The measurement error of continuous glucose monitoring sensors results from the combination of different error sources, including plasma-interstitium kinetics, calibration error and random noise. The aim of this work is to compare the measurement error components of two popular systems: Dexcom G5 Mobile (DG5M) and Eversense.
Eleven subjects were monitored in parallel using DG5M and Eversense. In the middle of sensors’ lifetime, subjects attended 6-hour clinical sessions where reference YSI measurements were collected every 15 min. Data were analysed using the methodology proposed by Facchinetti et al. (IEEE TBME 2014), which allows dissecting and quantifying the three main error components: the physiologic delay due to the plasma-interstitium kinetics (modeled as first-order linear dynamic system), the systematic error due to imperfect calibration (linear regression model), and the residual random noise (autoregressive model).
Plasma-interstitium time-constant was 12.31 [6.13-17.41] min for Eversense and 5.96 [2.64-9.16] min for DG5M. For increasing glucose concentration (range: 50-270 mg/dl), the average sensor calibration error ranged linearly from +4.92 to +1.44 mg/dl for Eversense and from -5.58 to –10.00 mg/dl for DG5M. Random noise standard deviation was 7.79 [5.25-11-86] mg/dl for Eversense and 4.01 [3.56-5.52] mg/dl for DG5M.
Eversense showed larger physiologic delay and random noise compared to DG5M. The calibration error was mostly positive (overestimation) for Eversense and mostly negative (underestimation) for DG5M over the entire glucose range. These different characteristics should be taken into account when comparing results obtained with the two sensors, e.g. for proper tuning of decision-making strategies.
Routine self-measurement of blood ketones by people with diabetes is recommended for detection of Diabetic ketoacidosis (DKA) and euglycemic DKA (euDKA) related to use of SGLT2 inhibitors, though level of access to testing equipment may limit clinical implementation of monitoring recommendations. We researched feasibility and accuracy of a novel sensing technology that continuously measures glucose and ketones simultaneously in the subcutaneous space in a pig model.
We have evaluated a spectroscopy-based, implanted continuous glucose/ketone sensor in 4 Göttingen minipigs. Sensors were implanted in the subcutaneous abdominal tissue over the study period of 2 months. Ketosis in the non-diabetic animals was induced with i.v. beta-hydroxybutyrate, sequentially to oral and i.v. glucose challenges. Accuracy of the s.c. ketone and glucose sensor measurements have been compared to blood reference values measured with the Menarini Glucomen LX and a Biosen C-line EKF Diagnostics, respectively.
In 130 paired data points, overall Mean Absolute Difference (MAD) was below 0.2mM for s.c. ketone measurement compared to i.v. ketones. Accuracy for glucose measurements had an overall Mean Absolute Relative Difference (MARD) of 6.5% in 812 paired data points, compared to laboratory reference measurements. No adverse events related to surgical procedures or implant function were observed.
Dynamics of s.c. ketone levels closely correlate to blood ketone levels, similar to s.c. glucose compared to blood glucose. Measuring ketones and glucose continuously, simultaneously and in real-time with a spectroscopy-based, implantable sensor is feasible in healthy minipigs, both within and outside the physiological range. Further research will validate clinical value of the technology in humans.
The effectiveness of CGM in patients with T2D needs to be clarified regarding the effect related to treatment regimen and glucose variability. The impact of and the relation between the different CGM-metrics to HbA1c and glucose control in patients with T1D and T2D needs to be further analysed.
The two cohorts of patients with diabetes and MDI-treatment was from the same background population of sweden and 162 patients with T1D was included from the GOLD-study and 124 patients with T2D from the MDI Liraglutide trial. Both RCTs used the same CGM-system and central laboratory. The CGM-data was collected from the run-in period of both studies when the CGM was masked and no modification of treatment was done.
The patients of the two cohorts of T1D and T2D had similar mean glucose levels, 10,9 mmol/l in the patients with T1D and 10.8 mmol/l in the patients with T2D. The time in hypoglycemia was increased, 7.19 percent of the time in the patients with T1D compared to 1.27 percent of the time in the patients with T2D. The SD of the glucose levels (4.38: SD 0.73 vs 2.99:SD 0.75) and the MAGE (10.1: SD 1.7 vs 7.04: SD 1.86) was more elevated in patients with T1D compared to the patients with T2D.
Persons with T2D and MDI-treatment have much less time in hypoglycemia and less glucose variability compared to patients with T1D with similar treatment. This should be taken into account when considering modification of glucose-lowering treatments in both populations.
Continuous and flash glucose monitoring (CGM/FGM) improve outcomes in type 1 diabetes (T1D). No data comparing CGM and FGM in patients treated with MDI (multiple daily injection) during sustained physical activity are available. The study aim was to compare efficacy and accuracy of using CGM and FGM in T1D children on MDI during sustained physical activity at sport camp.
Twenty-two children with T1D (8 boys, aged 8-14 years, mean HbA1c 51±1.4 mmol/mol) were prospectively followed up over 6 days and nights at sport camp. Participants were divided into two groups; CGM (DexcomG5®/DexcomG4®, n=12) and FGM (Abbott Free Style Libre®, n=13). Physical exertion was represented by various aerobic and anaerobic activities. Glucose control was evaluated by mean glycemia, time in range (3.9-10 mmol/l), hypoglycemia (<3.9 mmol/l) and hyperglycemia (>10 mmol/l), and by glycemic variability (standard deviation of glycaemia). The CGM/FGM accuracy was evaluated using MARD calculated from finger prick blood glucose measuring performed at least 5 times a day. ANOVA Kruskal-Wallis test was used for statistic evaluation.
The groups did not differ significantly in time in range (67% vs 61% for GCM vs FGM, respectively; p=0.20) or time in hypoglycemia (11.5% vs 15.5%, p=0.37). However, the CGM group had significantly lower mean glycemia (7.1 vs. 8.5 mmol/l, p=0.015), shorter time in hyperglycemia (17.0% vs. 30.5%, p=0.028) and lower glycemic variability (SD 3.3 vs. 4.2 mmol/l, p=0.016). CGM had greater accuracy compared to FGM (MARD 17.6% vs. 19.9%, p=0.022).
Longer time in hyperglycemia in FGM group might be explained by intermittent scanning only.
Accuracy and safety of the implantable Eversense CGM system, approved by the FDA in 2018, have been demonstrated in multiple clinical trials and real-world analyses. No glucometric outcomes by age have been reported.
Anonymized sensor glucose (SG) data from Eversense data management system (DMS) were analyzed for the first 582 patients with a 90‐day wear period. Mean SG, GMI, and percent time across glucose ranges were calculated for various age ranges from young adult to Medicare-age populations.
Among 582 patients, ~85 identified as TID, and ~1/3 reported being CGM naïve. Percent of time in various ranges demonstrated time in range (TIR, 70-180 mg/dL), time below ranges (<70 mg/dL and <54 mg/dL), and time above ranges (>180 mg/dL and >250 mg/dL) improved with age, with a 50% TIR in patients 18-24 years of age to 68% and 70% TIR in patients >60 and ≥65 years of age, respectively (Table). Mean GMI and SG also decreased with age. Hypoglycemia did not increase with age.
These data demonstrated that glycemic outcomes improve with age in Eversense CGM system users. The older, Medicare cohort did not have an increase in hypoglycemia compared to other adult groups, despite the lowest GMI and highest TIR. While glucometrics in young adults are not optimal, these results (in a small cohort) suggest that a long-term implantable sensor might offer this age group the opportunity to attain A1C results, as supported by GMI data, less than 8% with an acceptable risk of hypoglycemia.
The National Diabetes Register (NDR) launched in 1996 in Sweden includes primary and secondary care data and captures 94% of adult patients with diabetes. NDR initiated documentation of FreeStyle Libre usage in June 2016 and offers a unique opportunity to monitor the quality of diabetes care.
A cohort study using data from nationwide register from January 2014 to the 25th of June 2019 was initiated with the objective to better understand the data collected within the register and determine the effectiveness of the FreeStyle Libre system on HbA1c. The study population included all patients with diabetes (≥ 18 years old) using FreeStyle Libre recorded within the NDR. There were no exclusion criteria. Index date was the 1st record of FreeStyle Libre use. Methodology was a before/after comparison; prior period was closest HbA1c measurement within 6 months before index date and after period was HbA1c closest to 6 months after index date within Day 91 – Day 272.
During the study period, 40 793 T1 or T2 patients had at least one registration of FreeStyle Libre usage. HbA1c measurements were available within the defined prior and after period for a subset of the total patient study population who were incident FreeStyle Libre users (June 2016 to June 2019). HbA1c was significantly reduced in T1 and T2 users.
This large real-world study on a well-established diabetes register in Sweden concluded that people with T1DM and T2DM using FreeStyle Libre for between 3 to 9 months significantly reduced HbA1c.
Current CGM systems are invasive, costly and can give skin problems. We recently showed that measurement of glucose in tear fluid is possible and comparable with the results of the Freestyle Libre. We now show the results in 24 additional patients.
24 subjects with T1D, already wearing a Freestyle Libre device, were recruited from Haaglanden Diabetes Centre. In fasting state, the device was applied by the ophthalmologist. Glucose levels from the blood and interstitial fluid were recorded every 15 minutes, the current measured with tear glucose sensor was recorded continuously. The eye surface and lower eyelid and tolerability were regularly checked. A calibration algorithm to convert tear glucose to blood values was built using a neural network model and cross validated.
13 subjects were male, 11 were female. Apart from mild irritation due to probe wires exiting the eye no side effects were found and all patients could finish the 5-hour test. The MARD values for the 24-patient subset was 16.7. The MedARD was 13.3. The Abbott Freestyle Libre device generally shows an MARD of 15.7 on the first day dropping to 11.9 by day 2. Comparing this to the published data from Abbott, the NovioSense device is almost identical considering that the device was allowed only 5 hours performance time before the MARD was measured.
We have demonstrated that the NovioSense Tear glucose sensor measures blood glucose values from tears comparably to the Abbott Freestyle Libre and may become a good alternative for invasive devices.
This prospective observational study examined the performance of the Dexcom G6 CGM (G6) System in pregnant women with type 1 diabetes (T1D), type 2 diabetes (T2D), or gestational diabetes (GDM).
Participants wore up to two G6 Systems on either the abdomen, upper buttock, and/or back of the upper arm for 10 days. Participants completed one six-hour clinic session between days 3 -7 of the sensor wear period, with venous blood sampling every 30 minutes for comparison of G6 values to paired YSI comparator glucose values. Meals and snacks were consumed as desired. Performance was evaluated using the %20/20 accuracy (proportion of CGM values that were within ±20% of paired YSI values >100mg/dL or within ±20 mg/dL of YSI values ≤100 mg/dL), the mean absolute relative difference (MARD), and the proportion of matched pairs within Zone A of the Clarke Error Grid (clinical accuracy).
Of the 32 participants enrolled, twenty-one (65.6%) and eleven (34.4%) subjects were in the 2nd and 3rd trimesters, respectively. Twenty subjects (62.5%) had T1D, 9 (28.1%) had GDM, and 3 (9.4%) had T2D; 26 (81.3%) were using insulin, and 17 (53.1%) were active CGM users. The overall %20/20 accuracy, overall MARD, and clinical accuracy were 92.5%, 10.3%, and 90.2%, respectively. Accuracy was acceptable across glycemic ranges and was best on the upper arm. There were no device-related adverse events.
This study demonstrated that G6 is accurate and safe across various wear sites in pregnant women with diabetes during their 2nd or 3rd trimesters.