Measurement Of Glucose Levels Research Articles

Statistical Packages and Algorithms for the Analysis of Continuous Glucose Monitoring Data: A Systematic Review.

Continuous glucose monitoring (CGM) measures glucose levels every 1 to 15 minutes and is widely used in clinical and research contexts. Statistical packages and algorithms reduce the time-consuming and error-prone process of manually calculating CGM metrics and contribute to standardizing CGM metrics defined by international consensus. The aim of this systematic review is to summarize existing data on (1) statistical packages for retrospective CGM data analysis and (2) statistical algorithms for retrospective CGM analysis not available in these statistical packages. A systematic literature search in PubMed and EMBASE was conducted on September 19, 2023. We also searched Google Scholar and Google Search until October 12, 2023 as sources of gray literature and performed reference checks of the included literature. Articles in English and Danish were included. This systematic review is registered with PROSPERO (CRD42022378163). A total of 8731 references were screened and 46 references were included. We identified 23 statistical packages for the analysis of CGM data. The statistical packages could calculate many metrics of the 2022 CGM consensus and non-consensus CGM metrics, and 22/23 (96%) statistical packages were freely available. Also, 23 statistical algorithms were identified. The statistical algorithms could be divided into three groups based on content: (1) CGM data reduction (eg, clustering of CGM data), (2) composite CGM outcomes, and (3) other CGM metrics. This systematic review provides detailed tabular and textual up-to-date descriptions of the contents of statistical packages and statistical algorithms for retrospective analysis of CGM data.

Does Insulin Delivery Technology Change Our Relationship with Foods? A Scoping Review.

Introduction: Automated insulin delivery (AID) systems reduce burden and improve glycemic management for people with type 1 diabetes (PwT1D) by automatically adjusting insulin as a response to measured glucose levels. There is a lack of evidence on AID and nutrition variables such as dietary intake, eating behaviors, and disordered eating. Objectives: This scoping review aims to provide a summary of the literature regarding AID and nutrition variables and to identify gaps that require further investigation. Methods: Two researchers conducted a blinded search of Medline (OVID) and PubMed for studies, including AID use (compared to non-AID use) and nutrition variables. Studies from January 2000 to July 2023 were included, as were PwT1D of all ages. Results: A total of 3132 articles were screened for appropriateness. After exclusions, 7 studies were included (2017-2023): 4 qualitative, 1 crossover, 1 randomized controlled, and 1 observational. Studies included adolescents (n = 1), adults (n = 3) or both (n = 2), and all ages (n = 1). In quantitative studies, AID was associated with lower eating distress (-0.43 ± 0.12, P = 0.004) and higher quality of life (3.1, 95% confidence interval [CI]: 0.8-5.4, P = 0.01), but not grams of carbohydrates at meals (1.0; 95% CI: -0.7 to 3.0; P = 0.24) and snacks (0.004; 95% CI: -0.8 to 0.8; P = 0.99) compared to non-AID use. In qualitative studies, AID increased the frequency and portions of food intake and led to less dietary control from parents. AID users reported eating foods higher in energy density. PwT1D were less worried about achieving accurate carbohydrate counting (CC) when using AID. Conclusions: AID use appears to influence eating behaviors, dietary patterns, and CC, although evidence was limited. AID may reduce food management burden due to the perception that AID can correct for CC inaccuracy. Significance: Further research needs to determine if AID allows for simplification of CC and improves eating behaviors while maintaining glycemic stability.

Clinacanthus nutans leaf extract reduces pancreatic β-cell apoptosis by inhibiting JNK activation and modulating oxidative stress and inflammation in streptozotocin-induced diabetic rats.

Controlling apoptosis induced by oxidative stress in pancreatic β-cells provides promising strategies for preventing and treating diabetes. Clinacanthus nutans leaves possess bioactive constituents with potential antioxidant and anti-diabetic properties. This study aimed to investigate the molecular mechanisms by which C. nutans extract protects pancreatic β-cells from apoptotic damage in streptozotocin (STZ)-induced diabetic rats. Diabetes was induced in male Wistar rats by intraperitoneal injection of 45 mg/kg STZ, followed by 28 days of treatment with C. nutans leaf extract and Glibenclamide as the standard drug. At the end of the study, blood samples were collected to measure glucose levels, oxidative stress markers, and inflammation. Pancreatic tissue was stained immunohistochemically to detect c-Jun N-terminal kinase (JNK) and Caspase-3 expression. The administration of C. nutans leaf extract to diabetic rats significantly reduced fasting blood glucose, malondialdehyde, and tumor necrosis factor-α levels, while concurrently enhancing the activity of superoxide dismutase. The immunohistochemical studies revealed a decrease in the expression of JNK and caspase-3 in the pancreatic islets of diabetic rats. Clinacanthus nutans exhibits the potential to protect pancreatic β-cells from apoptosis by suppressing oxidative stress and inflammation.

A computer vision enhanced smart phone platform for microfluidic urine glucometry.

Glucose is an important biomarker for diagnosing and prognosing various diseases, including diabetes and hypoglycemia, which can have severe side effects, symptoms, and even lead to death in patients. As a result, there is a need for quick and economical glucose level measurements to help identify those at potential risk. With the increase in smartphone users, portable smartphone glucose sensors are becoming popular. In this paper, we present a disposable microfluidic glucose sensor that accurately and rapidly quantifies glucose levels in human urine using a combination of colorimetric analysis and computer vision. This glucose sensor implements a disposable microfluidic device based on medical-grade tapes and glucose analysis strips on a glass slide integrated with a custom-made polydimethylsiloxane (PDMS) micropump that accelerates capillary flow, making it economical, convenient, rapid, and equipment-free. After absorbing the target solution, the disposable device is slid into the 3D-printed main chassis and illuminated exclusively with Light Emitting Diode (LED) illumination, which is pivotal to color-sensitive experiments. After collecting images, the images are imported into the algorithm to measure the glucose levels using computer vision and average RGB values measurements. This article illustrates the impressive accuracy and consistency of the glucose sensor in quantifying glucose in sucrose water. This is evidenced by the close agreement between the computer vision method used by the sensor and the traditional method of measuring in the biology field, as well as the small variation observed between different sensor performances. The exponential regression curve used in the study further confirms the strong relationship between glucose concentrations and average RGB values, with an R-square value of 0.997 indicating a high degree of correlation between these variables. The article also emphasizes the potential transferability of the solution described to other types of assays and smartphone-based sensors.

Community service: stroke risk detection and primary prevention of stroke education

Stroke is a neurovascular disease that is the second cause of death and the third cause of disease in the world. The prevalence of stroke in Indonesia has increased. The increasing prevalence of stroke can be caused by low stroke prevention. Factors that influence stroke prevention behavior are knowledge and awareness. Efforts to reduce the incidence of stroke are primary preventions. The first activity was detection of stroke risk using the Stroke Risk Scorecard, examination of blood pressure, body weight, measurement of blood glucose and cholesterol levels. The second was providing education. This activity was carried out at Kendangan, Caturharjo, Sleman, Yogyakarta. The stroke risk detection was attended by 67 people. The results of risk factor detection found that people at high risk of stroke were 4 people (6%), and 63 people at low risk of stroke (94%). People with hypertension 31 (46%), hypercholesterolemia 26 (38%), smoking 7 (10%), never exercising 50 (74%), and overweight 7 (10%). Education of stroke was attended by 36 people. The knowledge has increased after being given education (score 15) with an average pre-test score of 59,41 (min-max 20-100) and a post-test of 74.41 (min-max 30-100). Stroke risk detection and primary prevention education is an effort to prevent stroke in an early and continuous manner

Community service: Stroke risk detection and primary prevention of stroke education

Abstract. Stroke is a neurovascular disease and is the second cause of death and the third cause of disease in the world. The prevalence of stroke in Indonesia has increased. The increasing prevalence of stroke can be caused by low stroke prevention. Factors that influence stroke prevention behavior are knowledge and awareness. Efforts to reduce the incidence of stroke are primary prevention. This community service program made 2 basic efforts in stroke prevention. The first activity was detection of stroke risk using the stroke risk scorecard, examination of blood pressure and body weight, and measurement of blood glucose and cholesterol levels. The second one was providing education. This program was carried out at Kendangan, Caturharjo, Sleman, Yogyakarta. Stroke risk detection was attended by 67 people. The results of risk factor detection found that there were 4 people at high risk of stroke (6%), and 63 people were at low risk of stroke (94%). There were also other health issues found; 31 people with hypertension (46%), 26 people with hypercholesterolemia (38%), 7 people smoking (10%), 50 people never exercise (74%), and 7 people with overweight (10%). Education of stroke was attended by 36 people. The knowledge had increased after given education with an average pretest score of 59.41 (with minimum score of 20 and maximum score of 100) and an average post-test score of 74.41 (with minimum score of 30 and maximum score of 100). Stroke risk detection and primary prevention education are efforts to prevent stroke early, so they need to be done continuously.

Effect of Cell Density of a Methacrylic Acid-Based Hydrogel Implant on Embedded Islet Function and Viability.

Subcutaneous delivery of islets in a methacrylic acid-based hydrogel may offer a functional cure for type 1 diabetes. Here we show in mice that the hydrogel is able to provide sufficient vasculature to support islet function and viability, when islets are used at a low islet volume fraction (i.e., cell density). The Krogh cylinder model was used to mathematically estimate the effect of implant volume, for a fixed islet dose (600 islet equivalents [IEQ]), on the minimum vessel density required to maintain sufficient pO2 within the graft. Modeling suggested that 200 μL implants would have low enough islet densities and enough vessels to have islets remain viable, but that 50 μL implants would not; this was confirmed experimentally through measurement of glucose level in streptozotocin-induced diabetic severe combined immunodeficiency disease (SCID/bg) mice, comparing 200 and 50 μL implants, both with 600 IEQ. Vessel densities were ∼20-30 vessels/mm2 independent of implant volume and vessels were sufficient to increase subcutaneous oxygen tension, as measured with microcapsules containing oxygen sensitive material (a platinum [Pt] porphyrin); both these results were determined without cells. These results are useful in thinking about the scale-up of this system to humans: to maintain a low islet density (∼0.5%), many more islets will require attention to the subcutaneous implant configuration to satisfy the oxygen needs of the cells.

Blood glucose forecasting from temporal and static information in children with T1D.

The overarching goal of blood glucose forecasting is to assist individuals with type 1 diabetes (T1D) in avoiding hyper- or hypoglycemic conditions. While deep learning approaches have shown promising results for blood glucose forecasting in adults with T1D, it is not known if these results generalize to children. Possible reasons are physical activity (PA), which is often unplanned in children, as well as age and development of a child, which both have an effect on the blood glucose level. In this study, we collected time series measurements of glucose levels, carbohydrate intake, insulin-dosing and physical activity from children with T1D for one week in an ethics approved prospective observational study, which included daily physical activities. We investigate the performance of state-of-the-art deep learning methods for adult data-(dilated) recurrent neural networks and a transformer-on our dataset for short-term ( min) and long-term ( h) prediction. We propose to integrate static patient characteristics, such as age, gender, BMI, and percentage of basal insulin, to account for the heterogeneity of our study group. Integrating static patient characteristics (SPC) proves beneficial, especially for short-term prediction. LSTMs and GRUs with SPC perform best for a prediction horizon of min (RMSE of mmol/l), a vanilla RNN with SPC performs best across different prediction horizons, while the performance significantly decays for long-term prediction. For prediction during the night, the best method improves to an RMSE of mmol/l. Overall, the results for our baselines and RNN models indicate that blood glucose forecasting for children conducting regular physical activity is more challenging than for previously studied adult data. We find that integrating static data improves the performance of deep-learning architectures for blood glucose forecasting of children with T1D and achieves promising results for short-term prediction. Despite these improvements, additional clinical studies are warranted to extend forecasting to longer-term prediction horizons.

Association between daily screen time and risk of stroke among middle-aged and elderly people: research based on China health and nutrition survey.

We aimed to explore the independent associations between screen time and the risk of stroke among Chinese adults based on the China Health and Nutrition Survey (CHNS). Data on Chinese adults aged older than 40 years from the CHNS in during 2004-2009 were selected. A total of 4,587 individuals were included in 2009, including screen time and the risk of stroke. Simultaneously, we traced the previous screen time to 2004 for those with outcome measures in 2009 (n = 2,100). Basic information, lifestyle, and screen behavior were obtained through face-to-face interviews and self-completed questionnaires. Anthropometric data collected included blood pressure, body weight, height, hip circumference, and waist circumference. Fasting blood was obtained for measurements of lipid and glucose levels. Cross-sectional analysis and cohort analysis were both performed using multivariate logistic regression. Of all participants, 3,004 (65.49%) participants spent more than 2 h per day on screen time. Taking the men who spent less than 2 h on screen per day as reference, the crude odds ratio (OR) of the high risk of stroke was 1.53 [95% confidence interval (CI), 1.20-1.95] for the men who spent 2-3 h per day on screen and 2.37 (95% CI, 1.78-3.16) for the men who spent more than 3 h per day on screen. This difference remained significant after adjusting for confounding factors. No association was observed among women. However, in the cohort analysis with screen time in 2006 as the independent variable, the association between screen time and stroke risk was found both in men [OR, 1.83 (95% CI, 1.19-2.82)] and women [OR, 1.48 (95% CI, 1.10-1.99)]). We found that the high screen time was associated with an increased stroke risk, which was pronounced in men, warranting a universal need to limit screen time in order to improve health.

Prevalence of lifestyle cardiovascular risk factors and estimated framingham 10-year risk scores of adults with psychotic disorders compared to controls at a referral hospital in Eldoret, Kenya

IntroductionLifestyle factors such as smoking, alcohol use, suboptimal diet, and inadequate physical activity have been associated with increased risk of cardiovascular diseases. There are limited data on these risk factors among patients with psychosis in low- and middle-income countries.ObjectivesThis study aimed to establish the prevalence of lifestyle cardiovascular risk factors, and the 10-year cardiovascular risk scores and associated factors in patients with psychosis compared to controls at Moi Teaching and Referral Hospital in Eldoret, Kenya.MethodsA sample of 297 patients with schizophrenia, schizoaffective disorder, or bipolar mood disorder; and 300 controls matched for age and sex were included in this analysis. A study specific researcher-administered questionnaire was used to collect data on demographics, antipsychotic medication use, smoking, alcohol intake, diet, and physical activity. Weight, height, abdominal circumference, and blood pressure were also collected to calculate the Framingham 10-year Cardiovascular Risk Score (FRS), while blood was drawn for measurement of glucose level and lipid profile. Pearson’s chi-squared tests and t-tests were employed to assess differences in cardiovascular risk profiles between patients and controls, and a linear regression model was used to determine predictors of 10-year cardiovascular risk in patients.ResultsCompared to controls, patients with psychosis were more likely to have smoked in their lifetimes (9.9% vs. 3.3%, p = 0.006) or to be current smokers (13.8% vs. 7%, p = 0.001). Over 97% of patients with psychosis consumed fewer than five servings of fruits and vegetables per week; 78% engaged in fewer than three days of vigorous exercise per week; and 48% sat for more than three hours daily. The estimated 10-year risk of CVD was relatively low in this study: the FRS in patients was 3.16, compared to 2.93 in controls. The estimated 10-year cardiovascular risk in patients was significantly associated with female sex (p = 0.007), older patients (p < 0.001), current tobacco smoking (p < 0.001), and metabolic syndrome (p < 0.001).ConclusionIn the setting of Eldoret, there is suboptimal physical exercise and intake of healthy diet among patients with psychosis and controls. While the estimated risk score among patients is relatively low in our study, these data may be useful for informing future studies geared towards informing interventions to promote healthy lifestyles in this population.

Protective Effect of Hydroalcoholic Extract of Punica granatum Leaves on High Fructose Induced Insulin Resistance in Experimental Animals.

Insulin resistance (IR) is a condition characterized by reduced sensitivity of body tissues to insulin, leading to impaired regulation of downstream metabolic pathways and elevated blood glucose levels. Diets rich in fructose have been proven to cause insulin resistance in test rats, resulting in decreased insulin sensitivity, particularly in the liver, and compromised disposal of glucose from the body. In the search for effective treatments, Plant-derived formulations have gained popularity because to their ability for treating a variety of ailments. One such plant is Punica granatum Linn. from the Punicaceae family, which has long been used in the treatment of diabetes and its consequences. This study investigates the insulin-resistant activity of an extract from Punica granatum leaves. The study goal is to assess the possible protective role of Punica granatum against insulin resistance through various analyses, including serum glucose and insulin levels, lipid profile assessment, measurement of liver enzymes (ALP, SGOT, SGPT), and histopathological examination of liver sections. The study involves several key methods to evaluate the insulin-resistant activity of Punica granatum extract in high fructose diet induced insulin resistance animal model. The extract was administered orally to the experimental animals. These methods include the measurement of serum glucose and serum insulin levels, analysis of the lipid profile, quantification of liver enzymes such as ALP, SGOT, and SGPT, and a detailed histopathological examination of liver tissue sections. These analyses collectively provide insights into the impact of Punica granatum extract on insulin resistance and related metabolic parameters. Findings of this study provide insight on the possible benefits of Punica granatum extract on insulin resistance. Through the assessment of serum glucose and insulin levels, lipid profile analysis, and measurement of liver enzymes, the study elucidates the impact of the extract on key metabolic indicators. Additionally, the histopathological examination of liver sections provides visual insights into the structural changes that may occur as a result of the treatment. In conclusion, this study highlights the ability of Punica granatum extract as a candidate for addressing insulin resistance. The findings suggest that the extract may have a protective role against insulin resistance, as evidenced by improvements in serum glucose and insulin levels, lipid profile, liver enzyme levels, and histopathological characteristics. Further research and investigations are warranted to fully understand the mechanisms underlying these observed effects and to validate the potential of Punica granatum extract as a therapeutic option for managing insulin resistance and its associated complications.

Current opportunities for glycaemic control in children and adolescents with type 1 diabetes mellitus: the path to achieving a goal

Type 1 diabetes is a highly prevalent disorder worldwide and the commonest form of diabetes in children and adolescents. The incidence rates are steadily increasing, despite numerous efforts aimed at finding the possibility to detect and interrupt autoimmune inflammation in the pancreas at preclinical stages. Modern technologies make it possible to set metabolic control goals that are increasingly closer to physiological ones. The article presents recommendations regarding new technologies for glycaemic control and criteria for compensation of T1DM in children and adolescents in accordance with the updated guidelines of the International Society of Diabetes Mellitus in Children and Adolescents (ISPAD, 2022) and the Russian standards for self-monitoring of glycemia using an individual blood glucose meter associated with the use of continuous glucose monitoring technologies to assess the accuracy and/or calibration of monitoring data and address treatment adjustment issues. The possibilities and advantages of modern blood glucose meters are highlighted both in terms of accuracy of readings and functional expandability. Clinical cases demonstrating the importance of using blood glucose meters in decision-making by patients (adolescents) with type 1 diabetes who receive insulin pump therapy are presented. Excessive haste in decision-making by patients resulting in non-target results on glycaemic levels, which could have been avoided with timely measurement of blood glucose levels with a glucose meter was stressed. The great role of continuous education of children and adolescents with T1DM together with assessment and analysis of the significance of new and existing technologies for diagnosis, treatment, and monitoring of this chronic disease is emphasized, so that the patients and their parents can fully and effectively use constantly emerging opportunities.

Copper oxide nanocolumns for high-sensitive non-enzymatic glucose sensing

This paper presents a facile method to fabricate nanostructured copper-oxide (Cu2O/CuO) electrodes with columnar morphology for non-enzymatic glucose sensing. The electrodes were fabricated using a two-step method; first by producing Cu nanostructures through glancing angle deposition (GLAD), followed by a thermal annealing process at various temperatures. The nanostructures were characterized by X-ray diffraction and scanning electron microscopy to evaluate their structural and morphological properties. The optical properties of the electrodes were also investigated by VIS/NIR spectroscopy. Electrochemical characterization revealed that Cu2O outperformed other copper-based nanostructures, with the best sensitivity of 1394 μAcm-2 mM-1 and the lowest limit of detection (LOD) of 0.052 μM. The superior sensor also exhibits two broad linear ranges of 0.01–2 mM and 2–5 mM at the optimized potential of 0.6 V. The Cu2O electrodes demonstrate the merits of reproducibility, selectivity, fast response time, and high accuracy in measuring glucose levels in real blood serum samples.

GWAS of random glucose in 476,326 individuals provide insights into diabetes pathophysiology, complications and treatment stratification

Conventional measurements of fasting and postprandial blood glucose levels investigated in genome-wide association studies (GWAS) cannot capture the effects of DNA variability on ‘around the clock’ glucoregulatory processes. Here we show that GWAS meta-analysis of glucose measurements under nonstandardized conditions (random glucose (RG)) in 476,326 individuals of diverse ancestries and without diabetes enables locus discovery and innovative pathophysiological observations. We discovered 120 RG loci represented by 150 distinct signals, including 13 with sex-dimorphic effects, two cross-ancestry and seven rare frequency signals. Of these, 44 loci are new for glycemic traits. Regulatory, glycosylation and metagenomic annotations highlight ileum and colon tissues, indicating an underappreciated role of the gastrointestinal tract in controlling blood glucose. Functional follow-up and molecular dynamics simulations of lower frequency coding variants in glucagon-like peptide-1 receptor (GLP1R), a type 2 diabetes treatment target, reveal that optimal selection of GLP-1R agonist therapy will benefit from tailored genetic stratification. We also provide evidence from Mendelian randomization that lung function is modulated by blood glucose and that pulmonary dysfunction is a diabetes complication. Our investigation yields new insights into the biology of glucose regulation, diabetes complications and pathways for treatment stratification.

Hypoglycemia measured by flash glucose monitoring system predicts liver-related events in chronic liver disease patients

Impaired glucose tolerance, glucose fluctuations, and hypoglycemia have been observed in patients with chronic liver disease (CLD). The flash glucose monitoring (FGM) system, which recognises continuous and dynamic glucose changes in real time, is used in daily clinical practice. This study aimed to examine the association between glucose fluctuations and hypoglycemia, as measured by the FGM system, and liver-related events. Seventy-two patients with CLD and type 2 DM who had their blood glucose measured using Freestyle Libre Pro between April 2017 and July 2018 at our institution were enrolled in this retrospective study. We assessed the results of the FGM system measurements and liver-related events, as defined by gastrointestinal bleeding, infection, ascites, encephalopathy, and liver-related death. The standard deviation (SD) of mean glucose as measured by the FGM system was 41.55 mg/dl, and hypoglycemia was observed in 48.6% (35/72) of the patients. Liver-related event-free survival was not significant when stratified based on SD; however, the event-free survival was significantly lower when stratified by hypoglycemia (p = 0.007). In a multivariate analysis using the Cox proportional hazards model, Child–Pugh class B [Hazards ratio (HR) 2.347 (95% confidence interval (CI): 1.042–5.283), p = 0.039] and hypoglycemia [HR 2.279 (95% CI: 1.064–4.881), p = 0.034] were identified as factors contributing to event-free survival. Hypoglycemia, as determined by the FGM system, was identified as a significant factor that was closely associated with liver-related events. In addition to measuring glucose levels, the FGM system is useful in predicting the occurrence of liver-related events.

Continuous Glucose Monitoring vs. Capillary Blood Glucose in Hospitalized Type 2 Diabetes Patients.

The emergence of continuous glucose monitoring devices revolutionized the monitoring of diabetes, allowing real-time measurement of interstitial glucose levels. These devices are especially important for people with diabetes treated with insulin therapy and have been extensively studied in outpatient settings. In hospitalized patients, studies using continuous glucose monitoring have focused mainly on evaluating its accuracy and feasibility, but the results were unclear on whether continuous glucose monitoring was superior to capillary blood glucose in improving glycemic control and further research is needed to support the use of these devices in hospitalized patients with diabetes. The primary endpoint of this study was to assess the increase in time-in-range (glycemic readings between 100-180 mg/dL) in hospitalized patients with continuous glucose monitoring, compared to capillary blood glucose. The secondary endpoints included the assessment of reductions in hypoglycemia incidence, mean glucose levels, and glucose coefficient of variation. Additionally, we assessed the intervention's impact on reducing the length of hospital stay, mortality rates, and incidence of inpatient infections. This was a retrospective, cohort study of 60 hospitalized patients with type 2 diabetes, divided into two groups of 30 individuals each: an intervention group monitored through continuous glucose monitoring and a control group using capillary blood glucose. Both groups were comparable in terms of demographic and clinical characteristics. Continuous glucose monitoring users had a higher number of readings per day (six vs. four, p < 0.001), in-range readings (53.5% vs. 35%, p = 0.027), fewer above-range readings (25.5% vs. 56.5%, p = 0.003), particularly above 250 mg/dL (5% vs. 27.5%, p = 0.001), with no difference in the percentage of hypoglycemia occurence (1% vs. 0%, p = 0.107). Lower mean glucose (161.9 mg/dL vs. 206.5 mg/dL, p < 0.001) was also observed in this group. No difference was observed in mortality, length of stay, or in infection rate (p = 1.000, p = 0.455, and p = 0.606, respectively). This retrospective study supports the use of continuous glucose monitoring in optimizing glycemic control in hospitalized patients with type 2 diabetes on intensive insulin therapy. These findings suggest that continuous glucose monitoring can improve time-in-range and prevent hyperglycemia.

CORRELATION OF WATER QUALITY FACTORS AND STOCK DENSITY TO GLUCOSE AND CORTISOL LEVELS IN CANTANG GROUPER (EPINEPHELUS FUSCOGUTTATUS X EPINEPHELUS LANCEOLATUS) RAISED IN CONVENTIONAL PONDS

The purpose of this study was to find a correlation between density and water quality with glucose and cortisol levels in Cantang grouper (Epinephelus fuscoguttatus x Epinephelus lanceolatus) reared in ponds as an indicator of stress. This study uses a time series sampling method in its implementation. There were 10 Cantang grouper samples taken in this study per pond with sizes ranging from 20-30 cm. Fish samples were taken from 3 different ponds so that a total of 30 cantang grouper samples were found, while 1.5 L of water samples were taken from each pond. The results of measuring glucose levels showed that the highest average glucose levels in fish blood were obtained in pond number 6 (51.22 ± 14.9 mg dl-1) while the lowest was in pool number 5 (40.95 ± 15.2 mg dl-1). Similar to glucose levels, the results of blood cortisol measurements showed that the highest average cortisol levels in fish blood were obtained in pond number 6 (116.45 ± 5.49 ng ml-1) while the lowest was in pool number 5 (112.64 ± 4.55 ng ml-1). Based on the results of the regression analysis between the variables of water quality factors and stocking density on glucose levels (Figure 1), an R-value of 0.729 is obtained, which means that there is a 72.9% relationship between the variables of water quality factors and stocking density on glucose (moderate relationship). While the results of the regression analysis between the variables of water quality factors and stocking density on cortisol levels (Figure 2), an R-value of 0.722 was obtained, which means that there is a 72.2% relationship between the variables of water quality factors and stocking density on cortisol (moderate relationship). According to this research study, water quality factors that had a significant effect (p&gt;0.05) on glucose levels in Cantang grouper were Temperature, DO, Salinity and Ammonia.

Glucose Concentration Monitoring Using Microstrip Spurline Sensor

Abstract This article reports a microstrip spurline sensor for glucose concentration monitoring. The microstrip spurline sensor is a low-cost and easy-to-fabricate device that uses printed circuit board (PCB) technology. It consists of a combination of four spurlines and transmission lines. The four spurlines are used to reject unwanted frequencies, while the transmission lines allow the desired frequencies to pass through. The resonance frequency (Fr) and reflection coefficient (S11) were recorded through meticulous simulations and experiments over a frequency range from 1.5 GHz to 4 GHz. In addition, the sensor was used to detect changes in glucose concentration, ranging from 0 mg/dL to 150 mg/dL. The findings of this study show that the antenna-based sensor proposed in this research can effectively measure glucose levels across the diabetes range, from hypoglycemia to normoglycemia to hyperglycemia, with a high degree of sensitivity of 7.82 x 10−3 dB/(mg/dL) and 233.33 kHz/(mg/dL).

Sosialisasi dan Skrining Sindrom Metabolik melalui Pengukuran IMT, Tekanan Darah, serta Pemeriksaan Glukosa Darah pada Orang Dewasa di Masa Pandemi Covid-19

Metabolic syndrome is caused by a poor lifestyle, excessive food consumption, lack of physical activity. Someone with metabolic syndrome will be more susceptible to Covid-19. This community service activity aims to provide knowledge about metabolic syndrome as well as measurement of Body Mass Index (BMI), measurement of blood pressure and checking blood glucose levels. The method of carrying out activities is in the form of outreach related to metabolic syndrome and screening for metabolic syndrome through BMI measurements, measuring blood pressure using a digital tensimeter and checking blood glucose levels using the Point of Care method. The activity was carried out in Bangetayu Kulon RT 07 RW 01 Semarang City on May 13-15 2022. The target audience is adults aged 20-65 years with a total of 56 people. From the results of the examination, it was found that 87.5% of respondents had hypertension, 12.5% of respondents had diabetes mellitus and 73.2% of respondents were obese. Community service activities provide an overview of public health about metabolic disorders so that it is hoped that after this activity the community routinely conducts health checks to prevent metabolic syndrome.

Improving the Accuracy of Continuous Blood Glucose Measurement Using Personalized Calibration and Machine Learning.

Despite tremendous developments in continuous blood glucose measurement (CBGM) sensors, they are still not accurate for all patients with diabetes. As glucose concentration in the blood is <1% of the total blood volume, it is challenging to accurately measure glucose levels in the interstitial fluid using CBGM sensors due to within-patient and between-patient variations. To address this issue, we developed a novel data-driven approach to accurately predict CBGM values using personalized calibration and machine learning. First, we scientifically divided measured blood glucose into smaller groups, namely, hypoglycemia (<80 mg/dL), nondiabetic (81-115 mg/dL), prediabetes (116-150 mg/dL), diabetes (151-181 mg/dL), severe diabetes (181-250 mg/dL), and critical diabetes (>250 mg/dL). Second, we separately trained each group using different machine learning models based on patients' personalized parameters, such as physical activity, posture, heart rate, breath rate, skin temperature, and food intake. Lastly, we used multilayer perceptron (MLP) for the D1NAMO dataset (training to test ratio: 70:30) and grid search for hyperparameter optimization to predict accurate blood glucose concentrations. We successfully applied our proposed approach in nine patients with type 1 diabetes and observed that the mean absolute relative difference (MARD) decreased from 17.8% to 8.3%.