Monitoring Of Blood Glucose Levels Research Articles

Unprecedented Rise of Mucormycosis in COVID-19 Patients: Urgent Need for Protocol Adaptation and Awareness in India – A Review

Mucormycosis, a rare fungal infection, has seen a concerning surge in incidence among COVID-19 patients in India. Unlike infectious diseases, Mucormycosis spreads through fungal spores ubiquitous in the environment. COVID-19 patients with diabetes are particularly susceptible, presenting symptoms such as headache, fever, eye pain, nasal congestion, and vision loss. Early diagnosis is crucial for successful treatment. Management involves a multidisciplinary approach, including antifungal medications like liposomal amphotericin-B and posaconazole. However, treatment challenges arise due to limited availability, high cost, and prolonged administration of these drugs. Monitoring blood glucose levels during steroid therapy and raising awareness among healthcare workers and patients are essential preventive measures. Improved ventilation and hygiene practices in hospitals can reduce the risk of exposure to fungal spores. Early detection and prompt treatment are vital in preventing severe outcomes of Mucormycosis. Public education and environmental control measures are essential to mitigate the increasing incidence of this life-threatening fungal infection.

Role of Pathology and Point of Care Testing in the Estimation of Fasting Blood Glucose Levels in Type 2 Diabetes Mellitus Patients

Background: Diabetes mellitus (DM) is a global health concern with significant morbidity and mortality. Effective management of type 2 DM necessitates accurate monitoring of fasting blood glucose levels. Traditional laboratory methods, while accurate, are not always convenient for patients, leading to a growing interest in reliable point-of-care testing. Objective: The aim of this study was to compare the accuracy of fasting blood glucose measurements between point-of-care testing using a glucometer and traditional laboratory methods (hexokinase and end-point) to determine the feasibility of home-based patient monitoring. Methods: This comparative cross-sectional study included 150 type 2 DM patients from Farooq Hospital Westwood, Lahore. Participants underwent fasting blood glucose testing using three methods: the hexokinase method, the end-point method, and a glucometer (Accu-check instant S Meter). The Pearson correlation was employed to assess the linear relationship between the methods, while multivariate ANOVA was used to compare the means. Results: The Pearson correlation coefficients indicated a strong positive correlation between the glucometer readings and both laboratory methods, with coefficients of 0.994 for hexokinase and 0.997 for the end-point method. The average fasting blood glucose levels measured were 128.43 mg/dL (±61.257) for hexokinase, 128.59 mg/dL (±61.110) for the end-point method, and slightly lower at 123.59 mg/dL (±58.920) for the glucometer. Conclusion: The study concluded that glucometer readings are highly correlated with traditional laboratory methods, indicating that point-of-care testing can be a reliable alternative for patients to monitor fasting blood glucose levels at home.

Smartphone-based portable electrochemical-colorimetric dual-mode biosensor for glucose detection in a co-reaction system

Regular monitoring of blood sugar levels is essential for diabetics, both for adjusting medication or insulin doses and for preventing complications like blindness, nerve damage, heart disease, and kidney failure. This paper presents a novel smartphone-based electrochemical-colorimetric dual-mode detecting system for detecting glucose at low concentrations. This system utilizes a smartphone as a mobile terminal to control the electrochemical circuit board and enable data analysis. The circuit board integrates cyclic voltammetry and differential pulse voltammetry, providing a low-cost and palm-sized solution for glucose detection. Additionally, digital image colorimetry is employed to enable efficient and accurate colorimetric detection. The use of glucose oxidase and horseradish peroxidase (GOx/HRP) in combination with 2,2′-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) ABTS substrates facilitates glucose dual-mode quantitative analysis in a-coreaction system. The electrochemical and colorimetric methods exhibit limits of detection of 0.467 µM and 10 µM, respectively. This system shows a point-of-care testing (POCT) potential for reliable and convenient monitoring of blood glucose levels, particularly for individuals with diabetes.

EMD-Based Noninvasive Blood Glucose Estimation from PPG Signals Using Machine Learning Algorithms

Effective management of diabetes requires accurate monitoring of blood glucose levels. Traditional invasive methods for such monitoring can be cumbersome and uncomfortable for patients. In this study, we introduce a noninvasive approach to estimate blood glucose levels using photoplethysmography (PPG) signals. We have focused on blood glucose prediction using wrist PPG signals and explored various PPG waveform-based features, including AC to DC ratio (AC/DC) and intrinsic mode function (IMF)-based features derived from empirical mode decomposition (EMD). To the best of our knowledge, no studies have been found using EMD-based features to estimate blood glucose levels noninvasively. Additionally, feature importance-based selection has also been used to further improve the accuracy of the proposed model. Among the four machine learning algorithms considered in this study, CatBoost consistently outperformed XGBoost, LightGBM, and random forest across a wide number of features. The best performing model, CatBoost, achieved Pearson’s r of 0.96, MSE 0.08, R2 score 0.92, and MAE 8.01 when considering the top 50 features selected from both PPG waveform-based features and IMF-based features. The p-values for all models were <0.001, indicating statistically significant correlations. Overall, this study provides valuable insights into the feasibility and effectiveness of noninvasive blood glucose monitoring using advanced machine learning techniques.

Hypoglycemia after Mitral Valve Repair in Dogs.

Hypoglycemia has not been previously reported as a postoperative complication of mitral valve repair (MVR) in dogs; however, the authors have encountered cases of hypoglycemia after MVR. This study aimed to determine the incidence of hypoglycemia in dogs after MVR and investigate its causes. Blood glucose levels were measured at multiple timepoints in dogs undergoing MVR. Simultaneously, insulin and glucagon blood concentrations in dogs with hypoglycemia preoperatively and postoperatively were compared to verify the physiological responses to hypoglycemia. Furthermore, risk factors for hypoglycemia, using variables selected based on the characteristics of MVR and dogs undergoing MVR, were examined prospectively. The incidence of hypoglycemia after MVR was 14.2%, and plasma glucagon concentrations increased in these dogs (mean: 260 pg/mL and 644 pg/mL pre- and postoperatively, p < 0.001), whereas serum insulin concentrations decreased (median: 0.50 ng/mL and 0.29 ng/mL pre- and postoperatively, p = 0.002). Therefore, hyperinsulinemia or hypoglucagonemia is unlikely to be the cause of postoperative hypoglycemia. The identified risk factors for hypoglycemia included low body weight and asymptomatic myxomatous mitral valve disease. Monitoring blood glucose levels after MVR should be included in the standard hospitalization plan to prevent hypoglycemic emergencies in dogs.

Melanocortins and Their Potential for the Treatment, Prevention and Amelioration of Complications of Diabetes

Diabetes mellitus (type I and II) is an advancing global health problem, concerningly increasing in prevalence in most of the developed and developing world. Current therapies, such as the subcutaneous injection of insulin, are invasive and require a close monitoring of blood glucose levels to prevent hypo- or hyperglycaemia from occurring. Despite an inexorable search for a cure since Banting and Best discovered and purified insulin in 1921, insulin remains a solitary insula, still the gold standard for treatment of type I and late-stage type II diabetes mellitus. Apropos of complications, diabetes causes a myriad of secondary maladies, ranging from diabetic kidney disease, diabetic retinopathy and diabetic neuropathy to erectile dysfunction and peripheral vascular disease. While scientists continue to interminably tinker with perfecting mechanical insulin pumps or dampening the immune response to pancreatic beta cells, an important aspect of the aetiology of diabetes should not be neglected, that of the metabolism. At its heart, diabetes can arguably be considered a metabolic disease, and this review suggests a return to focusing on preventing and treating diabetes by focussing on its metabolic causes. This narrative review summarises the potential of a recent class of synthetic peptides, the melanocortins, to help prevent and treat the complications of diabetes mellitus. The review summarises recent work showing the potential benefits of the melanocortins in treating diabetic complications through various pathways.

A Review on artificial pancreas mathematical models

The development of an artificial pancreas (AP) has been a topic of interest in the field of diabetes management for several decades. An AP system is designed to mimic the function of the pancreas by continuously monitoring blood glucose levels and delivering insulin or glucagon in response to changes in glucose concentration. Mathematical models play a crucial role in the development and evaluation of AP systems, as they enable the simulation and prediction of the system’s performance. This review paper provides an overview of the mathematical models used in AP research. The paper discusses the strengths and limitations of each type of model, as well as their applications in AP research. The review also highlights the challenges and opportunities in AP model development, such as the need for personalized models and the integration of data from multiple sources. Overall, this review provides a comprehensive understanding of the role of mathematical models in AP research and their potential for improving diabetes management.

Rare, late onset of immune checkpoint inhibitor-induced type 1 diabetes mellitus in a patient with small-cell lung cancer treated with serplulimab: a case report and review of the literature

BackgroundAs a newly approved immune checkpoint inhibitor in China, serplulimab has been widely used in the immunotherapy of tumors. However, the immune-related adverse events of immune checkpoint inhibitors should not be ignored. Although immune checkpoint inhibitor-induced type 1 diabetes mellitus is a rare complication, it may cause diabetic ketoacidosis and endanger the lives of patients.Case presentationThis case report describes a 55-year-old male of Han nationality from China diagnosed with small-cell lung cancer with multiple metastases who experienced an adverse event of type 1 diabetes mellitus 68 weeks after receiving serplulimab therapy. The patient presented with typical symptoms of diabetic ketoacidosis, including severe thirst, nausea, vomiting, deep respirations, and stupor. Despite the absence of diabetes-related autoantibodies, the patient had extremely low levels of insulin and C-peptide release. Other potential causes of diabetes were ruled out, confirming the condition as serplulimab-induced immune checkpoint inhibitor-induced type 1 diabetes mellitus. After aggressive treatment to correct diabetic ketoacidosis, the patient’s blood glucose levels stabilized and symptoms of diabetes improved significantly, although long-term insulin maintenance therapy was necessary.ConclusionThis case highlights a rare, late-onset adverse event of immune checkpoint inhibitor-induced type 1 diabetes mellitus that may be overlooked during treatment with serplulimab. The monitoring of blood glucose levels and early signs and symptoms of diabetes cannot be relaxed at the late stage of treatment, even if patients do not have elevated blood glucose levels before and during the middle stage of treatment.

Early to mid-pregnancy HbA1c levels and its association with adverse pregnancy outcomes in three low middle-income countries in Asia and Sub-Saharan Africa

BackgroundHyperglycemia during pregnancy leads to adverse maternal and fetal outcomes. Thus, strict monitoring of blood glucose levels is warranted. This study aims to determine the association of early to mid-pregnancy HbA1c levels with the development of pregnancy complications in women from three countries in South Asia and Sub-Saharan Africa.MethodsWe performed a secondary analysis of the AMANHI (Alliance for Maternal and Newborn Health Improvement) cohort, which enrolled 10,001 pregnant women between May 2014 and June 2018 across Sylhet-Bangladesh, Karachi-Pakistan, and Pemba Island-Tanzania. HbA1c assays were performed at enrollment (8 to < 20 gestational weeks), and epidemiological data were collected during 2–3 monthly household visits. The women were followed-up till the postpartum period to determine the pregnancy outcomes. Multivariable logistic regression models assessed the association between elevated HbA1c levels and adverse events while controlling for potential confounders.ResultsA total of 9,510 pregnant women were included in the analysis. The mean HbA1c level at enrollment was found to be the highest in Bangladesh (5.31 ± 0.37), followed by Tanzania (5.22 ± 0.49) and then Pakistan (5.07 ± 0.58). We report 339 stillbirths and 9,039 live births. Among the live births were 892 preterm births, 892 deliveries via cesarean section, and 532 LGA babies. In the multivariate pooled analysis, maternal HbA1c levels of ≥ 6.5 were associated with increased risks of stillbirths (aRR = 6.3, 95% CI = 3.4,11.6); preterm births (aRR = 3.5, 95% CI = 1.8–6.7); and Large for Gestational Age (aRR = 5.5, 95% CI = 2.9–10.6).ConclusionMaternal HbA1c level is an independent risk factor for predicting adverse pregnancy outcomes such as stillbirth, preterm birth, and LGA among women in South Asia and Sub-Saharan Africa. These groups may benefit from early interventional strategies.

On Standardization and Evaluation of Continuous Glucose Monitoring Systems

Continuous glucose monitoring (CGM) systems are often used to monitor blood glucose levels. Most commercially available CGM systems continuously measure glucose concentrations in the interstitial fluid of subcutaneous adipose tissue. However, there is currently no internationally accepted reference method for measuring interstitial fluid glucose, which is a prerequisite for metrological traceability of glucose measurements obtained using CGM. Since manufacturers do not provide information about the traceability chain and measurement uncertainty of their systems, CGM-derived glucose values cannot currently be adequately traced to standards or higher order reference measurement procedures. Additionally, the «mean absolute relative difference» (MARD) often used to describe the analytical performance of CGM systems is dependent on many factors. For example, the MARD can be significantly affected by the «lag time» between the change in blood glucose and interstitial glucose, especially at high rates of change in glucose. Finally, modern automated insulin delivery (ADI) systems with integrated CGM can automatically suspend or increase insulin infusion in response to current and/or predicted hypoglycemic and hyperglycemic phenomenon in children and adults with type 1 diabetes mellitus (T1DM). The purpose of the review is justification of the necessity to establish metrological traceability of glucose measurements with CGM systems, as well as a discussion of the analytical and clinical characteristics of CGM systems proposed by various professional communities. Based on the results of the review, it was concluded that it is necessary to 1) develop metrological support for glucose measurements performed using CGM systems, 2) solve the problems of ensuring the accessibility and usability of CGM systems by patients in real conditions.

Review of: "The pancreas of diabetic patients does not produce enough insulin. In such cases, it is used for adjustment. Insulin is essential for continuous monitoring of blood glucose levels"

Review of: "The pancreas of diabetic patients does not produce enough insulin. In such cases, it is used for adjustment. Insulin is essential for continuous monitoring of blood glucose levels"

Epidemiological parameters and monitoring of analysis of treatment of children and adolescents with type 1 diabetes mellitus in insulin pump therapy with modified educational program.

Aim: The aim of the present published work is efficacy evaluation of the modified educational program in achieving the target levels of glycemia in children and adolescents with type 1 diabetes mellitus in pump insulin therapy in Almaty.. Materials and Methods: This study involved 125 children and adolescents with type 1 DM and evaluated the effectiveness of a modified educational program at the School of Type 1 Diabetes Mellitus. Participants were divided into subgroups based on their method of glycemia evaluation. The program's effectiveness was assessed through pre-and post-training questionnaires and measurement of glycohemoglobin levels. Statistical analysis was conducted using the Statistica application. Results: The study evaluated the effectiveness of a modified educational program for children and adolescents with type 1 DM. The results indicated that those who participated in the modified program demonstrated significant improvements in their knowledge and ability to manage their diabetes. They were able to correctly answer 80-90% of the questionnaire questions six months to a year after the training. Additionally, those in the modified program exhibited better carbohydrate metabolism rates and achieved higher rates of their individual treatment goals, especially when using the FreeStyle Libre system for continuous monitoring of blood glucose levels. These findings suggest that a modified educational approach can significantly enhance diabetes management and treatment outcomes in children and adolescents. Conclusions: The study concluded that a modified educational program leads to better target therapy levels in children and adolescents with type 1 diabetes mellitus, highlighting the importance of motivated parents and frequent blood glycemia measurements.

Advances in microneedle technology for biomedical detection.

Microneedles have recently emerged as a groundbreaking technology in the field of biomedical detection. Notable for their small size and ability to penetrate the superficial layers of the skin, microneedles provide an innovative platform for localized and real-time detection. This review explores the integration of various detection methods with microneedle technology, focusing particularly on its applications in biomedical contexts. First, the common detection methods, such as colorimetric, electrochemical, spectrometric, and fluorescence methods, combined with microneedle technology, are summarized. Then we showcase exemplary uses of microneedle technology in biomedical detection, including the monitoring of blood glucose levels, evaluating infection statuses in skin wounds, facilitating point-of-care testing, and identifying biomarkers in the interstitial fluid of the skin. Microneedle-based detection, with its painless, minimally invasive, and biocompatible approach, holds significant promise for enhancing biological assays. Finally, the review concludes by assessing the future potential and challenges of microneedle detection technology, underscoring its transformative capacity to advance personalized medicine and revolutionize healthcare practices.

Selective and sensitive non-enzymatic detection of glucose by Cu(ii)–Ni(ii)/SBA-15

Monitoring blood glucose levels in diabetic patients is vital, pressing the need for sensitive and affordable glucose sensors.

Predicting blood glucose level using salivary glucose and other associated factors: A machine learning model selection and evaluation study

IntroductionThere is a need for designing non-invasive methods to predict blood glucose levels to ensure timely diagnosis of Diabetes Mellitus. Needle anxiety and bleeding disorders preclude many from undertaking blood tests. ObjectivesThe primary objective of this study was to assess if biomarkers like saliva can be used to estimate blood glucose levels. The second objective was to develop and evaluate Machine Learning (ML) models to predict blood glucose levels based on salivary glucose and associated features. An insight into the patient's features, which was important for predicting blood glucose levels, was also required. MethodsA cross-sectional study was conducted, and blood and saliva samples, along with patient-related data, were collected from healthy and diabetic patients. ML techniques were applied to the data to develop a tool for predicting blood glucose levels using patient features. The prediction intervals were computed, clinical accuracy was assessed, and important features for the prediction were identified. ResultsThe Random Forest Regressor Model, with features identified using the wrapper method, was selected as the best, with an average RMSE of 43.28. The prediction intervals were computed for point estimate, MAE = 23.821, and coverage was 100 percent, the clinical accuracy was compared with that of glucometers and continuous monitoring systems. All predicted values are in Zones A and B of the Clarke error grid, and the bias was 6.41. The most important feature for predicting blood glucose level is salivary glucose level, followed by known risk factors like Family History, BMI, etc. The study found that salivary glucose levels are insufficient to classify blood glucose levels as high or normal. ConclusionThe study concluded that salivary glucose with associated patient features could be a potential non-invasive biomarker for predicting blood glucose levels in patients. The developed ML model could be deployed in a device that inputs patient features, analyzes salivary glucose, and can monitor blood glucose levels in a non-invasive manner. Further research is needed to validate the findings of this study and develop a proof of concept.

IoT-Enhanced Healthcare: A Patient Care Evaluation Using the IoT Healthcare Test

Empirical insights into the significant effects of IoT-Enhanced Healthcare on patient care and health outcomes are provided by this study. The transformational potential of IoT technology is shown by data generated from a varied patient group, which includes continuous monitoring of blood pressure, body temperature, heart rate, and blood glucose levels via IoT devices. The usage of IoT devices is directly correlated with greater cardiovascular stability, as shown by consistently normal vital signs, according to statistical assessments. Additionally, the data highlights how patients using IoT devices have better control over their blood glucose levels, as seen by fewer cases of increased glucose levels. Evaluations of the quality of patient care show improved levels of satisfaction, efficacy of therapy, and communication, highlighting the benefits of IoT-Enhanced Healthcare. The evaluation of the outcomes of the IoT Healthcare Test confirms the precision and dependability of IoT devices in medical diagnosis, highlighting the significance of IoT-Enhanced Healthcare in transforming patient care. Together, these results provide strong evidence of IoT's ability to improve patient outcomes, treatment quality, and patient health.

Type 2 diabetes mellitus: current diagnosis and treatment

Type 2 diabetes mellitus is a globally prevalent chronic disease caused by obesity, a sedentary lifestyle, hereditary and environmental factors, and multifactorial causes. The prevalence of diabetes has increased worldwide, and its complications cause high morbidity and mortality. With the increase in diabetes and its complications, treatment costs are also increasing. Early diagnosis of type 2 diabetes, timely initiation of treatment, and prevention of complications are crucial. Management of type 2 DM is multifaceted and includes lifestyle changes, pharmacotherapy, and close monitoring of blood glucose levels. In obese individuals, weight loss has been shown to improve glycemic control and reduce the risk of complications. Pharmacologic treatment is tailored to individual needs and may include oral antidiabetic agents, injectable drugs such as insulin, and newer classes of drugs that target specific pathways involved in glucose regulation. Glycemic control is of paramount importance to reduce the risk of microvascular and macrovascular complications associated with T2DM. In conclusion, the diagnosis and treatment of type 2 diabetes require an integrated approach focusing on lifestyle changes, regular follow-up, and personalized pharmacotherapy. Implementing early interventions and maintaining optimal glycemic control are vital to preventing complications and improving the overall condition of individuals with type 2 DM.

A new rectangular dielectric resonator sensor for glucose measurement: Design, modeling, and experimental validation

SummaryThis study introduces a novel sensor for glucose measurement based on a rectangular dielectric resonator (RDR) excited by a rectangular slot fed by a 50‐Ω microstrip line. The RDR operates at 6 GHz and incorporates a cubic portion section for accommodating a finger or container containing the test sample. By utilizing the distinctive resonant frequencies associated with varying dielectric permittivity of different glucose concentrations, the proposed RDR functions as a reliable sensor. The sensor's performance is evaluated through a 3D electromagnetic model of the human thumb and the application of the Cole‐Cole method for modeling the blood layer. Experimental validation is conducted using three alternatives (water, glucose, and alcohol) and a range of glucose concentrations (70 to 2000 mg/dL) in simulation. During experimental verification, an invasive glucometer is employed as a reference for blood sugar levels. Results demonstrate that the proposed RDR sensor exhibits higher sensitivity (36.86 MHz/(mg/dL)) than other sensor counterparts. The experimental outcomes confirm the resonance frequency alignment between the manufactured sensor and the simulated projections. Considering its economic viability and applicability, this sensor represents a promising alternative biosensor for monitoring blood glucose levels.

Effect of crocin and treadmill exercise on oxidative stress and heart damage in diabetic rats.

Diabetes increases the production of free radicals and inflammatory agents in the heart tissue and alters the expression of genes associated with the induction of apoptosis. Considering the importance of common cardiovascular disorders in diabetes, this study investigated the effect of eight weeks of aerobic exercise and crocin use, as well as tissue damage and oxidative stress caused by diabetes in the hearts of adult rats. Streptozotocin 50 mg/kg was injected as a single dose intraperitoneally to cause the diabetes. After 72 hours, a glucometer monitored blood glucose levels, and blood glucose above 250 mg/dl was considered diabetes. Continuous treadmill exercise was performed for eight weeks by placing the animal on the treadmill. Next, the animals were anesthetized, and samples were taken from the hearts and frozen in liquid nitrogen. Then, superoxide dismutase (SOD), glutathione peroxidase (GPx), and malondialdehyde (MDA) were measured in the cardiac tissue. Finally, the hearts of half of the animals were immediately immersed in a formalin solution for histological changes. According to our findings, diabetes increased lipid peroxidation, characterized by increased MDA levels in the control diabetes group and decreased SOD and GPx levels (P <0.05). It also changes the balance of expression of genes associated with apoptosis control, increased Bcl-2-associated X (Bax) expression, and decreased Bcl-2 expression (P <0.05). Also, we observed the induction of apoptosis in cardiac tissue. Using eight weeks of continuous exercise and administration of crocin significantly reduced blood sugar levels and lipid peroxidation and increased the activity of antioxidant enzymes and Bcl-2 gene expression compared to the diabetes control group. In addition, continuous exercise and crocin improved the oxidative stress parameters in the control group. This study showed that diabetes could cause oxidative stress and heart dysfunction. Moreover, simultaneously and separately, aerobic exercise with a treadmill and crocin administration can reduce these disorders and prevent apoptosis in the heart tissue.

Wearable filamentary continuous sensor for interstitial glucose detection in diabetes management

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