Delays in minimally invasive continuous glucose monitoring devices: a review of current technology

Noninvasive Continuous Glucose Monitoring With a Novel Wearable Dial Resonating Sensor: A Clinical Proof-of-Concept Study

BACKGROUND

A noninvasive, wearable continuous glucose monitor would be a major advancement in diabetes therapy. This trial investigated a novel noninvasive glucose monitor which analyzes spectral variations in radio frequency/microwave signals reflected from the wrist.

METHODS

A single-arm, open-label, experimental study compared glucose values from a prototype investigational device with laboratory glucose measurements from venous blood samples (Super GL Glucose Analyzer, Dr. Müller Gerätebau GmbH) at varying levels of glycemia. The study included 29 male participants with type 1 diabetes (age range = 19-56 years). The study comprised three stages with the following aims: (1) demonstrate initial proof-of-principle, (2) test an improved device design, and (3) test performance on two consecutive days without device recalibration. The co-primary endpoints in all trial stages were median and mean absolute relative difference (ARD) calculated across all data points.

RESULTS

In stage 1, the median and mean ARDs were 30% and 46%, respectively. Stage 2 produced marked performance improvements with a median and mean ARD of 22% and 28%, respectively. Stage 3 showed that, without recalibration, the device performed as well as the initial prototype (stage 1) with a median and mean ARD of 35% and 44%, respectively.

CONCLUSION

This proof-of-concept study shows that a novel noninvasive continuous glucose monitor was capable of detecting glucose levels. Furthermore, the ARD results are comparable to first models of commercially available minimally invasive products without the need to insert a needle. The prototype has been further developed and is being tested in subsequent studies.

TRIAL REGISTRATION NUMBER

NCT05023798.

Continuous Glucose, Insulin and Lifestyle Data Augmentation in Artificial Pancreas Using Adaptive Generative and Discriminative Models

Artificial pancreas requires data from multiple sources for accurate insulin dose estimation. These include data from continuous glucose sensors, past insulin dosage information, meal quantity and time and physical activity data. The effectiveness of closed-loop diabetes management systems might be hampered by the absence of these data caused by device error or lack of compliance by patients. In this study, we demonstrate the effect of output sequence length-driven generative and discriminative model selection in high quality data generation and augmentation. This novel generative adversarial network (GAN) based architecture automatically selects the generator and discriminator architecture based on the desired output sequence length. The proposed model is able to generate glucose, physical activity, meal information data for individual patients. The discriminative scores for Ohio T1DM (2018) dataset were 0.17 ±0.03 (Inputs: CGM, CHO, Insulin) and 0.15 ±0.02 (Inputs: CGM, CHO, Insulin, Heart Rate, Steps) and for Ohio T1D (2020) dataset was 0.16 ±0.02 (Inputs: CGM, CHO, Insulin) and 0.15 ±0.02 (Inputs: CGM, CHO, Insulin, acceleration). A mixture of generated and real data was used to test predictive scores for glucose forecasting models. The best RMSE and MARD achieved for OhioT1DM patients were 17.19 ±3.22 and 7.14 ±1.76 for PH=30 min with CGM, CHO, Insulin, heartrate and steps as inputs. Similarly, the RMSE and MARD for real+synthetic data were 15.63 ±2.57 and 5.86 ±1.69 respectively. Compared to existing generative models, we demonstrate that sequence length based architecture selection leads to better synthetic data generation for multiple output sequences (CGM, CHO, Insulin) and forecasting accuracy.

(Hybrid) Closed-Loop Systems: From Announced to Unannounced Exercise

Physical activity and exercise have many beneficial effects on general and type 1 diabetes (T1D) specific health and are recommended for individuals with T1D. Despite these health benefits, many people with T1D still avoid exercise since glycemic management during physical activity poses substantial glycemic and psychological challenges - which hold particularly true for unannounced exercise when using an AID system. Automated insulin delivery (AID) systems have demonstrated their efficacy in improving overall glycemia and in managing announced exercise in numerous studies. They are proven to increase time in range (70-180 mg/dL) and can especially counteract nocturnal hypoglycemia, even when evening exercise was performed. AID-systems consist of a pump administering insulin as well as a CGM sensor (plus transmitter), both communicating with a control algorithm integrated into a device (insulin pump, mobile phone/smart watch). Nevertheless, without manual pre-exercise adaptions, these systems still face a significant challenge around physical activity. Automatically adapting to the rapidly changing insulin requirements during unannounced exercise and physical activity is still the Achilles' heel of current AID systems. There is an urgent need for improving current AID-systems to safely and automatically maintain glucose management without causing derailments - so that going forward, exercise announcements will not be necessary in the future. Therefore, this narrative literature review aimed to discuss technological strategies to how current AID-systems can be improved in the future and become more proficient in overcoming the hurdle of unannounced exercise. For this purpose, the current state-of-the-art therapy recommendations for AID and exercise as well as novel research approaches are presented along with potential future solutions - in order to rectify their deficiencies in the endeavor to achieve fully automated AID-systems even around unannounced exercise.

Pediatric Type 1 Diabetes: Mechanisms and Impact of Technologies on Comorbidities and Life Expectancy

Type 1 diabetes (T1D) is one of the most common chronic diseases in childhood, with a progressively increasing incidence. T1D management requires lifelong insulin treatment and ongoing health care support. The main goal of treatment is to maintain blood glucose levels as close to the physiological range as possible, particularly to avoid blood glucose fluctuations, which have been linked to morbidity and mortality in patients with T1D. Indeed, the guidelines of the International Society for Pediatric and Adolescent Diabetes (ISPAD) recommend a glycated hemoglobin (HbA1c) level < 53 mmol/mol (<7.0%) for young people with T1D to avoid comorbidities. Moreover, diabetic disease strongly influences the quality of life of young patients who must undergo continuous monitoring of glycemic values and the administration of subcutaneous insulin. In recent decades, the development of automated insulin delivery (AID) systems improved the metabolic control and the quality of life of T1D patients. Continuous subcutaneous insulin infusion (CSII) combined with continuous glucose monitoring (CGM) devices connected to smartphones represent a good therapeutic option, especially in young children. In this literature review, we revised the mechanisms of the currently available technologies for T1D in pediatric age and explored their effect on short- and long-term diabetes-related comorbidities, quality of life, and life expectation.

Finger-Actuated Micropump of Constant Flow Rate without Backflow

This paper presents a finger-actuated micropump with a consistent flow rate and no backflow. The fluid dynamics in interstitial fluid (ISF) extraction microfluidics are studied through analytical, simulation, and experimental methods. Head losses, pressure drop, diodocity, hydrogel swelling, criteria for hydrogel absorption, and consistency flow rate are examined in order to access microfluidic performance. In terms of consistency, the experimental result revealed that after 20 s of duty cycles with full deformation on the flexible diaphragm, the output pressure became uniform and the flow rate remained at nearly constant levels of 2.2 μL/min. The flow rate discrepancy between the experimental and predicted flow rates is around 22%. In terms of diodicity, when the serpentine microchannel and hydrogel-assisted reservoir are added to the microfluidic system integration, the diodicity increases by 2% (Di = 1.48) and 34% (Di = 1.96), respectively, compared to when the Tesla integration (Di = 1.45) is used alone. A visual and experimentally weighted analysis finds no signs of backflow. These significant flow characteristics demonstrate their potential usage in many low-cost and portable microfluidic applications.

Insight into continuous glucose monitoring: from medical basics to commercialized devices

According to the latest statistics, more than 537 million people around the world struggle with diabetes and its adverse consequences. As well as acute risks of hypo- or hyper- glycemia, long-term vascular complications may occur, including coronary heart disease or stroke, as well as diabetic nephropathy leading to end-stage disease, neuropathy or retinopathy. Therefore, there is an urgent need to improve diabetes management to reduce the risk of complications but also to improve patient's quality life. The impact of continuous glucose monitoring (CGM) is well recognized, in this regard. The current review aims at introducing the basic principles of glucose sensing, including electrochemical and optical detection, summarizing CGM technology, its requirements, advantages, and disadvantages. The role of CGM systems in the clinical diagnostics/personal testing, difficulties in their utilization, and recommendations are also discussed. In the end, challenges and prospects in future CGM systems are discussed and non-invasive, wearable glucose biosensors are introduced. Though the scope of this review is CGMs and provides information about medical issues and analytical principles, consideration of broader use will be critical in future if the right systems are to be selected for effective diabetes management.

Graphene Nanoribbon Field Effect Transistor Simulations for the Detection of Sugar Molecules: Semi-Empirical Modeling

Graphene has remarkable characteristics that make it a potential candidate for optoelectronics and electronics applications. Graphene is a sensitive material that reacts to any physical variation in its environment. Due to its extremely low intrinsic electrical noise, graphene can detect even a single molecule in its proximity. This feature makes graphene a potential candidate for identifying a wide range of organic and inorganic compounds. Graphene and its derivatives are considered one of the best materials to detect sugar molecules due to their electronic properties. Graphene has low intrinsic noise, making it an ideal membrane for detecting low concentrations of sugar molecules. In this work, a graphene nanoribbon field effect transistor (GNR-FET) is designed and utilized to identify sugar molecules such as fructose, xylose, and glucose. The variation in the current of the GNR-FET in the presence of each of the sugar molecules is utilized as the detection signal. The designed GNR-FET shows a clear change in the device density of states, transmission spectrum, and current in the presence of each of the sugar molecules. The simulated sensor is made of a pair of metallic zigzag graphene nanoribbons (ZGNR) joint via a channel of armchair graphene nanoribbon (AGNR) and a gate. The Quantumwise Atomistix Toolkit (ATK) is used to design and conduct the nanoscale simulations of the GNR-FET. Semi-empirical modeling, along with non-equilibrium Green's functional theory (SE + NEGF), is used to develop and study the designed sensor. This article suggests that the designed GNR transistor has the potential to identify each of the sugar molecules in real time with high accuracy.

Comparative assessment of blood glucose monitoring techniques: a review

Monitoring blood glucose levels is a vital indicator of diabetes mellitus management. The mainstream techniques of glucometers are invasive, painful, expensive, intermittent, and time-consuming. The ever-increasing number of global diabetic patients urges the development of alternative non-invasive glucose monitoring techniques. Recent advances in electrochemical biosensors, biomaterials, wearable sensors, biomedical signal processing, and microfabrication technologies have led to significant research and ideas in elevating the patient's life quality. This review provides up-to-date information about the available technologies and compares the advantages and limitations of invasive and non-invasive monitoring techniques. The scope of measuring glucose concentration in other bio-fluids such as interstitial fluid (ISF), tears, saliva, and sweat are also discussed. The high accuracy level of invasive methods in measuring blood glucose concentrations gives them superiority over other methods due to lower average absolute error between the detected glucose concentration and reference values. Whereas minimally invasive, and non-invasive techniques have the advantages of continuous and pain-free monitoring. Various blood glucose monitoring techniques have been evaluated based on their correlation to blood, patient-friendly, time efficiency, cost efficiency, and accuracy. Finally, this review also compares the currently available glucose monitoring devices in the market.

A modelling approach to hepatic glucose production estimation

Stable isotopes are currently used to measure glucose fluxes responsible for observed glucose concentrations, providing information on hepatic and peripheral insulin sensitivity. The determination of glucose turnover, along with fasting and postprandial glucose concentrations, is relevant for inferring insulin sensitivity levels. At equilibrium (e.g. during the fasting state) the rate of glucose entering the circulation equals its rate of disappearance from the circulation. If under these conditions tracer is infused at a constant rate and Specific Activity (SA) or Tracer to Tracee (TTR) ratio is computed, the Rate of Appearance (RA) equals the Rate of Disappearance (RD) and equals the ratio between infusion rate and TTR or SA. In the post-prandial situation or during perturbation studies, however, estimation of RA and RD becomes more complex because they are not necessarily equal and, furthermore, may vary over time due to gastric emptying, glucose absorption, appearance of ingested or infused glucose, variations of EGP and glucose disappearance. Up to now, the most commonly used approach to compute RA, RD and EGP has been the single-pool model by Steele. Several authors, however, report pitfalls in the use of this method, such as "paradoxical" increase in EGP immediately after meal ingestion and "negative" rates of EGP. Different attempts have been made to reduce the impact of these errors, but the same problems are still encountered. In the present work a completely different approach is proposed, where cold and labeled [6, 6-2H2] glucose observations are simultaneously fitted and where both RD and EGP are represented by simple but reasonable functions. As an example, this approach is applied to an intra-venous experiment, where cold glucose is infused at variable rates to reproduce a desired glycaemic time-course. The goal of the present work is to show that appropriate, if simple, modelling of the whole infusion procedure together with the underlying physiological system allows robust estimation of EGP with single-tracer administration, without the artefacts produced by the Steele method.

From islet of Langerhans transplantation to the bioartificial pancreas

Type 1 diabetes is a disease resulting from autoimmune destruction of the insulin-producing beta cells in the pancreas. When type 1 diabetes develops into severe secondary complications, in particular end-stage nephropathy, or life-threatening severe hypoglycemia, the best therapeutic approach is pancreas transplantation, or more recently transplantation of the pancreatic islets of Langerhans. Islet transplantation is a cell therapy procedure, that is minimally invasive and has a low morbidity, but does not display the same rate of functional success as the more invasive pancreas transplantation because of suboptimal engraftment and survival. Another issue is that pancreas or islet transplantation (collectively known as beta cell replacement therapy) is limited by the shortage of organ donors and by the need for lifelong immunosuppression to prevent immune rejection and recurrence of autoimmunity. A bioartificial pancreas is a construct made of functional, insulin-producing tissue, embedded in an anti-inflammatory, immunomodulatory microenvironment and encapsulated in a perm-selective membrane allowing glucose sensing and insulin release, but isolating from attacks by cells of the immune system. A successful bioartificial pancreas would address the issues of engraftment, survival and rejection. Inclusion of unlimited sources of insulin-producing cells, such as xenogeneic porcine islets or stem cell-derived beta cells would further solve the problem of organ shortage. This article reviews the current status of clinical islet transplantation, the strategies aiming at developing a bioartificial pancreas, the clinical trials conducted in the field and the perspectives for further progress.

In Silico Investigation of SNR and Dermis Sensitivity for Optimum Dual-Channel Near-Infrared Glucose Sensor Designs for Different Skin Colors

Diabetes is a serious health condition that requires patients to regularly monitor their blood glucose level, making the development of practical, compact, and non-invasive techniques essential. Optical glucose sensors-and, specifically, NIR sensors-have the advantages of being non-invasive, compact, inexpensive, and user-friendly devices. However, these sensors have low accuracy and are yet to be adopted by healthcare providers. In our previous work, we introduced a non-invasive dual-channel technique for NIR sensors, in which a long channel is utilized to measure the glucose level in the inner skin (dermis) layer, while a short channel is used to measure the noise signal of the superficial skin (epidermis) layer. In this work, we investigated the use of dual-NIR channels for patients with different skin colors (i.e., having different melanin concentrations). We also adopted a Monte Carlo simulation model that takes into consideration the differences between different skin layers, in terms of blood content, water content, melanin concentration in the epidermis layer, and skin optical proprieties. On the basis of the signal-to-noise ratio, as well as the sensitivities of both the epidermis and dermis layers, we suggest the selection of wavelengths and source-to-detector separation for optimal NIR channels under different skin melanin concentrations. This work facilitates the improved design of a compact and non-invasive NIR glucose sensor that can be utilized by patients with different skin colors.

Exploring Minimally Invasive Approach to Define Stages of Type 1 Diabetes Remotely

Objective: New methods are pivotal in accurately predicting, monitoring, and diagnosing the clinical manifestation of type 1 diabetes (T1D) in high-risk children. Continuous glucose monitoring (CGM) is a valuable tool for patients with T1D, but there is still a knowledge gap regarding its utility in the prediction of diabetes. The current study explored whether 10-day CGM or CGM during an oral glucose tolerance test (OGTT) performed in the laboratory or at home (home-OGTT) could be accurate in detecting stages of T1D. Research Design and Methods: Forty-six subjects 4-25 years of age carrying genetic risk for T1D were recruited and classified into the following groups: islet autoantibody (IAb) negative, one IAb, and stages 1-3 of T1D, based on the laboratory OGTT and IAb results at baseline. A 10-day CGM was initiated before the OGTT. Results: In this study, we showed that CGM was sensitive in detecting asymptomatic individuals at stage 3, and dysglycemic individuals in stage 2 of T1D both during OGTT and the 10-day period. CGM also showed significant differences in several variables during the 10-day sensoring among individuals at different stages of T1D. Furthermore, CGM showed different OGTT profiles and detected significantly more abnormal OGTT results when compared with plasma glucose. Conclusions: CGM together with home-OGTT could detect stages of T1D and offer an alternative method to confirm normoglycemia in high-risk individuals.

Wearable flexible body matched electromagnetic sensors for personalized non-invasive glucose monitoring

This work introduces novel body-matched, vasculature-inspired, quasi-antenna-arrays that act as electromagnetic sensors to instantaneously, continuously, and wirelessly sense glucose variations in the bloodstream. The proposed sensors are personalized, leverage electromagnetic waves, and are coupled with a custom machine-learning-based signal-processing module. These sensors are flexible, and embedded in wearable garments such as socks, which provide conformity to curved skin surfaces and movement resilience. The entire wearable system is calibrated against temperature, humidity, and movement resulting in high accuracy in glucose variations tracking. In-Vivo experiments on diabetic rats and pigs exhibit a 100% diagnostic accuracy over a wide range of glucose variations. Human trials on patients with diabetes and healthy individuals reveal a clinical accuracy of continuous glucose monitoring of 99.01% in twenty-eight subjects who underwent Oral Glucose Tolerance Tests. Hence, our approach ensures the continuous tracking of glucose variations from hypo-to-hyper glycemic levels with great fidelity.

Feasibility and Safety of Continuous Glucose Monitoring in Infants at Risk of Hypoglycemia in a Rooming-in Setting

Background:Screening of neonatal hypoglycemia uses currently intermittent blood sampling. Continuous glucose monitoring (CGM) allows for tighter glucose control and better comfort for newborns and parents. CGM has previously been used in intensive care setting or blinded to clinicians. Our pilot study uses CGM in real time in rooming-in setting. Methods: CGM was attached within first two hours of life. Low glucose readings were verified to prevent overtreatment. Pairs of sensor readings and corresponding blood glucose measurements were assessed retrospectively. Neurodevelopmental evaluation was performed at 24 months. Results: 44 infants were enrolled. Three had verified hypoglycemia found due to CGM. No patient was below 2 standard deviations in any components of Bayley scales. Median scores were: Cognitive 100, language 86, motor 94. Conclusion: Use of CGM in a rooming-in environment is safe from clinical and neurodevelopmental point of view. Randomized trials are needed to evaluate superiority in longer term outcomes.

Practical aspects of diabetes technology use: Continuous glucose monitors, insulin pumps, and automated insulin delivery systems

There have been tremendous advances in diabetes technology in the last decade. Continuous glucose monitors (CGM), insulin pumps, and automated insulin delivery (AID) systems aim to improve glycemic control while simultaneously decreasing the burden of diabetes management. Although diabetes technologies have been shown to decrease both hypoglycemia and hyperglycemia and to improve health-related quality of life in individuals with type 1 diabetes, the impact of these devices in individuals with cystic fibrosis-related diabetes (CFRD) is less clear. There are unique aspects of CFRD, including the different underlying pathophysiology and unique lived health care experience and comorbidities, that likely affect the use, efficacy, and uptake of diabetes technology in this population. Small studies suggest that CGM is accurate and may be helpful in guiding insulin therapy for individuals with CFRD. Insulin pump use has been linked to improvements in lean body mass and hemoglobin A1c among adults with CFRD. A recent pilot study highlighted the promise of AID systems in this population. This article provides an overview of practical aspects of diabetes technology use and device limitations that clinicians must be aware of in caring for individuals with CF and CFRD. Cost and limited insurance coverage remain significant barriers to wider implementation of diabetes technology use among patients with CFRD. Future studies exploring strategies to improve patient and CF provider education about these devices and studies showing the effectiveness of these technologies on health and patient-reported outcomes may lead to improved insurance coverage and increased rates of uptake and sustained use of these technologies in the CFRD community.

Phenomenological-based model of glucose transport from liver to abdominal subcutaneous adipose tissue

BACKGROUND

A good treatment for type 1 diabetes mellitus (T1DM) requires accurate measurements of blood glucose levels. Continuous glucose monitors (CGM) measure the glucose concentration in the interstitial fluid of the abdominal subcutaneous adipose tissue. However, glucose measured in the abdominal interstitial fluid does not represent blood glucose concentrations accurately due to the complex blood transport through the body and glucose diffusion in interstitial fluid.

METHODS

To gain insight into this problem, a phenomenological-based semiphysical model (PBSM) of glucose transport by volumetric flow and diffusion from the bloodstream to interstitial fluid was constructed. A published 10-step modeling procedure was used to obtain a model for glucose transport time through the blood vessels and from the blood capillaries to the interstitial fluid, glucose diffusion within the interstitial fluid, and glucose diffusion through the semipermeable coating of the sensor needle. For this model, a healthy person is considered at rest with average parameters.

RESULTS

The simulations performed using the PBSM allow obtaining the glucose transport time from the liver to the sensor needle. In this way, it is possible to reconstruct an accurate dynamic measurement of blood glucose from the measurements in the interstitial fluid of the abdominal subcutaneous adipose tissue.

CONCLUSIONS

PBSMs with parameters interpretability illustrate the connection of glucose concentrations in the interstitial fluid with that currently in the blood. Implementing this model in a CGM will result in more reliable measurements of blood glucose levels for T1DM treatment.

Microfluidic chip connected to porous microneedle array for continuous ISF sampling

Minimally invasive biosensing using microneedles (MNs) is a desirable technology for continuous healthcare monitoring. Among a wide range of MNs, porous MNs are expected to be applied for sampling of interstitial fluids (ISF) by connecting the internal tissue to external measurement devices. In order to realize a continuous measurement of biomarkers in ISF through porous MNs, their integration with a microfluidic chip is a promising approach due to its applicability to micro-total analysis system (μTAS) technology. In this study, we developed a fluidic system to directly interface porous MNs to a microfluidic chip consisting of a capillary pump for the continuous sampling of ISF. The porous and flexible MNs made of PDMS are connected to the microfluidic chip fabricated by standard microelectro-mechanical system (MEMS) processes, showing a continuous flow of phosphate buffered saline (PBS). The developed device will lead to the minimally invasive and continuous biosampling for long-term healthcare monitoring.

A personalized blood glucose level prediction model with a fine-tuning strategy: A proof-of-concept study

BACKGROUND

The accurate prediction of blood glucose (BG) level is still a challenge for diabetes management. This is due to various factors such as diet, personal physiological characteristics, stress, and activities influence changes in BG level. To develop an accurate BG level predictive model, we propose a personalized model based on a convolutional neural network (CNN) with a fine-tuning strategy.

METHODS

We utilized continuous glucose monitoring (CGM) datasets from 1052 professional CGM sessions and split them into three groups according to type 1, type 2, and gestational diabetes mellitus (T1DM, T2DM, and GDM, respectively). During the preprocessing, only CGM data points were utilized, and future BG levels of four different prediction horizons (PHs, 15, 30, 45, and 60 min) were used as output. In training, we trained a general CNN and a multi-output random forest regressor using a hold-out method for each group. Next, we developed two personalized models: (1) by fine-tuning the general CNN on partial sample points of each CGM dataset, and (2) by learning a CNN from scratch on the points.

RESULTS

For all groups, the fine-tuned CNN showed the lowest average root mean squared error, average mean absolute percentage error, highest average time gain (PH = 15 and 60 min in T1DM) and highest percentage in region A of Clarke error grid analysis at all PHs. In the performance comparison between the fine-tuned CNN and other models, we found that the fine-tuned CNN improved the performance of the general CNN in most cases and outperformed the scratch CNN at all PHs in all groups, making the fine-tuning strategy was useful for accurate BG level prediction. We analyzed all cases of four predictive patterns in each group, and found that the input BG level trend and the BG level at the time of prediction were related to the future BG level trend.

CONCLUSIONS

We demonstrated the efficacy of the fine-tuning method in a large number of CGM datasets and analyzed the four predictive patterns. Therefore, we believe that the proposed method will significantly contribute to the development of an accurate personalized model and the analysis for its predictions.

A metabolic function of the hippocampal sharp wave-ripple

The hippocampus has previously been implicated in both cognitive and endocrine functions1-15. We simultaneously measured electrophysiological activity from the hippocampus and interstitial glucose concentrations in the body of freely behaving rats to identify an activity pattern that may link these disparate functions of the hippocampus. Here we report that clusters of sharp wave-ripples recorded from the hippocampus reliably predicted a decrease in peripheral glucose concentrations within about 10 min. This correlation was not dependent on circadian, ultradian or meal-triggered fluctuations, could be mimicked with optogenetically induced ripples in the hippocampus (but not in the parietal cortex) and was attenuated to chance levels by pharmacogenetically suppressing activity of the lateral septum, which is the major conduit between the hippocampus and the hypothalamus. Our findings demonstrate that a function of the sharp wave-ripple is to modulate peripheral glucose homeostasis, and offer a mechanism for the link between sleep disruption and blood glucose dysregulation in type 2 diabetes16-18.

Catalytic effects of magnetic and conductive nanoparticles on immobilized glucose oxidase in skin sensors

Wearable skin sensors is a promising technology for real-time health care monitoring. They are of particular interest for monitoring glucose in diabetic patients. The concentration of glucose in sweat can be more than two orders of magnitude lower than in blood. In consequence, the scientific and technological efforts are focused in developing new concepts to enhance the sensitivity, decrease the limit of detection (LOD) and reduce the response time (RT) of glucose skin sensors. This work explores the effect of adsorbed superparamagnetic magnetite nanoparticles (MNPs) and conductive nanoparticles (CNPs) on carbon nanotube substrates (CNTs) used to immobilize glucose oxidase enzyme in the working electrode of skin sensors. MNPs and CNPs are made of magnetite and gold, respectively. The performance of the sensors was tested in standard buffer solution, artificial sweat, fresh sweat and on the skin of a healthy volunteer during an exercise session. In the case of artificial sweat, the presence of MNPs accelerated the RT from 7 to 5 s at the expense of increasing the LOD from 0.017 to 0.022 mM with slight increase of the sensitivity from 4.90 to 5.09μAm M^-1cm^-2. The presence of CNPs greatly accelerated the RT from 7 to 2 s and lowered the LOD from 0.017 to 0.014 mM at the expense of a great diminution of the sensitivity from 4.90 to 4.09μAm M^-1cm^-2. These effects were explained mechanistically by analyzing the changes in the concentration of free oxygen and electrons promoted by MNPs and CNPs in the CNTs and its consequences on the the glucose oxidation process.

A review of biomarkers in the context of type 1 diabetes: Biological sensing for enhanced glucose control

As wearable healthcare monitoring systems advance, there is immense potential for biological sensing to enhance the management of type 1 diabetes (T1D). The aim of this work is to describe the ongoing development of biomarker analytes in the context of T1D. Technological advances in transdermal biosensing offer remarkable opportunities to move from research laboratories to clinical point-of-care applications. In this review, a range of analytes, including glucose, insulin, glucagon, cortisol, lactate, epinephrine, and alcohol, as well as ketones such as beta-hydroxybutyrate, will be evaluated to determine the current status and research direction of those analytes specifically relevant to T1D management, using both in-vitro and on-body detection. Understanding state-of-the-art developments in biosensing technologies will aid in bridging the gap from bench-to-clinic T1D analyte measurement advancement.

Glucose Level Sensing Using Single Asymmetric Split Ring Resonator

In this article, a biosensor composed of a single metamaterial asymmetric resonator is specifically designed for sensing the glucose level of 1 µL of solution. The resonator has two gaps, and one of them ends with a semicircle shape on which the glucose solution is placed. This design helps in confining the drops of glucose solutions in a specific area where the field is maximally confined in order to enhance the electromagnetic wave-matter interaction. Six samples of glucose solutions with concentrations that cover hypoglycemia, normal and hyperglycemia conditions that vary from around 41 to 312 mg/dL were prepared and examined by this biosensor. The resonance frequency redshift was used as a measure of the changes in the glucose level of the solutions. Without glucose solution, an excellent agreement between the measured and simulated transmission amplitude was observed. The increase in glucose concentrations exhibited clear and noticeable redshifts in the resonance frequency. This biosensor revealed a 0.9997 coefficient of determination, which implies an excellent prediction fitting model. More importantly, a sensitivity of 438 kHz/(mg/dL) was observed over the range of concentrations of the aqueous solution.

Comparison between a flash glucose monitoring system and a portable blood glucose meter for monitoring dogs with diabetes mellitus

Background

Flash glucose monitoring system (FGMS; FreeStyle Libre) was recently validated for use in diabetic dogs (DD). It is not known if this system is clinically useful in monitoring DD.

Objective

To compare the clinical utility of FGMS against blood glucose curves (BGCs) obtained with a portable blood glucose meter (PBGM) in monitoring DD.

Animals

Twenty dogs with diabetes mellitus.

Methods

Prospective study. Dogs with diabetes mellitus on insulin treatment for at least 1 month were included. Comparisons of insulin dose recommendations based on the in‐hospital GCs acquired using FGMS and a PBGM, consecutive‐day interstitial GCs (IGCs) acquired at home using the FGMS, and consecutive‐day, home vs hospital IGCs acquired using the FGMS were made using concordance analysis.

Results

There was good concordance between insulin dose recommendations based on FGMS and PBGM generated GCs and IGCs obtained in the 2 different environments on 2 consecutive days, but almost absent concordance between IGCs obtained on 2 consecutive days at home. Glucose nadirs were detected in 34/43 (79%) of Ambulatory Glucose Profile (AGP) reports of the FGMS. In comparison, concordant glucose nadirs were identified in 14/34 (41%) BGCs using PBGM. The individual FGMS scans and PBGM identified 60% and 9% of low IG/hypoglycemic episodes, respectively.

Conclusions and Clinical Importance

Insulin dose adjustments based on BGCs can be suboptimal. The FGMS allows a more accurate identification of the glucose nadirs and hypoglycemic episodes compared to the use of a PBGM and assessment of day‐to‐day variations in glycemic control.

The Diabits App for Smartphone-Assisted Predictive Monitoring of Glycemia in Patients With Diabetes: Retrospective Observational Study

BACKGROUND

Diabetes mellitus, which causes dysregulation of blood glucose in humans, is a major public health challenge. Patients with diabetes must monitor their glycemic levels to keep them in a healthy range. This task is made easier by using continuous glucose monitoring (CGM) devices and relaying their output to smartphone apps, thus providing users with real-time information on their glycemic fluctuations and possibly predicting future trends.

OBJECTIVE

This study aims to discuss various challenges of predictive monitoring of glycemia and examines the accuracy and blood glucose control effects of Diabits, a smartphone app that helps patients with diabetes monitor and manage their blood glucose levels in real time.

METHODS

Using data from CGM devices and user input, Diabits applies machine learning techniques to create personalized patient models and predict blood glucose fluctuations up to 60 min in advance. These predictions give patients an opportunity to take pre-emptive action to maintain their blood glucose values within the reference range. In this retrospective observational cohort study, the predictive accuracy of Diabits and the correlation between daily use of the app and blood glucose control metrics were examined based on real app users' data. Moreover, the accuracy of predictions on the 2018 Ohio T1DM (type 1 diabetes mellitus) data set was calculated and compared against other published results.

RESULTS

On the basis of more than 6.8 million data points, 30-min Diabits predictions evaluated using Parkes Error Grid were found to be 86.89% (5,963,930/6,864,130) clinically accurate (zone A) and 99.56% (6,833,625/6,864,130) clinically acceptable (zones A and B), whereas 60-min predictions were 70.56% (4,843,605/6,864,130) clinically accurate and 97.49% (6,692,165/6,864,130) clinically acceptable. By analyzing daily use statistics and CGM data for the 280 most long-standing users of Diabits, it was established that under free-living conditions, many common blood glucose control metrics improved with increased frequency of app use. For instance, the average blood glucose for the days these users did not interact with the app was 154.0 (SD 47.2) mg/dL, with 67.52% of the time spent in the healthy 70 to 180 mg/dL range. For days with 10 or more Diabits sessions, the average blood glucose decreased to 141.6 (SD 42.0) mg/dL (P<.001), whereas the time in euglycemic range increased to 74.28% (P<.001). On the Ohio T1DM data set of 6 patients with type 1 diabetes, 30-min predictions of the base Diabits model had an average root mean square error of 18.68 (SD 2.19) mg/dL, which is an improvement over the published state-of-the-art results for this data set.

CONCLUSIONS

Diabits accurately predicts future glycemic fluctuations, potentially making it easier for patients with diabetes to maintain their blood glucose in the reference range. Furthermore, an improvement in glucose control was observed on days with more frequent Diabits use.

Are prolonged sitting and sleep restriction a dual curse for the modern workforce? a randomised controlled trial protocol

INTRODUCTION

Prolonged sitting and inadequate sleep are a growing concern in society and are associated with impairments to cardiometabolic health and cognitive performance. However, the combined effect of prolonged sitting and inadequate sleep on measures of health and cognitive performance are unknown. In addition, the circadian disruption caused by shiftwork may further impact workers' cardiometabolic health and cognitive performance. This protocol paper outlines the methodology for exploring the impact of simultaneous exposure to prolonged sitting, sleep restriction and circadian disruption on cardiometabolic and cognitive performance outcomes.

METHODS AND ANALYSIS

This between-subjects study will recruit 208 males and females to complete a 7-day in-laboratory experimental protocol (1 Adaptation Day, 5 Experimental Days and 1 Recovery Day). Participants will be allocated to one of eight conditions that include all possible combinations of the following: dayshift or nightshift, sitting or breaking up sitting and 5 hour or 9 hour sleep opportunity. On arrival to the laboratory, participants will be provided with a 9 hour baseline sleep opportunity (22:00 to 07:00) and complete five simulated work shifts (09:00 to 17:30 in the dayshift condition and 22:00 to 06:30 in the nightshift condition) followed by a 9 hour recovery sleep opportunity (22:00 to 07:00). During the work shifts participants in the sitting condition will remain seated, while participants in the breaking up sitting condition will complete 3-min bouts of light-intensity walking every 30 mins on a motorised treadmill. Sleep opportunities will be 9 hour or 5 hour. Primary outcome measures include continuously measured interstitial blood glucose, heart rate and blood pressure, and a cognitive performance and self-perceived capacity testing battery completed five times per shift. Analyses will be conducted using linear mixed models.

ETHICS AND DISSEMINATION

The CQUniversity Human Ethics Committee has approved this study (0000021914). All participants who have already completed the protocol have provided informed consent. Study findings will be disseminated via scientific publications and conference presentations.

TRIAL REGISTRATION DETAILS

This study has been registered on Australian New Zealand Clinical Trials Registry (12619001516178) and is currently in the pre-results stage.

Electrogenetic cellular insulin release for real-time glycemic control in type 1 diabetic mice

Sophisticated devices for remote-controlled medical interventions require an electrogenetic interface that uses digital electronic input to directly program cellular behavior. We present a cofactor-free bioelectronic interface that directly links wireless-powered electrical stimulation of human cells to either synthetic promoter–driven transgene expression or rapid secretion of constitutively expressed protein therapeutics from vesicular stores. Electrogenetic control was achieved by coupling ectopic expression of the L-type voltage-gated channel CaV1.2 and the inwardly rectifying potassium channel Kir2.1 to the desired output through endogenous calcium signaling. Focusing on type 1 diabetes, we engineered electrosensitive human β cells (Electroβ cells). Wireless electrical stimulation of Electroβ cells inside a custom-built bioelectronic device provided real-time control of vesicular insulin release; insulin levels peaked within 10 minutes. When subcutaneously implanted, this electrotriggered vesicular release system restored normoglycemia in type 1 diabetic mice.

Perioperative Considerations for Evolving Artificial Pancreas Devices

Type 1 diabetes mellitus is a lifelong condition. It requires intensive patient involvement including frequent glucose measurements and subcutaneous insulin dosing to provide optimal glycemic control to decrease short- and long-term complications of diabetes mellitus without causing hypoglycemia. Variations in insulin pharmacokinetics and responsiveness over time in addition to illness, stress, and a myriad of other factors make ideal glucose control a challenge. Control-to-range and control-to-target artificial pancreas devices (closed-loop artificial pancreas devices [C-APDs]) consist of a continuous glucose monitor, response algorithm, and insulin delivery device that work together to automate much of the glycemic management for an individual while continually adjusting insulin dosing toward a glycemic target. In this way, a C-APD can improve glycemic control and decrease the rate of hypoglycemia. The MiniMed 670G (Medtronic, Fridley, MN) system is currently the only Food and Drug Administration-cleared C-APD in the United States. In this system, insulin delivery is continually adjusted to a glucose concentration, and the patient inputs meal-time information to modify insulin delivery as needed. Data thus far suggest improved glycemic control and decreased hypoglycemic events using the system, with decreased need for patient self-management. Thus, the anticipated use of these devices is likely to increase dramatically over time. There are limited case reports of safe intraoperative use of C-APDs, but the Food and Drug Administration has not cleared any device for such use. Nonetheless, C-APDs may offer an opportunity to improve patient safety and outcomes through enhanced intraoperative glycemic control. Anesthesiologists should become familiar with C-APD technology to help develop safe and effective protocols for their intraoperative use. We provide an overview of C-APDs and propose an introductory strategy for intraoperative study of these devices.

Monitoring of Pediatric Type 1 Diabetes

Regular self-monitoring of blood glucose levels, and ketones when indicated, is an essential component of type 1 diabetes (T1D) management. Although fingerstick blood glucose monitoring has been the standard of care for decades, ongoing rapid technological developments have resulted in increasingly widespread use of continuous glucose monitoring (CGM). This article reviews recommendations for self-monitoring of glucose and ketones in pediatric T1D with particular emphasis on CGM and factors that impact the accuracy and real-world use of this technology.

Fibrotic Encapsulation Is the Dominant Source of Continuous Glucose Monitor Delays

Continuous glucose monitor (CGM) readings are delayed relative to blood glucose, and this delay is usually attributed to the latency of interstitial glucose levels. However, CGM-independent data suggest rapid equilibration of interstitial glucose. This study sought to determine the loci of CGM delays. Electrical current was measured directly from CGM electrodes to define sensor kinetics in the absence of smoothing algorithms. CGMs were implanted in mice, and sensor versus blood glucose responses were measured after an intravenous glucose challenge. Dispersion of a fluorescent glucose analog (2-NBDG) into the CGM microenvironment was observed in vivo using intravital microscopy. Tissue deposited on the sensor and nonimplanted subcutaneous adipose tissue was then collected for histological analysis. The time to half-maximum CGM response in vitro was 35 ± 2 s. In vivo, CGMs took 24 ± 7 min to reach maximum current versus 2 ± 1 min to maximum blood glucose (P = 0.0017). 2-NBDG took 21 ± 7 min to reach maximum fluorescence at the sensor versus 6 ± 6 min in adipose tissue (P = 0.0011). Collagen content was closely correlated with 2-NBDG latency (R = 0.96, P = 0.0004). Diffusion of glucose into the tissue deposited on a CGM is substantially delayed relative to interstitial fluid. A CGM that resists fibrous encapsulation would better approximate real-time deviations in blood glucose.

Reporting of hypoglycaemia in clinical trials of basal insulins: A need for consensus

Hypoglycaemia is a common side-effect of diabetes therapies, particularly insulin, and imposes a substantial burden on individuals and healthcare systems. Consequently, regulatory approval of newer basal insulin (BI) therapies has relied on demonstration of a balance between achievement of good glycaemic control and less hypoglycaemia. Randomized controlled trials (RCTs) are the gold standard for assessing efficacy and safety, including hypoglycaemia risk, of BIs and are invaluable for obtaining regulatory approval. However, their highly selected patient populations and their conditions lead to results that may not be representative of real-life situations. Real-world evidence (RWE) studies are more representative of clinical practice, but they also have limitations. As such, data both from RCTs and RWE studies provide a fuller picture of the hypoglycaemia risk with BI therapies. However, substantial differences exist in the way hypoglycaemia is reported across these studies, which confounds comparisons of hypoglycaemia frequency among different BIs. This problem is ongoing and persists in recent trials of second-generation BI analogues. Although they provide a lower risk of hypoglycaemia when compared with earlier BIs, they do not eliminate it. This review describes differences in the way hypoglycaemia is reported across RCTs and RWE studies of second-generation BI analogues and examines potential reasons for these differences. For studies of BIs, there is a need to standardize aspects of design, analysis and methods of reporting to better enable interpretation of the efficacy and safety of such insulins among studies; such aspects include length of follow-up, glycaemic targets, hypoglycaemia definitions and time intervals for determining nocturnal events.

Glucose Variations During Driving in People With Type 1 Diabetes Using a Continuous Glucose Monitoring System

OBJECTIVE

Hypoglycemic events during driving are life-threatening complications in people with type 1 diabetes (T1D). While preliminary studies showed increased glucose demand in driving simulations, we investigated interstitial fluid (ISF) glucose when driving under real-life circumstances.

RESEARCH DESIGN AND METHODS

We measured ISF glucose in 10 participants with stable T1D during a 2-h driving course using a continuous glucose monitoring system.

RESULTS

Our data show a driving-associated rise of ISF glucose. Initially increasing glucose was followed by decreasing values. Under control conditions at the same time of the day without driving, no specific glucose changes were observed.

CONCLUSIONS

Real-life driving may have caused an initial glucose increase followed by decreasing glucose values in this cohort with well-controlled T1D. These findings may be limited to the selected study population.

Lag Time Remains with Newer Real-Time Continuous Glucose Monitoring Technology During Aerobic Exercise in Adults Living with Type 1 Diabetes

Background: Real-time continuous glucose monitoring (CGM) devices help detect glycemic excursions associated with exercise, meals, and insulin dosing in patients with type 1 diabetes (T1D). However, the delay between interstitial and blood glucose may result in CGM underestimating the true change in glycemia during activity. The purpose of this study was to examine CGM discrepancies during exercise and the meal postexercise versus self-monitoring of blood glucose (SMBG). Methods: Seventeen adults with T1D using insulin pump therapy and CGM completed 60 min of aerobic exercise on three occasions. A standardized meal was given 30 min postexercise. SMBG was measured during exercise and in recovery using OmniPod® Personal Diabetes Manager (PDM; Insulet, Billerica, MA) with built-in glucose meter (FreeStyle; Abbott Laboratories, Abbott Park, IL), while CGM was measured with Dexcom G4® with 505 algorithm (n = 4) or G5® (n = 13), which were calibrated with subjects' own PDM. Results: SMBG showed a large drop in glycemia during exercise, while CGM showed a lag of 12 ± 11 (mean ± standard deviation) minutes and bias of -7 ± 19 mg/dL/min during activity. Mean absolute relative difference (MARD) for CGM versus SMBG was 13 (6-22)% [median (interquartile range)] during exercise and 8 (5-14)% during mealtime. Clarke error grids showed CGM values were in zones A and B 94%-99% of the time for SMBG. Conclusion: In summary, the drop in CGM lags behind the drop in blood glucose during prolonged aerobic exercise by 12 ± 11 min, and MARD increases to 13 (6-22)% during exercise as well. Therefore, if hypoglycemia is suspected during exercise, individuals should confirm glucose levels with a capillary glucose measurement.

Higher blood glucose and larger fluctuations detected postoperatively using continuous glucose monitoring: a preliminary study following total knee or hip arthroplasty

BACKGROUND

The control of diabetes mellitus (DM) should help reduce the incidence of periprosthetic joint infection (PJI). Self-monitoring of blood glucose (SMBG) concentration is usually undertaken at fixed time-points. Therefore, the extent of postoperative blood glucose fluctuation might be underestimated. To provide a more comprehensive assessment, continuous glucose monitoring (CGM) is beginning to be used. However, no previous studies have evaluated blood glucose concentrations using CGM following orthopedic surgery. Therefore, the differences between the maximum blood glucose concentrations measured using SMBG and CGM, and the mean amplitude of the glycemic fluctuation in patients with frank diabetes mellitus (DM) or pre-diabetes were evaluated. Blood glucose was measured in 20 patients who had undergone total hip or total knee arthroplasty (12 patients with DM and eight with pre-diabetes). Patients were fitted with a CGM device in the operating room, which was worn for 6 days postoperatively, and used to evaluate blood glucose concentration continuously. SMBG was performed simultaneously for the same period.

RESULTS

The mean difference between the maximum blood glucose concentrations measured using SMBG and CGM was 25.0 ± 20.3 mg/dl (range, - 17 to 81 mg/dl), with the concentrations measured using CGM tending to be higher than those measured using SMBG (P = 0.04). Blood glucose concentrations measured using CGM tended to be higher than those measured using SMBG until postoperative day 2, and to decrease gradually after postoperative day 4. There were no significant differences in the standard deviation of the blood glucose concentrations between the two groups.

CONCLUSIONS

Blood glucose concentrations > 200 mg/dl and larger fluctuations were more frequently recorded using CGM than SMBG, especially until postoperative day 2. Thus, CGM is more useful for the identification of high blood glucose concentrations and larger fluctuations. However, this information was not provided in real time.

The barriers against initiating insulin therapy among patients with diabetes living in Yazd, Iran

INTRODUCTION

The decision to start insulin therapy is often difficult. Determining the barriers against insulin therapy initiation can facilitate care and treatment strategies. The aim of this study was to evaluate the barriers against initiating insulin therapy among patients with diabetes living in Yazd, Iran.

METHODS

This descriptive study was conducted on 214 patients referred to the Diabetes Center of Yazd University of Medical Sciences in 2015. Participants were randomly selected, and then they completed the insulin noncompliance questionnaire (20 questions). The percentage of adherence and the factors contributing to nonadherence to insulin therapy were analyzed using descriptive statistics, the Kruskal-Wallis test, and the Mann-Whitney test.

RESULTS

The most prevalent reason for insulin therapy refusal was expecting a new method of diabetes treatment (54.7%), followed by requiring someone else to administer the injection (19.2%), fear of needles, cost, traveling (18.7%), and stress/emotional problems (18.2%). Lack of trust in the physician was the least restrictive reason for nonadherence to insulin therapy.

CONCLUSION

The most common reason given for insulin therapy refusal was the lack of adequate education. Therefore, specialized educational interventions can help minimize barriers and improve patients' outcomes.

Continuous glucose monitoring as a screening tool for neonatal hypoglycemia in infants of diabetic mothers

Objective: To assess the plausibility of using the continuous glucose monitoring as a sole source of data for the screening of the neonatal hypoglycemia.Study design: Infants of mothers with diabetes were screened for neonatal hypoglycemia (less than 2.5 mmol/l after 4 h of life). Initial measurement was performed using point of care analyzer. We applied continuous glucose monitoring system subsequently. Infants were monitored up to 5 days or until discharge.Results: Out of 32 infants 11 had postnatal hypoglycemia resolved within 12 h of life. Two infants had hypoglycemia found due to continuous glucose monitoring after 24 h of life when sufficient feeding was established and they did not show any signs of hypoglycemia. We did not have any false negative measurements. No infant showed clinical signs of neonatal hypoglycemia.Conclusions: Continuous glucose monitoring is plausible and safe to use for screening of neonatal hypoglycemia. It operates well within the range that is accepted as safe for neurodevelopment. In addition, it can be used after first day of life where regular screening ends. Limitation of this method is possible alarm negligence of caregivers.

Device and Method for Noninvasive Glucose Assessment

BACKGROUND

Intensive monitoring of blood glucose levels is crucial in diabetes management. This article presents a new device, the TensorTip Combo Glucometer (CoG), developed by Cnoga Medical Ltd, which enables to predict capillary tissue glucose concentration noninvasively.

METHODS

Noninvasive glucose readings usually provide irregular or disordered mathematical manifold over the measurement space. To establish a transfer function, which correctly correlates the noninvasive raw data and the actual invasive glucose level, we suggest a mathematical concept that employs a personal calibration procedure to associate glucose pattern and multiple optical signals derived from tissue response to light emission in the range of visible to IR. The traversed light is detected by a color image sensor to predict the tissue glucose concentration at the fingertip. This article presents the mathematical concept underlying the technology and the requirements for device operation.

RESULTS

The device was clinically evaluated and compared to standard invasive blood glucose monitoring devices in few medical centers and by home users. Based on consensus error grid analysis, more than 98% of the measurements of each study were in zones A (more than 81%) and B (more than 11%). Postmarketing evaluations showed high correlations comparing the CoG to other invasive reference devices.

CONCLUSIONS

The CoG device employs a unique mathematical approach to predict glucose concentrations based on multiple optical signals. The first clinical results indicate that the device may show appropriate agreement with reference methods to be used for pain-free glucose assessment in daily routine.

Evaluation of the FreeStyle® Libre Flash Glucose Monitoring System in Children and Adolescents with Type 1 Diabetes

BACKGROUND/AIMS

The FreeStyle® Libre Flash Glucose Monitoring System (FGM, Abbott) measures glucose concentrations in the interstitial fluid for up to 14 days. It has been approved for use in children aged > 4 years in January 2016. Experience in children is still limited. We evaluated the accuracy and usability of the FGM in children with type 1 diabetes mellitus (DM).

METHODS

67 children with type 1 DM (35 girls), aged 4-18 years, were included. Subjects wore a sensor on the back of their upper arm. For the first 14 days, they regularly measured capillary blood glucose (BG) with their usual BG meter (Accu-Chek® Mobile [ACM], Roche [n = 24]; Contour® Next Link [CNL], Bayer [n = 26]; OneTouch® Verio® IQ [OTV], LifeScan [n = 17]) followed by a sensor glucose (SG) scanning. SG readings were compared to BG measurements by consensus error grid (CEG) analysis; the mean difference (MD), the mean relative difference (MRD), the mean absolute difference (MAD), and the mean absolute relative difference (MARD) were calculated. After 14 days, subjects were asked to fill in a questionnaire on the usability of the FGM.

RESULTS

2,626 SG readings were paired with BG results. FGM readings were highly correlated with BG (r = 0.926, p < 0.001). 80.3% of the data pairs were in zone A (= no effect on clinical action) and 18.4% were in zone B (= altered clinical action with little or no effect on the clinical outcome) of the CEG. Overall MD was +7.5 mg/dL; MD varied with the BG meter: ACM +10.4 mg/dL, CNL +14.2 mg/dL, OTV -3.6 mg/dL (p < 0.001). Overall, MARD was 16.7%. We observed a large interindividual variability in the accuracy parameters. MD and MRD were inversely related to BMI (r = -0.261 [p < 0.05]; r = -0.266 [p < 0.05], respectively). MARD was inversely related to age (r = -0.266 [p < 0.05]). Twenty-nine patients (43.3%) reported sensor problems, mainly early detachment of the sensor. Nonetheless, the usability questionnaire indicated high levels of satisfaction.

CONCLUSIONS

Our results showed a reasonable agreement between the FGM SG readings and capillary BG measurements in children. There was, however, a large interindividual variability. The wearing of the sensor requires special attention. Further studies in children are imperative in order to document the accuracy and safety of the FGM in the paediatric population.

Calibration of Minimally Invasive Continuous Glucose Monitoring Sensors: State-of-The-Art and Current Perspectives

Minimally invasive continuous glucose monitoring (CGM) sensors are wearable medical devices that provide real-time measurement of subcutaneous glucose concentration. This can be of great help in the daily management of diabetes. Most of the commercially available CGM devices have a wire-based sensor, usually placed in the subcutaneous tissue, which measures a "raw" current signal via a glucose-oxidase electrochemical reaction. This electrical signal needs to be translated in real-time to glucose concentration through a calibration process. For such a scope, the first commercialized CGM sensors implemented simple linear regression techniques to fit reference glucose concentration measurements periodically collected by fingerprick. On the one hand, these simple linear techniques required several calibrations per day, with the consequent patient's discomfort. On the other, only a limited accuracy was achieved. This stimulated researchers to propose, over the last decade, more sophisticated algorithms to calibrate CGM sensors, resorting to suitable signal processing, modelling, and machine-learning techniques. This review paper will first contextualize and describe the calibration problem and its implementation in the first generation of CGM sensors, and then present the most recently-proposed calibration algorithms, with a perspective on how these new techniques can influence future CGM products in terms of accuracy improvement and calibration reduction.

Design of non-invasive glucose meter using near-infrared technique

Diabetics need to keep track of their blood glucose level and measure it regularly to determine their insulin dose intake and to ensure that glucose level is always within the normal range. In this article, a system that enables the measurement of blood glucose level non-invasively is designed. This article uses a near infra-red (NIR) transmittance spectroscopy, without drawing blood, puncturing the skin, or causing pain. It involves a light source and light detector circuits positioned on a certain region of the body. The attenuated received infra-red signal by the detector is a measure of the blood glucose level of that region. Data are collected from the receiving circuit and sent to a microcontroller using CoolTerm application, then exporting it to Excel Sheet, in which mean values and graphs are obtained. The performance of the circuit with and without Filtering is examined. A downward pattern was noticed, as the glucose concentration in the solution increased, the voltage output decreased, meaning that a less intensity light was detected by the receiving circuit. An improvement in the accuracy of measurements by 17% was achieved, when a notch filter is implemented to cut the voltage components corresponding to the power line noisy signals.

Acute Glycemic Changes in Brain and Subcutaneous Tissue Measured by Continuous Glucose Monitoring System in Hereditary Hypertriglyceridemic Rat

Parallel glucose measurements in blood and other different tissues give us knowledge about dynamics of glycemia changes, which depend on vascularization, distribution space and local utilization by tissues. Such information is important for the understanding of glucose homeostasis and regulation. The aim of our study was to determine the time-lag between blood, brain, and adipose tissue during rapid glucose changes in a male hHTG rat (n=15). The CGMS sensor Guardian RT (Minimed/Medtronic, USA) was inserted into the brain and into the abdominal subcutaneous tissue. Fixed insulin and variable rate of glucose infusion was used to maintain euglycemia during sensor calibration period. At 0 min, 0.5 g/kg of bolus of glucose was administered, and at 50 min, 5 IU/kg of bolus of insulin was administered. Further glucose and insulin infusion was stopped at this time. The experiment was finished at 130 min and animals were euthanized. The time-shift between glycemia changes in blood, brain, and subcutaneous tissue was calculated by identification of the ideal correlation function. Moreover, the time to achieve 90 % of the maximum glucose excursion after intervention (T90) was measured to compare our data with the literature. The time-lag blood vs. brain and blood vs. subcutaneous tissue was 10 (10; 15) min and 15 (15; 25) min, respectively. The difference was statistically significant (P=0.01). T90 after glucose bolus in brain and subcutaneous tissue was 10 min (8.75; 15) and 15 min (13.75; 21.25), respectively. T90 after insulin bolus in brain and subcutaneous tissue was 10 min (10; 15) and 20 min (20; 27.5), respectively. To the contrary, with literature, our results showed earlier glucose level changes in brain in comparison with subcutaneous tissue after glucose and insulin boluses. Our results suggest that glucose dynamics is different within monitored tissues under rapid changing glucose level and we can expect similar behavior in humans. Improved knowledge about glucose distribution and dynamics is important for avoiding hypoglycemia.

Accuracy and Time Delay of Glucose Measurements of Continuous Glucose Monitoring and Bedside Artificial Pancreas During Hyperglycemic and Euglycemic Hyperinsulinemic Glucose Clamp Study

BACKGROUND

Glucose values of continuous glucose monitoring (CGM) have time delays compared with plasma glucose (PG) values. The artificial pancreas (STG-55, Nikkiso, Japan) (AP), which measures venous blood glucose directly, also has a time delay because of the long tubing lines from sampling vessel to the glucose sensor. We investigate accuracy and time delay of CGM and AP in comparison with PG values during 2-step glucose clamp study.

METHODS

Seven patients with type 2 diabetes and 2 healthy volunteers were included in this study. CGM (Enlite sensor, Medtronic, Northridge, CA, USA) was attached on the day before the experiment. Hyperglycemic (200 mg/dL) clamp was performed for 90 minutes, followed by euglycemic (100 mg/dL) hyperinsulinemic (100 μU/mL) clamp for 90-120 minutes using AP. CGM sensor glucose was calibrated just before and after the clamp study. AP and CGM values were compared with PG values.

RESULTS

AP values were significantly lower than PG values at 5, 30 minute during hyperglycemic clamp. In comparison, CGM value at 0 minute was significantly higher, and its following values were almost significantly lower than PG values. The time delay of AP and CGM values to reach maximum glucose levels were 5.0 ± 22.3 (NS) and 28.6 ± 32.5 ( P < .05) min, respectively. Mean absolute rate difference of CGM was significantly higher than AP (24.0 ± 7.6 vs 15.3 ± 4.6, P < .05) during glucose rising period (0-45 min); however, there were no significant differences during other periods.

CONCLUSIONS

Both CGM and AP failed to follow plasma glucose values during nonphysiologically rapid glucose rising, but indicated accurate values during physiological glucose change.

A Comparison of Time Delay in Three Continuous Glucose Monitors for Adolescents and Adults

BACKGROUND

The physiologic delay in glucose diffusion from the blood to the interstitial fluid and instrumental factors contribute to the delay between changes in plasma glucose (PG) and measurements made by continuous glucose monitors (CGMs). This study compared the duration of this delay for three CGMs.

METHODS

A total of 24 healthy adolescent and adult subjects with type 1 diabetes wore three CGM devices simultaneously for 48 hours: Dexcom G4 Platinum, Abbott Navigator, and Medtronic Enlite. The time delay between PG and CGM-estimated plasma glucose (CGMG) was estimated by comparing time-shifted CGMG with reference PG taken every 15 minutes.

RESULTS

The delay estimated by our approach was larger for the Navigator than for the G4 Platinum in adolescents (7.7 ± 1.1 versus 5.6 ± 0.9 min, P = .0396) and adults (10.9 ± 1.1 versus 8.1 ± 0.7 min, P = .0107). The delay was nominally longer for the Navigator than for the Enlite in both the adolescent (7.7 ± 1.1 versus 4.3 ± 1.0 min, P = .0728) and adult (10.9 ± 1.1 versus 8.3 ± 0.9 min, P = .111) populations, but these differences were not statistically significant. There was no difference in the delay between G4 Platinum and Enlite. Adolescents had shorter delays than adults for all three devices. There was a significant correlation between longer delay and increasing age for the G4 Platinum and Navigator.

CONCLUSIONS

There are differences in the estimated PG to CGMG time delays between CGM devices in the same subjects. The delay between PG and CGMG is smaller for adolescents than for adults. The PG-to-CGMG time delay is influenced by both instrument and host factors.

Continuous glucose monitoring: A review of the technology and clinical use

Continuous glucose monitoring (CGM) is an increasingly adopted technology for insulin-requiring patients that provides insights into glycemic fluctuations. CGM can assist patients in managing their diabetes with lifestyle and medication adjustments. This article provides an overview of the technical and clinical features of CGM based on a review of articles in PubMed on CGM from 1999 through January 31, 2017. A detailed description is presented of three professional (retrospective), three personal (real-time) continuous glucose monitors, and three sensor integrated pumps (consisting of a sensor and pump that communicate with each other to determine an optimal insulin dose and adjust the delivery of insulin) that are currently available in United States. We have reviewed outpatient CGM outcomes, focusing on hemoglobin A1c (A1C), hypoglycemia, and quality of life. Issues affecting accuracy, detection of glycemic variability, strategies for optimal use, as well as cybersecurity and future directions for sensor design and use are discussed. In conclusion, CGM is an important tool for monitoring diabetes that has been shown to improve outcomes in patients with type 1 diabetes mellitus. Given currently available data and technological developments, we believe that with appropriate patient education, CGM can also be considered for other patient populations.

Quantization improves stabilization of dynamical systems with delayed feedback

We show that an unstable scalar dynamical system with time-delayed feedback can be stabilized by quantizing the feedback. The discrete time model corresponds to a previously unrecognized case of the microchaotic map in which the fixed point is both locally and globally repelling. In the continuous-time model, stabilization by quantization is possible when the fixed point in the absence of feedback is an unstable node, and in the presence of feedback, it is an unstable focus (spiral). The results are illustrated with numerical simulation of the unstable Hayes equation. The solutions of the quantized Hayes equation take the form of oscillations in which the amplitude is a function of the size of the quantization step. If the quantization step is sufficiently small, the amplitude of the oscillations can be small enough to practically approximate the dynamics around a stable fixed point.

Wearable physiological systems and technologies for metabolic monitoring

Wearable sensors allow continuous monitoring of metabolites for diabetes, sports medicine, exercise science, and physiology research. These sensors can continuously detect target analytes in skin interstitial fluid (ISF), tears, saliva, and sweat. In this review, we will summarize developments on wearable devices and their potential applications in research, clinical practice, and recreational and sporting activities. Sampling skin ISF can require insertion of a needle into the skin, whereas sweat, tears, and saliva can be sampled by devices worn outside the body. The most widely sampled metabolite from a wearable device is glucose in skin ISF for monitoring diabetes patients. Continuous ISF glucose monitoring allows estimation of the glucose concentration in blood without the pain, inconvenience, and blood waste of fingerstick capillary blood glucose testing. This tool is currently used by diabetes patients to provide information for dosing insulin and determining a diet and exercise plan. Similar technologies for measuring concentrations of other analytes in skin ISF could be used to monitor athletes, emergency responders, warfighters, and others in states of extreme physiological stress. Sweat is a potentially useful substrate for sampling analytes for metabolic monitoring during exercise. Lactate, sodium, potassium, and hydrogen ions can be measured in sweat. Tools for converting the concentrations of these analytes sampled from sweat, tears, and saliva into blood concentrations are being developed. As an understanding of the relationships between the concentrations of analytes in blood and easily sampled body fluid increases, then the benefits of new wearable devices for metabolic monitoring will also increase.