-10 mmol/l, respectively. Mean time in hyperglycaemia was lower in the liraglutide group: 457 versus 723 min/24 h (p = 0.001) and 134 versus 264 min/24 h (p = 0.023) for the two cutoffs considered, > 10 mmol/l and > 14 mmol/l, respectively. Lower mean glucose level, lower C-peptide, and higher glucose variability were associated with an increased risk of hypoglycaemia in both treatment groups. Higher proinsulin level was associated with a lower risk of hypoglycaemia in the liraglutide group. CONCLUSION: For type 2 diabetes patients initially treated with MDI, introducing liraglutide had a beneficial effect on glucose profiles estimated by masked CGM. Mean glucose level, glycaemic variability, C-peptide, and proinsulin level influenced the risk of hypoglycaemia in this population. TRIAL REGISTRATION: ClinicalTrials.gov, number (EudraCT nr: 2012-001941-42). FUNDING: Novo Nordisk funded this study. The Diabetes Research Unit, NU-Hospital Group funded the journal's Rapid Service Fee.

Predictors and correlates of systolic blood pressure reduction with liraglutide treatment in patients with type 2 diabetes.

Liraglutide is associated with blood pressure reduction in patients with type 2 diabetes. However, it is not known whether this blood pressure reduction can be predicted prior to treatment initiation, and to what extent it correlates with weight loss and with improved glycemic control during follow-up. We analyzed data from a double-blind, placebo-controlled trial, in which 124 insulin-treated patients with type 2 diabetes were randomized to liraglutide or placebo. We evaluated various baseline variables as potential predictors of systolic blood pressure (SBP) reduction, and evaluated whether changes in SBP correlated with weight loss and with improved glycemic control. A greater reduction in SBP among liraglutide-treated patients was predicted by higher baseline values of SBP (P < 0.0001) and diastolic blood pressure (P = 0.012), and by lower baseline values of mean glucose measured by continuous glucose monitoring (CGM; P = 0.044), and serum fasting C-peptide (P = 0.015). The regression coefficients differed significantly between the liraglutide group and the placebo group only for diastolic blood pressure (P = 0.037) and mean CGM (P = 0.021). During the trial period, SBP reduction correlated directly with change in body weight and BMI, but not with change in HbA1c. We conclude that patients with lower mean CGM values at baseline responded to liraglutide with a larger reduction in SBP, and that improved HbA1c during follow-up was not associated with reductions of SBP. Our data suggest that some patients with type 2 diabetes may benefit from liraglutide in terms of weight and SBP reduction.