Discordance between mean glucose and time in range in relation to HbA1c in individuals with type 1 diabetes: results from the GOLD and SILVER trials.

AIMS/HYPOTHESIS: Previous studies have shown that individuals with similar mean glucose levels (MG) or percentage of time in range (TIR) may have different HbA1c values. The aim of this study was to further elucidate how MG and TIR are associated with HbA1c. METHODS: Data from the randomised clinical GOLD trial (n=144) and the follow-up SILVER trial (n=98) of adults with type 1 diabetes followed for 2.5 years were analysed. A total of 596 paired HbA1c/continuous glucose monitoring measurements were included. Linear mixed-effects models were used to account for intra-individual correlations in repeated-measures data. RESULTS: In the GOLD trial, the mean age of the participants (± SD) was 44±13 years, 63 (44%) were female, and the mean HbA1c (± SD) was 72±9.8 mmol/mol (8.7±0.9%). When correlating MG with HbA1c, MG explained 63% of the variation in HbA1c (r=0.79, p<0.001). The variation in HbA1c explained by MG increased to 88% (r=0.94, p value for improvement of fit <0.001) when accounting for person-to-person variation in the MG-HbA1c relationship. Time below range (TBR; <3.9 mmol/l), time above range (TAR) level 2 (>13.9 mmol/l) and glycaemic variability had little or no effect on the association. For a given MG and TIR, the HbA1c of 10% of individuals deviated by >8 mmol/mol (0.8%) from their estimated HbA1c based on the overall association between MG and TIR with HbA1c. TBR and TAR level 2 significantly influenced the association between TIR and HbA1c. At a given TIR, each 1% increase in TBR was related to a 0.6 mmol/mol lower HbA1c (95% CI 0.4, 0.9; p<0.001), and each 2% increase in TAR level 2 was related to a 0.4 mmol/mol higher HbA1c (95% CI 0.1, 0.6; p=0.003). However, neither TIR, TBR nor TAR level 2 were significantly associated with HbA1c when accounting for MG. CONCLUSIONS/INTERPRETATION: Inter-individual variations exist between MG and HbA1c, as well as between TIR and HbA1c, with clinically important deviations in relatively large groups of individuals with type 1 diabetes. These results may provide important information to both healthcare providers and individuals with diabetes in terms of prognosis and when making diabetes management decisions.

The effect of carbohydrate intake on glycaemic control in individuals with type 1 diabetes: a randomised, open-label, crossover trial.

Background: Few studies have examined the effects of lower carbohydrate diets on glucose control in persons with type 1 diabetes (T1D). The objective of the study was to investigate whether a moderate carbohydrate diet improves glucose control in persons with T1D. Methods: A randomised, multicentre, open-label, crossover trial over 12 weeks. There were 69 individuals assessed for eligibility, 54 adults with T1D and HbA1c ≥ 58 mmol/mol (7.5%) were randomised. Interventions were moderate carbohydrate diet versus traditional diet (30 vs 50% of total energy from carbohydrates) over four weeks, with a four-week wash-out period between treatments. Masked continuous glucose monitoring was used to evaluate effects on glucose control. The primary endpoint was the difference in mean glucose levels between the last 14 days of each diet phase. Findings: 50 individuals were included in the full analysis set with a mean baseline HbA1c of 69 mmol/mol (8.4%), BMI 29 kg/m2, age of 48 years, and 50% were female. The difference in mean glucose levels between moderate carbohydrate and traditional diet was -0.6 mmol/L, 95% CI -0.9 to -0.3, p < 0.001. Time in range increased during moderate carbohydrate diet by 4.7% (68 min/24 h) (95% CI 1.3 to 8.0), p = 0.008. Time above range (>10 mmol/L) decreased by 5.9% (85 min/24 h), 95% CI -9.6 to -2.2, p = 0.003. There were no significant differences in the standard deviation of glucose levels (95% CI -0.3 to 0.0 mmol/L, p = 0.15) or hypoglycaemia in the range <3.9 mmol/L (95% CI -0.4 to 2.9%, p = 0.13) and <3.0 mmol/L (95% CI -0.4 to 1.6%, p = 0.26). Four participants withdrew, none because of adverse events. There were no serious adverse events including severe hypoglycaemia and ketoacidosis. Mean ketone levels were 0.17 (SD 0.14) mmol/L during traditional and 0.18 (SD 0.13) mmol/L during moderate carbohydrate diet (p = 0.02). Interpretation: A moderate carbohydrate diet is associated with decreases in mean glucose levels and time above range and increases in time in range without increased risk of hypoglycaemia or ketoacidosis compared with a traditional diet in individuals with T1D. Funding: The Healthcare Board, Region Västra Götaland, The Dr P Håkansson Foundation and the Swedish state under the agreement between the Swedish government and the county councils, the ALF-agreement [ALFGBG-966173].

Evaluating a systematic intensive therapy using continuous glucose monitoring and intermittent scanning glucose monitoring in clinical diabetes care: a protocol for a multi-center randomized clinical trial.

Introduction: As many people with type 1 diabetes find it hard to reach the recommended glycemic goals, even with CGM, this study aims to determine if a closer, digitally supported collaboration on interpreting CGM data together with a diabetes nurse can improve glycemic control. Methods and analysis: A total of 120 individuals, 18 years and older and with HbA1c ≥ 58 mmol/mol will be included in the study at 8 different sites in Sweden and Norway. To be included, the participants must use a CGM or isCGM and be able to upload the data to the appropriate online service for their clinic and sensor. Both those with insulin pumps and insulin pens will be included in the study. Participants will be randomized into two different groups, that is, the intensive therapy group and the control group. The intensive therapy group will upload their glucose data weekly for the first 4 months and have telephone contact with their diabetes care team to receive support in interpreting CGM data and taking appropriate actions if their mean blood glucose level is above 8.4 mmol/L. After the 4-month-long intensive treatment phase, both randomized groups will have the same number of clinical visits and receive the same type of diabetes support. Discussion: It is of great importance to find new ways to help people with type 1 diabetes manage their condition as well as they can to help them achieve better glycemic control so that hopefully more people can achieve the recommended glycemic goals, which are associated with fewer diabetes complications. If it is shown that people with type 1 diabetes achieve better glycemic control with intensive therapy, then this can be incorporated into clinical praxis as an option for those not currently reaching the recommended glycemic goals. Clinical Trial Registration: https://clinicaltrials.gov/study/NCT03474393?locStr=Uddevalla,%20Sweden&country=Sweden&distance=50&cond=Diabetes&aggFilters=ages:adult%20older&state=V%C3%A4stra%20G%C3%B6taland%20County&city=Uddevalla&page=4&rank=34, identifier 03474393.

Design of a randomized cross-over study evaluating effects of carbohydrate intake on glycemic control in persons with type 1 diabetes.

Introduction: Diet is an important factor in managing glycemic control in type 1 diabetes (T1D). Reducing carbohydrate intake may be important for stabilizing blood glucose levels in certain groups of patients with T1D. There are few studies examining the effects of a low carbohydrate diet in patients with T1D. The aim of this study is to investigate the effects of carbohydrate intake on glucose control in adults with T1D. Materials and methods: Adults with T1D (N = 54) and inadequate glycemic control (HbA1c ≥ 7.5%; 58 mmol/mol) were randomized in a cross-over design to a moderate carbohydrate diet (30 percent of total energy from carbohydrates) versus a traditional diabetes diet (50 percent of total energy from carbohydrates) for 4 weeks with a between wash-out period of 4 weeks. Masked continuous glucose monitoring was used throughout the study to evaluate effects on mean blood glucose levels, time-in-range, hypoglycemia, hyperglycemia, and glycemic variability. Diabetes treatment satisfaction, hypoglycemic confidence, and physical activity were measured using questionnaires during different phases of the trial. HbA1c, blood lipids, blood pressure, and ketone levels were also measured. The primary endpoint is the difference in mean blood glucose level between the diet periods. Study completion is anticipated during winter 2022. Discussion: The study seeks to increase knowledge about the effects of dietary carbohydrate intake on glycemic control and other health parameters in patients with T1D. If beneficial effects on mean blood glucose level without elevated risk of hypoglycemia or ketoacidosis are shown, a moderate carbohydrate diet may be a treatment option for people with T1D that have unsatisfactory blood glucose levels.Clinical Trials Registration: www.clinicaltrials.gov, ID: NCT03400618.

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.

Risk factors and incidence over time for lower extremity amputations in people with type 1 diabetes: an observational cohort study of 46,088 patients from the Swedish National Diabetes Registry.

AIMS/HYPOTHESIS: The aim of this work was to study the incidence over time of lower extremity amputations and determine variables associated with increased risk of amputations in people with type 1 diabetes. METHODS: Individuals with type 1 diabetes registered in the Swedish National Diabetes Registry with no previous amputation from 1 January 1998 and followed to 2 October 2019 were included. Time-updated Cox regression and gradient of risk per SD were used to evaluate the impact of risk factors on the incidence of amputation. Age- and sex-adjusted incidences were estimated over time. RESULTS: Of 46,088 people with type 1 diabetes with no previous amputation (mean age 32.5 years [SD 14.5], 25,354 [55%] male sex), 1519 (3.3%) underwent amputation. Median follow-up was 12.4 years. The standardised incidence for any amputation in 1998-2001 was 2.84 (95% CI 2.32, 3.36) per 1000 person-years and decreased to 1.64 (95% CI 1.38, 1.90) per 1000 person-years in 2017-2019. The incidence for minor and major amputations showed a similar pattern. Hyperglycaemia and renal dysfunction were the strongest risk factors for amputation, followed by older age, male sex, cardiovascular comorbidities, smoking and hypertension. Glycaemic control and age- and sex-adjusted renal function improved during the corresponding time period as amputations decreased. CONCLUSIONS/INTERPRETATION: The incidence of amputation and of the most prominent risk factors for amputation, including renal dysfunction and hyperglycaemia, has improved considerably during recent years for people with type 1 diabetes. This finding has important implications for quality of life, health economics and prognosis regarding CVD, indicating a trend shift in the treatment of type 1 diabetes.

Sustained Intensive Treatment and Long-term Effects on HbA1c Reduction (SILVER Study) by CGM in People With Type 1 Diabetes Treated With MDI.

OBJECTIVE: Continuous glucose monitoring (CGM) reduces HbA1c and time spent in hypoglycemia in people with type 1 diabetes (T1D) treated with multiple daily insulin injections (MDI) when evaluated over shorter time periods. It is unclear to what extent CGM improves and helps to maintain glucose control, treatment satisfaction, diabetes distress, hypoglycemic concerns, and overall well-being over longer periods of time. RESEARCH DESIGN AND METHODS: The GOLD trial was a randomized crossover trial performed over 16 months of CGM treatment in people with T1D treated with MDI. People completing the trial (n = 141) were invited to participate in the current SILVER extension study in which 107 patients continued CGM treatment over 1 year along with the support of a diabetes nurse every 3 months. RESULTS: The primary end point of the change in HbA1c over 1.0-1.5 years of CGM use compared with previous self-monitoring of blood glucose during GOLD showed a decrease in HbA1c of 0.35% (95% CI 0.19-0.50, P < 0.001). Time spent in hypoglycemia <3.0 mmol/L (54 mg/dL) and <4.0 mmol/L (72 mg/dL) decreased from 2.1% to 0.6% (P < 0.001) and from 5.4% to 2.9% (P < 0.001), respectively. Overall well-being (World Health Organization 5-item well-being index, P = 0.009), treatment satisfaction (Diabetes Treatment Satisfaction Questionnaire, P < 0.001), and hypoglycemic confidence (P < 0.001) increased, while hypoglycemic fear (Hypoglycemia Fear Survey-Worry, P = 0.016) decreased and diabetes distress tended to decrease (Problem Areas in Diabetes Scale, P = 0.06). From randomization and screening in GOLD, HbA1c was lowered by 0.45% (P < 0.001) and 0.68% (P < 0.001) after 2.3 and 2.5 years, respectively. CONCLUSIONS: The SILVER study supports beneficial long-term effects from CGM on HbA1c, hypoglycemia, treatment satisfaction, well-being, and hypoglycemic confidence in people with T1D managed with MDI.

The majority of people with type 1 diabetes and multiple daily insulin injections benefit from using continuous glucose monitoring: An analysis based on the GOLD randomized trial (GOLD-5).

AIM: To identify responders to continuous glucose monitoring (CGM) in relation to reductions in HbA1c and percentage of time spent in hypoglycaemia after initiation of CGM for individuals with type 1 diabetes treated with multiple daily insulin injections. MATERIALS AND METHODS: We analysed data from 142 participants in the GOLD randomized clinical trial. We evaluated how many lowered their HbA1c by more than 0.4% (>4.7 mmol/mol) or decreased the time spent in hypoglycaemia over 24 hours by more than 20 or 30 minutes, and which baseline variables were associated with those improvements. RESULTS: Lower reduction of HbA1c was associated with greater reduction of hypoglycaemia (r = -0.52; P < .0001). During CGM, 47% of participants lowered their HbA1c values by more than 0.4% (>4.7 mmol/mol) than with self-measurement of blood glucose, and 47% decreased the time spent in hypoglycaemia by more than 20 minutes over 24 hours. Overall, 78% either reduced their HbA1c by more than 0.4% (>4.7 mmol/mol) or the time spent in hypoglycaemia by more than 20 minutes over 24 hours, but only 14% improved both. Higher HbA1c, a lower percentage of time at less than 3.0 or 3.9 mmol/L, a lower coefficient of variation (CV) and a higher percentage of time above 13.9 mmol/L (P = .016) were associated with greater HbA1c reduction during CGM. The variables associated with a greater reduction of time in hypoglycaemia were female sex, greater time with glucose levels at less than 3.0 mmol/L, higher CV, and higher hypoglycaemia confidence as evaluated by a hypoglycaemic confidence questionnaire. CONCLUSION: The majority of people with type 1 diabetes managed by multiple daily insulin injections benefit from CGM; some experienced reduced HbA1c while others reduced the time spent in hypoglycaemia. These factors need to be considered by healthcare professionals and decision-makers for reimbursement and diabetes guidelines.

The Association Between HbA1c and Time in Hypoglycemia During CGM and Self-Monitoring of Blood Glucose in People With Type 1 Diabetes and Multiple Daily Insulin Injections: A Randomized Clinical Trial (GOLD-4).

OBJECTIVE: According to recent guidelines, individuals with type 1 diabetes should spend <4.0% of time per day with glucose levels <3.9 mmol/L (<70 mg/dL) and <1.0% per day with glucose levels <3.0 mmol/L (<54 mg/dL). RESEARCH DESIGN AND METHODS: In the GOLD randomized crossover trial, 161 individuals with type 1 diabetes treated with multiple daily insulin injections (MDI) were randomized to continuous glucose monitoring (CGM) or conventional therapy with self-monitoring of blood glucose (SMBG) and evaluated over 16 months. We estimated the association between time spent in hypoglycemia and various mean glucose and HbA1c levels. RESULTS: Time spent in hypoglycemia (<3.9 mmol/L and <3.0 mmol/L) increased significantly with lower mean HbA1c and mean glucose levels during both CGM and conventional therapy. During CGM, 24 (57.1%) individuals with HbA1c <7.5% (<58 mmol/mol) had <1.0% time spent in hypoglycemia <3.0 mmol/L and 23 (54.8%) had <4.0% time spent in hypoglycemia <3.9 mmol/L. During CGM, mean time spent in hypoglycemia for individuals with mean HbA1c 7.0% (52 mmol/mol) was estimated to be 5.4% for <3.9 mmol/L and 1.5% for <3.0 mmol/L. The corresponding values during SMBG were 9.2% and 3.5%, respectively. Individuals with mean glucose levels of 8 mmol/L spent 4.9% units more time with glucose levels <3.9 mmol/L and 2.8% units more time <3.0 mmol/L during SMBG compared with CGM. CONCLUSIONS: Reaching current targets for time in hypoglycemia while at the same time reaching HbA1c targets is challenging for patients with type 1 diabetes treated with MDI both with CGM and SMBG monitoring. However, CGM is associated with considerably less time in hypoglycemia than SMBG at a broad range of HbA1c levels and is crucial for patients with MDI treatment if they are to have a chance to approach hypoglycemia targets.

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.

HbA1c level as a risk factor for retinopathy and nephropathy in children and adults with type 1 diabetes: Swedish population based cohort study.

OBJECTIVE: To evaluate if the lowest target level for glycated haemoglobin (HbA1c) of <6.5% is associated with lower risk for retinopathy and nephropathy than less tight control in children and adults with type 1 diabetes. DESIGN: Population based cohort study. SETTING: Swedish National Diabetes Registry, 1 January 1998 to 31 December 2017. PARTICIPANTS: 10 398 children and adults with type 1 diabetes followed from diagnosis, or close thereafter, until end of 2017. MAIN OUTCOME MEASURES: Relative risk (odds ratios) for retinopathy and nephropathy for different mean levels of HbA1c. RESULTS: Mean age of participants was 14.7 years (43.4% female), mean duration of diabetes was 1.3 years, and mean HbA1c level was 8.0% (63.4 mmol/mol). After adjustment for age, sex, duration of diabetes, blood pressure, blood lipid levels, body mass index, and smoking, the odds ratio for mean HbA1c <6.5% (<48 mmol/mol) compared with 6.5-6.9% (48-52 mmol/mol) for any retinopathy (simplex or worse) was 0.77 (95% confidence interval 0.56 to 1.05, P=0.10), for preproliferative diabetic retinopathy or worse was 3.29 (0.99 to 10.96, P=0.05), for proliferative diabetic retinopathy was 2.48 (0.71 to 8.62, P=0.15), for microalbuminuria or worse was 0.98 (0.60 to 1.61, P=0.95), and for macroalbuminuria was 2.47 (0.69 to 8.87, P=0.17). Compared with HbA1c levels 6.5-6.9%, HbA1c levels 7.0-7.4% (53-57 mmol/mol) were associated with an increased risk of any retinopathy (1.31, 1.05 to 1.64, P=0.02) and microalbuminuria (1.55, 1.03 to 2.32, P=0.03). The risk for proliferative retinopathy (5.98, 2.10 to 17.06, P<0.001) and macroalbuminuria (3.43, 1.14 to 10.26, P=0.03) increased at HbA1c levels >8.6% (>70 mmol/mol). The risk for severe hypoglycaemia was increased at mean HbA1c <6.5% compared with 6.5-6.9% (relative risk 1.34, 95% confidence interval 1.09 to 1.64, P=0.005). CONCLUSIONS: Risk of retinopathy and nephropathy did not differ at HbA1c levels <6.5% but increased for severe hypoglycaemia compared with HbA1c levels 6.5-6.9%. The risk for severe complications mainly occurred at HbA1c levels >8.6%, but for milder complications was increased at HbA1c levels >7.0%.

Risk Factors for Atrial Fibrillation in People With Type 1 Diabetes: An Observational Cohort Study of 36,258 Patients From the Swedish National Diabetes Registry.

OBJECTIVE: This study identified variables associated with increased risk of atrial fibrillation in people with type 1 diabetes. RESEARCH DESIGN AND METHODS: We performed a cohort study of people with type 1 diabetes from the Swedish National Diabetes Registry followed up between 1 January 2001 and 31 December 2013. Median follow-up was 9.7 years (interquartile range 5.2-13.0). The association between potential risk factors and incident atrial fibrillation was investigated using adjusted Cox regression. To compare the impact of each risk factor, the gradient of risk per 1 SD was estimated. RESULTS: In this cohort of 36,258 patients with type 1 diabetes, 749 developed atrial fibrillation during follow-up. Older age, male sex, renal complications, increased BMI and HbA1c, coronary artery disease, heart failure, and heart valve disease increased the risk of atrial fibrillation. Age, signs of renal dysfunction with macroalbuminuria, and decreasing estimated glomerular filtration rate were associated with the highest gradient of risk for atrial fibrillation. High blood pressure, severe obesity (BMI >35 kg/m2), and elevated levels of HbA1c (>9.6%) were associated with increased risk, but no associations were found with hyperlipidemia or smoking. CONCLUSIONS: The most prominent risk factors for atrial fibrillation in people with type 1 diabetes were older age, cardiovascular comorbidities, and renal complications, while obesity, hypertension, and hyperglycemia had more modest affects.

A Randomized Clinical Trial of the Effect of Continuous Glucose Monitoring on Nocturnal Hypoglycemia, Daytime Hypoglycemia, Glycemic Variability, and Hypoglycemia Confidence in Persons with Type 1 Diabetes Treated with Multiple Daily Insulin Injections (GOLD-3).

BACKGROUND: To evaluate the effects of continuous glucose monitoring (CGM) on nocturnal and daytime hypoglycemia in persons with type 1 diabetes treated with multiple daily insulin injections (MDI); we also evaluated factors related to differences in hypoglycemia confidence in this population. METHODS: Evaluations were performed from the GOLD randomized trial, an open-label multicenter crossover randomized clinical trial (n = 161) over 69 weeks comparing CGM to self-measurement of blood glucose (SMBG) in persons with type 1 diabetes treated with MDI. Masked CGM and the hypoglycemia confidence questionnaire were used for evaluations. RESULTS: Time with nocturnal hypoglycemia, glucose levels <70 mg/dL was reduced by 48% (10.2 vs. 19.6 min each night, P < 0.001) and glucose levels <54 mg/dL by 65%. (3.1 vs. 8.9 min, P < 0.001). For the corresponding glucose cutoffs, daytime hypoglycemia was reduced by 40% (29 vs. 49 min, P < 0.001) and 54% (8 vs. 18 min., P < 0.001), respectively. Compared with SMBG, CGM use improved hypoglycemia-related confidence in social situations (P = 0.016) and confidence in more broadly avoiding serious problems due to hypoglycemia (P = 0.0020). Persons also reported greater confidence in detecting and responding to decreasing blood glucose levels (thereby avoiding hypoglycemia) during CGM use (P = 0.0033) and indicated greater conviction that they could more freely live their lives despite the risk of hypoglycemia (P = 0.022). CONCLUSION: CGM reduced time in both nocturnal and daytime hypoglycemia in persons with type 1 diabetes treated with MDI and improved hypoglycemia-related confidence, especially in social situations, thus contributing to greater well-being and quality of life. TRIAL REGISTRATION: ClinicalTrials.gov , number NCT02092051.

A Clinical Trial of the Accuracy and Treatment Experience of the Flash Glucose Monitor FreeStyle Libre in Adults with Type 1 Diabetes.

BACKGROUND: In Sweden, FreeStyle Libre a flash glucose monitoring system came onto the market in 2014 as a complement to self-monitoring of blood glucose. The aim of this study was to evaluate the accuracy and treatment experience of the FreeStyle Libre system. METHODS: Fifty-eight adults with type 1 diabetes used FreeStyle Libre for 10-14 days and measured capillary blood glucose levels with the HemoCue blood glucose measurement system at least six times a day simultaneously. RESULTS: For the entire study period, the mean absolute relative difference (MARD) was 13.2% (95% confidence interval [CI] 12.0%-14.4%). MARD was 13.6% (95% CI 12.1%-15.4%) during week 1 and 12.7% (95% CI 11.5%-13.9%) during week 2. The mean absolute difference (MAD) for the whole study period was 19.8 mg/dL (1.1 mmol/L) (95% CI 17.8-21.8 mg/dL), including 20.5 mg/dL (1.14 mmol/L) during week 1 and 19.0 mg/dL (1.05 mmol/L) during week 2. The overall correlation coefficient was 0.96. For glucose values <72, 72-180, and >180 mg/dL (<4, 4-10, and >10 mmol/L), the MARD was 20.3% (95% CI 17.7%-23.1%), 14.7% (95% CI 13.4%-16%), and 9.6% (95% CI 8.5%-10.8%), respectively, and respective MAD values were 12.3, 17.8, and 23.6 mg/dL (0.69, 0.99, and 1.31 mmol/L). Using the 10-item visual analog scale, patients rated their experience with FreeStyle Libre as generally positive, with mean values ranging from 8.22 to 9.8. CONCLUSIONS: FreeStyle Libre had a similar overall MARD as continuous blood glucose monitoring systems in earlier studies when studied in similar at-home conditions. The overall patient satisfaction was high.