Blood Glucose Variability Research Articles

Metabolic control level and glucose variability in adolescents with type 1 diabetes during low and high-intensity exercise.

The main purpose of this study was to characterize the determinants of metabolic changes in young type 1 diabetes (T1DM) and to determine glycemic variability during low and high-intensity exercise. 20 young male T1DM patients were divided into two subgroups characterized by levels of glycated hemoglobin (HbA1c): HbA1c<7.3% (better HbA1c subgroup, n=10) and with levels HbA1c>7.3% (worse HbA1c subgroup, n=10). All participants performed a maximal oxygen uptake test and two efforts of various intensities (45 minutes of aerobic exercise and 30 minutes of mixed aerobic-anaerobic intensity exercise). Continuous glucose monitors (CGM) were used to control the glucose concentration. Changes in biomarkers describing the metabolic response were similar in both groups. A comparison of applied efforts exhibited that maximal capacity effort resulted in the highest values of blood glucose (BG) at the end (150.9-160.6 mg/dl) and 1 hour after the exercise (140.2-161.3 mg/dl). BG concentration before, during, 1 hour, and 24 hours after each exercise was insignificantly higher in the worse Hb1Ac group. HbA1c levels are insufficient to confirm whether the applied effort is performed in acceptable glycemic values. The CGM monitors allow for precise control of BG variations and accurate planning of physical activity by adjusting the insulin and carbohydrate consumption dose.

The safety of preoperative carbohydrate drinks in extremely elderly patients assessed by gastric ultrasonography: a randomized controlled trial

BackgroundModern perioperative guidelines encourage drinking oral carbohydrates 2 h before management. Nevertheless, research on the safety of preoperative carbohydrate drinks, particularly in extremely elderly patients is lacking. We aimed to evaluate the safety of carbohydrate drinks 2 h before surgery in extremely elderly patients (≥ 80 years) using gastric ultrasonography.MethodsWe conducted a randomized prospective comparative study of 70 patients aged over 80 years who were scheduled for total knee arthroplasty, hip fracture or humerus fracture surgery. These patients were randomly assigned to the carbohydrate group (n = 35), which fasted from midnight, except for drinking 355 mL of a carbohydrate-containing fluid 2 h before surgery, or the fasting group (n = 35), which fasted from midnight and drank no fluid before surgery. The primary outcome of the study was the cross-sectional area (CSA) of the gastric antrum in the right lateral decubitus position (RLDP) before surgery. The secondary outcomes included CSA in the supine position, intraoperative blood glucose levels and their variability coefficients, Perlas grade, and the visual analog scale of subjective feelings.ResultsThe CSA in the RLDP and supine positions revealed no differences between the carbohydrate and fasting groups at 0 h preoperatively (P > 0.05). In the qualitative assessment, preoperative 0-h Perlas grading did not differ significantly between the groups (P > 0.05). From 2 h before surgery to transfer out of the post-anesthesia care unit, the average blood glucose level of patients in the carbohydrate group was significantly higher than that in the fasting group (P < 0.001) but remained within the normal range. Moreover, the blood glucose variability coefficient was significantly lower in the carbohydrate group than in the fasting group (P = 0.009). Oral intake of 355 mL carbohydrates before surgery significantly relieved patients’ feelings (P < 0.001).ConclusionPreoperative consumption of carbohydrate drinks 2 h before surgery is safe in “healthy” extremely elderly patients. In addition, preoperative drinking has potential value in maintaining ideal blood glucose levels and stable blood glucose fluctuations perioperatively and improving subjective perceptions of preoperative preparation. This finding warrants further investigation in clinical practice.Trial registrationChinese Clinical Trial Registry (Registration Number ChiCTR1900024812), first registered on 29/07/2019.

Associations of variability in blood glucose and systolic blood pressure with mortality in patients with coronary artery disease: A retrospective cohort study from the MIMIC-IV database

AimsVariability of metabolic parameters, such as glycemic variability (GV) and systolic blood pressure variability (SBPV), are associated with adverse cardiovascular outcomes. However, whether these parameters have additive effects on mortality in patients with coronary artery disease (CAD) hospitalized in the intensive care unit (ICU) remains unclear. MethodsWe retrospectively enrolled patients with CAD from the Medical Information Mart for Intensive Care-IV database. The highest tertile of variability was defined as high variability. A variability scoring system was established, which assigned 0 points to tertile 1, 1 point to tertile 2, and 2 points to tertile 3 for GV and SBPV. ResultsAmong 4237 patients with CAD, 400 patients died in hospital, and 967 patients died during 1-year follow-up. High GV and high SBPV were associated with an increased risk of mortality. The effects of GV and SBPV on in-hospital mortality were partially mediated by ventricular arrhythmias (18.0 % and 6.6 %, respectively). The risk of mortality gradually increased with the number of high-variability parameters and increasing variability scores. ConclusionsGV and SBPV have additive effects on the risk of mortality in patients with CAD hospitalized in the ICU. Ventricular arrhythmias partially mediate the effects of GV and SBPV on in-hospital mortality.

Effect of Sevoflurane, Isoflurane, and Desflurane on the Random Blood Glucose Levels in Non-diabetic Patients Undergoing General Anesthesia: A Randomized, Single-Blind Study.

Volatile anesthetic agents like sevoflurane, isoflurane, and desflurane are widely used for maintaining general anesthesia (GA). Their effect on the autonomic system is different and can impact the blood sugar homeostasis. This study compares the intraoperative blood glucose levels in non-diabetic patients undergoing non-cardiac surgery under GA with the three volatile agents. A randomized, single-blind, parallel-arm study recruited 105 non-diabetic patients into three groups. GA induction and maintenance were standardized except for the volatile agent. Capillary blood sugar levels were measured at different time points and compared between and within the groups. A p-value of <0.05 was considered significant. Entire participants completed the study, and their baseline characteristics were statistically indifferent. Intraoperative blood glucose rise and variation were the highest in the desflurane group and the lowest in the isoflurane group; the differences were statistically significant at 15, 30, and 45 minutes. The highest blood sugar level was noted at 60 minutes in all groups; after that, the level started falling. However, none of the raises were beyond 140 mg% to categorize them as hyperglycemia. Intraoperative glycemic variation was evident with isoflurane, sevoflurane, and desflurane. The maximum increase from the pre-induction level was noted at 60 minutes. However, none of the readings reached the hyperglycemia level. The rise was significantly higher in desflurane-based anesthesia than in isoflurane. This study was, however, conducted in non-diabetic patients; hence, results might not be extrapolated to diabetic patients.

МЕТЕОЗАВИСИМОСТЬ: МИФ ИЛИ РЕАЛЬНОСТЬ (НА ПРИМЕРЕ АРТЕРИАЛЬНОЙ ГИПЕРТОНИИ)

The paper examines the relationship of meteorological factors with the development of cardiovascular complications. Statistically significant seasonal fluctuations in the level and variability of blood pressure, heart rate, cholesterol, glucose, and body mass have been revealed. The variability of blood pressure is maximal in winter and minimal in summer. It is known that heat and cold waves are associated with an increase in mortality and cardiovascular complications, including hypertensive crises. Their frequency depends on the level of cardiovascular risk of a patient and is maximal in people with coronary heart disease, cerebrovascular disease, and type 2 diabetes. The influence of such poorly predictable factors as temperature waves and magnetic storms has been less studied. It seems promising to examine the relationship of the variability of blood pressure and complications of arterial hypertension with meteorological factors using the method for remote blood pressure monitoring, which is currently actively implemented in the regions of the Russian Federation.

Relationship between blood glucose variation, collateral circulation and Batman score and prognosis after mechanical thrombectomy with Solitaire stent in acute posterior vascular occlusive stroke

Objective: To explore the relationship between blood glucose variability, collateral circulation and basilar artery computed scan angiography score (Batman) and prognosis of mechanical thrombectomy with Solitaire stent in patients with large vascular occlusive APCI. Methods: A retrospective study was conducted on 113 patients with large vessel occlusive APCI who underwent Solitaire stent mechanical thrombectomy in the Department of Neurology of Nanyang Central Hospital from March 2021 to July 2022. According to the prognosis, they were divided into outcome group (46 cases) and adverse group (67 cases). Evaluate the prognosis based on the Modified Rankin Scale three months after the surgery. The differences in collateral circulation, GV and Batman score between the two groups were compared, and the related factors affecting the prognosis of large vessel occlusive APCI patients treated with Solitaire stent mechanical thrombectomy were analyzed by multivariate logistic regression model. Results: The age of 113 patients with acute large vessel occlusive APCI was (65.3±8.9) years old. The proportion of female was 34.5% (39 cases). Compared with the outcome group, the adverse group had a lower proportion of collateral circulation [40 cases (87.0%) vs 47 cases (70.2%)], higher GV score [(25.19±3.54) vs (30.36±4.11) points], lower Batman score [(7.49±1.52) vs (6.65±1.33) points], higher proportion of atrial fibrillation history [16 cases (23.9%) vs 4 cases (8.7%)], higher National Institutes of Health Stroke Scale (NIHSS) score at admission [(8.33±0.74) vs (7.25±0.92) points], larger core infarct volume [(32.57±4.87) vs (29.54±5.14) ml], and longer time from admission to vascular recanalization [(123.52±31.17) vs (102.47±29.54) min] (all P<0.05). Atrial fibrillation history, core infarct volume, NIHSS score at admission, time from admission to vascular recanalization, glycemic variability, collateral circulation, and Batman score were related factors for the prognosis of large vessel occlusive APCI patients treated with Solitaire stent mechanical thrombectomy, with ORvalues (95%CI) of 1.383 (1.124-1.641), 1.166 (1.007-1.350), 4.777 (1.856-12.297), 3.068 (2.379-3.757), 1.477 (1.209-1.806), 0.742 (0.654-0.831), and 0.717 (0.214-1.221), respectively (all P<0.05). Conclusion: Blood glucose variation is a risk factor for prognosis of mechanical thrombectomy with Solitaire stent in patients with large vascular occlusive APCI, and collateral circulation and Batman score are protective factors.

Improvement of blood glucose control and reduction of hypoglycemia, body weight, and C-reactive protein in type 1 diabetic patients treated with intensive insulin therapy with insulin analogs

Background/Aim. Good metabolic control can delay the onset and progression of chronic complications of diabetes mellitus (DM). Intensified insulin therapy (IIT) is the cornerstone of good metabolic control in the treatment of type 1 DM (T1DM) while avoiding hypoglycemia and body weight (BW) gain in those patients. The aim of the study was to assess the effects of IIT with insulin analogs (aspart and glargine) in T1DM patients. Methods. This prospective clinical study included 49 patients with at least one year of T1DM duration, who were on IIT with human insulin at that moment. They commenced therapy with insulin aspart for three months, followed by insulin glargine for another three months. An analysis of blood glucose (BG) control (glycated hemoglobin ? HbA1c, mean BG, fasting BG, postprandial BG, and glycemic variability) and analysis of BW, hypoglycemia, and C-reactive protein (CRP) levels were performed. Results. The HbA1c level decreased slightly (non-significantly) after three months of insulin aspart therapy (from 9.28% to 8.83%) and decreased significantly after the aspart/glargine combination (to 8.08%; p &lt; 0.001). After the first three months with aspart therapy, a significant reduction in postprandial BG was noted after all three main meals. The mean postprandial rise of BG was significantly reduced. The variability of daily BG was significantly reduced (standard deviation of BG fell from 2.28 mmol/L to 1.90 mmol/L; p &lt; 0.05). The mean BG value in the profiles decreased (from 9.11 mmol/L to 8.31 mmol/L; p &lt; 0.05). All BG values in the profiles after six months were statistically significantly lower compared to the initial values, as well as the mean BG (6.88 mmol/L; p &lt; 0.001) and the variability of daily BG (1.49 mmol/L; p &lt; 0.01). Our results showed a significant reduction in the number of hypoglycemias after three months, especially after the introduction of insulin glargine therapy (significant reduction in the number of symptomatic, asymptomatic, and nocturnal hypoglycemias). The results showed a discrete but significant reduction in BW and a significant reduction in CRP levels (from 3.43 mg/L to 2.25 mg/L; p &lt; 0.001). Conclusion. Treatment of patients with T1DM with insulin analogs (insulin aspart and insulin glargine) in IIT leads to improved BG control with a reduction in the number of hypoglycemia, BW, and CRP levels.

Observational study on stability of within-day glycemic variability of type 2 diabetes inpatients treated with decoctions of traditional Chinese medicine.

Within-day glycemic variability (GV), characterized by frequent and significant fluctuations in blood glucose levels, is a growing concern in hospitalized patients with type 2 diabetes mellitus (T2DM). It is associated with an increased risk of hypoglycemia and potentially higher long-term mortality rates. Robust clinical evidence is needed to determine whether traditional Chinese medicine (TCM) decoctions can be a beneficial addition to the management of within-day GV in this patient population. This retrospective cohort study utilized data from adult inpatients diagnosed with T2DM admitted to the Traditional Chinese Medicine Hospital of Kaifeng. The primary outcome investigated was the association between the use of TCM decoctions and improved stability of within-day GV. Blood glucose variability was assessed using the standard deviation of blood glucose values (SDBG). For each patient, the total number of hospitalization days with SDBG below 2mmol/L was calculated to represent within-day GV stability. Hospitalization duration served as the secondary outcome, compared between patients receiving TCM decoctions and those who did not. The primary analysis employed a multivariable logistic regression model, with propensity score matching to account for potential confounding variables. A total of 1,360 patients were included in the final analysis. The use of TCM decoctions was significantly associated with enhanced stability of within-day GV (OR = 1.77, 95% CI: 1.34-2.33, P < 0.01). This association was most prominent in patients with a diagnosis of deficiency syndrome (predominantly qi-yin deficiency, accounting for 74.8% of cases) and a disease duration of less than 5years (OR = 2.28, 95% CI: 1.21-4.29, P = 0.03). However, TCM decoctions did not exert a statistically significant effect on hospitalization duration among patients with T2DM (OR = 0.96, 95% CI: 0.91-1.01, P = 0.22). This study suggests that TCM decoctions may be effective in improving within-day GV stability in hospitalized patients with T2DM. This effect appears to be most pronounced in patients diagnosed with deficiency syndrome, particularly those with qi-yin deficiency and a shorter disease course. Further investigation is warranted to confirm these findings and elucidate the underlying mechanisms.

Nutrient Involvement in Insulin Secretion and Blood Glucose Variability

Nutrient Involvement in Insulin Secretion and Blood Glucose Variability

Correlation of blood glucose variability based on CGMS monitoring during cardiopulmonary bypass and postoperative delirium in patients with rheumatic heart disease valve replacement

Correlation of blood glucose variability based on CGMS monitoring during cardiopulmonary bypass and postoperative delirium in patients with rheumatic heart disease valve replacement

On the Performance of Metamaterial based Printed Circuit Antenna for Blood Glucose Level Sensing Applications: A Case Study

Due to the urgent need to develop technologies for continuous glucose monitoring in diabetes individuals, poten tial research has been applied by invoking the microwave tech niques. Therefore, this work presents a novel technique based on a single port microwave circuit, antenna structure, based on Metamaterial (MTM) transmission line defected patch for sensing the blood glucose level in noninvasive process. For that, the proposed antenna is invoked to measure the blood glu cose through the field leakages penetrated to the human blood through the skin. The proposed sensor is constructed from a closed loop connected to an interdigital capacitor to magnify the electric field fringing at the patch center. The proposed an tenna sensor is found to operate excellently at the first mode, 0.6GHz, with S11 impedance matching less than -10dB. The proposed sensor performance is tested experimentally with 15 cases, different patients, through measuring the change in the S11 spectra after direct touching to the sensor a finger print of a patient. The proposed sensor is found to be effectively very efficient detector for blood glucose variation with a low manu facturing cost when printed on an FR-4 substrate. The experi mental measurements are analyzed mathematically to obtain the calibration equation of the sensor from the curve fitting. Finally, the theoretical and the experimental results are found to be agreed very well with a percentage of error less than 10%.

A novel hypoglycemia alarm framework for type 2 diabetes with high glycemic variability.

In patients with type 2 diabetes (T2D), accurate prediction of hypoglycemic events is crucial for maintaining glycemic control and reducing their frequency. However, individuals with high blood glucose variability experience significant fluctuations over time, posing a challenge for early warning models that rely on static features. This article proposes a novel hypoglycemia early alarm framework based on dynamic feature selection. The framework incorporates domain knowledge and introduces multi-scale blood glucose features, including predicted values, essential for early warnings. To address the complexity of the feature matrix, a dynamic feature selection mechanism (Relief-SVM-RFE) is designed to effectively eliminate redundancy. Furthermore, the framework employs online updates for the random forest model, enhancing the learning of more relevant features. The effectiveness of the framework was evaluated using a clinical dataset. For T2D patients with a high coefficient of variation (CV), the framework achieved a sensitivity of 81.15% and specificity of 98.14%, accurately predicting most hypoglycemic events. Notably, the proposed method outperformed other existing approaches. These results indicate the feasibility of anticipating hypoglycemic events in T2D patients with high CV using this innovative framework.

Correlation between long-term glycemic variability and cognitive function in middle-aged and elderly patients with type 2 diabetes mellitus: a retrospective study.

To investigate the correlation between long-term glycemic variability and cognitive function in middle-aged and elderly patients with type 2 diabetes mellitus (T2DM). This retrospective analysis includes 222 patients hospitalized at Second Affiliated Hospital of Anhui Medical University from June 2021 to June 2023. Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination (MMSE). All patients were categorized into the MCI group and the non-MCI group based on their MoCA score. Long-term blood glucose fluctuations were measured using glycated hemoglobin A1c standard deviation (HbA1c-SD) and fasting plasma glucose standard deviation (FPG-SD). The study compared general clinical data, blood biochemical indicators, and glycemic variability indicators between the two groups. The differences between the groups were compared using t-test, Chi-Square Test, or Mann-Whitney U test. Kendall's correlation analysis, multivariate logistic regression analysis and ROC curve correlation analysis were further used to analyze the correlation and diagnostic power. The differences in age, MoCA scores, MMSE scores, HOMA-β, HbA1c-M, HbA1c-SD, FPG-M, FPG-SD, eGFR, Smoking, GLP-1RA and SGLT-2i usage were statistically significant between the two groups (P<0.05). Kendall's correlation analysis showed that age, HbA1c-M, HbA1c-SD, FPG-M, and FPG-SD was negatively correlated with MoCA scores; meanwhile, the HOMA-β, and eGFR was positively correlated with MoCA scores. Multiple logistic regression analysis revealed that HbA1c-SD, FPG-SD and Smoking were risk factors for cognitive dysfunction, while eGFR, GLP-1RA and SGLT-2i usage was a protective effect. The area under the curve (AUC) values for predicting MCI prevalence were 0.830 (95% CI [0.774-0.877], P<0.001) for HbA1c-SD, 0.791 (95% CI [0.655-0.808], P<0.001) for FPG-SD, and 0.698 (95% CI [0.633-0.757], P<0.001) for eGFR. The optimal diagnostic values were 0.91, 1.32, and 74.81 ml/min/1.73 m2 for HbA1c-SD, FPG-SD, and eGFR, respectively. Cognitive function in middle-aged and elderly T2DM patients is influenced by long-term blood glucose variability, with poorer cognitive function observed in individuals with higher blood glucose variability. The impact of HbA1c-SD on MCI exhibited a greater magnitude compared to that of PFG-SD and smoking. Additionally, renal function, GLP-1RA and SGLT-2i usage exert positive effects on cognitive function.

Data-driven meal events detection using blood glucose response patterns

BackgroundIn the Diabetes domain, events such as meals and exercises play an important role in the disease management. For that, many studies focus on automatic meal detection, specially as part of the so-called artificial β\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\beta$$\\end{document}-cell systems. Meals are associated to blood glucose (BG) variations, however such variations are not peculiar to meals, it mostly comes as a combination of external factors. Thus, general approaches such as the ones focused on glucose signal rate of change are not enough to detect personalized influence of such factors. By using a data-driven individualized approach for meal detection, our method is able to fit real data, detecting personalized meal responses even when such external factors are implicitly present.MethodsThe method is split into model training and selection. In the training phase, we start observing meal responses for each individual, and identifying personalized patterns. Occurrences of such patterns are searched over the BG signal, evaluating the similarity of each pattern to each possible signal subsequence. The most similar occurrences are then selected as possible meal event candidates. For that, we include steps for excluding less relevant neighbors per pattern, and grouping close occurrences in time globally. Each candidate is represented by a set of time and response signal related qualitative variables. These variables are used as input features for different binary classifiers in order to learn to classify a candidate as Meal or Non-Meal. In the model selection phase, we compare all trained classifiers to select the one that performs better with the data of each individual.ResultsThe results show that the method is able to detect daily meals, providing a result with a balanced proportion between detected meals and false alarms. The analysis on multiple patients indicate that the approach achieves good outcomes when there is enough reliable training data, as this is reflected on the testing results.ConclusionsThe approach aims at personalizing the meal detection task by relying solely on data. The premise is that a model trained with data that contains the implicit influence of external factors is able to recognize the nuances of the individual that generated the data. Besides, the approach can also be used to improve data quality by detecting meals, opening opportunities to possible applications such as detecting and reminding users of missing or wrongly informed meal events.

Effect of Preoperative Corticosteroids on Postoperative Glucose Control in Total Joint Arthroplasty

BackgroundDexamethasone is a commonly used perioperative medication for the management of postoperative nausea and vomiting following total joint arthroplasty (TJA). However, concerns have been raised about its potential to cause hyperglycemia. This study aimed to investigate the impact of dexamethasone administration on glucose levels and complications in both diabetic and nondiabetic patients undergoing TJA. MethodsWe performed a retrospective review of 1928 patients who underwent primary total knee and hip arthroplasty procedures at a large tertiary medical institution. Patients were divided into 2 groups based on whether they received preoperative dexamethasone. Postoperative blood glucose values and variability were measured, and data on complications were collected. We performed statistical analysis using descriptive analysis, multivariate logistic regression models, negative binomial regression, and a subset analysis to assess the impact of dexamethasone dose on postoperative glycemic control. ResultsPreoperative dexamethasone did not significantly increase the mean glucose, fasting glucose, glucose variability, or 90-day complications in both the diabetic and nondiabetic groups. Nondiabetic patients who received dexamethasone had a significantly lower rate of intensive care unit admission (P < .01). Additionally, patients who received dexamethasone had a significantly shorter length of hospital stay compared to those who did not (P < .001). ConclusionsPreoperative dexamethasone administration is a safe and effective method for preventing postoperative nausea and vomiting in patients undergoing TJA without significant adverse effects on glucose levels, glucose variability, or infection rates in both diabetics and nondiabetics. Preoperative dexamethasone decreases postoperative length of stay.

Diabetes mellitus and blood glucose variability increases the 30-day readmission rate after kidney transplantation.

Inpatient hyperglycemia is an established independent risk factor among several patient cohorts for hospital readmission. This has not been studied after kidney transplantation. Nearly one-third of patients who have undergone a kidney transplant reportedly experience 30-day readmission. Data on first-time solitary kidney transplantations were retrieved between September 2015 and December 2018. Information was linked to the electronic health records to determine diagnosis of diabetes mellitus and extract glucometric and insulin therapy data. Univariate logistic regression analysis and the XGBoost algorithm were used to predict 30-day readmission. We report the average performance of the models on the testing set on bootstrapped partitions of the data to ensure statistical significance. The cohort included 1036 patients who received kidney transplantation; 224 (22%) experienced 30-day readmission. The machine learning algorithm was able to predict 30-day readmission with an average area under the receiver operator curve (AUC) of 78% with (76.1%, 79.9%) 95% confidence interval (CI). We observed statistically significant differences in the presence of pretransplant diabetes, inpatient-hyperglycemia, inpatient-hypoglycemia, minimum and maximum glucose values among those with higher 30-day readmission rates. The XGBoost model identified the index admission length of stay, presence of hyper- and hypoglycemia, the recipient and donor body mass index (BMI) values, presence of delayed graft function, and African American race as the most predictive risk factors of 30-day readmission. Additionally, significant variations in the therapeutic management of blood glucose by providers were observed. Suboptimal glucose metrics during hospitalization after kidney transplantation are associated with an increased risk for 30-day hospital readmission. Optimizing hospital blood glucose management, a modifiable factor, after kidney transplantation may reduce the risk of 30-day readmission.

Individualized Prediction of Blood Glucose Outcomes Using Compositional Data Analysis

This paper presents an individualized multiple linear regression model based on compositional data where we predict the mean and coefficient of variation of blood glucose in individuals with type 1 diabetes for the long-term (2 and 4 h). From these predictions, we estimate the minimum and maximum glucose values to provide future glycemic status. The proposed methodology has been validated using a dataset of 226 real adult patients with type 1 diabetes (Replace BG (NCT02258373)). The obtained results show a median balanced accuracy and sensitivity of over 90% and 80%, respectively. A information system has been implemented and validated to update patients on their glycemic status and associated risks for the next few hours.

On-body non-invasive glucose monitoring sensor based on high figure of merit (FoM) surface plasmonic microwave resonator

High-figure of merit (FoM) plasmonic microwave resonator is researched as a non-invasive on-body sensor to monitor the human body's blood glucose variation rate in adults for biomedical applications, e.g., diabetic patients. The resonance frequencies of the proposed sensor are measured to be around {f}_{01}=3.25 GHz and {f}_{01}=4.67 GHz over the frequency band of DC to 6GHz which are suitable for monitoring interstitial fluid (ISF) changing rate. The 40times 40 {mathrm{mm}}^{2} sensor is experimentally wrapped on the human body arm to monitor the blood glucose changing rate via amplitude and frequency variations of the sensor. Amplitude variation and frequency shift are measured to be around 7 dB and 30 MHz, respectively. The measured results demonstrate the high precision of the proposed approach to depict a valid diagram for glucose changing rate due to good impedance matching of the designed microwave sensor and human body. The sensor is shown to enhance the sensitivity by a factor of 5 compared to the conventional ones.

Physical Activity and Type 2 Diabetes: In Search of a Personalized Approach to Improving β-Cell Function.

Type 2 diabetes mellitus (T2DM) is one of the most widespread diseases worldwide. Lifestyle interventions, including diet and physical activity (PA), are fundamental non-pharmacological components of T2DM therapy. Exercise interventions are strongly recommended for people with or at risk of developing or already with overt diabetes, but adherence to PA guidelines in this population is still challenging. Furthermore, the heterogeneity of T2DM patients, driven by differing residual β-cell functionality, as well as the possibility of practicing different types and intensities of PA, has led to the need to develop tailored exercise and training plans. Investigations on blood glucose variation in response to exercise could help to clarify why individuals do not respond in the same way to PA, and to guide the prescription of personalized treatments. The aim of this review is to offer an updated overview of the current evidence on the effects of different regimens and modalities of PA regarding glucose sensing and β-cell secretory dynamics in individuals with prediabetes or T2DM, with a special focus on β-cell function.

Impact of early postoperative blood glucose variability on serum endocan level in cardiac surgery patients: a sub study of the ENDOLUNG observational study

BackgroundEarly postoperative glycemic variability is associated with worse outcome after cardiac surgery, but the underlying mechanisms remain unknown. This study aimed to describe the relationship between postoperative glycemic variability and endothelial function, as assessed by serum endocan level in cardiac surgery patients.MethodsWe performed a post hoc analysis of patients included in the single-center observational ENDOLUNG study. Adult patients who underwent planned isolated coronary artery bypass graft surgery were eligible. Postoperative glycemic variability was assessed by calculating the coefficient of variability (CV) of blood glucose measured within 24 (CV24) and 48 (CV48) hours after surgery. Serum endocan level was measured at 24 (Endocan24) and 48 (Endocan48) hours after surgery. Pearson’s correlation coefficient with 95% confidence interval (95% CI) was calculated between CV24 and Endocan24, and between CV48 and Endocan48.ResultsData from 177 patients were analyzed. Median CV24 and CV48 were 18% (range 7 to 39%) and 20% (range 7 to 35%) respectively. Neither CV48 nor CV24 were significantly correlated to Endocan48 and Endocan24 respectively (r (95% CI) = 0.150 (0.001 to 0.290; and r (95% CI) = 0.080 (-0.070 to 0.220), respectively).ConclusionsEarly postoperative glycemic variability within 48 h after planned cardiac surgery does not appear to be correlated with postoperative serum endocan level.Clinical trial registration numberNCT02542423.