Accuracy of FreeStyle Libre in Adults with Type 1 Diabetes: The Effect of Sensor Age

Continuous glucose monitoring and intrapersonal variability in fasting glucose

Plasma fasting glucose (FG) levels play a pivotal role in the diagnosis of prediabetes and diabetes worldwide. Here we investigated FG values using continuous glucose monitoring (CGM) devices in nondiabetic adults aged 40-70 years. FG was measured during 59,565 morning windows of 8,315 individuals (7.16 ± 3.17 days per participant). Mean FG was 96.2 ± 12.87 mg dl-1, rising by 0.234 mg dl-1 per year with age. Intraperson, day-to-day variability expressed as FG standard deviation was 7.52 ± 4.31 mg dl-1. As there are currently no CGM-based criteria for diabetes diagnosis, we analyzed the potential implications of this variability on the classification of glycemic status based on current plasma FG-based diagnostic guidelines. Among 5,328 individuals who would have been considered to have normal FG based on the first FG measurement, 40% and 3% would have been reclassified as having glucose in the prediabetes and diabetes ranges, respectively, based on sequential measurements throughout the study. Finally, we revealed associations between mean FG and various clinical measures. Our findings suggest that careful consideration is necessary when interpreting FG as substantial intraperson variability exists and highlight the potential impact of using CGM data to refine glycemic status assessment.

Continuous Glucose Monitoring Alarms in Adults with Type 1 Diabetes: User Characteristics and the Impact of Hypoglycemia and Hyperglycemia Alarm Thresholds on Glycemic Control

Background: Few studies have evaluated the implications of the alarm thresholds of continuous glucose monitoring (CGM) systems for individuals with diabetes. The present study aimed to investigate the influence of hypoglycemia and hyperglycemia alarm thresholds on glycemic control in adults with type 1 diabetes (T1DM) and the characteristics of patients who use these alarms more frequently. Methods: This observational cross-sectional study included 873 users of the FreeStyle Libre 2 system (501 men, median age 48 years, range 18-90 years) with T1DM from a single center. We investigated the role of demographic and metabolic factors on the use of alarms and the impact of hypoglycemia and hyperglycemia alarms and their thresholds on glycemic control. Results: Alarm users were older than nonusers (median age 49 vs. 43 years, respectively; P < 0.001). The hypoglycemia alarms were set by 76.1% of women and by 69.1% of men (P = 0.022). The hypoglycemia alarms reduced hypoglycemia features and glucose variability, although at the expense of shorter time in range. The higher the hypoglycemia alarm threshold, the greater these effects. The hyperglycemia alarms were effective in reducing hyperglycemia and lowering the glucose management indicator, although at the expense of a greater tendency to hypoglycemia. The lower the hyperglycemia alarm threshold, the greater these effects. Conclusions: CGM alarms contribute to better glycemic control. However, hypoglycemia and hyperglycemia alarms have advantages and disadvantages. Adults with T1DM should explore, under medical supervision, which alarm thresholds will best help them achieve their individual glycemic goals.

Accuracy of continuous glucose monitoring during exercise-related hypoglycemia in individuals with type 1 diabetes

Background

Hypoglycemia is common in individuals with type 1 diabetes, especially during exercise. We investigated the accuracy of two different continuous glucose monitoring systems during exercise-related hypoglycemia in an experimental setting.

Materials and methods

Fifteen individuals with type 1 diabetes participated in two separate euglycemic-hypoglycemic clamp days (Clamp-exercise and Clamp-rest) including five phases: 1) baseline euglycemia, 2) plasma glucose (PG) decline ± exercise, 3) 15-minute hypoglycemia ± exercise, 4) 45-minute hypoglycemia, and 5) recovery euglycemia. Interstitial PG levels were measured every five minutes, using Dexcom G6 (DG6) and FreeStyle Libre 1 (FSL1). Yellow Springs Instruments 2900 was used as PG reference method, enabling mean absolute relative difference (MARD) assessment for each phase and Clarke error grid analysis for each day.

Results

Exercise had a negative effect on FSL1 accuracy in phase 2 and 3 compared to rest (ΔMARD = +5.3 percentage points [(95% CI): 1.6, 9.1] and +13.5 percentage points [6.4, 20.5], respectively). In contrast, exercise had a positive effect on DG6 accuracy during phase 2 and 4 compared to rest (ΔMARD = -6.2 percentage points [-11.2, -1.2] and -8.4 percentage points [-12.4, -4.3], respectively). Clarke error grid analysis showed a decrease in clinically acceptable treatment decisions during Clamp-exercise for FSL1 while a contrary increase was observed for DG6.

Conclusion

Physical exercise had clinically relevant impact on the accuracy of the investigated continuous glucose monitoring systems and their ability to accurately detect hypoglycemia.

T1DiabetesGranada: a longitudinal multi-modal dataset of type 1 diabetes mellitus

Type 1 diabetes mellitus (T1D) patients face daily difficulties in keeping their blood glucose levels within appropriate ranges. Several techniques and devices, such as flash glucose meters, have been developed to help T1D patients improve their quality of life. Most recently, the data collected via these devices is being used to train advanced artificial intelligence models to characterize the evolution of the disease and support its management. Data scarcity is the main challenge for generating these models, as most works use private or artificially generated datasets. For this reason, this work presents T1DiabetesGranada, an open under specific permission longitudinal dataset that not only provides continuous glucose levels, but also patient demographic and clinical information. The dataset includes 257 780 days of measurements spanning four years from 736 T1D patients from the province of Granada, Spain. This dataset advances beyond the state of the art as one the longest and largest open datasets of continuous glucose measurements, thus boosting the development of new artificial intelligence models for glucose level characterization and prediction.

Glucose pattern in children with classical congenital adrenal hyperplasia: evidence from continuous glucose monitoring

BACKGROUND

While the risk for hypoglycemia during acute illness is well described in children with classical congenital adrenal hyperplasia (CAH), there is little evidence for the prevalence of asymptomatic hypoglycemia and the daily glucose patterns in CAH. Herein, we explored the daytime glucose profile of children with classical CAH.

METHODS

We conducted an observational study in 11 children (6 female; age 3.1 years [1.4, 5.1]; body mass index 17.3 kg/m2 [15.6, 17.9]) with a genetic diagnosis of classical CAH receiving hydrocortisone and fludrocortisone replacement therapy. Participants underwent 2 14-day continuous glucose monitoring (CGM) sessions and an inpatient 24 h series cortisol and adrenocorticotropic hormone (ACTH) measures. Data were analyzed for 3 daytime lags (7 Am-4 Pm, 4 Pm-10pm, 10 Pm-7 Am) corresponding to the hydrocortisone dosing period with cortisol and ACTH measured before the hydrocortisone dose.

RESULTS

Eleven participants completed at least 1 CGM session, and 7 out of 11 underwent both the CGM session and the cortisol/ACTH serial measures. In the whole cohort, the percentage of time of sensor glucose values <70 mg/dL was higher during the 10 Pm-7 Am and the 7 Am-4 Pm time slots than in the late afternoon period (17% [7, 54] and 15% [6.8, 24] vs 2% [1.1, 16.7] during the periods 7 Am-4 Pm and 4 Pm-10 Pm, respectively [P = .006 and P = .003]). Nighttime hypoglycemia was mostly spent below the 65 mg/dL (10.9% [4.1, 34]). The glycemic pattern paralleled the nadir of daily cortisol at 7 Am (10.3±4.4 μg/dL). A greater percentage of time in hypoglycemia was associated with lower cortisol concentration at 7 Am and 10 Pm (P < .001 and P = .005).

CONCLUSIONS

Continuous glucose monitoring demonstrated a disrupted daily glucose pattern in children with CAH, paralleled by a lower cortisol concentration.

CLINICALTRIALS.GOV REGISTRATION

NCT04322435.

Food & You: A digital cohort on personalized nutrition

Nutrition is a key contributor to health. Recently, several studies have identified associations between factors such as microbiota composition and health-related responses to dietary intake, raising the potential of personalized nutritional recommendations. To further our understanding of personalized nutrition, detailed individual data must be collected from participants in their day-to-day lives. However, this is challenging in conventional studies that require clinical measurements and site visits. So-called digital or remote cohorts allow in situ data collection on a daily basis through mobile applications, online services, and wearable sensors, but they raise questions about study retention and data quality. "Food & You" is a personalized nutrition study implemented as a digital cohort in which participants track food intake, physical activity, gut microbiota, glycemia, and other data for two to four weeks. Here, we describe the study protocol, report on study completion rates, and describe the collected data, focusing on assessing their quality and reliability. Overall, the study collected data from over 1000 participants, including high-resolution data of nutritional intake of more than 46 million kcal collected from 315,126 dishes over 23,335 participant days, 1,470,030 blood glucose measurements, 49,110 survey responses, and 1,024 stool samples for gut microbiota analysis. Retention was high, with over 60% of the enrolled participants completing the study. Various data quality assessment efforts suggest the captured high-resolution nutritional data accurately reflect individual diet patterns, paving the way for digital cohorts as a typical study design for personalized nutrition.

Clinical Performance Evaluation of Continuous Glucose Monitoring Systems: A Scoping Review and Recommendations for Reporting

The use of different approaches for design and results presentation of studies for the clinical performance evaluation of continuous glucose monitoring (CGM) systems has long been recognized as a major challenge in comparing their results. However, a comprehensive characterization of the variability in study designs is currently unavailable. This article presents a scoping review of clinical CGM performance evaluations published between 2002 and 2022. Specifically, this review quantifies the prevalence of numerous options associated with various aspects of study design, including subject population, comparator (reference) method selection, testing procedures, and statistical accuracy evaluation. We found that there is a large variability in nearly all of those aspects and, in particular, in the characteristics of the comparator measurements. Furthermore, these characteristics as well as other crucial aspects of study design are often not reported in sufficient detail to allow an informed interpretation of study results. We therefore provide recommendations for reporting the general study design, CGM system use, comparator measurement approach, testing procedures, and data analysis/statistical performance evaluation. Additionally, this review aims to serve as a foundation for the development of a standardized CGM performance evaluation procedure, thereby supporting the goals and objectives of the Working Group on CGM established by the Scientific Division of the International Federation of Clinical Chemistry and Laboratory Medicine.

Safety and Functional Integrity of Continuous Glucose Monitoring Sensors When Used During Radiologic Procedures Under High Exposure Conditions

BACKGROUND

We investigated wearable components of the Abbott Diabetes Care FreeStyle Libre® (continuous glucose monitoring [CGM 1), FreeStyle Libre® 2 (CGM 2), and FreeStyle Libre® 3 (CGM 3) systems in simulated diagnostic radiologic procedures.

METHODS

Sensors were loaded with simulated glucose data and exposed to X-ray scanning, computed tomography (CT), and magnetic resonance imaging (MRI) to simulate radiotherapeutic procedures. The exposure settings were representative of maximum in clinical settings. After the simulations, bench tests were used to assess data integrity and responsiveness of sensors to various concentrations of aqueous glucose.

RESULTS

All sensors passed all acceptance criteria following each session of X-ray, CT, and MRI exposures. During the 3 T MRI simulation, the displacement forces for the CGM 1, CGM 2, and CGM 3 sensors were 0.132, 0.109, and 0.063 N, respectively, which are more than 100× smaller than the force of 15.97 N required to dislodge the sensor from the body. Data stored in the sensors prior to the exposures remained intact.

CONCLUSION

The sensors maintained functionality following a series of high exposure conditions in both X-ray and CT scanning systems, and the sensors were easily visible and identifiable when scanned using clinically relevant scanning parameters. Therefore, patients can continue to wear and use their sensors during and after imaging. The nonclinical MRI testing demonstrated that the sensors can be worn under the specified MRI conditions.

Effectiveness of Using the FreeStyle Libre® System for Monitoring Blood Glucose during the COVID-19 Pandemic in Diabetic Individuals: Systematic Review

BACKGROUND

Artificial Intelligence (AI) is an area of computer science/engineering that is aiming to spread technological systems. The COVID-19 pandemic caused economic and public health turbulence around the world. Among the many possibilities for using AI in the medical field is FreeStyle Libre^® (FSL), which uses a disposable sensor inserted into the user's arm, and a touchscreen device/reader is used to scan and retrieve other continuous monitoring of glucose (CMG) readings. The aim of this systematic review is to summarize the effectiveness of FSL blood glucose monitoring during the COVID-19 pandemic.

METHODS

This systematic review was carried out in accordance with the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) and was registered in the international prospective register of systematic reviews (PROSPERO: CRD42022340562). The inclusion criteria considered studies involving the use of the FSL device during the COVID-19 pandemic and published in English. No publication date restrictions were set. The exclusion criteria were abstracts, systematic reviews, studies with patients with other diseases, monitoring with other equipment, patients with COVID-19, and bariatrics patients. Seven databases were searched (PubMed, Scopus, Embase, Web of Science, Scielo, PEDro and Cochrane Library). The ACROBAT-NRSI tool (A Cochrane Risk of Bias Assessment Tool for Non-Randomized Studies) was used to evaluate the risk of bias in the selected articles.

RESULTS

A total of 113 articles were found. Sixty-four were excluded because they were duplicates, 39 were excluded after reading the titles and abstracts, and twenty articles were considered for full reading. Of the 10 articles analyzed, four articles were excluded because they did not meet the inclusion criteria. Thus, six articles were included in the current systematic review. It was observed that among the selected articles, only two were classified as having serious risk of bias. It was shown that FSL had a positive impact on glycemic control and on reducing the number of individuals with hypoglycemia.

CONCLUSION

The findings suggest that the implementation of FSL during COVID-19 confinement in this population can be confidently stated to have been effective in diabetes mellitus patients.

CGMap: Characterizing continuous glucose monitor data in thousands of non-diabetic individuals

Despite its rising prevalence, diabetes diagnosis still relies on measures from blood tests. Technological advances in continuous glucose monitoring (CGM) devices introduce a potential tool to expand our understanding of glucose control and variability in people with and without diabetes. Yet CGM data have not been characterized in large-scale healthy cohorts, creating a lack of reference for CGM data research. Here we present CGMap, a characterization of CGM data collected from over 7,000 non-diabetic individuals, aged 40-70 years, between 2019 and 2022. We provide reference values of key CGM-derived clinical measures that can serve as a tool for future CGM research. We further explored the relationship between CGM-derived measures and diabetes-related clinical parameters, uncovering several significant relationships, including associations of mean blood glucose with measures from fundus imaging and sleep monitoring. These findings offer novel research directions for understanding the influence of glucose levels on various aspects of human health.

Switching to an advanced hybrid closed-loop system in real-world practice improves hypoglycemia awareness and metabolic control in adults with type 1 diabetes, particularly in those with impaired perception of hypoglycemia symptoms

AIMS

To evaluate the efficacy of an advance closed-loop (AHCL) system in restoring awareness of hypoglycemia in patients with type 1 diabetes (T1D).

METHODS

We conducted a prospective study including 46 subjects with T1D flash glucose monitoring (FGM) or continuous glucose monitoring (CGM) switching to a Minimed 780G® system. Patients were classified in three groups according to the therapy used before switching to Minimed® 780G: multiple dose insulin (MDI) therapy + FGM (n = 6), continuous subcutaneous insulin infusion + FGM (n = 21), and sensor-augmented pump with predictive low-glucose suspend (n = 19). FGM/CGM data were analyzed at baseline, after 2 and 6 months on AHCL. Clarke's score of hypoglycemia awareness was compared at baseline and 6 months recordings. We also compared the efficacy of the AHCL system in improving A_1c among patients with appropriate perception of symptoms of hypoglycemia compared to those presenting with impaired awareness of hypoglycemia (IAH).

RESULTS

Participants had a mean age of 37 ± 15 and a diabetes duration of 20 ± 10 years. At baseline, 12 patients (27%) showed IAH as defined by a Clarke's score ≥ 3. Patients with IAH were older and had lower estimated glomerular filtration rate (eGFR) compared with those who did not have IAH; with no differences in baseline CGM metrics or A_1c. An overall decrease in A_1c was observed after 6 months on AHCL system (from 6.9 ± 0.5% to 6.7 ± 0.6%, P < 0.001), regardless of prior insulin therapy. The improvement in metabolic control was greater in patients with IAH, showing a reduction in A_1c from 6.9 ± 0.5 to 6.4 ± 0.4% vs 6.9 ± 0.5 to 6.8 ± 0.6% (P = 0.003), showing a parallel increase in total daily boluses of insulin and automatic bolus correction administered by the AHCL system. In patients with IAH Clarke's score decreased from 3.6 ± 0.8 at baseline to 1.9 ± 1.6 after 6 months (P < 0.001). After 6 months on AHCL system, only 3 patients (7%) presented with a Clarke's score ≥ 3, resulting in an absolute risk reduction of 20% (95% confidence interval: 7-32) of having IAH.

CONCLUSIONS

Switching from any type of insulin administration to AHCL system improves restoration of hypoglycemia awareness and metabolic control in patients with T1D, particularly in adults with impaired perception of hypoglycemia symptoms.

TRIAL REGISTRATION

ClinicalTrial.gov ID NCT04900636.

[Smart skin-A new technology in the area of digital dermatology]

Numerous developments in the field of digital medicine have helped to improve the treatment and management of diseases. Smart skin is one promising technology. Through sensors that are attached to the skin, a wide variety of physiological parameters can be measured, e.g., concentration of hormones, presence of inflammation markers, or the glucose level. As this technology can be applied to different parts of the body, information about various organ systems can be obtained. In the case of diabetes, research is already very advanced due to its endemic relevance and the need for long-term treatment. For example, invasive blood measurement can be replaced by implantable tattoos which react to a change in the glucose level by changing its color. In the context of type 1 diabetes, a closed-loop control circuit can be created with so-called microneedling, which results in independent insulin delivery when blood glucose levels are too high. Moreover, there are also smart skin innovations for the management of chronic wounds. With the continuous measurement of physiological indicators such as pH, temperature, or bacterial milieu, the condition of the wound can be observed. The basic principles of the smart skin technology can be transferred into many areas in the field of dermatological care and, therefore, also represent a relevant aspect for dermatologists in the care of their patients. Continuous developments in the field of smart skin technologies show high potential for further research in a wide range of specialties with the aim to facilitate everyday clinical life for patients and physicians.

Discordance between postprandial plasma glucose measurement and continuous glucose monitoring

BACKGROUND

There has been growing interest in studying postprandial glucose responses using continuous glucose monitoring (CGM) in nondiabetic individuals. Accurate measurement of glucose responses to meals can facilitate applications such as precision nutrition and early detection of diabetes.

OBJECTIVES

We aimed to quantify the discordance between simultaneous postprandial glucose measurements made using plasma and CGM.

METHODS

We studied 10 nondiabetic older adults who randomly consumed 9 predefined meals of varying macronutrient compositions. Glucose was measured for 8 h after the meal by the CGM, blood samples for plasma collection were taken regularly, and plasma glucose was quantified using gold-standard laboratory measurement and a fingerstick blood glucose meter. The primary outcome measured was the mean absolute relative difference (MARD) of CGM and fingerstick measurements relative to the gold standard. Secondary outcomes were Bland-Altman statistics, Clarke Error Grid, and time in range metrics. Additional subgroup analyses were performed by stratifying the postprandial glucose measurements based on the macronutrient composition of the meals.

RESULTS

When compared against the gold-standard postprandial glucose measurements, the fingerstick meter was more accurate (MARD: 8.0%; 95% CI: 7.6%, 8.6%) than the CGM (MARD: 13.7%; 95% CI: 13.1%, 14.3%; P < 0.0001). After the meals, Bland-Altman analysis demonstrated that the CGM underestimated the 8-h gold-standard glucose rise by 12.8 mg/dL on average (P < 0.0001), whereas the fingerstick meter did so by 5.5 mg/dL on average (P < 0.0001). The CGM underestimated the time spent in the 70-180 mg/dL range (P = 0.002) and overestimated the time spent <70 mg/dL (P < 0.0001) compared with the other 2 methods.

CONCLUSIONS

We discovered discordance between gold standard, fingerstick, and CGM in measuring plasma glucose concentrations after a meal. Consequently, emerging applications of CGM in healthy individuals, such as precision nutrition and diabetes onset prediction, may need to account for these discordances.This trial was registered at clinicaltrials.gov as NCT04928872.

Switching to the Minimed™ 780G system achieves clinical targets for CGM in adults with type 1 diabetes regardless of previous insulin strategy and baseline glucose control

AIMS

Advanced hybrid closed-loop (AHCL) systems represent the latest introduction in the treatment of type 1 diabetes (T1DM). Randomized controlled trials and real-world evidence studies showed that AHCL systems are a safe and effective insulin management strategy. Aim of this retrospective, single-center, real-life study was to evaluate the effect on metabolic control, evaluated by continuous glucose monitoring (CGM) metrics, of the switch from four available insulin strategies to an AHCL system in adult patients with type 1 diabetes.

METHODS

A total of 102 patients with T1DM (mean age 42.1 ± 16.3 years, males/females 47/55, duration of diabetes 21.4 ± 13.3 years, BMI 24.4 ± 4.5 kg/m², HbA_1c 59.9 ± 9.6 mmol/mol or 7.6 ± 0.9%), treated with four different insulin therapies [multiple daily insulin (MDI) therapy, continuous subcutaneous insulin infusion (CSII), sensor-augmented pump (SAP) with predictive low-glucose suspend (PLGS), and hybrid closed loop (HCL) system] were evaluated before hand, two months and six months after switching to an AHCL (Minimed™ 780G system, Medtronic, Northridge, CA) system.

RESULTS

Two months after the switch, mean GCM metrics improved in all four treatment groups. Six months after the switch, the participants of all four groups achieved a mean GMI < 53 mmol/mol, TIR > 70%, TBR < 4%, and CV < 36%, which is recommended by the ADA Standard of Medical Care in Diabetes 2022, including the MDI group with worse baseline glycemic control.

CONCLUSIONS

Switching to an AHCL leads to a rapid improvement in glycemic control lasting for up to six months independently of previous insulin treatment and baseline conditions.

Experiences of Using Wearable Continuous Glucose Monitors in Adults With Diabetes: A Qualitative Descriptive Study

PURPOSE

The purpose of the study was to understand the experiences of adults with diabetes wearing a continuous glucose monitor (CGM).

METHODS

This qualitative, descriptive study included 19 adults with type 1 diabetes or type 2 diabetes, who had used the FreeStyle Libre CGM for at least 4 weeks, from an outpatient clinic at a university-affiliated hospital in Korea. Data were collected through in-depth interviews and analyzed using an inductive content analysis approach.

RESULTS

The content analysis revealed 3 major themes-navigating glucose level fluctuations, reframing diabetes self-care and improving quality of life, and device improvement and service quality. Participants reported that CGMs offered convenient glucose level monitoring, allowed early response to rapid glucose changes, and facilitated effective patient-clinician communication. Participants expressed concerns about the financial burden and limited services, recommending improvements for devices, consumer services, and health insurance coverage.

CONCLUSIONS

Study findings indicated that using wearable CGMs could improve self-care and quality of life in adults with diabetes. Using CGMs could improve patients' understanding of how diabetes self-care management affects real-time glucose levels. Health care providers could support patients' self-care by using device data. Improvements in quality, services, and insurance coverage could increase user satisfaction and promote self-care.

Discrepancies in glycemic metrics derived from different continuous glucose monitoring systems in adult patients with type 1 diabetes mellitus

BACKGROUND

Continuous glucose monitoring systems have been widely used but discrepancies among various brands of devices are rarely discussed. This study aimed to explore differences in glycemic metrics between FreeStyle Libre (FSL) and iPro2 among adults with type 1 diabetes mellitus (T1DM).

METHODS

Participants with T1DM and glycosylated hemoglobin of 7%-10% were included and wore FSL and iPro2 for 2 weeks simultaneously. Datasets collected on the insertion and detachment day, and those with insufficient quantity (<90%) were excluded. Agreements of measurement accuracy and glycemic metrics were evaluated.

RESULTS

A total of 40 498 paired data were included. Compared with the values from FSL, significantly higher median value was observed in iPro2 (147.6 [106.2, 192.6] vs. 144.0 [100.8, 192.6] mg/dl, p < 0.001) and the largest discordance was observed in hypoglycemic range (median absolute relative difference with iPro2 as reference value: 25.8% [10.8%, 42.1%]). Furthermore, significant differences in glycemic metrics between iPro2 and FSL were also observed in time in range (TIR) 70-180 mg/dl (TIR, 62.8 ± 12.4% vs. 58.8 ± 12.3%, p = 0.004), time spent below 70 mg/dl (4.4 [1.8, 10.9]% vs. 7.2 [5.4, 13.3]%, p < 0.001), time spent below 54 mg/dl (0.9 [0.3, 4.0]% vs. 2.6 [1.3, 5.6]%, p = 0.011), and coefficient of variation (CV, 38.7 ± 8.5% vs. 40.9 ± 9.3%, p = 0.017).

CONCLUSIONS

During 14 days of use, FSL and iPro2 provided different estimations on TIR, CV, and hypoglycemia-related parameters, which needs to be considered when making clinical decisions and clinical trial designs.

Use of a Continuous Glucose Monitor to Determine the Glycaemic Index of Rice-Based Mixed Meals, Their Effect on a 24 h Glucose Profile and Its Influence on Overweight and Obese Young Adults' Meal Preferences

Postprandial hyperglycaemia is associated with an increased risk of type-2 diabetes. This study aims to determine the glycaemic index (GI) of three varieties of rice-based mixed meals and their effects on glycaemic variability (GV), 24 h mean glucose levels and target ranges, and rice variety preferences among overweight and obese young adults using real-time continuous glucose monitoring (rtCGM). In a randomised controlled crossover design, 14 participants (22.8 ± 4.6 years, 32.9 ± 5.8 kg/m2) were randomly assigned to receive 3 rice-based mixed meals containing 50 g of available carbohydrates (white rice meal = WRM; brown rice meal = BRM; and parboiled basmati rice meal = PBRM) and 50 g of a glucose reference drink on alternate days. GI, GV, 24 h mean glucose levels and target ranges were measured. Rice variety preferences were compared with those of baseline data and determined at the end of the study period. Results: The analysis found that PBRM was low in GI (45.35 ± 2.06), BRM medium in GI (56.44 ± 2.34), and WRM high in GI (83.03 ± 2.19). PBRM had a significantly (p < 0.05) lower 24 h mean glucose level, higher in-target 24 h glucose level percentage and non-significantly (p > 0.05) lower GV compared to WRM. Prior to observing their postprandial glucose levels generated by rtCGM, the participants preferred WRM (64.3%) over other meals, whereas this preference changed significantly (p < 0.05) at the endpoint (PBRM, 71.4%). PBRM reduced 24 h glucose level and GV of overweight and obese young adults. The rtCGM is proven to be reliable in measuring GI, while providing robust continuous glycaemic information. This may serve as an educational tool that motivates eating behaviour changes among overweight and obese young adults.

Commercial and Scientific Solutions for Blood Glucose Monitoring-A Review

Diabetes is a chronic and, according to the state of the art, an incurable disease. Therefore, to treat diabetes, regular blood glucose monitoring is crucial since it is mandatory to mitigate the risk and incidence of hyperglycemia and hypoglycemia. Nowadays, it is common to use blood glucose meters or continuous glucose monitoring via stinging the skin, which is classified as invasive monitoring. In recent decades, non-invasive monitoring has been regarded as a dominant research field. In this paper, electrochemical and electromagnetic non-invasive blood glucose monitoring approaches will be discussed. Thereby, scientific sensor systems are compared to commercial devices by validating the sensor principle and investigating their performance utilizing the Clarke error grid. Additionally, the opportunities to enhance the overall accuracy and stability of non-invasive glucose sensing and even predict blood glucose development to avoid hyperglycemia and hypoglycemia using post-processing and sensor fusion are presented. Overall, the scientific approaches show a comparable accuracy in the Clarke error grid to that of the commercial ones. However, they are in different stages of development and, therefore, need improvement regarding parameter optimization, temperature dependency, or testing with blood under real conditions. Moreover, the size of scientific sensing solutions must be further reduced for a wearable monitoring system.

Pitfalls of intermittent continuous glucose monitoring in patients with steroid diabetes

Only a few studies of continuous glucose monitoring (CGM) in patients with steroid diabetes have been published. Therefore, we investigated all patients with type 2 diabetes (n = 121) and steroid diabetes (n = 40) who used the FreeStyle Libre Pro^® device (Abbott Japan) at Gunma University Hospital between 2017 and 2019. Glycated hemoglobin (HbA1c), mean sensor glucose (SG), and glucose management indicator values were similar in both groups. However, the indices for glycemic variabilities, expressed as standard deviations and percent coefficients of variation, were higher in patients with steroid diabetes than in those with type 2 diabetes. The associations between HbA1c, mean SG, and time in range (TIR) when glucose values were 70-180, <70, or >180 mg/dL were assessed using Pearson's product-moment correlation coefficient, which demonstrated good correlations in both patient groups. However, patients with steroid diabetes had a higher SG and lower TIR than did counterparts with type 2 diabetes who had similar HbA1c levels. To examine the effect of prednisolone on CGM data, we divided patients with steroid diabetes into 2 subgroups according to prednisolone dose (≤5 and >5 mg), and found that the dose of this steroid impacted the associations between HbA1c and CGM data, mean SG, and TIR. In summary, our data highlight the importance of cautiously interpreting CGM data and the optimal HbA1c level in patients with steroid diabetes to prevent diabetes-related complications. Further analyses using other CGM devices are necessary to further validate our findings.

The Optimal "Time in Range" and "Time below Range" are Difficult to Coordinate in Patients with Type 1 Diabetes

Achieving the optimal glucose level time in range (TIR), as recently proposed by the "International Consensus on Time in Range," is challenging. We retrospectively analyzed data from 192 patients, including 58 with type 1 diabetes, using the FreeStyle Libre Pro system. This device was used by physicians for continuous glucose monitoring (CGM) and for making therapeutic decisions based on unbiased data, as the patients were blinded to their blood glucose levels during monitoring. The desired 70% TIR among patients with type 2 diabetes corresponded to an HbA1c of 7.7%. Importantly, however, a 70% TIR for patients with type 1 diabetes corresponded to an HbA1c of 6.9%, which diverged markedly from the HbA1c of 7.9% that corresponded to the desired 4% time below range (TBR). Moreover, these dissociations were observed more in patients with type 1 diabetes with a higher % coefficient of variation (> 36%). Hence, while the TIR is strongly correlated with HbA1c, it is difficult to coordinate with the TBR in Japanese patients with type 1 diabetes. As these metrics (which are critical indicators in clinical practice) are rapidly gaining popularity globally, including in Japan, our data strongly support the cautious use of new CGM metrics such as TIR and TBR/time above range, and emphasize the importance of individualized treatment in achieving the optimal TIR and TBR, especially in patients with type 1 diabetes.

Impact of Switching from Intermittently Scanned to Real-Time Continuous Glucose Monitoring Systems in a Type 1 Diabetes Patient French Cohort: An Observational Study of Clinical Practices

Aim: Assess the impact of switching from intermittently scanned (FreeStyle Libre [FSL]) to real-time (Dexcom G4 platinum [DG4]) continuous glucose monitoring systems on glycemia control in type 1 diabetes (T1D) patients with high risk of hypoglycemia and/or elevated glycated hemoglobin (HbA1c). Methods: We conducted an observational study in 18 T1D adults with poor glycemic control on FSL. Ambulatory glucose profile data were collected during the last 3 months of FSL use before inclusion (M0 period), during the first 3 months (M3 period) and the last 3 months (M6 period) of DG4 use. Data were then expressed as 24-h averages. Biological HbA1c was measured for all three periods. Patients were their own-controls and statistics were performed using paired t-test or Wilcoxon for matched-pairs. Results: The switch to DG4 at M3 resulted in a higher time-in-range (TIR) 70-180 mg/dL (median [Q1;Q3], 53.1 [44.5;67.3] vs. 41.5 [28.5;62.0], P = 0.0008), and a lower time-below-range <70 mg/dL (TBR mean ± standard deviation (SD), 5.4 ± 3.7 vs. 10.9 ± 7.1, P = 0.0009) and in the glucose % coefficient of variation (%CV mean ± SD, 40.1 vs. 46.9, P = 0.0001). Mean (SD) changes were +10.3 (8.0) percentage points for TIR, -5.5 (5.8) percentage points for TBR, and -6.8 (5.8) percentage points for %CV. These results were confirmed at the M6 period. Conclusions: Switching from FSL to DG4 appears to provide a beneficial therapeutic option without changing insulin delivery systems, regardless of the origin of the patient's initial glycemic issue.

The association between hypoglycemia and glycemic variability in elderly patients with type 2 diabetes: a prospective observational study

BACKGROUND

This study aimed to explore predictive factors of time below target glucose range (TBR) ≥ 1% among patients' characteristics and glycemic variability (GV) indices using continuous glucose monitoring data in elderly patients with type 2 diabetes.

METHODS

We conducted a prospective observational study on 179 (71 female) Japanese outpatients with type 2 diabetes aged ≥ 65 years. The characteristics of the participants with TBR ≥ 1% were evaluated by multivariate logistic regression analysis. Receiver-operating characteristic (ROC) curve analyses of GV indices, comprising coefficient of variation (CV), standard deviation, and mean amplitude of glycemic excursions, were performed to identify the optimal index for the identification of patients with TBR ≥ 1%.

RESULTS

In the multivariate logistic regression analysis, none of the clinical characteristics, including HbA1c and C-peptide index, were independent markers for TBR ≥ 1%, while all three GV indices showed significant associations with TBR ≥ 1%. Among the three GV indices, CV showed the best performance based on the area under the curve in the ROC curve analyses.

CONCLUSIONS

Among elderly patients with type 2 diabetes, CV reflected TBR ≥ 1% most appropriately among the GV indices examined. Trial registration UMIN-CTR: UMIN000029993. Registered 16 November 2017.

A pilot non-inferiority randomized controlled trial to assess automatic adjustments of insulin doses in adolescents with type 1 diabetes on multiple daily injections therapy

BACKGROUND

Multiple daily injections (MDI) therapy for type 1 diabetes involves basal and bolus insulin doses. Non-optimal insulin doses contribute to the lack of satisfactory glycemic control. We aimed to evaluate the feasibility of an algorithm that optimizes daily basal and bolus doses using glucose monitoring systems for MDI therapy users.

METHODS

We performed a pilot, non-inferiority, randomized, parallel study at a diabetes camp comparing basal-bolus insulin dose adjustments made by camp physicians (PA) and a learning algorithm (LA), in children and adolescents on MDI therapy. Participants wore a glucose sensor and underwent 11 days of daily dose adjustments in either arm. Algorithm adjustments were reviewed and approved by a physician. The last 7 days were examined for outcomes.

RESULTS

Twenty-one youths (age 13.3 [SD, 3.7] years; 13 females; HbA1c 8.6% [SD, 1.8]) were randomized to either group (LA [n = 10] or PA [n = 11]). The algorithm made 293 adjustments with a 92% acceptance rate from the camp physicians. In the last 7 days, the time in target glucose (3.9-10 mmol/L) in LA (39.5%, SD, 20.7) was similar to PA (38.4%, SD, 15.6) (P = .89). The number of hypoglycemic events per day in LA (0.3, IQR, [0.1-0.6]) was similar to PA (0.2, IQR, [0.0-0.4]) (P = .42). There was no incidence of severe hypoglycemia nor ketoacidosis.

CONCLUSIONS

In this pilot study, glycemic outcomes in the LA group were similar to the PA group. This algorithm has the potential to facilitate MDI therapy, and longer and larger studies are warranted.