System accuracy evaluation of systems for point-of-care testing of blood glucose: a comparison of a patient-use system with six professional-use systems.

BACKGROUND: Point-of-care testing (POCT) of blood glucose (BG) is performed by medical personnel in clinical settings as well as by patients themselves for self-monitoring of blood glucose (SMBG) at home. We investigated if a system mainly intended for SMBG by people with diabetes, but also suitable for BG measurements by medical personnel, can achieve measurement accuracy on capillary blood samples comparable with professional-use POCT systems. METHODS: System accuracy was evaluated under standardised conditions, following the ISO standard 15197:2003. For each system (one SMBG system with three test strip lots and six professional-use systems), measurement results from capillary blood samples of 100 subjects were compared with a standardised laboratory glucose oxidase method (YSI 2300 glucose analyser). RESULTS: The seven evaluated systems showed 99.5% or 100% of the measurement results within the required system accuracy limits of ISO 15197:2003 (±0.83 mmol/L at BG concentrations <4.2 mmol/L and ±20% at BG concentrations ≥4.2 mmol/L). Applying the more stringent requirements of the revision ISO 15197:2013, the systems showed between 99% and 100% of the measurement results within the accuracy limits (±0.83 mmol/L at BG concentrations <5.55 mmol/L and ±15% at BG concentrations ≥5.55 mmol/L) and between 82% and 98% when even more restrictive limits were applied (±0.56 mmol/L and ±10%, respectively). CONCLUSIONS: Data from this study, which focused on system accuracy, suggest that SMBG systems can achieve system accuracy that is comparable with professional-use systems when measurements are performed on capillary blood samples by trained personnel in a standardised and controlled setting.

Effect of Arterialization on Venous Blood Glucose Concentrations and Implications for Observed Continuous Glucose Monitoring Accuracy.

Background: Heating of the arm and/or hand ("arterialization") is sometimes used in continuous glucose monitoring (CGM) performance studies with the reported aim of reducing differences between venous and capillary glucose concentrations. In this study, the effect of heating on venous glucose concentrations and CGM accuracy was investigated. Methods: A heating pad set to 50°C (122°F) was used with 20 participants to heat either the dominant or nondominant arm and hand. Venous and capillary samples were obtained every 15 min on both arms throughout each of three 6-h glucose challenges. CGM sensors were worn on each upper arm for each of the three visits. Results: Heating of the arm led to a median increase in venous glucose concentrations of +1.4%. No similar effect on capillary concentrations was observed. As a result, the median capillary to venous difference decreased from +5.9% in the nonheated arm to +4.2% in the heated arm. CGM accuracy observed in this study was affected by the selection of heated venous, nonheated venous, or capillary glucose concentrations as comparator data. The heating effect was more pronounced with rapidly decreasing glucose concentrations. Temperatures on the skin did not exceed 40°C (104°F). No adverse events or protocol deviations were associated with the use of the heating pad. Conclusions: Heating of the arm led to a small increase in venous glucose concentrations, but venous concentrations did not reach the level of capillary glucose concentrations. CGM accuracy observed in this study varied depending on the selected comparator data. This study was registered at the German Clinical Trials Register (DRKS00031197).

Performance Assessment of Three Continuous Glucose Monitoring Systems in Adults With Type 1 Diabetes.

BACKGROUND: FIND, the global alliance for diagnostics, identified the nonmarket-approved continuous glucose monitoring (CGM) system, FiberSense system (FBS), as a potential device for use in low- and middle-income countries. Together with two market-approved, factory-calibrated CGM systems, namely, the FreeStyle Libre 2 (FL2) and the GlucoRx AiDEX (ADX), the FBS was subjected to a clinical performance evaluation. METHODS: Thirty adult participants with type 1 diabetes were enrolled. The study was mainly conducted at home, with three in-clinic sessions conducted over the study period of 28 days. Comparator measurements were collected from capillary samples, using a high-quality blood glucose monitoring system. RESULTS: Data from 31, 70, and 78 sensors of FBS, FL2, and ADX, respectively, were included in the performance analysis. The mean absolute relative differences between CGM and comparator data for FBS, FL2, and ADX were 14.7%, 9.2%, and 21.9%, and relative biases were -2.1%, -2.5%, and -18.5%, respectively. Analysis of individual sensor accuracy revealed low, moderate, and high sensor-to-sensor variability for FBS, FL2, and ADX, respectively. Sensor survival probabilities until the end of sensor life were 47.2% for FBS (28 days), 71.3% for FL2 (14 days), and 48.4% for ADX (14 days). CONCLUSIONS: The results of FBS were encouraging enough to conduct further performance and usability evaluations in a low- and middle-income country. The results of FL2 mainly agreed with existing studies, whereas ADX showed substantial deviations from previously reported results.

Variation of Mean Absolute Relative Differences of Continuous Glucose Monitoring Systems Throughout the Day.

BACKGROUND: There is an increasing use of continuous glucose monitoring (CGM) by people with diabetes. Measurement performance is often characterized by the mean absolute relative difference (MARD). However, MARD is influenced by a number of factors and little is known about whether MARD is stable throughout the day. MATERIAL AND METHODS: A total of 24 participants with type 1 diabetes were enrolled in the study. The study was performed for seven in-patient days. Participants wore two CGM systems in parallel and performed additional frequent blood glucose (BG) measurements. On two days, glucose excursions were induced.MARD was calculated between pairs of CGM and BG values, with BG values serving as reference values. ARD values calculated from CGM-BG pairs were grouped by hour of the day. Results were analyzed separately for glucose excursion days and for regular days. RESULTS: Total MARDs for the complete study duration were 12.5% ± 3.6% and 13.2% ± 2.4% (n = 24). Throughout the day marked variability of MARD was observed (8.0% ± 1.3%-16.3% ± 2.9% (G5); 9.1% ± 1.4%-16.3% ± 5.3% (FL), up to n = 157 each). Low(est) MARD values were observed before breakfast and dinner, when subjects were in or near a fasting state. Especially after breakfast and lunch, MARD values were higher than average. CONCLUSIONS: Analytical performance of the two CGM systems, assessed by MARD, was found to vary markedly throughout the day. Activities of daily life likely triggered these variations. An increasing number of CGM users base therapeutic decisions on CGM values, and they should be aware of these variations of performance throughout the day.

Impact of Two Different Reference Measurement Procedures on Apparent System Accuracy of 18 CE-Marked Current-Generation Blood Glucose Monitoring Systems.

BACKGROUND: Measurement accuracy has been assessed for many different blood glucose monitoring systems (BGMS) over the years by different study groups. However, the choice of the comparison measurement procedure may impact the apparent level of accuracy found in such studies. MATERIALS AND METHODS: Measurement accuracy of 18 different BGMS was assessed in a setting based on ISO 15197 using two different comparison methods in parallel: a glucose oxidase (GOD)-based and a hexokinase (HK)-based method. Accuracy limits of ISO 15197 were applied, and additional analyses were performed, including bias, linear regression, and mean absolute relative difference (MARD) to assess the impact of possible differences between comparison methods on the apparent level of accuracy. RESULTS: While ≈80% of BGMS met the accuracy criteria of ISO 15197 when compared with the respective manufacturers' reference measurement procedure, only two-thirds did so against both comparison methods. The mean relative bias ranged from -6.6% to +5.7% for the analysis against the GOD-based method and from -11.1% to +1.3% for the analysis against the HK-based method, whereas MARD results ranged from 3.7% to 9.8% and from 2.3% to 10.5%, respectively. Results of regression analysis showed slopes between 0.85 and 1.08 (GOD-based method) and between 0.81 and 1.01 (HK-based method). CONCLUSIONS: The results of this study indicate that there are systematic differences between the reference measurement procedures used for BGMS calibration as well as for system accuracy assessment. Because of the potential impact on therapy of patients with diabetes resulting from these differences, further steps toward harmonization of the measurement procedures' results are important.

Choice of Continuous Glucose Monitoring Systems May Affect Metrics: Clinically Relevant Differences in Times in Ranges.

BACKGROUND: Continuous glucose monitoring-derived parameters are becoming increasingly important in the treatment of people with diabetes. The aim of this study was to assess whether these parameters, as calculated from different continuous glucose monitoring systems worn in parallel, are comparable. In addition, clinical relevance of differences was investigated. METHODS: A total of 24 subjects wore a FreeStyle Libre (A) and a Dexcom G5 (B) sensor in parallel for 7 days. Mean glucose, coefficient of variation, glucose management indicator and time spent in different glucose ranges were calculated for each system. Pairwise differences between the two different continuous glucose monitoring systems were computed for these metrics. RESULTS: On average, the two CGM systems indicated an identical time in range (67.9±10.2 vs. 67.9±11.5%) and a similar coefficient of variation; both categorized as unstable (38.1±5.9 vs. 36.0±4.8%). In contrast, the mean time spent below and above range, as well as the individual times spent below, in and above range differed substantially. System A indicated about twice the time spent below range than system B (7.7±7.2 vs. 3.8±2.7%, p=0.003). This could have led to different therapy recommendations in approximately half of the subjects. DISCUSSION: The differences in metrics found between the two continuous glucose monitoring systems may result in different therapy recommendations. In order to make adequate clinical decisions, measurement performance of CGM systems should be standardized and all available information, including the HbA1c, should be utilized.

Continuous Glucose Profiles in Healthy People With Fixed Meal Times and Under Everyday Life Conditions.

BACKGROUND: The increased use of continuous glucose monitoring (CGM) and automated insulin delivery systems raises the question about therapeutic targets for glucose profiles in people with diabetes. This study aimed to assess averaged pre- and postprandial glucose profiles in people without diabetes to provide guidance for normal glucose patterns in clinical practice. For that, number and timing of meal intake were predefined. MATERIAL AND METHODS: To assess glucose traces in 36 participants without diabetes (mean age = 23.7 ± 5.7 years), CGM was performed for up to 14 days, starting with a run-in phase (first 3 days, excluded from analysis) followed by 4 days with fixed meal times at 8:00 am, 1:00 pm, and 6:00 pm and the remaining 7 days spent under everyday life conditions. Data from two simultaneously worn CGM sensors were averaged and adjusted to capillary plasma-equivalent glucose values. Glucose data were evaluated through descriptive statistics. RESULTS: Median glucose concentration on days with fixed meal times and under everyday life conditions was 95.0 mg/dL (91.6-99.1 mg/dL, interquartile range) and 98.1 mg/dL (93.7-100.8 mg/dL), respectively. On days with fixed meal times, mean premeal glucose was 92.8 ± 9.4 mg/dL, and mean peak postmeal glucose was 143.3 ± 23.5 mg/dL. CONCLUSIONS: By defining the time of meal intake, a clear pattern of distinct postprandial glucose excursions in participants without diabetes could be demonstrated and analyzed. The presented glucose profiles might be helpful as an estimate for adequate clinical targets in people with diabetes.

Comparative Accuracy Analysis of a Real-time and an Intermittent-Scanning Continuous Glucose Monitoring System.

BACKGROUND: Currently, two different types of continuous glucose monitoring (CGM) systems are available: real time (rt) CGM systems that continuously provide glucose values and intermittent-scanning (is) CGM systems. This study compared accuracy of an rtCGM and an isCGM system when worn in parallel. METHODS: Dexcom G5 Mobile (DG5) and FreeStyle Libre (FL) were worn in parallel by 27 subjects for 14 days including two clinic sessions with induced glucose excursions. The percentage of CGM values within ±20% or ±20 mg/dL of the laboratory comparison method results (YSI 2300 STAT Plus, YSI Inc., Yellow Springs, OH, United States; glucose oxidase based) or blood glucose meter values and mean absolute relative difference (MARD) were calculated. Consensus error grid and continuous glucose error grid analyses were performed to assess clinical accuracy. RESULTS: Both systems displayed clinically accurate readings. Compared to laboratory comparison method results during clinic sessions, DG5 had 91.5% of values within ±20%/20 mg/dL and a MARD of 9.5%; FL had 82.5% of scanned values within ±20%/20 mg/dL and an MARD of 13.6%. Both systems showed a lower level of performance during the home phase and when using the blood glucose meter as reference. CONCLUSION: The two systems tested in this study represent two different principles of CGM. DG5 generally provided higher accordance with laboratory comparison method results than FL.

Skin Reaction Report Form: Development and Design of a Standardized Report Form for Skin Reactions Due to Medical Devices for Diabetes Management.

BACKGROUND: Skin reactions due to medical devices for diabetes management have become a common problem in diabetes technology. There is a varying degree in how detailed skin reactions are described in scientific literature and diabetes practice, and no uniform structured documentation is given. Whereas most articles only describe findings, some others already document final diagnoses, such as contact dermatitis. Furthermore, inconsistent wordings for comparable issues were used. METHODS: A more detailed and standardized documentation, possibly facilitated by a generally accepted guideline for structured descriptions, of skin reactions could be helpful to enable better differentiations between the described skin reactions. Therefore, a report form to assess skin reactions due to medical devices in diabetes therapy was developed and will be presented in this article. RESULTS: The one-page report form is divided into four categories and a separate instruction paper. Beside general information the form includes the location, size, severity and duration of skin appearances, the grading of itching, and suspected diagnoses. CONCLUSION: A consistent use of the form in daily practice and clinical trials could facilitate a fast and standardized documentation and help to evaluate the occurrence and severity of different skin reactions due to medical devices in diabetes management.

Time in Specific Glucose Ranges, Glucose Management Indicator, and Glycemic Variability: Impact of Continuous Glucose Monitoring (CGM) System Model and Sensor on CGM Metrics.

BACKGROUND: International consensus recommends a set of continuous glucose monitoring (CGM) metrics to assess quality of diabetes therapy. The impact of individual CGM sensors on these metrics has not been thoroughly studied yet. This post hoc analysis aimed at comparing time in specific glucose ranges, coefficient of variation (CV) of glucose concentrations, and glucose management indicator (GMI) between different CGM systems and different sensors of the same system. METHOD: A total of 20 subjects each wore two Dexcom G5 (G5) sensors and two FreeStyle Libre (FL) sensors for 14 days in parallel. Times in ranges, GMI, and CV were calculated for each 14-day sensor experiment, with up to four sensor experiments per subject. Pairwise differences between different sensors of the same CGM system as well as between sensors of different CGM system were calculated for these metrics. RESULTS: Pairwise differences between sensors of the same model showed larger differences and larger variability for FL than for G5, with some subjects showing considerable differences between the two sensors. When pairwise differences between sensors of different CGM models were calculated, substantial differences were found in some subjects (75th percentiles of differences of time spent <70 mg/dL: 5.0%, time spent >180 mg/dL: 9.2%, and GMI: 0.42%). CONCLUSION: Relevant differences in CGM metrics between different models of CGM systems, and between different sensors of the same model, worn by the same study subjects were found. Such differences should be taken into consideration when these metrics are used in the treatment of diabetes.

Proof of Concept for a New Raman-Based Prototype for Noninvasive Glucose Monitoring.

BACKGROUND: Noninvasive glucose monitoring (NIGM) in diabetes is a long-sought-for technology. Among the many attempts Raman spectroscopy was considered as the most promising because of its glucose specificity. In this study, a recently developed prototype (GlucoBeam, RSP Systems A/S, Denmark) was tested in patients with type 1 diabetes to establish calibration models and to demonstrate proof of concept for this device in real use. METHODS: The NIGM table-top prototype was used by 15 adult subjects with type 1 diabetes for up to 25 days at home and in an in-clinic setting. On each day, the subjects performed at least six measurement units throughout the day. Each measurement unit comprised two capillary blood glucose measurements, two scans with an intermittent scanning continuous glucose monitoring (CGM) system, and two NIGM measurements using the thenar of the subject's right hand. RESULTS: Calibration models were established using data from 19 to 24 days. The remaining 3-8 days were used for independent validation. The mean absolute relative difference of the NIGM prototype was 23.6% ± 13.1% for the outpatient days, 28.2% ± 9.9% for the in-clinic day, and 26.3% ± 10.8% for the complete study. Consensus error grid analysis of the NIGM prototype for the complete study showed 93.6% of values in clinically acceptable zones A and B. CONCLUSIONS: This proof of concept study demonstrated a practical realization of a Raman-based NIGM device, with performance on par with early-generation CGM systems. The findings will assist in further performance improvements of the device.

System accuracy evaluation of 18 CE-marked current-generation blood glucose monitoring systems based on EN ISO 15197:2015.

OBJECTIVE: Accuracy of 18 current-generation blood glucose monitoring systems (BGMS) available in Europe was evaluated applying criteria adapted from EN ISO 15197:2015 with one reagent system lot. BGMS were selected based on market research data. RESEARCH DESIGN AND METHODS: The BGMS ABRA, Accu-Chek Guide, AURUM, CareSens Dual, CERA-CHEK 1CODE, ContourNext One, eBsensor, FreeStyle Freedom Lite, GL50 evo, GlucoCheck GOLD, GlucoMen areo 2K, GluNEO, MyStar DoseCoach, OneTouch Verio Flex, Pic GlucoTest, Rightest GM700S, TRUEyou, and WaveSense JAZZ Wireless were tested using capillary blood from 100 different subjects and assessing the percentage of results within ±15 mg/dL (0.83 mmol/L) or 15% of comparison method results for BG concentrations below or above 100 mg/dL (5.55 mmol/L), respectively. In addition, the minimal deviation from comparison method results within which ≥95% of results of the respective BGMS were found was calculated. RESULTS: In total, 14 BGMS had ≥95% of results within ±15 mg/dL (0.83 mmol/L) or ±15% and 3 BGMS had ≥95% of results within ±10 mg/dL (0.55 mmol/L) or ±10% of the results obtained with the comparison method. The smallest deviation from comparison method results within which ≥95% of results were found was ±7.7 mg/dL (0.43 mmol/L) or ±7.7%; the highest deviation was ±19.7 mg/dL (1.09 mmol/L) or ±19.7%. CONCLUSIONS: This accuracy evaluation shows that not all CE-labeled BGMS fulfill accuracy requirements of ISO 15197 reliably and that there is considerable variation even among BGMS fulfilling these criteria. This safety-related information should be taken into account by patients and healthcare professionals when making therapy decisions. TRIAL REGISTRATION NUMBER: NCT03737188.

Performance and Usability of Three Systems for Continuous Glucose Monitoring in Direct Comparison.

BACKGROUND: To be able to compare continuous glucose monitoring (CGM) systems, they have to be worn in parallel by the same subjects. This study evaluated the performance and usability of three different CGM systems in direct comparison. METHOD: In this open, prospective study at two sites, 54 patients with diabetes wore three CGM systems each (Dexcom G5™ Mobile CGM system [DG5], Guardian™ Connect system [GC], and a Roche CGM system [RCGM]) in parallel for 6 or 7 days in a mixed inpatient and outpatient setting. Capillary comparison measurements were performed using a self-monitoring of blood glucose (SMBG) system. During study site visits, glucose excursions were induced. Performance of the systems was evaluated by calculating mean absolute relative differences (MARD, calculated as absolute differences for glucose concentrations <100 mg/dL and as relative differences for glucose concentrations ≥100 mg/dL), and mean relative differences (MRD, bias) between CGM and SMBG results. In addition, usability of the systems was assessed. RESULTS: Overall MARD was 10.1 ± 2.1 for DG5, 11.5 ± 4.2 for GC, and 11.9 ± 5.6 for RCGM. Performance improved in all systems after the first day of use. All systems showed >99% of values within zones A and B of the consensus error grid. Overall, all CGM systems showed a small negative bias compared to SMBG. Usability of the systems differed regarding patch adhesion rate, failure rate, and patient rating. Most patients preferred GC, but in general all systems were rated positively. CONCLUSION: All three CGM systems showed similar overall accuracy in this direct comparison, but small differences were observed with regard to specific glucose ranges and usability aspects.

Prediction Quality of Glucose Trend Indicators in Two Continuous Tissue Glucose Monitoring Systems.

BACKGROUND: Continuous interstitial glucose monitoring (CGM) systems often provide glucose trend indicators (e.g., arrows) in addition to current glucose values. These indicators are recommended to be used in therapeutic decisions, because they are ascribed predictive qualities by CGM system manufacturers and expert committees. This study assessed how reliably trend indicators match future glucose change, because such information is missing. METHODS: In a clinical trial, two different CGM systems were used by 20 participants, with two sensors of each system per patient. Participants used the systems for 14 days with three study site visits (48 h each). During study site visits, glucose trend indicators, as displayed by the CGM systems, were recorded at least once per hour during daytime and once at night in a diary. In addition, CGM data were downloaded from the devices. Trend indicators were compared with glucose change calculated from CGM data >30 min after recording the trend indicator. RESULTS: Approximately 60% of trend indicators matched the glucose change calculated from CGM data. More than 10% of trend indicators differed by at least two trend indicator categories. Focusing on trend indicators recorded around carbohydrate (CHO) intake and insulin deliveries resulted in approximately half of trend indicators matching the calculated glucose change. CONCLUSIONS: Trend indicators do not always match future glucose change, especially within the first few hours after CHO intake and insulin deliveries. Manufacturers' labeling and recommendations should reflect this, so that CGM users can make informed decisions.

Measurement Performance of Two Continuous Tissue Glucose Monitoring Systems Intended for Replacement of Blood Glucose Monitoring.

BACKGROUND: Currently, two systems for continuous tissue glucose monitoring (CGM) (Dexcom® G5 [DG5] and FreeStyle Libre [FL]) are intended to replace blood glucose monitoring (BGM) and, according to manufacturer labeling, are distributed as such in some jurisdictions, including the United States and the European Union. METHODS: The measurement performance of these two systems in comparison with a BGM system was analyzed in a 14-day study with 20 participants comprising study site visits, which included phases of induced rapid glucose changes, and home use phases. Performance analysis was mainly based on deviations between CGM readings and BGM results. Sensor-to-sensor precision was also analyzed. RESULTS: Approximately 25% of DG5 and FL results showed differences from BGM results exceeding 15 mg/dL or 15% (at glucose concentration below or above 100 mg/dL, respectively) at times of therapeutic decisions, and ∼5% of differences exceeded 30 mg/dL or 30%. Performance was different depending on the setting (study site visits, home use phases, and phases of induced rapid glucose changes). In consensus error grid (CEG) analysis, both systems showed >99.5% of results within the clinically acceptable zones A and B. CONCLUSIONS: In this study, both systems showed deviations from blood glucose (BG) measurements, the current standard approach in diabetes therapy. Although a large percentage of results was found in CEG zones A and B, for approximately one in four therapeutic decisions, CGM and BG readings differed by at least 15 mg/dL or 15%. Such deviations should be taken into account when using CGM systems.

Flash Glucose Monitoring: Differences Between Intermittently Scanned and Continuously Stored Data.

The flash glucose monitoring system FreeStyle Libre (Abbott Diabetes Care Ltd., Witney, UK) measures interstitial glucose concentrations and continuously stores measurement values every 15 minutes. To obtain a current glucose reading, users have to scan the sensor with the reader. In a clinical trial, 5% of the scanned data showed relative differences of more than ±10% compared with continuously stored data points (median -0.5%). Such differences might impact results of studies using this system. It should be indicated whether scanned or continuously stored data were used for analyses. Health care professionals might have to differentiate between data reports from clinical software and the scanned data their patients are provided with. Additional information on these differences and their potential impact on therapeutic decisions would be helpful.

Acceptability of Implantable Continuous Glucose Monitoring Sensor.

BACKGROUND: Real-time continuous glucose monitoring is associated with significant benefits for diabetes management. Implantable sensors could overcome some challenges reportedly associated with device visibility, psychosocial functioning and sensor durability. METHODS: A psychosocial assessment was conducted to determine acceptability and impact of an implantable continuous glucose monitoring (CGM) sensor as part of the PRECISE trial. Questionnaires were administered to participants comprising the Diabetes Distress Scale, the CGM impact scale, and bespoke device satisfaction. RESULTS: Fifty-one participants across the United Kingdom (n = 10) and Germany (n = 41) completed the questionnaires. Of these, 90% had T1D, 50% followed an insulin pump therapy regimen, and 45% of the participants were previous CGM users. CGM Impact Scale results show 86% (n = 44) of participants reported feeling better (14% neutral) about their diabetes control with 90% CGM naïve participants and 81% previous CGM users reporting increased confidence about their diabetes management. Furthermore, 73% (n = 37) felt more safe (27% neutral) while sleeping and 78% (n = 39) more confident (22% neutral) about avoiding serious hypoglycemia. Responses correspond with an average improvement in HbA1c from 7.51 to 7.05 ( P < .0001) over the 90 days use of the CGM. Overall, the system was rated highly on ease of use, convenience and comfort. 84% would choose to be inserted again with 93% of CGM naïve participants (86% previous CGM users) reporting minimized burden of diabetes. CONCLUSIONS: Implantable CGM devices are acceptable to users and are evaluated favorably. The considerable majority of participants (93% of first time users and 77% previous CGM users) would like to continue using the system to help manage their diabetes more effectively.

Improved Glycemic Control in a Patient Group Performing 7-Point Profile Self-Monitoring of Blood Glucose and Intensive Data Documentation: An Open-Label, Multicenter, Observational Study.

INTRODUCTION: Regular self-monitoring of blood glucose (SMBG) is recommended as an integral part of therapy for all patients with diabetes treated with insulin. In the current study, the effects on glycemic control of taking 7-point SMBG profiles and using a diabetes management system (DMA) on a smartphone were investigated. METHODS: In a 12-week, open-label, multicenter, observational study, 51 patients [26 with type 1 diabetes mellitus (T1DM) and 25 with type 2 diabetes mellitus (T2DM)] were instructed to perform SMBG at least seven times a day using DMA combined with the iBGStar ® SMBG system. HbA1c was measured at regular visits to the study sites. Patients reviewed and managed their data as well as their treatment on their own and there were no further assistance or treatment recommendations. Adverse events (AEs) were recorded throughout. RESULTS: Overall, mean (SD) change from baseline in HbA1c at week 12 was -0.46 (0.57)% [-5 (6) mmol/mol (p < 0.0001)]. The change in HbA1c was observed in patients with T1DM [-0.27 (0.45)% (-3 [5] mmol/mol; p = 0.0063)] and T2DM [-0.65 (0.62)% (-7 [7] mmol/mol; p < 0.0001)]. The change in HbA1c was not correlated with an increased number of hypoglycemic events (blood glucose less than 55 mg/dL). The majority of AEs were symptomatic hypoglycemic events (42 events; nine patients). CONCLUSIONS: Glycemic control can be improved, without receiving any recommendations or advice on insulin dose, by performing daily 7-point SMBG profiles and using electronic documentation with a smartphone app. These results must be confirmed in a larger controlled trial, but they already strengthen the importance of structured SMBG in diabetes therapy. FUNDING: Sanofi.

Accuracy and Longevity of an Implantable Continuous Glucose Sensor in the PRECISE Study: A 180-Day, Prospective, Multicenter, Pivotal Trial.

OBJECTIVE: It is known that continuous glucose monitoring (CGM) systems can lower mean glucose compared with episodic self-monitoring of blood glucose. Implantable CGM systems may provide additional benefits. RESEARCH DESIGN AND METHODS: We studied the Eversense (Senseonics Inc.) implantable CGM sensor in 71 participants aged 18 years and older with type 1 and type 2 diabetes in a 180-day multinational, multicenter pivotal trial. Participants used the CGM system at home and in the clinic. CGM accuracy was assessed during eight in-clinic visits with the mean absolute relative difference (MARD) for venous reference glucose values >4.2 mmol/L as the primary end point. Secondary end points included Clarke Error Grid Analysis and alarm performance. The primary safety outcome was device-related serious adverse events. This trial is registered with ClinicalTrials.gov, number NCT02154126. RESULTS: The MARD value against reference glucose values >4.2 mmol/L was 11.1% (95% CI 10.5, 11.7). Clarke Error Grid Analysis showed 99.2% of samples in the clinically acceptable error zones A and B. Eighty-one percent of hypoglycemic events were detected by the CGM system within 30 min. No device-related serious adverse events occurred during the study. CONCLUSIONS: Our results indicate the safety and accuracy of this new type of implantable CGM system and support it as an alternative for transcutaneous CGM.