Glucose Readings Research Articles

Noninvasive Real-Time Glucose Monitoring Is in the Near Future.

Objective: Since the introduction of continuous glucose monitoring (CGM) technology, developers have rigorously researched the feasibility of creating a noninvasive glucose monitoring device. In a recent pilot study, investigators reported a strong correlation between glucose values obtained from novel noninvasive monitoring device (GWave) values to venous and capillary glucose measurements. Research Design and Methods: We investigated whether the level of accuracy observed in the pilot study could be reproduced in a larger cohort, using a smaller third-generation manufacturable device (Gen III GWave) containing a standardized sensor chip that can be mass produced for commercial use. The evaluation assessed concordance with capillary blood glucose, reproducibility between two Gen III devices, and accuracy during insulin-induced hypoglycemia. Results: Assessment of samples from 75 subjects (type 2 diabetes, n = 6; type 1 diabetes, n = 28; nondiabetic pregnant subjects, n = 10; and nondiabetic, n = 31) showed that 97% of values were in Zone A with 3% in Zone B of the Clarke Error Grid, with a mean absolute relative difference of 6.7% from reference blood glucose. Comparison between two independent Gen III GWave devices demonstrated reproducibility between the sensors (R2 = 0.95), with 100% of values within Zone A. In the hypoglycemia assessment, measurements from the Gen III sensor tightly followed the capillary glucose measurements down to 42 mg/dL (2.3 mmol/L), whereas the CGM measurements from two different CGM only converged with the GWave and capillary glucose readings after 90 min of decreasing glucose levels. Conclusion: Our results show promise as potentially the first noninvasive technology. Future studies will focus on larger number of people in all glucose ranges. Real-time noninvasive blood glucose monitoring is possible using GWave technology.

A smart device for smart self-monitoring of glycemia in patients with diabetes

A smart device for smart self-monitoring of glycemia in patients with diabetes

Non-invasive Blood Glucose Monitoring System

The project presents a novel approach to blood glucose monitoring, offering a non-invasive and pain-free method for individuals with diabetes to track their glucose levels. The system utilizes advanced sensor technology coupled with signal processing techniques to detect glucose levels in the body without the need for traditional needle pricking. The key components of the system include a power supply, voltage regulator, ESP32 microcontroller, LCD display, photo sensor, amplifier circuit, and linearization circuit, all seamlessly integrated to provide accurate and real-time glucose readings. This breakthrough technology holds great promise in revolutionizing diabetes management, enhancing the quality of life for millions of affected individuals.By placing the sensor on the individual’s hand, the Glucometer system employs a combination of photonic and electronic principles to non-invasively measure glucose levels. The photo sensor captures specific wavelengths of light that interact with glucose molecules within the tissue, generating a signal proportional to the glucose concentration. This signal is then amplified and processed through the integrated circuits, ensuring accurate linearization and calibration. The ESP32 microcontroller orchestrates these operations, facilitating seamless communication with the LCD display to present the glucose reading in a clear and user-friendly format.The Glucometer’s innovative design eliminates the discomfort associated with traditional blood sampling methods, making it a highly accessible and convenient tool for diabetes management. The system’s efficiency in providing accurate glucose readings without the need for invasive procedures represents a significant advancement in healthcare technology. With further development and refinement, the Glucometer holds the potential to significantly enhance the daily lives of individuals living with diabetes, offering a reliable and painless means of monitoring blood glucose levels.

Continuous Glucose Monitoring Using the Dexcom G6 in Cardiac Surgery During the Postoperative Period

ObjectiveCardiac surgery is associated with hyperglycemia, which in turn is associated with adverse postsurgical outcomes such as wound infections, acute renal failure, and mortality. This pilot study seeks to determine if Dexcom G6Pro continuous glucose monitor (Dexcom G6Pro CGM) is accurate during the postoperative cardiac surgery period when fluid shifts, systemic inflammatory response syndrome, and vasoactive medications are frequently encountered, compared to standard glucose monitoring techniques. MethodsThis study received institutional review board approval. In this prospective study, correlation between clinical and Dexcom glucose readings was evaluated. Clinical glucose (blood gas, metabolic panel, and point of care) data set included 1428 readings from 29 patients, while the Dexcom G6Pro CGM data included 45 645 data points following placement to upper arm. Additionally, average clinical measurements of day and overnight temperatures and hemodynamics were evaluated.Clinical and Dexcom data were restricted to being at least 1 hour after prior clinical reading Matching Dexcom G6Pro CGM data were required within 5 minutes of clinical measure. Data included only if taken at least 2 hours after Dexcom G6Pro CGM insertion (warm-up time) and analyzed only following intensive care unit (ICU) admission. Finally, a data set excluding the first 24 hours after ICU admission was created to explore stability of the device. Patients remained on Dexcom G6Pro CGM until discharge or 10 days postoperatively. ResultsThe population was 71% male, 14% with known diabetes; 66% required intravenous insulin infusion. The Clarke error grid plot of all measures post-ICU admission showed 53.5% in zone A, 45.9% in zone B, and 0.6% (n = 5) in zones D or E. The restricted dataset that excluded the first 24 hours post-ICU admission showed 55.9% in zone A, 43.9% in zone B, and 0.2% in zone D. Mean absolute relative difference between clinical and Dexcom G6Pro CGM measures was 20.6% and 21.6% in the entire post-ICU admission data set, and the data set excluding the first 24 hours after ICU admission, respectively. In the subanalysis of the 12 patients who did not have more than a 5-minute tap in the operating room, a consensus error grid, demonstrated that after ICU admission, percentage in zone A was 53.9%, zone B 45.4%, and zone C 0.7%. Similar percentages were obtained removing the first 24 hours post-ICU admission. These numbers are very similar to the entire cohort.A consensus error grid created post-ICU admission demonstrated: (zone A) 54%, (zone B) 45%, (zone C) 0.9%, and the following for the dataset created excluding the first 24 hours: (zone A) 56%, (zone B) 44%, (zone C) 0.4%, which demonstrated very close agreement with the original Clarke error grid. No adverse events were reported. ConclusionsAlmost 100% of Dexcom G6Pro CGM and clinical data matching points fell within areas considered as giving clinically correct decisions (zone A) and clinically uncritical decisions (zone B). However, the relatively high mean absolute relative difference precludes its use for both monitoring and treatment in the clinical context. As technology evolves, interstitial glucose monitoring may become an important tool to limit iatrogenic anemia and mitigate glycemic fluctuations.

Glycated hemoglobin (HbA1c) and biofluid-based diagnosis in diabetes: A comprehensive review

The global rise in diabetes has fueled new developments in wearable devices. Diabetes, characterized by high glucose levels and impaired insulin secretion, causes a variety of complications. Diabetes rates in Southeast Asia and the Western Pacific are alarmingly high, with projections of a significant increase by 2045. The economic burden in the Asia-Pacific region is expected to reach USD 881.03 billion by 2030. Due to the unreliability of traditional blood glucose readings, glycated hemoglobin (HbA1c) has emerged as a stable biomarker that provides a consistent view of glycemic status over 2–3 months. Despite effective hospital-based HbA1c measurements, labor-intensive methods limit their use. Wearable systems that investigate glucose levels in alternative biofluids have promising potential for continuous monitoring, particularly in prediabetes cases. Current monitoring systems, while effective, are uncomfortable and expensive. This review examines diabetes diagnosis with HbA1c and biofluid-based sensors, focusing on blood-based evaluations and the complementary nature of glucose and HbA1c sensors. It emphasizes the critical importance of combining biofluid-based diagnosis with HbA1c measurement for effective diabetes management.

Differences in glucose readings between the continuous glucose monitoring calibration free interstitial sensors versus capillary blood glucose monitoring by glucometer: An analysis of two cases

AimTo assess the differences in glucose readings between the continuous glucose monitoring calibration-free interstitial sensors versus capillary blood glucose monitoring by glucometer. Study designTwo healthy non-pregnant volunteers participated in the study, and wore simultaneously both the calibration-free Freestyle Libre and the Dexcom G6 sensor. Glucose values were recorded before and after meals during breakfast, lunch, and dinner on three separate days by either scanning the Freestyle Libre CGM sensor with a smartphone, or obtaining glucose readings real-time through the Dexcom G6 CLARITY mobile application. Blood glucose values were recorded using the Accu-Chek Active glucose meter. The Wilcoxon signed-rank test was used for paired non-parametric data to compare glucose readings between groups. ResultsThe average glucose values obtained from the Dexcom G6 CGM consistently registered higher (6.54 ± 0.80 mmol/L) and those from the Freestyle Libre (5.49 ± 0.65 mmol/L) consistently lower, from the glucometer (6.17 ± 0.55 mmol/L), with p-value <0.05 between groups. In the three-way comparison, the Dexcom G6 CGM sensor yielded the highest values, followed by the glucose meter, and finally the Freestyle Libre CGM sensor ConclusionBoth CGM systems exhibited discrepancies from blood glucose (BG) measurements, and variations were observed among the different CGM systems themselves.

Variation in monitoring: Glucose measurement in the ICU as a case study to preempt spurious correlations

ObjectiveHealth inequities can be influenced by demographic factors such as race and ethnicity, proficiency in English, and biological sex. Disparities may manifest as differential likelihood of testing which correlates directly with the likelihood of an intervention to address an abnormal finding. Our retrospective observational study evaluated the presence of variation in glucose measurements in the Intensive Care Unit (ICU). MethodsUsing the MIMIC-IV database (2008–2019), a single-center, academic referral hospital in Boston (USA), we identified adult patients meeting sepsis-3 criteria. Exclusion criteria were diabetic ketoacidosis, ICU length of stay under 1 day, and unknown race or ethnicity. We performed a logistic regression analysis to assess differential likelihoods of glucose measurements on day 1. A negative binomial regression was fitted to assess the frequency of subsequent glucose readings. Analyses were adjusted for relevant clinical confounders, and performed across three disparity proxy axes: race and ethnicity, sex, and English proficiency. ResultsWe studied 24,927 patients, of which 19.5% represented racial and ethnic minority groups, 42.4% were female, and 9.8% had limited English proficiency. No significant differences were found for glucose measurement on day 1 in the ICU. This pattern was consistent irrespective of the axis of analysis, i.e. race and ethnicity, sex, or English proficiency. Conversely, subsequent measurement frequency revealed potential disparities. Specifically, males (incidence rate ratio (IRR) 1.06, 95% confidence interval (CI) 1.01 – 1.21), patients who identify themselves as Hispanic (IRR 1.11, 95% CI 1.01 – 1.21), or Black (IRR 1.06, 95% CI 1.01 – 1.12), and patients being English proficient (IRR 1.08, 95% CI 1.01 – 1.15) had higher chances of subsequent glucose readings. ConclusionWe found disparities in ICU glucose measurements among patients with sepsis, albeit the magnitude was small. Variation in disease monitoring is a source of data bias that may lead to spurious correlations when modeling health data.

The Maintain High Blood Glucose subscale of the child hypoglycemia fear survey: proposed preliminary cut points for screening youth with type 1 diabetes.

To improve the clinical utility of the Maintain High Blood Glucose subscale of the Hypoglycemia Fear Surveys (HFS) by identifying clinically meaningful cut points associated with glycemic outcomes. Youth (N = 994; 13.96 ± 2.3 years) with type 1 diabetes and their caregivers (N = 1,111; 72% female) completed the Child or Parent version of the HFS. Modal Score Distribution, Standard Deviation Criterion, and Elevated Item Criterion approaches were used to identify proposed preliminary cut points for the Maintain High Blood Glucose subscale. The association between proposed preliminary cut points was examined with youth glycemic outcomes. A cut point of ≥7 for the Maintain High Blood Glucose subscale on the Child HFS was associated with a greater percentage of blood glucose readings >180 mg/dl (p < .01), higher mean blood glucose (p < .001), and a higher hemoglobin A1c (p < .05). In subsequent multiple regression analyses, controlling for other factors associated with glycemia, the significant association between scores above ≥7 and higher mean blood glucose and higher hemoglobin A1c remained. A clinically useful cut point was not identified for caregivers. However, elevated youth scores on the Maintain High Blood Glucose subscale were positively associated with elevated caregiver scores (phi = .171, p < .001). The proposed preliminary cut point for the Maintain High Blood Glucose subscale will aid the type 1 diabetes care team in identifying youth whose behaviors may be contributing to their suboptimal glycemia.

Carbohydrate Ingestion Increases Interstitial Glucose and Mitigates Neuromuscular Fatigue during Single-Leg Knee Extensions.

We aimed to investigate the neuromuscular contributions to enhanced fatigue resistance with carbohydrate (CHO) ingestion and to identify whether fatigue is associated with changes in interstitial glucose levels assessed using a continuous glucose monitor (CGM). Twelve healthy participants (six males, six females) performed isokinetic single-leg knee extensions (90°·s -1 ) at 20% of the maximal voluntary contraction (MVC) torque until MVC torque reached 60% of its initial value (i.e., task failure). Central and peripheral fatigue were evaluated every 15 min during the fatigue task using the interpolated twitch technique and electrically evoked torque. Using a single-blinded crossover design, participants ingested CHO (85 g sucrose per hour), or a placebo (PLA), at regular intervals during the fatigue task. Minute-by-minute interstitial glucose levels measured via CGM and whole blood glucose readings were obtained intermittently during the fatiguing task. CHO ingestion increased time to task failure over PLA (113 ± 69 vs 81 ± 49 min, mean ± SD; P < 0.001) and was associated with higher glycemia as measured by CGM (106 ± 18 vs 88 ± 10 mg·dL -1 , P < 0.001) and whole blood glucose sampling (104 ± 17 vs 89 ± 10 mg·dL -1 , P < 0.001). When assessing the values in the CHO condition at a similar time point to those at task failure in the PLA condition (i.e., ~81 min), MVC torque, percentage voluntary activation, and 10 Hz torque were all better preserved in the CHO versus PLA condition ( P < 0.05). Exogenous CHO intake mitigates neuromuscular fatigue at both the central and peripheral levels by raising glucose concentrations rather than by preventing hypoglycemia.

A primary care-led weight management intervention for adults with diabetes and obesity: quantitative results from a randomised controlled trial of total meal replacement (DiRECT)

Methods to reduce obesity and type 2 diabetes in Aotearoa New Zealand are desperately needed, with obesity one of the greatest predisposing factors for type 2 diabetes as well as heart disease, and certain cancers.1 A recent New Zealand report2 identified several interventions that might benefit people with established diabetes, the most promising being a period of rapid weight loss, followed by supported weight-loss maintenance. Such weight loss has shown to achieve what was previously thought impossible, diabetes remission,3 as well as appreciably reduce the risk of cardiovascular disease and prevent diabetes-related chronic kidney disease, retinopathy, nephropathy, and lower limb amputation.2 While the findings from the studies of low energy total meal replacement diets have stimulated great interest, their use in Aotearoa New Zealand has not been considered. The purpose of this primary-care led intervention therefore was to consider the acceptability and efficacy of such a weight loss programme, DiRECT, in Aotearoa New Zealand. Te Kāika DiRECT is a 12-month study conducted within a Māori primary healthcare provider in O¯tepoti Dunedin. The DiRECT protocol is three months of total meal replacement for rapid weight loss followed by food reintroduction and a longer period of supported weight loss maintenance. Participants were adults with prediabetes or T2 diabetes and obesity wanting to lose weight. Twenty participants (70% female, age 46 (SD 10), BMI 41 (9), HbA1c 51 (11)) were randomised to receive the DiRECT protocol, twenty more (70% female, age 50 (SD 8), BMI 40 (7), HbA1c 54 (14)) were randomised to receive best practice weight loss support (usual care). All participants had the same number of visits with the in-house Dietitian and free access to the onsite gym. Participants in the control group also received regular grocery vouchers to purchase the foods encouraged by healthy eating guidelines. Recruitment began in February, 2022. After the initial three month study period, DiRECT participants reported consuming 3.0MJ (95% CI 1.2 to 4.8MJ) less energy per day than those in usual care. Mean weight loss was 6kg (2.3-9.6kg) greater for DiRECT participants than usual care participants, while medication use and systolic blood pressure (12mmHg (0-24mmHg)) were lower. Continuous glucose monitoring identified that at baseline, participants on average only spent 10% of the day with a blood glucose reading under 8mmol/L (normoglycaemia). After three months, the usual care group spent on average 48% of the day within the normoglycaemic range, while DiRECT participants spent 78% of the day within the normoglycaemic range. Results at 12 months will enable comment on longer term markers of blood glucose control (HbA1c) and diabetes remission rates, as well as indicate if the body weight, medication, and blood pressure improvements observed at three months are sustained.

After-meal blood glucose level prediction for type-2 diabetic patients

Type 2 Diabetes, a metabolic disorder disease, is becoming a fast growing health crisis worldwide. It reduces the quality of life, and increases mortality and health care costs unless managed well. After-meal blood glucose level measure is considered as one of the most fundamental and well-recognized steps in managing Type 2 diabetes as it guides a user to make better plans of their diet and thus control the diabetes well. In this paper, we propose a data-driven approach to predict the 2 h after meal blood glucose level from the previous discrete blood glucose readings, meal, exercise, medication, & profile information of Type 2 diabetes patients. To the best of our knowledge, this is the first attempt to use discrete blood glucose readings for 2 h after meal blood glucose level prediction using data-driven models. In this study, we have collected data from five prediabetic and diabetic patients in free living conditions for six months. We have presented comparative experimental study using different popular machine learning models including support vector regression, random forest, and extreme gradient boosting, and two deep layer techniques: multilayer perceptron, and convolutional neural network. We present also the impact of different features in blood glucose level prediction, where we observe that meal has some modest and medication has a good influence on blood glucose level.

Perceived Social Support and Glycemic Control among Type 2 Diabetes Patients in a Tertiary Care Center in Chennai, Tamil Nadu, India

Introduction: Support from the external environment for enabling behavioral change, is often instrumental in mediating glycemic control in patients coping with diabetes. While evidence is scant in the Indian setting, there is a lack of consistency in findings among studies done elsewhere. Objective: To assess the perceived availability of social support and its association with glycemic control among type 2 diabetics. Method: Between October and December 2019, Cross sectional study was conducted among 150 adult patients, selected using convenient sampling method at the Diabetology clinic in a tertiary care centre in Chennai. Outpatients with a confirmed diagnosis of type 2 diabetes for at least one year, were recruited by convenient sampling. Perceived social support was assessed using the RAND-MOS social support survey instrument, while average of last three fasting blood glucose (FBG) readings determined glycemic status. Non-parametric Kruskal Wallis and Mann-Whitney U tests were used to analyze association of social support with glycemic control and socio-demographic determinants. Spearman’s correlation coefficients with 95% CIs are reported for association of individual domain scores with average FBG. All analyses were performed with SPSS Version 23. Results: Study participants were aged 35 to 85 years, and living with type 2 diabetes for a mean duration of 10 ± 7.7 years. The average FBG in the past year ranged from 79 to 398 mg/dl in these patients, with 41 (27%) and 109 (73%) being classified as having good and poor glycemic control, respectively. The median (IQR) social support summary score was 62 (40-81) on a scale of 0 – 100; perceived social support was reportedly low, intermediate, and high in 36 (24%), 74 (49%) and 40 (27%) participants, respectively. The level of social support was not found to be significantly associated with glycemic control (P=0.628); average FBG and summary social support score showed no correlation [ρ=.081 (95% CI: -.097, .253), P =.322]. Conclusion: While a three- fourths majority reported availability of social support for coping with diabetes, this was not found to be significantly associated with glycemic status. The potential role of support networks, beyond the immediate family, in improving health outcomes needs to be examined.

Body mass index moderates the association between diabetes distress and objective self-management behaviours in adolescents with type 1 diabetes and elevated A1Cs.

To examine the cross-sectional associations between diabetes distress, BMI (zBMI; BMI z-score), objectively measured mean daily blood glucose readings and insulin boluses administered, and A1C in adolescents with type 1 diabetes (T1D) using insulin pumps. T1D self-management behaviour data were downloaded from adolescents' (N = 79) devices and mean daily frequency of blood glucose readings and insulin boluses were calculated. Diabetes distress was measured (Problem Areas in Diabetes-Teen questionnaire [PAID-T]), A1C collected, and zBMI calculated from height and weight. Three multiple linear regressions were performed with blood glucose readings, insulin boluses, and A1C as the three dependent variables and covariates (age, T1D duration), zBMI, diabetes distress, and the diabetes distress x zBMI interaction as independent variables. Participants (55.7% female) were 14.9 ± 1.9 years old with T1D for 6.6 ± 3.4 years. zBMI moderated the relationship between diabetes distress and mean daily insulin boluses administered (b = -0.02, p = 0.02); those with higher zBMI and higher diabetes distress administered fewer daily insulin boluses. zBMI was not a moderator of the association between diabetes distress and blood glucose readings (b = -0.01, p = 0.29) or A1C (b = 0.002, p = 0.81). Using objective behavioural data is useful for identifying how adolescent diabetes distress and zBMI affect daily bolusing behaviour amongst adolescent insulin pump users. Although distinct interventions exist to improve T1D self-management or diabetes distress, none addresses them together while considering zBMI. Decreasing diabetes distress could be especially important for youth with high zBMI.

Non-invasive measurements of blood glucose levels by time-gating mid-infrared optoacoustic signals

Non-invasive glucose monitoring (NIGM) represents an attractive alternative to finger pricking for blood glucose assessment and management of diabetes. Nevertheless, current NIGM techniques do not measure glucose concentrations in blood but rely on indirect bulk measurement of glucose in interstitial fluid, where glucose is diluted and glucose dynamics are different from those in the blood, which impairs NIGM accuracy. Here we introduce a new biosensor, termed depth-gated mid-infrared optoacoustic sensor (DIROS), which allows, for the first time, non-invasive glucose detection in blood-rich volumes in the skin. DIROS minimizes interference caused by the stratum corneum and other superficial skin layers by time-gating mid-infrared optoacoustic signals to enable depth-selective localization of glucose readings in skin. In measurements on the ears of (female) mice, DIROS displays improved accuracy over bulk-tissue glucose measurements. Our work demonstrates how signal localization can improve NIGM accuracy and positions DIROS as a holistic approach, with high translational potential, that addresses a key limitation of current NIGM methods.

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

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

Changes in glucometric parameters in people living with diabetes users of the free-style libre 2 system before and after the update possibility to real-time glucose readings in real world practice

In Spain, from October 10th, 2023, the FreeStyle Libre 2 system offers the possibility to automatically changed from isCGM to rtCGM with a system update. Our study aimed to evaluate the glucometric before and after that date. We didn't find significant changes in TIR, however time of use increased and TBR decreased.

Use of FreeStyle Libre for continuous glucose monitoring in adult horses.

To evaluate the feasibility of using the FreeStyle Libre (a continuous glucose monitoring system [CGMS]) for instantaneous continuous monitoring of interstitial glucose in adult horses and examine the applicability and accuracy of this system in horses submitted to combined glucose-insulin test (CGIT). Laboratory measurements and continuous glucose monitoring system (CGMS) readings were analyzed using a 2 × 2 factorial statistical model with repeated measures over time. This analysis assessed the effects of the test (factor 1), group (factor 2), and their interactions (test × group, test × time, and group × time). Pearson's correlation analysis was applied to blood glucose values. Mean comparisons were conducted using the t-test, and agreement between techniques was assessed via the Bland-Altman method, with a 95% confidence interval. Field study on private horse farms in association with a veterinary school. Ten healthy stallions were assigned to one of two groups based on their body condition scores (BCS). Group 1 (G1, n= 5) consisted of nonobese horses with a BCS of 5 or 6, while Group 2 (G2, n= 5) consisted of obese horses with a BCS of 7 or higher. A CGMS sensor was attached to the dorsolateral aspect of the proximal one third of each horse's neck. Laboratory blood glucose measurements and CGMS interstitial glucose readings were compared at different time points for up to 7days after sensor fixation. Obese horses were also submitted to CGIT on Day 4. A comparative analysis of glucose measurements obtained in G1 and G2 horses using the CGMS and enzymatic methods revealed significant group×time interactions (P<0.001) and time effects (P<0.001). No interactions were detected between group (P=0.45), test (P=0.62), group and test (P=0.28), or time and test (P=0.92). In G1 and G2, tests were significantly correlated (r=0.84 and P=0.00) at all time points (T0-T5). Agreement between the glucose values obtained using different methods was excellent despite a small time delay in CGMS detection of rapid changes in blood glucose. It was concluded that the CGMS can be used for indirect assessment of glycemic status (ie, based on interstitial glucose measurements) in nonobese and obese adult horses submitted to CGIT.

Continuous inline monitoring of glucose in an organ-on-chip using FreeStyle™ libre glucometers

Introduction: Organ-on-chips have become an effective platform for studying the physiology of tissues and organs and for evaluating the safety and efficacy of drugs. In these systems, the inline monitoring of key parameters of biological performance (i.e., glucose, oxygen, or lactic acid concentrations) provides valuable information regarding the cell/tissue physiological state. However, significant limitations still exist when attempting to obtain inline information in these systems, and the microsensing technology of on-chip measurement of key parameters is still limited by size, cost, and availability.Methods: Here, we demonstrate the use of a commercially available glucometer (FreestleTM Libre; Abbott), normally used for continuous determination of blood glucose levels, to provide continuous inline measurements of the glucose concentration in tumor-on-chips. Here, we employed a colorectal tumor-on-chip as a first demonstration model and measured the on-chip concentration of glucose continuously for extended culture times (2 weeks).Results and Discussion: We show that inline glucose readings are reproducible and enable the accurate determination of glucose consumption rates (GCRs) by a tumor cell culture. In turn, the GCR measurements provide valuable information regarding the changes in the metabolic activity of the on-chip cultures following inlet perturbations (i.e., delivery of pulses of glucose, culture media additives, and drugs). Inline continuous glucose sensors will be useful tools in organ-on-chip research and will greatly enable cancer research in tumor-on-chip systems.

Sliding Scale Insulin Use in Nursing Homes Before and After Onset of the COVID-19 Pandemic

ObjectiveTo characterize sliding-scale insulin (SSI) use in US nursing homes (NHs) before and after the COVID-19 pandemic. DesignCross-sectional study. Setting and ParticipantsA total of 129,829 US NH residents on SSI (01/2018-06/2022) across 12 NH chains with a common electronic health record system. MethodsAmong all residents with at least 1 administration of SSI documented in the electronic medication administration record, we described resident demographics, frequency of SSI monotherapy vs combination therapy with another diabetes medication, number of daily capillary blood glucose readings (“fingersticks”), and hypoglycemia (capillary blood glucose <70 mg/dL) and hyperglycemia after first SSI use. We used interrupted time series analysis (ITS) with segmented linear regression models to examine whether the monthly prevalence of SSI use changed at and after the onset of the COVID-19 pandemic (March 2020). ResultsThere were 129,829 unique NH residents with SSI use [51% women, average age 71.3 (SD 11.7) years]. Of these, 36% of residents received SSI monotherapy and 64% received SSI combination therapy. Residents on SSI received an average of 3.96 (SD 1.41) fingersticks per day. Overall, 26% of SSI users experienced a hypoglycemic event within 30 days of the first SSI dose. The ITS analysis identified a step decrease in the rate of SSI use following the onset of the COVID-19 pandemic (43 fewer SSI users per 1000 insulin users) but no change in overall trend over time from before the onset of the pandemic. Conclusions and ImplicationsSSI use and fingerstick burden are high in NH residents. Hypoglycemia occurred commonly among residents on SSI. Future research should compare the safety and effectiveness of SSI monotherapy vs other diabetes medication regimens to guide person-centered prescribing decisions in NHs.

Impact of Lowered Inpatient Correctional Bedtime Insulin Dosing on Glycemic Outcomes of Veterans

Purpose: This study evaluated glycemic outcomes for hospitalized patients after reduction in bedtime correctional insulin dosing. Methods: This was a retrospective, single-center analysis of a protocol change that reduced bedtime correctional insulin scale. Comparable cohorts pre- and post-protocol change were created which included patients who were ordered correctional insulin with at least 1 blood glucose (BG) reading. The primary outcome was number of nocturnal hypoglycemia readings. Secondary outcomes included, but were not limited to, mean fasting BG, BG within various ranges, and length of stay. Results: 3 percent of patients in the post-protocol change group (N = 100) experienced nocturnal hypoglycemia compared to 6% of patients in the pre-change group (N = 100) (P = .507). There were no significant differences in BG ranges <110 mg/dL, <140 mg/dL, 140 to 180 mg/dL, and >180 mg/dL. However, 19% of patients in the post-protocol change group had BG of >250 mg/dL as compared to 9% in the pre-change group (P = .033). Mean fasting BG was higher in the post-protocol change group compared to the pre-change group (156.5 mg/dL vs 139.3 mg/dL [P = .002]), as was hospital length of stay (5.17 vs 4.6 days, [P = .024]). Conclusions: A decreased bedtime correctional insulin scale had mixed results with more patients achieving goal fasting BG but also more patients experiencing BG > 250 mg/dL and longer length of stay. Larger prospective studies are required to evaluate the safety and efficacy of this type of intervention and its long-term impact.