Monitoring Of Blood Glucose Levels Research Articles

Comparison of HPLC with Tinia for hba1c measurement in diabetic and non-diabetic patient; a study from a tertiary care hospital of Baluchistan

Background: Diabetes mellitus, a disease with serious implications on human health ,is on continuous rise. It is the need of hour to find and establish the markers to measure its long term effects. Diabetes Control and Complication Trial has confirmed role of HbA1c in effective blood glucose level monitoring .New methods are being developed for measurement of HbA1c .Before using these methods, it is essential to analyze these methods for reliability .Therefore in our study we will compare and evaluate correlation and agreement between Turbidimetric Inhibition Immunoassay TINIA and High Performance Liquid Chromatography HPLC for HbA1c measurement. Methods: Three hundred and ninety-four samples were analyzed simultaneously on Roche Cobas 501 and D-10 HbA1c analyzer by Bio-Rad for HbA1c level estimation. The results were entered into SPSS version 26 for method validation. This is an observational study conducted at Department of Pathology CMH Quetta from January 2022 to August 2023. Results: Inter and intra run coefficient of variation (CV) was within the allowable limit of 2 %. Mean difference between results of Turbidimetric Inhibition Immunoassay TINIA and High-Performance Liquid Chromatography HPLC was very low with HPLC results slightly on higher side. For low control TINIA had between run CV of 0.3% (Low control) 0.8 % (High control) and within run CV of 0.3% (Low control), 0.6% (High control); while HPLC had between run CV of 0.6%(Low control) 1.8% (High control), and within run CV of 0.3% (Low control), and 0.7%. Linear regression analysis displayed high concordance and agreement between the results of both methods. Conclusion: Both methods have comparable results in HbA1c estimation.

Enhanced Diabetes Detection and Blood Glucose Prediction Using TinyML-Integrated E-Nose and Breath Analysis: A Novel Approach Combining Synthetic and Real-World Data

Diabetes mellitus, a chronic condition affecting millions worldwide, necessitates continuous monitoring of blood glucose level (BGL). The increasing prevalence of diabetes has driven the development of non-invasive methods, such as electronic noses (e-noses), for analyzing exhaled breath and detecting biomarkers in volatile organic compounds (VOCs). Effective machine learning models require extensive patient data to ensure accurate BGL predictions, but previous studies have been limited by small sample sizes. This study addresses this limitation by employing conditional generative adversarial networks (CTGAN) to generate synthetic data from real-world tests involving 29 healthy and 29 diabetic participants, resulting in over 14,000 new synthetic samples. These data were used to validate machine learning models for diabetes detection and BGL prediction, integrated into a Tiny Machine Learning (TinyML) e-nose system for real-time analysis. The proposed models achieved an 86% accuracy in BGL identification using LightGBM (Light Gradient Boosting Machine) and a 94.14% accuracy in diabetes detection using Random Forest. These results demonstrate the efficacy of enhancing machine learning models with both real and synthetic data, particularly in non-invasive systems integrating e-noses with TinyML. This study signifies a major advancement in non-invasive diabetes monitoring, underscoring the transformative potential of TinyML-powered e-nose systems in healthcare applications.

Coral-like Ti3C2Tx/PANI Binary Nanocomposite Wearable Enzyme Electrochemical Biosensor for Continuous Monitoring of Human Sweat Glucose

With the continuous advancement of contemporary medical technology, an increasing number of individuals are inclined towards self-monitoring their physiological health information, specifically focusing on monitoring blood glucose levels. However, as an emerging flexible sensing technique, continuous and non-invasive monitoring of glucose in sweat offers a promising alternative to conventional invasive blood tests for measuring blood glucose levels, reducing the risk of infection associated with blood testing. In this study, we fabricated a flexible and wearable electrochemical enzyme sensor based on a two-dimensional Ti3C2Tx MXene nanosheets and coral-like polyaniline (PANI) binary nanocomposite (denoted as Ti3C2Tx/PANI) for continuous, non-invasive, real-time monitoring of sweat glucose. The exceptional conductivity of Ti3C2Tx MXene nanosheets, in conjunction with the mutual doping effect facilitated by coral-like PANI, significantly enhances electrical conductivity and specific surface areas of Ti3C2Tx/PANI. Consequently, the fabricated sensor exhibits remarkable sensitivity (25.16 μA·mM−1·cm−2), a low detection limit of glucose (26 μM), and an extensive detection range (0.05 mM ~ 1.0 mM) in sweat. Due to the dense coral-like structure of Ti3C2Tx/PANI binary nanocomposite, a larger effective area is obtained to offer more active sites for enzyme immobilization and enhancing enzymatic catalytic activity. Moreover, the sensor demonstrates exceptional mechanical performance, enabling a 60° bend in practical applications, thus satisfying the rigorous demands of human sweat detection applications. The results obtained from continuous 60 min in vitro monitoring of sweat glucose levels demonstrate a robust correlation with the data of blood glucose levels collected by a commercial glucose meter. Furthermore, the fabricated Ti3C2Tx/PANI/GOx sensor demonstrated agreement with HPLC findings regarding the actual concentration of added glucose. This study presents an efficient and practical approach for the development of a highly reliable MXene glucose biosensor, enabling stable and long-term monitoring of glucose levels in human sweat.

Accuracy enhancement of metabolic index-based blood glucose estimation with a screening process for low-quality data.

Many researchers have proposed various non-invasive glucose monitoring (NIGM) approaches using wearable or portable devices. However, due to the limited capacity of detectors for such compact devices and the movement of the body during measurement, the precision of the acquired data frequently diminishes, which can cause problems during actual use in daily life. In addition, intensive smoothing is often used in post-processing to mitigate the effects of erroneous values. However, this requires a considerable amount of data and results in a delay in the response to the actual blood glucose level (BGL). Instead of just applying data smoothing in the post-process of the data acquisition, we propose an active low-quality data screening method in the pre-process. In the proposal phase of the screening process, we employ an analytical approach to examine and formulate factors that might affect the BGL estimation accuracy. A signal quality index inspired by the standard deviation concept is introduced to detect visually apparent noise on signals. Furthermore, the total estimation error in the metabolic index (MI) is calculated based on potential perturbations defined by the signal-to-noise ratio (SNR) and the uncertainty due to discrete sampling. Thereafter, the acquired data were screened by these quality indices. By applying the proposed data screening process to the data obtained from a commercially available smartwatch device in the pre-process, the estimation accuracy of the MI-based BGL was improved significantly. Adopting the proposed screen process improves BGL estimation accuracy in the smartwatch-based prototype. Applying the proposed screen process will facilitate the integration of wearable and continuous BGL monitoring into size- and SNR-limited devices such as smartwatches and smart rings.

9267 Targeting IGF-I to Growth Plate Cartilage Augments Therapeutic Effects on Skeletal Growth and Reduces Hypoglycemic Effects in Mice

Abstract Disclosure: K. Tailor: None. T. Stowe: None. J. Ree: None. B. Ventura: None. J. Deursen: None. R. O'Brien: None. J. Baron: None. J. Lui: None. Recombinant human growth hormone (GH) is commonly used to treat short stature in children but has limited efficacy in severe, non-GH-deficient conditions, such as skeletal dysplasias, and has adverse off-target effects. Because short stature is the result of reduced growth plate chondrogenesis, we hypothesized that targeting chondrogenic growth factors specifically to the growth plate might augment the therapeutic skeletal effect while diminishing adverse effects on non-target tissues. Toward this end, we previously developed fusion proteins conjugating insulin-like growth factor-1 (IGF-1) with a single-chain human monoclonal antibody fragment (ScFv) targeting matrillin-3 (1), a protein specifically expressed in cartilage matrix, and demonstrated increased on-target therapeutic efficacy at the growth plate and decreased off-target effects in a GH-deficient (lit) mouse model (2). In the current study, we established a second GH-deficiency model by administration of a GH antagonist, pegvisomant (PEG), in C57BL/6 wild-type male mice. Alternate-day injection of pegvisomant at 40 mg/kg for 7 days reduced body weight, serum IGF-1 levels, and growth plate height in mice. Using this model, we found that once-daily SQ administration of cartilage-targeted IGF-I (named CV1574-1) for five days increased body weight and growth plate height greater than an equimolar dose of IGF-I itself administered twice daily. Hypoglycemia is an adverse effect of recombinant IGF-1 treatment. Therefore, we also monitored blood glucose levels after a single SQ injection of CV1574-1 and found that this fusion protein showed a reduced hypoglycemic effect compared to injection of IGF-I itself. Lastly, to gain mechanistic insight into the role of matrillin-3 targeting on therapeutic efficacy, we assessed the ability of CV1574-1 to induce pAKT signaling in vitro. Transient exposure to CV1574-1 caused more prolonged induction of pAKT signal in wild-type rat chondrosarcoma (RCS) cells compared to matrillin-3-knockout RCS cells, suggesting that matrillin-3 targeting extends the duration of IGF-1 receptor activation. To summarize, the current findings demonstrate that CV1574-1, a fusion protein that targets IGF-1 to cartilage, improves efficacy at the growth plate, reduces hypoglycemic effects, and, in vitro, prolongs receptor activation. Our study provides further evidence that cartilage-targeted therapy has the potential to provide new pharmacological approaches for the treatment of childhood linear growth disorders, including skeletal dysplasias and growth failure due to systemic disease. Reference:(1) Cheung et al. Pharma Res 2015, 32(7):2439-49.(2) Lui et al. Molecular Therapy 2019, 27(3):673-680 Presentation: 6/3/2024

7237 Targeting IGF-I to Growth Plate Cartilage Augments Therapeutic Effects on Skeletal Growth and Reduces Hypoglycemic Effects in Mice

Abstract Disclosure: K. Tailor: None. T. Stowe: None. J. Ree: None. B. Ventura: None. J. Deursen: None. R. O'Brien: None. J. Baron: None. J. Lui: None. Recombinant human growth hormone (GH) is commonly used to treat short stature in children but has limited efficacy in severe, non-GH-deficient conditions, such as skeletal dysplasias, and has adverse off-target effects. Because short stature is the result of reduced growth plate chondrogenesis, we hypothesized that targeting chondrogenic growth factors specifically to the growth plate might augment the therapeutic skeletal effect while diminishing adverse effects on non-target tissues. Toward this end, we previously developed fusion proteins conjugating insulin-like growth factor-1 (IGF-1) with a single-chain human monoclonal antibody fragment (ScFv) targeting matrillin-3 (1), a protein specifically expressed in cartilage matrix, and demonstrated increased on-target therapeutic efficacy at the growth plate and decreased off-target effects in a GH-deficient (lit) mouse model (2). In the current study, we established a second GH-deficiency model by administration of a GH antagonist, pegvisomant (PEG), in C57BL/6 wild-type male mice. Alternate-day injection of pegvisomant at 40 mg/kg for 7 days reduced body weight, serum IGF-1 levels, and growth plate height in mice. Using this model, we found that once-daily SQ administration of cartilage-targeted IGF-I (named CV1574-1) for five days increased body weight and growth plate height greater than an equimolar dose of IGF-I itself administered twice daily. Hypoglycemia is an adverse effect of recombinant IGF-1 treatment. Therefore, we also monitored blood glucose levels after a single SQ injection of CV1574-1 and found that this fusion protein showed a reduced hypoglycemic effect compared to injection of IGF-I itself. Lastly, to gain mechanistic insight into the role of matrillin-3 targeting on therapeutic efficacy, we assessed the ability of CV1574-1 to induce pAKT signaling in vitro. Transient exposure to CV1574-1 caused more prolonged induction of pAKT signal in wild-type rat chondrosarcoma (RCS) cells compared to matrillin-3-knockout RCS cells, suggesting that matrillin-3 targeting extends the duration of IGF-1 receptor activation. To summarize, the current findings demonstrate that CV1574-1, a fusion protein that targets IGF-1 to cartilage, improves efficacy at the growth plate, reduces hypoglycemic effects, and, in vitro, prolongs receptor activation. Our study provides further evidence that cartilage-targeted therapy has the potential to provide new pharmacological approaches for the treatment of childhood linear growth disorders, including skeletal dysplasias and growth failure due to systemic disease. Reference:(1) Cheung et al. Pharma Res 2015, 32(7):2439-49.(2) Lui et al. Molecular Therapy 2019, 27(3):673-680 Presentation: 6/3/2024

Feeding and Eating Disorders in Young People with Type 1 Diabetes: A Systematic Review

Eating disorders (ED) are a growing concern among young individuals with type 1 diabetes (T1D), with a prevalence significantly higher than that observed in the general adolescent population. Studies indicate that adolescents with diabetes are 2 to 3 times more likely to develop ED compared to their non-diabetic peers. This increased prevalence is partly attributed to several risk factors unique to this population. Adolescence itself is a major risk factor for ED, characterized by hormonal fluctuations, rising concerns about body image, and experimental eating behaviors. However, for young people with T1D, these risks are exacerbated by additional challenges. Daily diabetes management, which involves rigorous monitoring of blood glucose levels and precise control of dietary intake, can contribute to increased stress and excessive preoccupation with weight and body shape. Furthermore, social expectations and pressures related to glycemic control can reinforce problematic eating behaviors. ED in young diabetics can have severe consequences on diabetes management and overall health. Restrictive eating or purging behaviors can lead to glycemic imbalances, poor diabetes control, and increased risk of associated complications. This can also worsen psychological difficulties, such as anxiety and depression, thereby amplifying the cycle of deteriorating mental and physical health. Effective management of ED in young diabetics requires a multidisciplinary approach. It is crucial to integrate interventions that address not only nutritional and psychological aspects but also the specific challenges related to managing T1D. Early detection and treatment of ED can improve clinical outcomes and promote a better balance between diabetes management and the mental health of patients.

New therapeutic approaches in corticosteroid-induced diabetes mellitus in children

Corticosteroid-induced diabetes is a significant complication in pediatric patients receiving steroid therapy for various medical conditions. This article reviews the pathophysiology, diagnosis, and management of corticosteroid-induced diabetes in children. Key therapeutic strategies include lifestyle modifications, pharmacologic interventions, and careful monitoring of blood glucose levels. Emphasis is placed on individualized treatment plans tailored to the child's specific needs and underlying condition. The article also discusses the importance of interdisciplinary collaboration among healthcare providers to optimize outcomes and minimize long-term complications. Early recognition and proactive management are critical in improving the quality of life for affected children.

Development of a T2D App for Elderly Users: Participatory Design Study via Heuristic Evaluation and Usability Testing

Diabetes management applications effectively help patients monitor blood glucose levels and adjust diet and exercise plans. However, most diabetes management apps, including the SugarShift application developed in 2023, use generalized designs that often fail to consider the unique cognitive and physiological characteristics of elderly users, thereby impacting their acceptance and usage. This paper proposes an enhancement for the SugarShift application by introducing a mode specifically designed for elderly users. This proposed enhancement aims to directly involve elderly patients so as to meet their needs better through a participatory design approach. A heuristic evaluation conducted with six experts identified 126 usability issues and 179 heuristic violations in the current version, which has led to the recommendation to develop optimization strategies tailored for elderly users. Subsequent usability testing with 28 elderly patients and six experts emphasized the importance of interface simplicity, logical operation, and interaction quality in enhancing user experience. These factors improve usability, facilitate information processing, and reduce cognitive load. Despite the overall usability of SUS scores, significant challenges still need to be addressed in information display, system feedback, and user interaction. Recommendations for future enhancements include simplifying data entry and presentation, improving readability, and providing timely feedback to enhance usability and user satisfaction, ultimately increasing user retention.

Edge-functionalized graphene quantum dot as a nano-biosensor for simultaneous detection of glucose, galactose and lactose

The swift and accurate diagnosis of diseases, particularly diabetes, remains a pressing and critical concern in healthcare. Monitoring blood glucose levels is imperative for diabetic patients to manage their condition effectively. Addressing this necessity, developing non-invasive, simultaneous detection devices for sugars shows immense promise. Herein, we introduce the design of a novel nano-biosensor employing edge‐functionalized graphene quantum dots, enabling the concurrent detection of three pivotal sugars: glucose, galactose, and lactose. Through comprehensive molecular dynamics simulations, we demonstrate the feasibility and stability of the proposed biosensor. Our results show that the edge-functionalization of graphene quantum dots significantly enhances their binding affinity, with calculated average number of contacts of 2174 for glucose, 1085 for galactose, and 6274 for lactose. Furthermore, the radial distribution function analysis echoed these findings, highlighting lactose’s pronounced interaction with the biosensor, followed by glucose and then galactose. The detailed analysis reveals distinct and non-overlapping sugar bindings on the nano-biosensor surface, with lactose showing the highest affinity and interaction strength, followed by glucose and galactose. This innovative approach marks a significant stride forward in biosensor technology, providing a potential avenue for precise and dependable monitoring of blood sugar levels in diabetic patients.

Exploring the Feasibility of Digital Voice Assistants for Delivery of a Home-Based Exercise Intervention in Older Adults With Obesity and Type 2 Diabetes Mellitus: Randomized Controlled Trial.

Current clinical guidelines for the management of type 2 diabetes mellitus (T2DM) in older adults recommend the use of antihyperglycemic medications, monitoring of blood glucose levels, regular exercise, and a healthy diet to improve glycemic control and reduce associated comorbidities. However, adherence to traditional exercise programs is poor (<35%). Common barriers to adherence include fear of hypoglycemia and the need for blood glucose level monitoring before exercise. Digital health strategies offer great promise for managing T2DM as they facilitate patient-practitioner communication, support self-management, and improve access to health care services for underserved populations. We have developed a novel web-based software program allowing practitioners to create tailored interventions and deliver them to patients via digital voice assistants (DVAs) in their own homes. We aim to evaluate the feasibility of a 12-week, home-based, personalized lifestyle intervention delivered and monitored by DVAs for older adults with obesity and T2DM. In total, 50 older adults with obesity aged 50-75 years with oral hypoglycemic agent-treated T2DM were randomized to the intervention (DVA, n=25) or a control group (n=25). Participants allocated to the DVA group were prescribed a home-based muscle strengthening exercise program (~20- to 30-min sessions) and healthy eating intervention, delivered via DVAs (Alexa Echo Show 8; Amazon) using newly developed software ("Buddy Link"; Great Australian Pty Ltd). Control group participants received generalized physical activity information via email. Outcomes were feasibility, DVA usability (System Usability Scale), and objectively assessed physical activity and sedentary time (wrist-worn accelerometers). In total, 45 (90%) out of 50 participants completed this study. Mean adherence to prescribed exercise was 85% (SD 43%) with no intervention-related adverse events. System usability was rated above average (70.4, SD 16.9 out of 100). Compared with controls, the DVA group significantly decreased sedentary time (mean difference -67, SD 23; 95% CI -113 to -21 min/d), which was represented by a medium to large effect size (d=-0.6). A home-based lifestyle intervention delivered and monitored by health professionals using DVAs was feasible for reducing sedentary behavior and increasing moderate-intensity activity in older adults with obesity and T2DM. Australian New Zealand Clinical Trials Registry (ANZCTR) ACTRN12621000307808; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=381364&isReview=true.

Hyperkalemia Management with Intravenous Insulin in Patients with Reduced Kidney Function.

Background: Insufficient kidney function increases the risk of hyperkalemia and hypoglycemia, particularly in hemodialysis-dependent patients. Hypoglycemia is a common complication of insulin-based hyperkalemia treatment. This study aims to evaluate the efficacy and safety of hyperkalemia treatment in hemodialysis-dependent and -non-dependent patients and identify risk factors associated with hypoglycemia. Methods: A retrospective observational cohort study was conducted to assess the efficacy and safety of hyperkalemia treatment including patients with reduced kidney function and hyperkalemia treated with intravenous insulin. The decline rate of potassium and glucose levels were compared between hemodialysis-dependent and non-dependent patients. In addition, univariate and multivariable logistic regression analyses were performed to identify risk factors associated with hypoglycemia. Results: A total of 172 patients with hyperkalemia and reduced kidney function were included. The steepest reduction of serum potassium levels happened within the first 6 h after insulin administration, at 1.1 and 0.9 mmol/L for hemodialysis-dependent and non-dependent patients, respectively. The incidence of hypoglycemia was 18%, and no significant difference was found between cohorts. Hemodialysis-dependent patients were more likely to be readmitted within one month with hyperkalemia, while all-cause ICU admission was more likely for non-dependent patients. Older patients, and those who had heart failure or received a second dose of insulin to treat hyperkalemia, were more likely to experience hypoglycemia. Conclusions: Monitoring blood glucose levels following insulin administration is essential given the complexity of patients' factors associated with hypoglycemia resulting from hyperkalemia treatment in patients with insufficient kidney function.

Comparison of Glucose and Immunoglobulin a Levels in Serum and Saliva of Patients with Type 1 and Type 2 Diabetes

Introduction: The monitoring and management of blood glucose levels are of significant importance in individuals diagnosed with diabetes mellitus. Accordingly, the objective of this study was to examine the potential of a non-invasive approach for the diagnosis and management of diabetes, through the measurement of glucose concentration and salivary IgA, and a comparison with fasting glucose and serum IgA levels in individuals with type 1 and 2 diabetes, in relation to a control group of healthy individuals. Methods: This case-control study was conducted on 76 individuals with diabetes (31 with type 1 diabetes and 45 with type 2 diabetes) and 24 healthy individuals. After obtaining the code of ethics and informed consent, serum and salivary IgA levels as well as fasting glucose, were measured for each participant. The data were analyzed using SPSS version 16 statistical software and the Spearman, Kruskal-Wallis, and Mann-Whitney tests. Results: The results showed a significant difference among the three groups (type 1 diabetes, type 2 diabetes, and healthy group) based on Fasting Blood Glucose, Hemoglobin A1c, Immunoglobulin A, salivary sugar, and salivary IgA (p&lt;0.001). Additionally, in the case group, parameters such as FBS, HbA1c, and salivary IgA showed a significant correlation with salivary sugar. Conversely, in the control group, only the salivary sugar level demonstrated a significant relationship with serum glucose level. The study's findings indicated that serum and salivary IgA levels were lower and higher, respectively, in the control subjects compared to the diabetic group (p&lt;0.001). Conclusion: In healthy individuals, salivary sugar can serve as an indicator to determine fasting blood sugar levels. In diabetic patients, salivary sugar can predict of FBS, HbA1c, and salivary IgA levels.

Natural health product knowledge as a significant factor associated with health-promoting lifestyle in a low-income urban community in Kuala Lumpur

BackgroundLow income communities are vulnerable to non-communicable diseases (NCDs), which affect their economy and disability status. An effective approach to address the NCD burden is through the multidimensional concept of health-promoting lifestyle. Another preferred approach by the population worldwide for NCD treatment is natural health product (NHP). Studies on NHP and health-promoting lifestyle among this vulnerable population, specifically the low-income urban community, are limited. Therefore, this study, aimed at investigating the NHP knowledge and health-promoting lifestyle, and to determine the factors associated with health-promoting lifestyle in a low income urban community in Cheras, Kuala Lumpur. This study has focused on sociodemographic characteristics, annual health monitoring activities, and health status, which are modifiable and non-modifiable factors.MethodsPhase 1 of the study involves developing the Malay-version NHP knowledge questionnaire, whereas Phase 2 involves a cross-sectional study of 446 randomly selected low-income respondents to determine their level of health-promoting lifestyle and the associated factors. The respondents’ sociodemographic, socioeconomic, health monitoring activity, health status, and NHP knowledge data were obtained using the newly developed Malay-version NHP questionnaire and the Health-Promoting Lifestyle Profile II (HPLP II) questionnaire. The independent variables include sociodemographic status, annual health monitoring activities, health status and NHP knowledge were analysed using simple and multiple linear regression.ResultsIn this study, the 10-item NHP knowledge questionnaire developed in the Malay version contains two domains [safe use (eight items) and point of reference (two items)] (total variance explained: 77.4%). The mean of NHP knowledge score was 32.34 (standard deviation [SD] 7.37). Meanwhile, the mean score of health-promoting lifestyle was 109.67 (SD 25.01). The highest and lowest scores of health-promoting lifestyles are attributed to spiritual growth and physical activity, respectively. Ethnicity is associated with a higher health-promoting lifestyle level, same goes to the occupational status − NHP knowledge interaction. “Unclassified” education status and annual blood glucose level monitoring are associated with a lower level of health-promoting lifestyle.ConclusionA new questionnaire in Malay version was developed to measure NHP knowledge. Compared to other subpopulations, the respondents’ health-promoting lifestyle levels in this study were low, associated with ethnicity, education status, and health monitoring activities. The findings provided insight into the interaction between NHP knowledge and occupational status, which is associated with a higher health-promoting lifestyle level. Accordingly, the future health-promoting lifestyle intervention programmes in healthcare delivery should target these factors.

A Highly Sensitive H-Shaped Optical Fiber Sensor for Monitoring Blood Glucose Level

A Highly Sensitive H-Shaped Optical Fiber Sensor for Monitoring Blood Glucose Level

Application of the outlier detection method for web-based blood glucose level monitoring system

Recent advancements in biosensors have empowered individuals with diabetes to autonomously monitor their blood glucose levels through continuous glucose monitoring (CGM) sensors. Nevertheless, the data collected from these sensors may occasionally include outliers due to the inherent imperfections of the sensor devices. Consequently, the identification of these outliers is critical to determine whether blood glucose levels deviate significantly from the norm, necessitating further action. This study employs an outlier detection approach based on the 3-sigma method and the interquartile range (IQR), along with the application of the Winsorizing technique to correct the identified outliers. Additionally, a web-based system for visualizing blood glucose levels is developed, utilizing both outlier detection methods. In order to assess the system's performance, two types of testing are conducted: black box testing and load testing. The results of black box testing indicate that all test scenarios operate as anticipated. As for the load testing response times, it is observed that the 3-sigma visualization page loads an average of 606.75 milliseconds faster compared to the IQR visualization page. This study's outcomes are expected to enhance data quality, enhance the precision of analyses, and facilitate more informed decision-making by identifying and addressing extreme data points.

Persian Mobile Apps for Diabetic Patients: App Review and Evaluation Study

Background: The development of mobile apps in healthcare facilities helps users perform self-care effectively. Objectives: This study aimed to evaluate the quality, functionality, and features of Persian language diabetes mobile apps. Methods: Persian language diabetes self-management mobile apps were searched in the Android and iOS App Stores using relevant keywords such as "diabetes" and "blood sugar." Twelve apps met the inclusion criteria. Nine evaluators assessed the apps' quality based on the Mobile App Rating Scale (MARS), their functionality according to the IMS institute for healthcare informatics app functionality scoring system, and their features and content using a checklist. Results: The mean MARS score of the apps was 3.02 out of 5. Among the four dimensions of engagement, aesthetics, functionality, and information quality, functionality had the highest mean ± SD score (3.64 ± 1.13). Most of the apps used 5 - 7 out of the 11 defined functionalities. All self-management apps included the functionality of monitoring blood glucose levels, and the majority had health status monitoring features. Conclusions: The mobile apps had several drawbacks, including a lack of engagement strategies, insufficient evidence-based information for patients, limited guideline-based self-management functionalities, failure to evaluate clinical effectiveness in trials, and an absence of mutual communication with healthcare providers.

Flexible nanomaterial sensors for non-invasive health monitoring

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

The Importance of Monitoring Blood Glucose Test in Patients Post-operative Coronary Artery Bypass Graft Surgery

Hyperglycemia is a risk factor for cardiac surgery-associated acute kidney injury in post-operative coronary artery bypass graft surgery patients. Glycemic control is important to prevent cardiac surgery-associated acute kidney injury. Postoperative glycemic control suggested 110-150 mg/dL. The aims of this study were to lower blood glucose levels and reduce the risk of occurrence or severity of cardiac surgery-associated acute kidney injury in post coronary artery bypass graft surgery patients. This study was conducted with a case study design involving 2 post operative coronary artery bypass graft patients who experienced hyperglycemia on the 1st to the 3rd day of treatment. Data collection was carried out from May 22 to May 23, 2023. The results of the case study showed that monitoring blood glucose in post-cardiac surgery patients is very important. Both patients experienced hyperglycemia in the early postoperative phase. With close monitoring and administration of insulin therapy according to the doctor's advice, the blood sugar levels of both patients were controlled. Monitoring urine output and evaluating serum creatinine levels showed that the first patient had cardiac surgery-associated acute kidney injury stage 1 on day 2 and showed improvement on day 3. The second patient did not develop cardiac surgery-associated acute kidney injury. The role of critical nurses in monitoring blood glucose levels and administering insulin doses is supported by related research. Strict monitoring and target ranges of blood glucose levels, in collaboration with the medical team are necessary to reduce the risk of cardiac surgery-associated acute kidney injury events.

Simultaneous induction of systemic hyperglycaemia and stress impairs brain redox homeostasis in the adult zebrafish

For diabetic patients it is crucial to constantly monitor blood glucose levels to mitigate complications due to hyperglycaemia, including neurological issues and cognitive impairments. This activity leads to psychological stress, called “diabetes distress,” a problem for most patients living with diabetes. Diabetes distress can exacerbate the hyperglycaemia effects on brain and negatively impact the quality of life, but the underlying mechanisms remain poorly explored. We simulated diabetes distress in adult zebrafish by modelling hyperglycaemia, through exposure to dextrose solution, along with chronic unpredictable mild stress (CUMS), and evaluated brain redox homeostasis by assessing reactive oxygen species (ROS) content, the antioxidant system, and effects on mitochondrial biogenesis and fission/fusion processes. We also evaluated the total, cytosolic and nuclear content of nuclear factor erythroid 2-related factor 2 (NRF2), a critical regulator of redox balance, in the whole brain and total NRF2 in specific brain emotional areas. The combined CUMS + Dextrose challenge, but not the individual treatments, reduced total NRF2 levels in the entire brain, but strongly increased its levels in the nuclear fraction. Compensatory upregulation of antioxidant genes appeared inadequate to combat elevated levels of ROS, leading to lowering of the reduced glutathione content and total antioxidant capacity. CUMS + Dextrose treatment also upregulated transcription factors implicated in mitochondrial biogenesis and dynamics with a predominance of fission, which is consistent with increased oxidative stress. In conclusion, this study highlights the close interplay between hyperglycaemia and psychological distress causing overriding oxidative stress in the brain, rendering the organism vulnerable to the development of disease complications.