Continuous Glucose Monitoring Sensor Research Articles

Budget impact analysis of continuous glucose monitoring in individuals with type 2 diabetes on insulin treatment in England

IntroductionIn 2022, updated guidance from NICE expanded the options for self-monitoring of blood glucose for patients with type 2 diabetes (T2DM), to include continuous glucose monitoring (CGM). In this budget impact analysis, the cost impact of CGM was compared with traditional self-monitoring of blood glucose (SMBG) in adults with T2DM over 1 year from the commissioner perspective in England.Research Design and methodsThe NICE-eligible T2DM cohort was split into 4 subgroups to enable nuanced costing by insulin administration frequency: basal human insulin, premixed insulin, basal-bolus insulin and bolus insulin. The model’s cost components comprised mild and severe hypoglycaemia (SH), diabetic ketoacidosis (DKA), consumables and healthcare resource utilisation in primary and secondary care.ResultsThe introduction of CGM is estimated to be cost additive by approximately £4.6 million in the basecase, driven by increased spending on the CGM device. Overall, healthcare activity was reduced by approximately 20,000 attendances, due to fewer SH and DKA episodes in the CGM arm. General Practitioner (GP) practice-based activity is expected to drop after the first year as patients requiring CGM training is reduced. The budget impact could be neutralised if the CGM sensor was discounted by 13.2% (£29.76 to £25.83).ConclusionsCGM may result in increased spending in the NICE-eligible T2DM cohort but is expected to reduce demand on secondary care services and GP time. These findings may be of interest to local decision-makers who wish to resolve the COVID-19 backlog with transformational investment in primary care to reduce secondary care activity.

Long-term assessment of the NHS hybrid closed-loop real-world study on glycaemic outcomes, time-in-range, and quality of life in children and young people with type 1 diabetes

Hybrid closed-loop (HCL) systems seamlessly interface continuous glucose monitoring (CGM) with insulin pumps, employing specialised algorithms and user-initiated automated insulin delivery. This study aimed to assess the efficacy of HCLs at 12 months post-initiation on glycated haemoglobin (HbA1c), time-in-range (TIR), hypoglycaemia frequency, and quality of life measures among children and young people (CYP) with type 1 diabetes mellitus (T1DM) and their caregivers in a real-world setting. Conducted between August 1, 2021, and December 10, 2022, the prospective recruitment took place in eight paediatric diabetes centres across England under the National Health Service England’s (NHSE) HCL pilot real-world study. A cohort of 251 CYP (58% males, mean age 12.3 years) with T1DM participated (89% white, 3% Asian, 4% black, 3% mixed ethnicity, and 1% other). The study utilised three HCL systems: (1) Tandem Control-IQ AP system, which uses the Tandem t:slim X2 insulin pump (Tandem Diabetes Care, San Diego, CA, USA) with the Dexcom G6® CGM (Dexcom, San Diego, CA, USA) sensor; (2) Medtronic MiniMed™ 780G with the Guardian 4 sensor (Medtronic, Northridge, CA, USA); and (3) the CamAPS FX (CamDiab, Cambridge, UK) with the Ypsomed insulin pump (Ypsomed Ltd, Escrick, UK) and Dexcom G6® CGM.All systems were fully funded by the NHS. Results demonstrated significant improvements in HbA1c (average reduction at 12 months 7 mmol/mol; P < 0.001), time-in-range (TIR) (average increase 13.4%; P < 0.001), hypoglycaemia frequency (50% reduction), hypoglycaemia fear, and quality of sleep (P < 0.001) among CYP over a 12-month period of HCL usage. Additionally, parents and carers experienced improvements in hypoglycaemia fear and quality of sleep after 6 and 12 months of use. In addition to the improvements in glycaemic management, these findings underscore the positive impact of HCL systems on both the well-being of CYP with T1DM and the individuals caring for them.

Differences in glycemic trends due to reconstruction methods after proximal gastrectomy from the perspective of continuous glucose-monitoring.

In recent years, clinicians have focused on the importance of preventing hypoglycemia. We evaluated the impact of different reconstruction procedures after proximal gastrectomy on glycemic variability in non-diabetic patients with gastric cancer. This prospective observational study was conducted between April 2020 and March 2023. Flash continuous glucose-monitoring, a novel method for assessing glycemic control, was used to evaluate the glycemic profiles after gastrectomy. A flash continuous glucose-monitoring sensor was placed subcutaneously at the time of discharge, and glucose trends were evaluated for 2weeks. The anastomotic methods for proximal gastrectomy were esophagogastrostomy in 10 patients and double-tract reconstruction in 10 patients. The time below this range (glucose levels < 70mg/dL) was significantly higher in the double-tract reconstruction group than in the esophagogastrostomy group (p = 0.049). A higher nocturnal time below this range was significantly correlated with an older age and double-tract reconstruction (p = 0.025 and p = 0.025, respectively). These findings provide new insights into reconstruction methods after proximal gastrectomy by assessing postoperative hypoglycemia in non-diabetic patients with gastric cancer.

Optimizing type 2 diabetes management: AI-enhanced time series analysis of continuous glucose monitoring data for personalized dietary intervention.

Despite advanced health facilities in many developed countries, diabetic patients face multifold health challenges. Type 2 diabetes mellitus (T2DM) go along with conspicuous symptoms due to frequent peaks, hypoglycemia <=70 mg/dL (while fasting), or hyperglycemia >=180 mg/dL two hours postprandial, according to the American Diabetes Association (ADA)). The worse effects of Type 2 diabetes mellitus are precisely associated with the poor lifestyle adopted by patients. In particular, a healthy diet and nutritious food are the key to success for such patients. This study was done to help T2DM patients improve their health by developing a favorable lifestyle under an AI-assisted Continuous glucose monitoring (CGM) digital system. This study aims to reduce the blood glucose level fluctuations of such patients by rectifying their daily diet and maintaining their exertion vs. food consumption records. In this study, a well-precise prediction is obtained by training the ML model on a dataset recorded from CGM sensor devices attached to T2DM patients under observation. As the data obtained from the CGM sensor is time series, to predict blood glucose levels, the time series analysis and forecasting are done with XGBoost, SARIMA, and Prophet. The results of different Models are then compared based on performance metrics. This helped in monitoring various trends, specifically irregular patterns of the patient's glucose data, collected by the CGM sensor. Later, keeping track of these trends and seasonality, the diet is adjusted accordingly by adding or removing particular food and keeping track of its nutrients with the intervention of a commercially available all-in-one AI solution for food recognition. This created an interactive assistive system, where the predicted results are compared to food contents to bring the blood glucose levels within the normal range for maintaining a healthy lifestyle and to alert about blood glucose fluctuations before the time that are going to occur sooner. This study will help T2DM patients get in managing diabetes and ultimately bring HbA1c within the normal range (<= 5.7%) for diabetic and pre-diabetic patients, three months after the intervention.

Glucose Color Index: Development and Validation of a Novel Measure of the Shape of Glycemic Variability.

Standard continuous glucose monitoring (CGM) metrics: mean glucose, standard deviation, coefficient of variation, and time in range, fail to capture the shape of variability in the CGM time series. This information could facilitate improved diabetes management. We analyzed CGM data from 141 adults with type 2 diabetes in the Hyperglycemic Profiles in Obstructive Sleep Apnea (HYPNOS) trial. Participants in HYPNOS wore CGM sensors for up to two weeks at two time points, three months apart. We calculated the log-periodogram for each time period, summarizing using disjoint linear models. These summaries were combined into a single value, termed the Glucose Color Index (GCI), using canonical correlation analysis. We compared the between-wear correlation of GCI with those of standard CGM metrics and assessed associations between GCI and diabetes comorbidities in 398 older adults with type 2 diabetes from the Atherosclerosis Risk in Communities (ARIC) study. The GCI achieved a test-retest correlation of R = .75. Adjusting for standard CGM metrics, the GCI test-retest correlation was R = .55. Glucose Color Index was significantly associated (p < .05) with impaired physical functioning, frailty/pre-frailty, cardiovascular disease, chronic kidney disease, and dementia/mild cognitive impairment after adjustment for confounders. We developed and validated the GCI, a novel CGM metric that captures the shape of glucose variability using the periodogram signal decomposition. Glucose Color Index was reliable within participants over a three-month period and associated with diabetes comorbidities. The GCI suggests a promising avenue toward the development of CGM metrics which more fully incorporate time series information.

Beyond HbA1c: Identifying Gaps in Glycemic Control Among Children and Young People with Type 1 Diabetes Using Continuous Glucose Monitoring.

To describe continuous glucose monitoring (CGM) derived glycemic variables, and study their association with HbA1c and socio-economic factors in young people with Type 1 diabetes mellitus (T1DM). Ninety-two participants [age 15.7 ± 5.0 y (mean ± SD), HbA1c 8.0 ± 1.5% (mean ± SD)] wore a professional CGM sensor for 14 d. Median (IQR) time in range (TIR) was 41 (18)%. Participants spent 41 ± 20% of their day in hyperglycemia (>180mg/dl), and 14 (13)% in hypoglycemia (<70mg/dl). High glycemic variability (percent CV >36%) was seen in 92% participants. Older age at diagnosis was associated with higher TIR (β = 0.267, p = 0.01), lower time above range (TAR) (β = -0.352, p <0.001), but higher time below range (TBR) (β = 0.274, p = 0.006). The use of NPH vs. glargine basal insulin was associated with higher TBR (β = -0.262, p = 0.009) but lower TAR (β = 0.202, p = 0.041). HbA1c showed negative correlation with TIR (r= -0.449, p <0.001) and TBR (r= -0.466, p <0.001) and positive correlation with TAR (r = 0.580, p <0.001) and mean glucose (r = 0.589, p <0.001). These data demonstrate wide gaps between the recommended vs. real world glycemic variables in patients with T1DM in thisregionon multiple daily insulin injections. CGM identifies glycemic variability and complements HbA1c in improving glycemic control.

Glycaemic Effects of a 156-km Ultra-trail Race in Athletes: An Observational Field Study.

Ultra-trail running races pose appreciable physiological challenges, particularly for glucose metabolism. Previous studies that yielded divergent results only measured glycaemia at isolated times. We aimed to explore the impact of an ultra-endurance race on continuously measured glycaemia and to understand potential physiological mechanisms, as well as the consequences for performance and behavioural alertness. Fifty-five athletes (78% men, 43.7 ± 9.6years) ran a 156-km ultra-trail race (six 26-km laps, total elevation 6000m). Participants wore a masked continuous glucose monitoring sensor from the day before the race until 10days post-race. Blood was taken at rest, during refuelling stops after each lap, and after 24-h recovery. Running intensity (% heart rate reserve), performance (lap times), psychological stress, and behavioural alertness were explored. Linear mixed models and logistic regressions were carried out. No higher risk of hypo- or hyperglycaemia was observed during the exercise phases of the race (i.e. excluding stops for scientific measurements and refuelling) compared with resting values. Laps comprising a greater proportion of time spent at maximal aerobic intensity were nevertheless associated with more time > 180mg/dL (P = 0.021). A major risk of hyperglycaemia appeared during the 48-h post-race period compared with pre-race (P < 0.05), with 31.9% of the participants spending time with values > 180mg/dL during recovery versus 5.5% during resting. Changes in circulating insulin, cortisol, and free fatty acids followed profiles comparable with those usually observed during traditional aerobic exercise. However, creatine phosphokinase, and to a lesser extent lactate dehydrogenase, increased exponentially during the race (P < 0.001) and remained high at 24-h post-race (P < 0.001; respectively 43.6 and 1.8 times higher vs. resting). Glycaemic metrics did not influence physical performance or behavioural alertness. Ultra-endurance athletes were exposed to hyperglycaemia during the 48-h post-race period, possibly linked to muscle damage and inflammation. Strategies to mitigate muscle damage or subsequent inflammation before or after ultra-trail races could limit recovery hyperglycaemia and hence its related adverse health consequences. NCT05538442 2022-09-21 retrospectively registered.

Abstract P461: Concordance of Hypoglycemia Symptoms Reported in Real-Time via Smartphone and Hypoglycemia Detected Using Continuous Glucose Monitoring (CGM) in Adults With Type 2 Diabetes

Introduction: Understanding the association between low glucose readings (hypoglycemia) detected by CGM and hypoglycemic symptoms experienced by people with diabetes is critically important for diabetes management. However, tools that capture hypoglycemic symptoms in real-time are lacking. Objective: Implement a real-time hypoglycemia symptom reporting tool and examine agreement between self-reported hypoglycemia symptoms and CGM-detected hypoglycemia. Methods: We developed a survey tool for real-time reporting of symptoms via smartphone ( Fig. 1A ) using REDCap, and implemented this tool in an ongoing, randomized clinical trial of adults with type 2 diabetes, the Dietary Approaches to Stop Hypertension for Diabetes (DASH4D) trial. DASH4D participants wore a CGM sensor (Abbott Libre Pro) for up to 5 periods (max 2-weeks per period), and we offered the option to report symptoms using the real-time survey tool during each CGM wear. We examined the concordance of real-time reported symptoms and CGM-detected hypoglycemia (glucose &lt;70 mg/dL for &gt; 15 minutes) ( Fig. 1B ). Concordance was defined as CGM-detected hypoglycemia occurring within 30 minutes before or after a reported symptom. Results: Of 159 participants who wore a CGM, 114 (72%; mean age 64 years; 86% Black; 64% female) used the real-time symptom reporting tool (the remainder used a paper-based booklet). Across all CGM wear-periods (N=280), participants reported a mean 1.94 symptoms per period. Fatigue was the most common (37 occurrences); unsteadiness and passing out were not reported ( Fig. 1C ). The overall concordance between self-reported symptoms and CGM-detected hypoglycemia was 3% ( Fig. 1D ). Conclusion: We developed a simple and secure smartphone-based tool allowing patients with diabetes to report hypoglycemic symptoms in real-time. Concordance of CGM-detected hypoglycemia with symptoms was low, indicating substantial disconnect between perceived symptoms and CGM-detected hypoglycemic events among adults with type 2 diabetes. [NCT04286555]

Abstract P144: 1,5-Anhydroglucitol as a Marker of Hyperglycemic Excursions Defined by Continuous Glucose Monitoring in Older Adults

Background: Low levels (≤6 μg/mL) of serum 1,5-anhydroglucitol (1,5-AG) are thought to reflect periods of hyperglycemia. During periods of hyperglycemia, 1,5-AG competes with glucose for reabsorption in the kidney and is excreted in the urine, resulting in low serum concentrations of 1,5-AG. However, the performance of 1,5-AG to identify hyperglycemic excursions detected by continuous glucose monitoring (CGM) is unknown. Methods: We conducted a cross-sectional analysis of participants with diabetes in the Atherosclerosis Risk in Communities Study who wore a CGM sensor in 2021-2022 for up to 2 weeks. We evaluated the performance of 1,5-AG, modeled continuously and dichotomously (≤6 μg/mL, &gt;6 μg/mL), to identify CGM derived metrics of hyperglycemia. Hyperglycemic excursions were defined as percent time spent with CGM glucose above 140 mg/dL, area under the curve (AUC) &gt;140 mg/dL*minute, peak (maximum) CGM glucose, and the coefficient of variation (CV). Results: Among 322 participants with diabetes (mean age 83, 55% female), 22% had 1,5-AG≤6 μg/mL. The median CGM wear time was 13.9 days. The mean CGM glucose was 125 mg/dL (SD, 28) among those with 1,5-AG&gt;6 μg/mL and 156 mg/dL (SD, 45) among those with 1,5-AG≤6 μg/mL. 1,5-AG was inversely associated with percent of time CGM glucose &gt;140 mg/dL ( Figure ), AUC &gt;140 mg/dL (Pearson correlation, r =-0.25), peak CGM glucose ( r =-0.41) and CV ( r =-0.25). Individuals with 1,5-AG≤6 μg/mL spent 5.5 hours more per day above 140 mg/dL compared to those with 1,5-AG&gt;6 μg/mL. Conclusion: 1,5-AG is correlated with CGM-defined hyperglycemia. Low levels of 1,5-AG identify older adults with diabetes experiencing glycemic excursions.

Associations between continuous glucose monitoring (CGM) metrics and psycholinguistic measures: a correlational study.

Recently, the relationship between diabetes and mental health has been widely studied. With the advent of continuous glucose monitoring (CGM), some researchers have been interested in exploring the association between glucose-related metrics and psychological aspects. These studies have primarily relied on self-report questionnaires which present some limitations. Therefore, the present multicenter study aims at testing potential associations between CGM metrics and affective processes derived from narratives about using a CGM sensor. An exploratory correlational design was used. Fifty-eight adults with type 1 diabetes using CGM were enrolled and invited to complete an online survey, where they replied to an open-ended question regarding their personal experience with the CGM sensor. Texts derived from the answers were analyzed through Linguistic Inquiry andWord Count, a widely used text analysis tool that can automatically identify and quantify linguistic patterns related to various psychological dimensions. Psycholinguistic measures were correlated with CGM metrics. Higher levels of sadness/depression correlated with lower %TIR (r = - 339; p < .01) and higher %TAR (r = .342; p < .01). The study highlights the relationship between CGM metrics and psychological variables derived from patients' narratives. In particular, it is possible to hypothesize a positive role of %TIR in reducing depressive feelings in individuals with diabetes, as well as a negative role of depressive feelings in achieving desirable CGM outcomes. Additionally, there is a potential role of glycemic variability, particularly hyperglycemia, in the expression of depressive and sad feelings, which has been less studied compared to the effects of hypoglycemia.

Diabetes treatment by conversion of gut epithelial cells to insulin-producing cells.

Insulin-deficient (type 1) diabetes is treated by providing insulin to maintain euglycemia. The current standard of care is a quasi-closed loop integrating automated insulin delivery with a continuous glucose monitoring sensor. Cell replacement technologies are advancing as an alternative treatment and have been tested as surrogates to cadaveric islets in transplants. In addition, immunomodulatory treatments to delay the onset of type 1 diabetes in high-risk (stage 2) individuals have gained regulatory approval. We have pioneered a cell conversion approach to restore insulin production through pharmacological conversion of intestinal epithelial cells into insulin-producing cells. We have advanced this approach along a translational trajectory through the discovery of small molecule forkhead box protein O1 inhibitors. When administered to different rodent models of insulin-deficient diabetes, these inhibitors have resulted in robust glucose-lowering responses and generation of insulin-producing cells in the gut epithelium. We review past work and delineate a path to human clinical trials.

Glucose values from the same continuous glucose monitoring sensor significantly differ among readers with different generations of algorithm

Continuous glucose monitoring (CGM) values obtained from CGM systems using the same sensor but with different internal algorithms (the first- and third-generation FreeStyle Libre (1st-gen-libre and 3rd-gen-libre, respectively)) were compared. We used 19,819 paired and simultaneously measured CGM values of 13 patients with diabetes. The average CGM value was significantly higher (P < 0.0001) and the time below range (CGM value < 70 mg/dL) was significantly lower (P < 0.0001) with the 3rd-gen-libre than with the 1st-gen-libre. There was a significant correlation (P < 0.0001) between the CGM values of the 3rd-gen-libre (y-axis, mg/dL) and 1st-gen-libre (x-axis, mg/dL) using the following formula: y = 0.9728x + 10.024. On assessing the association between glycated hemoglobin (HbA1c (%), y-axis) and the average CGM values (x-axis, mg/dL) by applying the obtained equation to previously reported 1st-gen-libre data and converting it to 3rd-gen-libre data, we obtained the equation y = 0.02628x + 3.233, indicating that the glucose management indicator reported in the West may be underestimated compared with the laboratory-measured HbA1c in the Japanese population. Glucose values from the same sensor were found to be significantly different between readers with different algorithms, and the calculation of CGM-related indices may need to be individualized for each device.

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).

Co1.22xNixO4/fMWCNTs-hybrid nanocomposite-based self-adhesive wearable non-enzymatic electrochemical sensor for continuous glucose monitoring in sweat

The development of polymer-based wearable, eco-friendly, and non-invasive sensors has been boosted by the rapid emergence and evolution of soft electronics. However, challenges in the catalysis of glucose and sweat sampling have hampered these advances in the development of efficient wearable glucose sensors. Herein, the porous Co1.22xNixO4 hybrid composite material with interconnecting fMWCNTs, referred to as Co1.22xNixO4/fMWCNTs, was hydrothermally synthesized, and covalently crosslinked into well-patterned, flexible PDMS polymer networks. The hydrophilic fMWCNTs enhanced the anchoring spots for the in situ growth of NiCo–Oxides, which significantly improved the conductive networks and introduced many interface zones with high sensitivity of (1190.9 and 1312.1) µA·mM−1·cm−2, wide linear range of (0.001 − 8.0) mM, low detection limit (20 μM), good long-term stability, and excellent selectivity in alkaline solution. A prototype sensor was fabricated by assembling transparent PDMS film with a hydrophilic membrane of supramolecular double network hydrogel (SP−DN) as adhesive, and breathable substrate for sweat collection. The sensitivity of the calibrated prototype was found to be 1326.83 µA·mM−1·cm−2 with a linear range of ≤ 800 µM, tested in artificial sweat samples. The feasibility of a non-invasive glucose sensor was validated by assembling and testing prototype sensors on multiple volunteers. The SP−DN hydrogel acts as a continuous OH− ion supplier, and makes it possible to oxidize the glucose by metal-oxide-based nano-enzyme. The facile fabrication method and reliability of the results with real blood samples show the potential of the metal-oxide-based sensor prototype as a flexible, and environment-adaptable sensing device.

Comparison of Point Accuracy Between Two Widely Used Continuous Glucose Monitoring Systems.

Safe and effective self-management of glucose levels requires immediate access to accurate data. We assessed the point accuracy of the Dexcom G7 Continuous Glucose Monitoring System (Dexcom, Inc., San Diego, CA, USA) and FreeStyle Libre 3 (Abbott Diabetes Care, Alameda, CA, USA) sensors in a head-to-head comparison. Multicenter, single-arm, prospective, nonsignificant risk evaluation enrolled adults (≥ 18 years) with diagnosed type 1 diabetes (T1D) or type 2 diabetes (T2D). Accuracy was assessed by comparing sensor data to laboratory reference values Yellow Springs Instrument [YSI] and capillary blood glucose values. Outcome measures were differences in mean absolute relative difference (MARD), number and percentage of matched glucose pairs within ±20 mg/dL/±20 of reference values within glucose ranges: < 54, 54 to 69, 70 to 180, 181 to 250, > 250 mg/dL, and combined. Data from 55 adults were included in the analysis. Analysis showed significantly lower MARD with the FreeStyle Libre 3 sensor vs the Dexcom G7 sensor (8.9% vs 13.6%, respectively, P < .0001) with a higher percentage of glucose values within ±20 mg/dL/±20 of reference (91.4% vs 78.6%). The MARD values for both continuous glucose monitoring (CGM) sensors were similar during the first 12 hours; however, the FreeStyle Libre 3 MARD was notably lower than the Dexcom G7 MARD during the next 12 hours (10.0% vs 15.1%, respectively, P < .0001) and throughout the study period. The FreeStyle Libre 3 sensor was more accurate than the Dexcom G7 sensor in all metrics evaluated throughout the study period. This is the first head-to-head study to our knowledge that compares the flagship products currently in widespread use of the two largest CGM manufacturers.

Fully integrated wearable microneedle biosensing platform for wide-range and real-time continuous glucose monitoring

Wearable microneedle sensors for continuous glucose monitoring (CGM) have great potential for clinical impact by allowing access to large data sets to provide individualized treatment plans. To date, their development has been challenged by the accurate wide linear range tracking of interstitial fluid (ISF) glucose (Glu) levels. Here, we present a CGM platform consisting of a three-electrode microneedle electrochemical biosensor and a fully integrated radio-chemical analysis system. The long-term performance of the robust CGM on diabetic rats was achieved by electrodepositing Prussian blue (PB), and crosslinking glucose oxidase (GOx) and chitosan to form a 3D network using glutaraldehyde (GA). After redox by GOx, PB rapidly decomposes hydrogen peroxide and mediates charge transfer, while the 3D network and graphite powder provide enrichment and release sites for Glu and catalytic products, enabling a sensing range of 0.25–35 mM. Microneedle CGM has high sensitivity, good stability, and anti-interference ability. In diabetic rats, CGM can accurately monitor Glu levels in the ISF in real-time, which are highly consistent with levels measured by commercial Glu meters. These results indicate the feasibility and application prospects of the PB-based CGM for the clinical management of diabetes. Statement of SignificanceThis study addresses the challenge of continuous glucose monitoring system design where the narrow linear range of sensing due to the miniaturization of sensors fails to meet the monitoring needs of clinical diabetic patients. This was achieved by utilizing a three-dimensional network of glutaraldehyde cross-linked glucose oxidase and chitosan. The unique topology of the 3D network provides a large number of sites for glucose enrichment and anchors the enzyme to the sensing medium and the conductive substrate through covalent bonding, successfully blocking the escape of the enzyme and the sensing medium and shortening the electron transfer and transmission path.

Power and Sensitivity Management of Carbon Nanotube Transistor Glucose Biosensors.

Continuous glucose monitoring (CGM), which is significant for the daily management of diabetes, requires a low-power-consumption sensor system that can track low nanomolar levels of glucose in physiological fluids, such as sweat and tears. However, traditional electrochemical methods are limited to analytes in micromolar to millimolar ranges and entail high power consumption. Carbon nanotube (CNT) film field-effect transistors (FETs) are promising for constructing extremely sensitive biosensors, but their wide applications in CGM are limited by the strong screening effect of physiological fluids and the zero charge of glucose molecules. In this study, we demonstrate a glucose aptamer-modified CNT FET biosensor to realize a highly sensitive CGM system with sub-nW power consumption by applying a suitable gate voltage. A positive gate voltage can enlarge the effective Debye screening length at the double layer to reduce the local ion population nearby and then improve the sensitivity of the FET-based biosensors by 5 times. We construct CNT FET sensors for CGM with a limit of detection of 0.5 fM, a record dynamic range up to 109, and a power consumption down to ∼100 pW. The proposed field-modulated sensing performance scheme is applicable to other aptamer-based FET biosensors for detecting neutral or less charged molecules and opens opportunities to develop facilely modulated, highly sensitive, low-power, and noninvasive CGM systems.

Wearable filamentary continuous sensor for interstitial glucose detection in diabetes management

The development of novel diabetes monitoring sensors is important for the diabetes management of millions of diabetic patients. This work reports a flexible filamentary continuous glucose monitoring (CGM) sensor. A multilayer CGM sensor has been constructed on titanium filament with low cost and ease of use. The sensor, made of flexible material, offers better adaptability and comfort than traditional rigid filament CGM sensors, allowing continuous monitoring of subcutaneous blood glucose levels to provide patients with treatment strategies. The performance and reliability of the sensor were verified through rat experiments. The trend of the increase and decrease of the detected current was generally consistent with the actual blood glucose, and the detected values were located in regions A and B of the Clarke error grid. The results show that the sensor has the advantages of high sensitivity, high accuracy and fast response speed, which is suitable for monitoring the blood glucose level for a long time and has a broad application prospect in diabetes monitoring, exercise monitoring, health management and clinical application.

Impedance-based polymer microneedle patch sensor for continuous interstitial fluid glucose monitoring

Early detection and effective blood glucose control are critical for preventing and managing diabetes-related complications. Conventional glucometers provide point-in-time measurements but are painful and cannot facilitate continuous monitoring. Continuous glucose monitoring systems are comfortable but face challenges in terms of accuracy, cost, and sensor lifespan. This study aimed to develop a microneedle-based sensor patch for minimally invasive, painless, and continuous glucose monitoring in the interstitial fluid to address these limitations. Experimental results confirm painless and minimally invasive penetration of the skin tissue with cylindrical microneedles (3 × 3 array) to a depth of approximately 520 μm with minimal loading. The microneedle sensors fabricated with precision using the complementary metal-oxide semiconductor process were immobilized with glucose oxidase, as confirmed through phase angle analysis. Long-term tests confirmed the effective operation of the sensor for up to seven days. Glucose concentrations determined from the fitted concentration–impedance curves correlated well with those measured using commercial glucometers, indicating the reliability and precision of the microneedle sensor. The flexible and minimally invasive sensor developed in this study facilitates painless and continuous glucose monitoring.

SAT106 Use Of Data Sharing Feature Of Dexcom G6 Sensor Is Associated With Improved Glycemic Control: A Comparative Analysis

Abstract Disclosure: B. Sadek: None. Introduction: The use of Continuous Glucose Monitoring (CGM) sensors has significantly increased in part due to the seamless integration with smartphones. The Dexcom G6 CGM automatically sends real-time glucose readings to a compatible smart device. Moreover, the Dexcom Clarity app provides analytic tools and allows users to continuously share glucose data with their healthcare professionals, enabling remote monitoring of patients' glycemic control. Although multiple studies have shown better glucose control in patients who use CGM systems, what remains unexplored is if glucose metrics are further improved in those who share CGM data with healthcare providers. In this study, we compared glycemic outcomes among patients who use the sharing feature of the Dexcom G6 sensor to share their data with their healthcare providers to those who do not. Method: We conducted a single-center cross-sectional study in a community hospital with patients who use the Dexcom G6 CGM (n=201). Data was obtained from Dexcom Clarity for Healthcare Professionals, an online platform for clinicians to review patients' glucose patterns and statistics through interactive reports. The following data was collected for each patient: date of the last upload, data sharing status, average glucose, standard deviation, glucose management indicator (GMI) (%), glucose ranges (categorized as very high, high, in range, low, very low), sensor usage, and coefficient of variation (%). Two-tailed unpaired Student's t-tests were used to analyze the CGM metrics based on data sharing status. Significance was defined as a p-value less than 0.05. Results: 123 (61.19%) of the study participants shared data with healthcare providers. Participants with sharing data 'on' were significantly younger (49±15 years, p-value = 0.0007) and had increased sensor usage (90±21%, p-value = 0.0012), compared to those with sharing off. Participants who shared data spent more time in range (57±24 %, p-value = 0.0435), indicating a higher percentage of readings with glucose levels in a healthy range (70-180 mg/dL). Lastly, average glucose was lower in participants who shared data, although not statistically significant (179 ±44 mg/dL, p=0.08). Conclusion: The data-sharing feature on Dexcom G6 was utilized more frequently by younger people and was associated with a higher percentage of sensor usage. In addition, using the data-sharing feature of the Dexcom G6 could lead to a clinically meaningful improvement in glycemic control. Presentation: Saturday, June 17, 2023