Glucose Monitoring Devices Research Articles

Two-week continuous glucose monitoring-derived metrics and degree of hepatic steatosis: a cross-sectional study among Chinese middle-aged and elderly participants

BackgroundContinuous glucose monitoring (CGM) devices provide detailed information on daily glucose control and glycemic variability. Yet limited population-based studies have explored the association between CGM metrics and fatty liver. We aimed to investigate the associations of CGM metrics with the degree of hepatic steatosis.MethodsThis cross-sectional study included 1180 participants from the Guangzhou Nutrition and Health Study. CGM metrics, covering mean glucose level, glycemic variability, and in-range measures, were separately processed for all-day, nighttime, and daytime periods. Hepatic steatosis degree (healthy: n = 698; mild steatosis: n = 242; moderate/severe steatosis: n = 240) was determined by magnetic resonance imaging proton density fat fraction. Multivariate ordinal logistic regression models were conducted to estimate the associations between CGM metrics and steatosis degree. Machine learning models were employed to evaluate the predictive performance of CGM metrics for steatosis degree.ResultsMean blood glucose, coefficient of variation (CV) of glucose, mean amplitude of glucose excursions (MAGE), and mean of daily differences (MODD) were positively associated with steatosis degree, with corresponding odds ratios (ORs) and 95% confidence intervals (CIs) of 1.35 (1.17, 1.56), 1.21 (1.06, 1.39), 1.37 (1.19, 1.57), and 1.35 (1.17, 1.56) during all-day period. Notably, lower daytime time in range (TIR) and higher nighttime TIR were associated with higher steatosis degree, with ORs (95% CIs) of 0.83 (0.73, 0.95) and 1.16 (1.00, 1.33), respectively. For moderate/severe steatosis (vs. healthy) prediction, the average area under the receiver operating characteristic curves were higher for the nighttime (0.69) and daytime (0.66) metrics than that of all-day metrics (0.63, P < 0.001 for all comparisons). The model combining both nighttime and daytime metrics achieved the highest predictive capacity (0.73), with nighttime MODD emerging as the most important predictor.ConclusionsHigher CGM-derived mean glucose and glycemic variability were linked with higher steatosis degree. CGM-derived metrics during nighttime and daytime provided distinct and complementary insights into hepatic steatosis.

Performance of a Novel Continuous Glucose Monitoring Device in People With Diabetes.

In this multicenter study, performance of a novel continuous glucose monitoring (CGM) system was evaluated. Adult participants with diabetes were included in the study. They each wore three sensors of the CGM system on the upper arms for up to 14 days. During four in-clinic visits, frequent comparison measurements with capillary blood glucose (BG) samples were performed. The primary endpoint was the 20/20 agreement rate (AR): the percentage of CGM readings within ±20 mg/dL (at BG values <100 mg/dL) or ±20% (at BG values ≥100 mg/dL) of the comparator. Further evaluations included mean absolute relative difference (MARD) and 20/20 AR in different BG ranges and across the wear time. Data from 48 participants and 139 sensors were analyzed. During in-clinic sessions the 20/20 AR was 90.5% and the MARD was 9.2%. For BG ranges <70, 70-180, and >180 mg/dL, 20/20 AR was 94.3%, 89.0%, and 92.5%, respectively. At the beginning, middle, and end of sensor wear time, 20/20 AR was 92.8%, 91.5%, and 85.9%, respectively. The 14-day survival probability was 82.4%. Pain and bleeding after sensor insertion were within the expected range. Based on the study outcome, the use of the device is regarded as safe. The system showed a good performance compared to capillary BG measurements. This level of accuracy could be shown over the entire measurement range, especially in the low glycemic range, and the whole wear time of the sensors. The results of this study are supporting a non-adjunctive use of the device.

Renewable regeneration optic fiber glucose sensor based on succinylaminobenzenoboronic acid modified excessively tilted fiber grating

BackgroundOptical fiber sensors have been used to detect glucose owing to advantages such as low cost, small size, and ease of operation etc. phenylboronic acid is one of the commonly used receptors for glucose detection, however phenylboronic acid based regenerative optical fiber sensors are commonly cumulative regeneration, renewable regeneration sensor has been missing from the literature. ResultsIn this work, instead of using phenylboronic acid, we synthesized succinylaminobenzenoboronic acid molecule (BPOA) by introducing a short chain containing carboxyl group at the other end of phenylboronic acid then covalently bonded BPOA on the surface of excessively tilted fiber grating (Ex-TFG). This provides a very stable platform for renewable regeneration and the regenerative buffer was also optimized. The proposed renewable regeneration method exhibited higher linearity and sensitivity (R2 = 0.9992, 8 pm/mM) in relative to the conventional cumulative regeneration method (R2 = 0.9718, 4.9 pm/mM). The binding affinity between BPOA and glucose was found to be almost constant over 140 bind/release cycles with a variation of less than 0.3 % relative standard deviation. SignificanceThe regenerative and label-free sensing capacity of the proposed device provides a theoretical foundation for label-free saccharide detection and the development of wearable glucose monitoring devices based on fiber optic sensors.

Impact of Continuous Glucose Monitoring and its Glucometrics in Clinical Practice in Spain and Future Perspectives: A Narrative Review.

Continuous glucose monitoring (CGM) devices allow for 24-h real-time measurement of interstitial glucose levels and have changed the interaction between people with diabetes and their health care providers. The large amount of data generated by CGM can be analyzed and evaluated using a set of standardized parameters, collectively named glucometrics. This review aims to provide a summary of the existing evidence on the use of glucometrics data and its impact on clinical practice based on published studies involving adults and children with type 1 diabetes (T1D) in Spain. The PubMed and MEDES (Spanish Medical literature) databases were searched covering the years 2018-2022 and including clinical and observational studies, consensus guidelines, and meta-analyses on CGM and glucometrics conducted in Spain. A total of 16 observational studies were found on the use of CGM in Spain, which have shown that cases of severe hypoglycemia in children with T1D were greatly reduced after the introduction of CGM, resulting in a significant reduction in costs. Real-world data from Spain shows that CGM is associated with improved glycemic markers (increased time in range, reduced time below and above range, and glycemic variability), and that there is a relationship between glycemic variability and hypoglycemia. Also, CGM and analysis of glucometrics proved highly useful during the COVID-19 pandemic. New glucometrics, such as the glycemic risk index, or new mathematical approaches to the analysis of CGM-derived glucose data, such as "glucodensities," could help patients to achieve better glycemic control in the future. By using glucometrics in clinical practice, clinicians can better assess glycemic control and a patient's individual response to treatment.

Individualized selection of recent glucose monitoring devices for self-management based on competitive features.

Goal of the study was to systematically review competitive advantages of medical devices for glucose monitoring in diabetic patients. The review is done systematically according to SALSA criteria and PRISMA guidelines. The search for eligible articles was held from February 16th 2023 to March 1st 2023 in Russian and English languages. The results were synthesized narratively, tabularly, and visually. The search was conducted in the following databases of scientific literature: PubMed, IEEE Xplore, Google Scholar, CyberLeninka, and eLibrary. Twenty-two out of fifty-two manuscripts met the inclusion criteria. The most promising and advantageous characteristics of the evaluated devices, as identified by researchers, include the following: the capability for noninvasive examination; features that facilitate use by patients with fine motor, hearing, and visual impairments; add-ons and software designed to improve patient compliance, including in pediatric populations; and device attributes that enhance the speed and accuracy of analysis while being free of iatrogenic effects. With increasing prevalence of diabetes, glycemic control is crucial for preventing complications. The market offers numerous glucose monitoring devices (GMDs) with varying features, making selection challenging. Our study systematically categorized the strengths of each GMD model for diabetic patients, aiding informed device selection.

Flexible nanomaterial sensors for non-invasive health monitoring

According to the Center for Disease Control (CDC), diabetes is the eighth leading cause of death in the United States, while about 1 in 5 patients are unaware that they have been affected. Current detection methods are crude, using rudimentary pricking methods that require needles and being unconventional for continuous tracking, this strongly discourages people from early detection and management. Therefore, developing a non-invasive glucose monitoring technique is of utmost importance. The primary objective of this research is to address the limitations of existing glucose monitoring techniques through the development of nanomaterial sensors seamlessly integrated into wearable devices. A novel two-dimensional material, GeSe, is chosen for its flexibility and optical responsivity. Flexible polarimetric sensors are developed using a facile direct-transfer method. These sensors aim to provide accurate and non-invasive monitoring of blood glucose levels through measuring the light polarization after interaction with glucose molecules. To ensure reliability, the sensors are calibrated using glucose solutions with known concentrations. A machine-learning algorithm is developed to improve measurement accuracy. Rigorous testing of the nanomaterial sensors is conducted in comparison to traditional blood glucose monitoring devices, employing controlled studies that evaluated their effectiveness across different objects. This approach not only establishes the viability of nanomaterials in transforming health monitoring but also highlights their potential to significantly improve the accuracy and convenience of blood glucose monitoring for individuals managing diabetes. The integration of nanomaterial-based sensors into wearable devices represents a noteworthy stride towards enhancing the efficiency and accessibility of healthcare technologies.

Stenopool: A Comprehensive Platform for Consolidating Diabetes Device Data.

The growing adoption of diabetes devices has highlighted the need for integrated platforms to consolidate data from various vendors and device types, enhancing the patient experience and treatment. This shift could pave the way for a transition from conventional outpatient diabetes clinics to advanced home monitoring and virtual care methods. Overall, we wished to empower individuals with diabetes and healthcare providers to interpret and utilize information from diabetes devices more effectively. Stenopool integrates most diabetes devices for glucose monitoring and insulin administration in our clinic. The platform was initially developed with inspiration from open-source software, and the current version is a unique digital platform for managing and analyzing diabetes device data. The development process, outcomes, and status are described. Since November 2021, Stenopool has been used in our outpatient clinic to integrate over 30 different diabetes devices from around 7000 individuals. Data are primarily uploaded via wired connections, but also using semi-automated and automated cloud-to-cloud data transfers. The platform offers a streamlined workflow for healthcare providers and displays data from various glucose meter, insulin pump, and continuous glucose monitor (CGM) vendors on a single screen in a manner that healthcare providers can modify. A data warehouse with data from Stenopool and electronical health records is nearing completion, preparing the development of tools for population health management, quality assessment, and risk stratification of patients. Using Stenopool, we aimed to enhance diabetes device data management, facilitate the future for virtual patient care pathways, and improve outcomes. This article outlines the platform's development process and challenges.

Accuracy of a continuous glucose monitoring system applied before, during, and after an intense leg-squat session with low- and high-carbohydrate availability in young adults without diabetes.

The aim was to assess the accuracy of a continuous blood glucose monitoring (CGM) device (Abbott FreeStyle Libre 3) against capillary blood glucose measurement (BGM) before, during, and after an intense lower body strength training session in connection with high- versus low-carbohydrate breakfasts. Nine adults (22 ± 2 years) completed a strength training session (10 × 10 at 60% 1RM) twice after high-carbohydrate and twice after low-carbohydrate breakfasts. CGM accuracy versus BGM was assessed across four phases: post-breakfast, pre-exercise, exercise, and post-exercise. Overall fed state mean BGM levels were 84.4 ± 20.6mg/dL. Group-level Bland-Altman analysis showed acceptable agreement between CGM and BGM across all phases, with mean biases between -7.95 and -17.83mg/dL; the largest discrepancy was in the post-exercise phase. Mean absolute relative difference was significantly higher post-exercise compared to pre-exercise and exercise phases, for overall data and after the high-carbohydrate breakfast (all p ≤ 0.02). Clark Error Grid analysis showed 50.5-64.3% in Zone A and 31.7-44.6% in Zone B, with an increase in treatment errors during and after exercise. In this group of healthy participants undergoing strength training, CGM showed satisfactory accuracy in glucose monitoring but varied substantially between individuals compared to BGM and fails in meeting clinical criteria for diabetic monitoring. CGM could aid non-diabetic athletes by tracking glucose fluctuations due to diet and exercise. Although utilization of CGM shows potential in gathering, analyzing, and interpreting interstitial glucose for improving performance, the application in sports nutrition is not yet validated, and challenges in data interpretation could limit its adoption.

Advancements in Insulin Pumps: A Comprehensive Exploration of Insulin Pump Systems, Technologies, and Future Directions.

Insulin pumps have transformed the way diabetes is managed by providing a more accurate and individualized method of delivering insulin, in contrast to conventional injection routines. This research explores the progression of insulin pumps, following their advancement from initial ideas to advanced contemporary systems. The report proceeds to categorize insulin pumps according to their delivery systems, specifically differentiating between conventional, patch, and implantable pumps. Every category is thoroughly examined, emphasizing its unique characteristics and capabilities. A comparative examination of commercially available pumps is provided to enhance informed decision making. This section provides a thorough analysis of important specifications among various brands and models. Considered factors include basal rate and bolus dosage capabilities, reservoir size, user interface, and compatibility with other diabetes care tools, such as continuous glucose monitoring (CGM) devices and so on. This review seeks to empower healthcare professionals and patients with the essential information to improve diabetes treatment via individualized pump therapy options. It provides a complete assessment of the development, categorization, and full specification comparisons of insulin pumps.

Continuous glucose monitoring devices in people over 65 years: literature review

The use of continuous glucose monitoring (CGM) in elderly patients with diabetes is not well documented. The present study search to know the current status of use of CGM devices in patients with diabetes over 65 years of age. A systematic literature search was performed in PubMed and Scopus databases in November 2023. The following descriptors were used, linked using the Boolean operators AND and OR: Diabetes, Continuous glucose monitoring, Flash glucose monitoring, Glycemia, Glycemic control, Controlled diabetes, Diabetes care, Metrics, Older and Elder. The CASPe critical reading system and the PRISMA methodology were applied to document the review. Fourteen selected studies published between 2019 and 2023 were reviewed. Publications from European countries used small sample sizes and were intervention studies. The duration of the interventions was generally short: 7 were ≤14 days in duration and only 3 were 6-12 months in duration. Overall, the selected articles found that CGM improved glycemic outcomes due to a decrease in glycosylated hemoglobin value and an improvement in CGM metrics, and diabetes-associated complications in elderly patients with diabetes. CGM seems to be a useful and effective tool to improving glycemic outcomes of people with diabetes over age 65. Further studies under real-world conditions and of longer duration are needed to expand and improve the evidence.

Effect of Wearable Technology on Metabolic Control and the Quality of Life in Children and Adolescents with Type 1 Diabetes: A Systematic Review and Meta-Analysis

Type 1 diabetes is one of the most common chronic diseases in children. Wearable technology (insulin pumps and continuous glucose monitoring devices) that makes diabetes management relatively simple, in addition to education and follow-ups, enhances the quality of life and health of individuals with diabetes. To evaluate the impact of wearable technology on metabolic management and the quality of life in children and adolescents with type 1 diabetes. Systematic review and meta-analysis. The Preferred Reporting System for Systematic Reviews and Meta-Analyses was used to conduct a systematic review and meta-analysis. PubMed, Web of Science, MEDLINE, Cochrane Library, EBSCO, Ulakbim and Google Scholar were searched in July 2022 and July 2023 using predetermined keywords. The methodological quality of the studies was evaluated using the Joanna Briggs Institute’s Critical Appraisal Checklists for randomized controlled experimental and cross-sectional studies. The meta-analysis method was used to pool the data. Eleven studies published between 2011 and 2022 were included. The total sample size of the included studies was 1,853. The meta-analysis revealed that the decrease in hemoglobin A1C (HbA1c) level in those using wearable technology was statistically significant [mean difference (MD): -0.33, Z = 2.54, p = 0.01]. However, the technology had no effect on the quality of life [standardized mean difference (SMD): 0.44, Z = 1.72, p = 0.09]. The subgroup analyses revealed that the decrease in the HbA1c level occurred in the cross-sectional studies (MD: -0.49, Z = 2.54, p = 0.01) and the 12-19 (MD = 0.59, Z = 4.40, p < 0.001) and 4-18 age groups (MD: -0.31, Z = 2.56, p = 0.01). The subgroup analyses regarding the quality of life revealed that there was no difference according to the research design. However, the quality of life was higher in the wearable technology group than in the control group in the 8-12 and 4-18 age groups (SMD: 1.32, Z = 2.31, p = 0.02 and SMD: 1.00, Z = 5.76, p < 0.001, respectively). Wearable technology effectively reduces the HbA1c levels in children and adolescents with type 1 diabetes in some age groups. However, it does not affect the quality of life.

The Relationship Between Hemoglobin A1c, Time in Range, and Glycemic Management Indicator in Patients With Type 1 and Type 2 Diabetes in a Tertiary Care Hospital in Saudi Arabia.

This study aimed to assess the correlation between glycated hemoglobin A1 (HbA1c), time in range (TIR), and glycemic management indicator (GMI) in patients with both type 1 diabetes (T1D) and type 2 diabetes (T2D) who were using a flash glucose monitoring (FGM) device (FreeStyle Libre; Abbott Diabetic Care, Witney, UK). This was a retrospective study that looked at T1D and T2D FreeStyle Libre users' LibreView database in the period between January2020 to June 2022. The study was conducted at the diabetes department at the King Fahad Medical City (KFMC) in Riyadh, Saudi Arabia, following Institutional Review Board (IRB) approval. Data werecollected from the LibreView website, as well as from the electronic privacy information center (EPIC) hospital records. Data were available for 327 patients, mean age of 33.08(±17.1) years old, and 55.7% were females. HbA1c had a statistically significant correlation with both TIR and GMI with coefficient of correlation (r) values of 0.78 (p<0.001) and 0.82 (p<0.001), respectively. A linear regression model between TIR and Hb1Ac was also developed and found to be statistically significant (p<0.001) with an acceptable R2 value (0.60). Study findings revealed that the %TIR could be a reliable predictor of Hb1Ac. Thus, Freestyle Libre was able to determine Hb1Ac as close to the lab results as possible. Therefore, it is necessary to encourage diabetes patients to achieve at least 70% TIR in order to keep Hb1Ac within the desired range.

3D Prototyping of Medical Devices for Non-Invasive Glucose Monitoring

In recent years, as global diabetes rates have increased, a growing number of individuals have been experiencing pain and infections due to the invasive nature of conventional commercial glucose meters.

Continuous glucose monitoring with FreeStyle Libre PRO sensor in patients with type 2 diabetes and end-stage renal failure on haemoDIALysis (FSLPRO-DIAL pilot study).

For end-stage renal disease (ESRD) patients with diabetes on haemodialysis, diabetes control is difficult to achieve. Hypoglycaemia is a major problem in these frailty subjects. Continuous glucose monitoring (CGM) devices appear therefore to be a good tool to help patients monitor their glycaemic control and to help practitioners optimize treatment. We aimed to compare the laboratory value of Hba1c with the sensor-estimated value of Hba1c (= glucose management indicator, GMI) in ESRD patients with type 2 diabetes (T2D) (with or without insulin treatment) on haemodialysis. Secondly, we aimed to identify CGM-derived monitoring parameters [time in range, time in hypo/hyperglycaemia, glycaemic variability (coefficient of variation, CV)] to identify patients at risk of frequent hypo- or hyperglycaemia. The FSLPRO-DIAL pilot study (NCT04641650) was a prospective monocentric cohort study including 29 subjects with T2D who achieve the protocol. Inclusion criteria were: age ≥ 18years, haemodialysis duration for at least 3months, type 2 diabetes with no change in treatment for at least 3months. Demographic data and blood sample were collected at the day of inclusion. Freestyle Libre pro IQ sensor (blinded CGM) was inserted for 14days. After this period, all CGMs data were collected and analysed. Data were available for 27 patients. Mean age was 73 ± 10, mean BMI 27.2kg/m2, mean duration of diabetes 16.9years and mean dialysis duration 2.9years. Twenty-four subjects were treated with insulin. Mean HbA1c was 6.6% (SD 1.2), and mean GMI was 6.7% (SD 0.9) (no significant difference, p = 0.3). Twelve subjects (44.4%) had a discordance between HbA1c and GMI of < 0.5%, 11 (40.8%) had a discordance between 0.5 and 1%, and only 4 (14.8%) had a discordance of > 1%. Mean time in range (70-180mg/dl) was 71.9%, mean time below range (< 70mg/dl) was 5.6%, and mean time above range (> 180mg/dl) was 22.1%. Mean CV was 31.8%. For 13 out of 27 patients, we reduced antidiabetic treatment by stopping treatments or reducing insulin doses. In this pilot study, there was no global significant difference between HbA1c and GMI in this particular cohort with very well-controlled diabetes. However, the use of the sensor enabled us to identify an excessive time in hypoglycemia in this fragile population and to adapt their treatment.

Improving Diabetic Care Through Education and Innovation.

Background: Despite the innovative advancements in diabetes care, providers may not recognize patients with type 2 diabetes mellitus (T2DM) who qualify for a continuous glucose monitoring (CGM) device or the benefits of a telemedicine program for improving self-management behaviors. Objective: This quality improvement (QI) project aimed to determine if an advanced practice registered nurse (APRN)-led telemedicine program using CGM could improve glycemic control and self-management in patients with insulin-dependent T2DM. Methods: A 6-week telemedicine program was developed and implemented using the CGM's time-in-range to deliver patient-specific education. Clinical metrics were collected at each visit. All patients completed a pre- and postintervention Diabetes Self-Management Questionnaire-Revised (DSMQ-R) survey. Results: A repeated measures analysis of variance revealed that the telemedicine program had a statistically significant impact on time-in-range outcomes, F(2, 14) = 18.203, p < .001. Paired-samples t tests indicate that APRN-led education improved body mass index, t(8) = 4.232, p = .002; decreased systolic blood pressure, t(8) = 2.90, p = .010, and diastolic blood pressure, t(8) = 3.21, p = .007; and increased self-management skills as evidenced by DSMQ-R, t(8) = -5.498, p < .001. Conclusions: This QI project highlights multiple interventions for improving diabetes management in a primary care facility. Implications for Nursing: An APRN-led telemedicine program integrating CGM time-in-range data can improve glycemic control and self-management skills in patients with T2DM who administer insulin.

Highly Parallel Droplet Dispensing Approach to Provide Homogeneous and Controllable Droplet Arrays for Diagnostic Test Manufacturing.

We introduce a novel approach for highly parallel droplet dispensing with precise control over the droplet parameters such as droplet volume, droplet velocity, etc. This approach facilitates the fabrication of homogeneous and precise thin layers with uniform coverage on defined small areas (e.g., a specific area of 1 × 1.4 mm2 in microfluidic channels or microwells). The presented approach ensures layer uniformity and high precision in X/Y extent and edge resolution, making it well suited for achieving precise and controlled coating for a variety of applications such as homogeneous coatings for lateral flow tests, ELISA plates, and biosensors for continuous glucose monitoring (CGM) devices. Our approach is based on direct liquid displacement employing a piston that is in direct contact with the liquid and an array of nozzles. Considering a variety of nozzle chip designs (i.e., varying nozzle diameter and pitch), we evaluated a multitude of parameters to derive general design rules for the nozzle chip design. Thus, we achieved a tunable droplet volume from 200 to 800 pL and droplet velocities from 0.5 to 2.5 m/s, applying a nozzle diameter of 50 μm and a nozzle pitch of 165 μm. The presented results showcase the versatility of the approach, offering precise dispensing capabilities.

Perioperative Care of Patients Using Wearable Diabetes Devices.

The increasing prevalence of diabetes mellitus has been accompanied by a rapid expansion in wearable continuous glucose monitoring (CGM) devices and insulin pumps. Systems combining these components in a "closed loop," where interstitial glucose measurement guides automated insulin delivery (AID, or closed loop) based on sophisticated algorithms, are increasingly common. While these devices' efficacy in achieving near-normoglycemia is contributing to increasing usage among patients with diabetes, the management of these patients in operative and procedural environments remains understudied with limited published guidance available, particularly regarding AID systems. With their growing prevalence, practical management advice is needed for their utilization, or for the rational temporary substitution of alternative diabetes monitoring and treatments, during surgical care. CGM devices monitor interstitial glucose in real time; however, there are potential limitations to use and accuracy in the perioperative period, and, at the present time, their use should not replace regular point-of-care glucose monitoring. Avoiding perioperative removal of CGMs when possible is important, as removal of these prescribed devices can result in prolonged interruptions in CGM-informed treatments during and after procedures, particularly AID system use. Standalone insulin pumps provide continuous subcutaneous insulin delivery without automated adjustments for glucose concentrations and can be continued during some procedures. The safe intraoperative use of AID devices in their hybrid closed-loop mode (AID mode) requires the CGM component of the system to continue to communicate valid blood glucose data, and thus introduces the additional need to ensure this portion of the system is functioning appropriately to enable intraprocedural use. AID devices revert to non-AID insulin therapy modes when paired CGMs are disconnected or when the closed-loop mode is intentionally disabled. For patients using insulin pumps, we describe procedural factors that may compromise CGM, insulin pump, and AID use, necessitating a proactive transition to an alternative insulin regimen. Procedure duration and invasiveness is an important factor as longer procedures increase the risk of stress hyperglycemia, tissue malperfusion, and device malfunction. Whether insulin pumps should be continued through procedures, or substituted by alternative insulin delivery methods, is a complex decision that requires all parties to understand potential risks and contingency plans relating to patient and procedural factors. Currently available CGMs and insulin pumps are reviewed, and practical recommendations for safe glycemic management during the phases of perioperative care are provided.

Expert Panel Recommendations for a Standardized Ambulatory Glucose Profile Report for Connected Insulin Pens.

Connected insulin pens capture data on insulin dosing/timing and can integrate with continuous glucose monitoring (CGM) devices with essential insulin and glucose metrics into a single platform. Standardization of connected insulin pen reports is desirable to enhance clinical utility with a single report. An international expert panel was convened to develop a standardized connected insulin pen report incorporating insulin and glucose metrics into a single, clinically useful report. An extensive literature review and identification of examples of current connected insulin pen reports was performed serving as the basis for creation of a draft of a standardized connected insulin pen report. The expert panel participated in three virtual standardization meetings and online surveys. The AGP Report: Connected Insulin Pen brings all clinically relevant CGM-derived glucose and connected insulin pen metrics into a single simplified two-page report. The first page contains the time in ranges bar, summary of key insulin and glucose metrics, the ambulatory glucose profile (AGP) curve, and detailed basal (long-acting) insulin assessment. The second page contains the bolus (mealtime and correction) insulin assessment periods with information on meal timing, insulin-to-carbohydrate ratio (ICR), average bolus insulin dose and number of days with bolus doses recorded. The report's second page contains daily glucose profiles with an overlay of the timing and amount of basal and bolus insulin administered. The AGP Report: Connected Insulin Pen is a standardized clinically useful report that should be considered by companies developing connected pen technology as part of their system reporting/output.

Comparison of Ensemble Method Performance in Classifying Blood Sugar Levels Output from Non-Invasive Device

Diabetes Mellitus (DM) is a persistent health issue in many countries and is a leading cause of heart disease, kidney failure, and blindness The International Diabetes Federation (IDF) estimated in 2019 that at least 463 million people worldwide aged 20-79 suffer from diabetes. This number is expected to rise to 578 million by 2030 and 700 million by 2045. Machine learning is a type of machine learning that is very helpful in various fields, including healthcare. In classification cases, ensemble methods classify by combining decisions from several other models, one way being through majority voting. Ensemble methods often produce more accurate classification or prediction results. Several ensemble methods include random forest, extra trees, rotation forest, and double random forest. The data used in this study is part of research on the development and clinical testing of a prototype non-invasive blood glucose monitoring device by the non-invasive biomarking team at IPB. The data includes both invasive and non-invasive blood glucose measurements collected in 2019. This study compares the performance of the random forest, extra trees, rotation forest, and double random forest models on blood glucose level data obtained from non-invasive devices. The research results show that the Rotation Forest algorithm is the best model, with the highest average accuracy compared to the other three algorithms, achieving an accuracy level of 0.7142857 (71.42%).

Impact of lifestyle moderate-to-vigorous physical activity timing on glycemic control in sedentary adults with overweight/obesity and metabolic impairments.

Moderate-to-vigorous physical activity (MVPA) improves glucose levels; however, whether its timing affects daily glycemic control remains unclear. This study aims to investigate the impact of lifestyle MVPA timing on daily glycemic control in sedentary adults with overweight/obesity and metabolic impairments. A total of 186 adults (50% women; age, 46.8 [SD 6.2] years) with overweight/obesity (BMI, 32.9 [SD 3.5] kg/m2) and at least one metabolic impairment participated in this cross-sectional study. MVPA and glucose patterns were simultaneously monitored over a 14-day period using a triaxial accelerometer worn on the nondominant wrist and a continuous glucose-monitoring device, respectively. Each day was classified as "inactive" if no MVPA was accumulated; as "morning," "afternoon," or "evening" if >50% of the MVPA minutes for that day were accumulated between 0600 and 1200, 1200 and 1800, or 1800 and 0000 hours, respectively; or as "mixed" if none of the defined time windows accounted for >50% of the MVPA for that day. Accumulating >50% of total MVPA during the evening was associated with lower 24-h(mean difference [95% CI], -1.26 mg/dL [95% CI: -2.2 to -0.4]), diurnal (-1.10 mg/dL [95% CI: -2.0 to -0.2]), and nocturnal mean glucose levels (-2.16 mg/dL [95% CI: -3.5 to -0.8]) compared with being inactive. This association was stronger in those participants with impaired glucose regulation. The pattern of these associations was similar in both men and women. These findings suggest that timing of lifestyle MVPA is significant. Specifically, accumulating more MVPA during the evening appears to have a beneficial effect on glucose homeostasis in sedentary adults with overweight/obesity and metabolic impairments.