Fluctuations In Glucose Levels Research Articles

Postoperative early laboratory changes and follow-up process of patients underwent hyperthermic intrathoracic chemotherapy

BackgroundThe aim of combining hyperthermic intrathoracic chemotherapy (HITHOC) with surgery is to achieve local control in patients with pleural malignancies. Liver and kidney dysfunction resulting from this procedure have been reported in the literature. The objective of the study is to examine whether the laboratory abnormalities observed during the initial period persist until day 30.MethodsThe study conducted a retrospective analysis of the blood glucose levels, renal function markers, and hepatic function markers of 30 patients who underwent pleurectomy-decortication and HITHOC for pleural mesothelioma from January 2010 to April 2022. The measurements were taken in the postoperative period on the first four and 30th days. The study analyzed the initial and final laboratory results caused by the procedure.ResultsOut of the total of 30 patients, 29, 28, 14, and 12 patients had elevated glucose levels on the first four days after the surgery, respectively. There was no association between glucose abnormalities and preoperative-postoperative diabetes mellitus. A minority of patients experienced atypical alterations in kidney and liver functions during the initial postoperative period. There was no apparent relationship between the renal and hepatic functions in the early and late periods after the surgery.ConclusionAlthough there were fluctuations in glucose levels and renal and hepatic functions in the early period after surgery, there were no persistent alterations in these parameters by day 30. Elevated glucose levels during the early period were not associated with the development of newly diagnosed diabetes mellitus after surgery. The findings of our study provide evidence that HITHOC is a favorable and well-tolerated treatment option for mesothelioma.

Metabolic Stress Responses in Labeo rohita Subjected to Di (2-ethylhexyl) Phthalate (DEHP), Dibutyl Phthalate (DBP), and Diethyl Phthalate (DEP)

This study investigates the stress response of glucose and cholesterol levels in Labeo rohita (Rohu) upon exposure to three widely used phthalates: Di(2-ethylhexyl) phthalate (DEHP), Dibutyl phthalate (DBP), and Diethyl phthalate (DEP). Phthalates, recognized for their endocrine-disrupting properties, are prevalent environmental contaminants. Specimens of Labeo rohita were subjected to environmentally relevant concentrations of DEHP, DBP, and DEP over a controlled period. Blood samples were collected periodically to measure fluctuations in glucose and cholesterol levels, serving as biomarkers of metabolic stress. The results indicate significant alterations in both glucose and cholesterol concentrations, with each phthalate demonstrating a distinct impact on these metabolic parameters. DEHP and DBP elicited more pronounced disruptions compared to DEP, underscoring their higher toxicity. These findings highlight the differential metabolic responses of Labeo rohita to various phthalates and underscore the ecological risks associated with phthalate contamination. The study advocates for stricter regulatory measures to mitigate phthalate pollution and protect aquatic ecosystems. This research enhances our understanding of the biochemical pathways affected by phthalate exposure and lays the groundwork for future investigations into the mechanisms underlying phthalate-induced stress in fish.

Seasonal fluctuations of CGM metrics in individuals with type 1 diabetes using an intermittently scanned CGM device or sensor augmented pump.

To elucidate the fluctuations in glucose levels measured using CGM-metrics during the four distinct seasons of the year in individuals with type 1 diabetes mellitus (T1DM) using an intermittently scanned CGM (isCGM) device or sensor augmented pump (SAP). This retrospective, single-center study enrolled 93 individuals with T1DM who were equipped with an isCGM device or SAP at Kobe University Hospital. The subjects had a median age of 47.0 years [interquartile range, 37.0-62.0 years], 25 individuals (26.9%) were male, median body mass index was 22.0 kg/m2 [20.8-23.8 kg/m2], and median hemoglobin A1c level was 7.4% [6.9-8.0%]. CGM data were reviewed from January to December 2019, and the mean sensor glucose (SG) value, time above range (TAR), time in range (TIR), time below range (TBR), and standard deviation (SD) of SG were calculated for each season (spring, March-May; summer, June-August; autumn, September-November; winter, December-February). Seasonal fluctuations were detected for mean SG, TAR, TIR, and SD, with TIR being lower and mean SG, TAR, and SD being higher in cold seasons (spring or winter) than in warm seasons (summer or autumn). Seasonal fluctuations in CGM metrics should be taken into account in future studies performed to evaluate the favorable impact of CGM on glycemic management in individuals with T1DM.

Accuracy of FreeStyle Libre flash glucose monitoring in patients with type 2 diabetes who migrated from highlands to plains

BACKGROUND The FreeStyle Libre flash glucose monitoring (FGM) system entered the Chinese market in 2017 to complement the self-monitoring of blood glucose. Due to its increased usage in clinics, the number of studies investigating its accuracy has increased. However, its accuracy has not been investigated in highland popu-lations in China. AIM To evaluate measurements recorded using the FreeStyle Libre FGM system compared with capillary blood glucose measured using the enzyme electrode method in patients with type 2 diabetes (T2D) who had migrated within 3 mo from highlands to plains. METHODS Overall, 68 patients with T2D, selected from those who had recently migrated from highlands to plains (within 3 mo), were hospitalized at the Department of Endocrinology from August to October 2017 and underwent continuous glucose monitoring (CGM) with the FreeStyle Libre FGM system for 14 d. Throughout the study period, fingertip capillary blood glucose was measured daily using the enzyme electrode method (Super GL, China), and blood glucose levels were read from the scanning probe during fasting and 2 h after all three meals. Moreover, the time interval between reading the data from the scanning probe and collecting fingertip capillary blood was controlled to < 5 min. The accuracy of the FGM system was evaluated according to the CGM guidelines. Subsequently, the factors influencing the mean absolute relative difference (MARD) of this system were analyzed by a multiple linear regression method. RESULTS Pearson’s correlation analysis showed that the fingertip and scanned glucose levels were positively correlated (R = 0.86, P = 0.00). The aggregated MARD of scanned glucose was 14.28 ± 13.40%. Parker's error analysis showed that 99.30% of the data pairs were located in areas A and B. According to the probe wear time of the FreeStyle Libre FGM system, MARD1 d and MARD2–14 d were 16.55% and 14.35%, respectively (t = 1.23, P = 0.22). Multiple stepwise regression analysis showed that MARD did not correlate with blood glucose when the largest amplitude of glycemic excursion (LAGE) was < 5.80 mmol/L but negatively correlated with blood glucose when the LAGE was ≥ 5.80 mmol/L. CONCLUSION The FreeStyle Libre FGM system has good accuracy in patients with T2D who had recently migrated from highlands to plains. This system might be ideal for avoiding the effects of high hematocrit on blood glucose monitoring in populations that recently migrated to plains. MARD is mainly influenced by glucose levels and fluctuations, and the accuracy of the system is higher when the blood glucose fluctuation is small. In case of higher blood glucose level fluctuations, deviation in the scanned glucose levels is the highest at extremely low blood glucose levels.

Analyzing Protein and Glucose Levels in Pregnant Women Attending Antenatal Care at Health Centers in Port Harcourt, Rivers State

Protein and glucose serve as crucial indicators of potential maternal health complications and fetal outcomes during pregnancy. This study aimed to investigate protein and glucose level of pregnant women attending antenatal care in some health centre, in Port Harcourt, Nigeria. A total of sixty pregnant women between ages 16-45 who attended antenatal care in the selected health centres were randomly selected and their urine samples were collected and analyzed for protein and glucose levels using urinometre (combi 2). The result obtained for protein level ranged between 200± 14.0mg/dl to 350± 16.2 mg/dl while the glucose level ranged between 180± 11.0mg/dl to 200± 12.0mg/dl. The least protein level of 200± 14.0mg/dl were recorded among 7-9 months (3rd trimester) pregnancy, while the highest protein level of 350± 16.0mg/dl were recorded between 0-3 months (1st trimester). The least glucose value of 180± 11.0mg/dl was recorded among pregnant women that are in their 1st trimester, while the highest value of 200± 12.0mg/dl was recorded among pregnant women in their 2nd trimester. The result indicates significant fluctuations in protein and glucose levels across trimesters, reflecting dynamic metabolic changes during pregnancy.Factors like advanced maternal age, knowledge gaps, misconceptions, symptoms, and treatment-seeking behaviour highlighted in the questionnaire data can be considered as potential risk factors or indicators concerning protein and glucose levels during pregnancy. Addressing these factors through targeted education, early detection, and appropriate medical intervention is recommended in the study area to ensure an optimal pregnancy outcome

Optimizing type 2 diabetes management: AI-enhanced time series analysis of continuous glucose monitoring data for personalized dietary intervention.

Despite advanced health facilities in many developed countries, diabetic patients face multifold health challenges. Type 2 diabetes mellitus (T2DM) go along with conspicuous symptoms due to frequent peaks, hypoglycemia <=70 mg/dL (while fasting), or hyperglycemia >=180 mg/dL two hours postprandial, according to the American Diabetes Association (ADA)). The worse effects of Type 2 diabetes mellitus are precisely associated with the poor lifestyle adopted by patients. In particular, a healthy diet and nutritious food are the key to success for such patients. This study was done to help T2DM patients improve their health by developing a favorable lifestyle under an AI-assisted Continuous glucose monitoring (CGM) digital system. This study aims to reduce the blood glucose level fluctuations of such patients by rectifying their daily diet and maintaining their exertion vs. food consumption records. In this study, a well-precise prediction is obtained by training the ML model on a dataset recorded from CGM sensor devices attached to T2DM patients under observation. As the data obtained from the CGM sensor is time series, to predict blood glucose levels, the time series analysis and forecasting are done with XGBoost, SARIMA, and Prophet. The results of different Models are then compared based on performance metrics. This helped in monitoring various trends, specifically irregular patterns of the patient's glucose data, collected by the CGM sensor. Later, keeping track of these trends and seasonality, the diet is adjusted accordingly by adding or removing particular food and keeping track of its nutrients with the intervention of a commercially available all-in-one AI solution for food recognition. This created an interactive assistive system, where the predicted results are compared to food contents to bring the blood glucose levels within the normal range for maintaining a healthy lifestyle and to alert about blood glucose fluctuations before the time that are going to occur sooner. This study will help T2DM patients get in managing diabetes and ultimately bring HbA1c within the normal range (<= 5.7%) for diabetic and pre-diabetic patients, three months after the intervention.

Enhancement of Ambulatory Glucose Profile for Decision Assistance and Treatment Adjustments.

The ambulatory glucose profile (AGP) lacks sufficient statistical metrics and insightful graphs; indeed, it is missing important information on the temporal patterns of glucose variations. The AGP graph is difficult to interpret due to the overlapping metrics and fluctuations in glucose levels over 14 days. The objective of this proposed work is to overcome these challenges, specifically the lack of insightful information and difficulty in interpreting AGP graphs, to create a platform for decision assistance. The present work proposes 20 findings built from decision rules that were developed from a combination of AGP metrics and additional statistical metrics, which have the potential to identify patterns and insightful information on hyperglycemia and hypoglycemia. The "CGM Trace" webpage was developed, in which insightful metrics and graphical representations can be used to make inferences regarding the glucose data of any user. However, doctors (endocrinologists) can access the "Findings" tab for a summarized presentation of their patients' glycemic control. The findings were implemented for 67 patients' data, in which the data of 15 patients were collected from a clinical study and the data of 52 patients were gathered from a public dataset. The findings were validated by means of MANOVA (multivariate analysis of variance), wherein a p value of < 0.05 was obtained, depicting a strong significant correlation between the findings and the metrics. The proposed work from "CGM Trace" offers a deeper understanding of the CGM data, enhancing AGP reports for doctors to make treatment adjustments based on insightful information and hidden patterns for better diabetic management.

A comparative observational study of carbohydrate intake and continuous blood glucose levels in relation to performance in ultramarathon

Ultra-endurance events have gained global participation, whereas the critical factors of competition results remain to be well elucidated. This study used a nutritional approach to evaluate the association of competition results with carbohydrate intake and blood glucose control during a 100-mile ultramarathon. This observational study was conducted in the 2021 LAKE BIWA 100, which covered 100 miles (169 km) and 10,500 m elevation. The course was divided into 9 segments by aid station. According to the competition results, 22 participants (18 men and 4 women) were divided into higher finishers (n = 7), lower finishers (n = 9), and non-finishers (n = 6). The participants self-recorded their overall dietary intake throughout the race. Glucose levels were monitored every 15 min by a flash glucose monitoring system. Running speed in each segment was standardized to the average of the top five finishers for each gender. Among finishers, the carbohydrate intakes were significantly higher in the higher finishers than in the lower finishers during overall segments, especially in the first half of the race (p < 0.05). There was a significant positive correlation between running speed and carbohydrate intake in the lower finishers (rho = 0.700, p = 0.036). Two-way ANOVA analysis revealed that lowering glucose levels in each segment were more frequently observed in the lower finishers compared to the higher finishers (p = 0.012). Compared to the higher finishers, the lower finishers exhibited significantly greater fluctuations (⊿highest-lowest) in glucose levels (p < 0.001). The fluctuations in glucose levels were significantly and negatively correlated with the running speed of the finishers (rho = − 0.612, p = 0.012). Faster runners consume high amounts of carbohydrates and maintain glucose levels during the 100-mile ultramarathon on the trail, especially at the beginning. Lowering and fluctuating glucose levels during the race are associated with lower running speed in endurance athletes.

Sodium fluoride preserves blood metabolite integrity for biomarker discovery in large-scale, multi-site metabolomics investigations.

Background: Metabolite profiling of blood by nuclear magnetic resonance (NMR) is invaluable to clinical biomarker discovery. To ensure robustness, biomarkers require validation in large cohorts and across multiple centres. However, collection procedures are known to impact on the stability of biofluids that may, in turn, degrade biomarker signals. We trialled three blood collection tubes with the aim of solving technical challenges due to preanalytical variation in blood metabolite levels that are common in cohort studies. Methods: We first investigated global NMR-based metabolite variability between biobanks, including the large-scale UK Biobank and TwinsUK biobank of the general UK population, and more targeted biobanks derived from multicentre clinical trials relating to inflammatory bowel disease. We then compared the blood metabolome of 12 healthy adult volunteers when collected into either sodium fluoride/potassium oxalate, lithium heparin, or serum blood tubes using different pre-processing parameters. Results: Preanalytical variation in the method of blood collection strongly influences metabolite composition within and between biobanks. This variability can largely be attributed to glucose and lactate. In the healthy control cohort, the fluoride oxalate collection tube prevented fluctuation in glucose and lactate levels for 24 hours at either 4 °C or room temperature (20 °C). Conclusions: Blood collection into a fluoride oxalate collection tube appears to preserve the blood metabolome with delayed processing up to 24 hours at 4 °C. This method may be considered as an alternative when rapid processing is not feasible.

Progression of insulin resistance in individuals with type 1 diabetes: A retrospective longitudinal study on individuals from Thailand

Aims To investigate temporal changes in glycaemic control and weight contributing to insulin resistance (IR), in Thai individuals with type 1 diabetes (T1D). Methods Longitudinal data of 69 individuals with T1D were retrospectively collected over a median follow-up of 7.2 years. The estimated glucose disposal rate (eGDR), a marker of IR, was calculated using an established formula. Individuals were assigned as insulin-sensitive T1D (the latest eGDR≥8 mg/kg/min), or insulin-resistant T1D/double diabetes (the latest eGDR&lt;8 mg/kg/min). Generalised linear mixed model was employed to compare the temporal patterns of HbA1c, BMI, and eGDR between the two groups. Results 26 insulin-resistant T1D had a gradual decline in eGDR, corresponding with increased weight and HbA1c. In contrast, 43 insulin-sensitive T1D had stable insulin sensitivity with an improvement in HbA1c over time, associated with a modest weight gain. Fluctuations of glucose levels were observed during the early diabetes course leading to unstable eGDR, thus limiting the use of eGDR to classify insulin-resistant T1D. Conclusion T1D individuals who eventually develop IR are likely to experience early increasing IR over time. In contrast, those who ultimately do not have IR, maintain their insulin sensitivity throughout their course at least in the medium term.

The effect of sodium-glucose cotransporter 2 inhibitors as an adjunct to insulin in patients with type 1 diabetes assessed by continuous glucose monitoring: A systematic review and meta-analysis

AimsPatients undergoing insulin-based therapy for type 1 diabetes often experience poor glycemic control characterized by significant fluctuations. This study was undertaken to analyze the effect of sodium-glucose cotransporter 2 inhibitors (SGLT2Is), as an adjunct to insulin, on time in range (TIR) and glycemic variability in patients with type 1 diabetes, using continuous glucose monitoring (CGM). In addition, we examined which type of SGLT2I yielded a superior effect compared to others. MethodsWe conducted a comprehensive search of PubMed, EMBASE, the Cochrane Library, Web of Science, and clinical trial registry websites, retrieving all eligible randomized clinical trials (RCTs) published up until February 2023. We analyzed the mean TIR, mean amplitude of glucose excursions (MAGE), mean daily glucose (MDG), diabetic ketoacidosis (DKA), standard deviation (SD), total insulin dose, and severe hypoglycemia to evaluate the efficacy and safety of SGLT2Is. A random-effects model was also employed. ResultsThis study encompassed 15 RCTs. The meta-analysis revealed that the use of SGLT2Is as an adjuvant therapy to insulin led to a significant increase in TIR (MD = 10.78, 95%CI = 9.33–12.23, I2 = 42 %, P < 0.00001) and a decrease in SD (MD = −0.38, 95%CI = −0.50 to −0.26, I2 = 0 %, P < 0.00001), MAGE (MD = −0.92, 95%CI = −1.17 to −0.67, I2 = 19 %, P < 0.00001), MDG(MD = −1.01, 95%CI = −1.32 to −0.70, I2 = 48 %, P < 0.00001), and total insulin dose (MD = −5.81, 95%CI = −7.81 to −3.82, I2 = 32 %, P < 0.00001). No significant increase was observed in the rate of severe hypoglycemia (RR = 1.04, 95 % CI = 0.76–1.43, P = 0.80). However, SGLT2I therapy was associated with increased DKA occurrence (RR = 2.79, 95 % CI = 1.42–5.48; P = 0.003, I2 = 16 %). In addition, the subgroup analyses based on the type of SGLT2Is revealed that dapagliflozin might exhibit greater efficacy compared to other SGLT2Is across most outcomes. ConclusionsSGLT2Is exhibited a positive effect on improving blood glucose level fluctuations. Subgroup analysis showed that dapagliflozin appeared to have more advantages. However, giving due consideration to preventing adverse effects, particularly DKA, is paramount. RegistrationProspero CRD42023408276.

Comparative Analysis of Predictive Interstitial Glucose Level Classification Models.

New methods of continuous glucose monitoring (CGM) provide real-time alerts for hypoglycemia, hyperglycemia, and rapid fluctuations of glucose levels, thereby improving glycemic control, which is especially crucial during meals and physical activity. However, complex CGM systems pose challenges for individuals with diabetes and healthcare professionals, particularly when interpreting rapid glucose level changes, dealing with sensor delays (approximately a 10 min difference between interstitial and plasma glucose readings), and addressing potential malfunctions. The development of advanced predictive glucose level classification models becomes imperative for optimizing insulin dosing and managing daily activities. The aim of this study was to investigate the efficacy of three different predictive models for the glucose level classification: (1) an autoregressive integrated moving average model (ARIMA), (2) logistic regression, and (3) long short-term memory networks (LSTM). The performance of these models was evaluated in predicting hypoglycemia (<70 mg/dL), euglycemia (70-180 mg/dL), and hyperglycemia (>180 mg/dL) classes 15 min and 1 h ahead. More specifically, the confusion matrices were obtained and metrics such as precision, recall, and accuracy were computed for each model at each predictive horizon. As expected, ARIMA underperformed the other models in predicting hyper- and hypoglycemia classes for both the 15 min and 1 h horizons. For the 15 min forecast horizon, the performance of logistic regression was the highest of all the models for all glycemia classes, with recall rates of 96% for hyper, 91% for norm, and 98% for hypoglycemia. For the 1 h forecast horizon, the LSTM model turned out to be the best for hyper- and hypoglycemia classes, achieving recall values of 85% and 87% respectively. Our findings suggest that different models may have varying strengths and weaknesses in predicting glucose level classes, and the choice of model should be carefully considered based on the specific requirements and context of the clinical application. The logistic regression model proved to be more accurate for the next 15 min, particularly in predicting hypoglycemia. However, the LSTM model outperformed logistic regression in predicting glucose level class for the next hour. Future research could explore hybrid models or ensemble approaches that combine the strengths of multiple models to further enhance the accuracy and reliability of glucose predictions.

Immobilization of GOX on PEG/fluoresence functionalized nanographene oxide to describe fluctuation of glucose level

Enzyme, produced and worked in all living things, could work as macromolecular biological catalysts in diverse biochemical processes with particular specificity, like glucose oxidase (GOX). The efficient use of enzyme properties has great importance in pharmaceutics and therapeutics. In this work, we could fabricate naive and effective electrochemical biosensors in the determination of glucose levels via utilizing GOX. Graphene oxide, as a water-soluble derivative of graphene, has shown great promise in a variety of biomedical applications including biosensors. Thus, we established a new-type special platform for GOX immobilization to perform its prosperities, in which nanographene oxide (nGO) was employed as an ideal base and poly(ethylene glycol) (PEG) was conjugated on the edge of nGO sheets to enhance its biocompatibility. Additionally, preferable functional dyes (Rhodamine B/fluorescein isothiocyanate) were also introduced to the platform. Enzyme-nanocomposites were then provided by locating GOX on the platform, i.e., GOX@nGO-PEG-RhB and GOX@nGO-PEG-FITC. The microstructure and composite of platforms and enzyme-nanocomposites were confirmed by diverse characterizations. Finally, on account of corresponding cyclic voltammetric and typical ready-state amperometric curves, it was informed that GOX@nGO-PEG-RhB and GOX@nGO-PEG-FITC could effectively respond to the fluctuation of glucose level as electrochemical biosensor. The present work presents special platforms for the immobilization of enzymes like GOX and provides new-type biosensors in the detection of glucose levels.

Relationship of hyperglycaemic and glycaemic fluctuations to major adverse cardiovascular events in type 2 Diabetes Mellitus

Abstract Funding Acknowledgements Type of funding sources: Public Institution(s). Main funding source(s): Dean's funds of the University of Malta Medical School. Background Type 2 diabetes mellitus (T2DM) is a known major risk factor for cardiovascular disease. Nonetheless, tight glycaemic control has not convincingly shown to lead to improved cardiovascular outcomes in clinical trials. This could be due to the fact that the vast majority of trials did not assess the effect of hypoglycaemia and glucose fluctuations in their study population. The aim of this study was thus to investigate the effects of hyperglycaemia, hypoglycaemia and glucose variability in subjects with T2DM at a median follow-up of 6.4 years. Methods Subjects with T2DM of less than 10 years duration, and on stable anti-glycaemic treatment were recruited. At baselines, all participants underwent 72-hour continuous glucose monitoring, as well as parameters assessment. Moreover, risk factor bloods, including an HbA1c level, were taken. Patients were consequently followed up at 6.4 years (median: 2338 days, IQR: 2116-2446 days) and MACE (major adverse cardiovascular events) was assessed. This comprised a composite of all-cause mortality, non-fatal myocardial infarction (both ST-elevation myocardial infarction and non-ST elevation myocardial infarction), revascularisation (both percutaneous and coronary artery bypass grafting), non-fatal stroke and hospitilisation for heart failure. The incidence of MACE was assessed from electronic database available at the local public hospital that caters for the entire Maltese population. Univariate analysis was performed using Mann-Whitney U test for non-parametric variables and independent samples t-test for parametric variables. Variables with a p value &amp;lt;0.1 were consequently put in the multivariate Cox regression model to assess for independent predictors of MACE. Statistical analysis was performed using SPSS version 24.0 for Windows. Findings: The study population comprised 122 subjects with T2DM (89 males: 32 females). The mean age was 62.6 years and the mean DM duration was 3.7 years at baseline. At follow-up, 19 participants exhibited MACE. Variables with a p value of &amp;lt;0.1 in univariate analysis comprised fructosamine, HbA1c, mean systolic blood pressure measurements as well as duration of BG (blood glucose) &amp;lt;3.9 mmol/L and standard deviation of BG (an indicator of intra-individual blood glucose variability; the latter two were derived from 72-hour continuous glucose monitoring). Following adjustment for both age and gender, HbA1c (OR: 1.9, 95% CI: 1.32-2.73, p= 0.001) levels at baseline as well as standard deviation of BG (OR: 1.93, 95% CI: 1.68-3.16, p= 0.009) were shown to be independent predictors of MACE. Interpretation: This study demonstrates that cardiovascular disease in subjects with T2DM of relatively short duration is not only influenced by poor glycaemic control but also by fluctuations in glucose levels, as evidenced by measurements obtained from continuous glucose monitoring obtained at baseline.

Chronostructure and circadian rhythms of the parameters of the coagulation system and neurohumoral regulatory systems determining diurnal profile of blood pressure

The article is devoted to circadian rhythms of parameters of the hemostatic systems and humoral vasoactive factors determining diurnal profile of blood pressure. Researches indicate the presence of circadian rhythms of activity of autonomic nervous system and renin-angiotensin-aldosterone system in healthy human. Plasma catecholamines maximal activity is observed during the daytime, minimal one at night. Plasma renin activity and aldosterone concentration gradually decreases during the day, reaching its minimum at 4 p.m., followed by increase overnight to a peak at 8 a.m. Angiotensin-converting enzyme diurnal pattern is characterized by monophasic curve with maximal activity in the evening and minimum at night. Physiological features of hemostasis chronobiological characteristics in patients with coronary heart disease are present. All indexes of progressing coagulation and anticoagulation blood system has shown pronounced expressive shift of hypercoagulations in patients in the evening and at night. Fluctuations of insulin and glucose levels during 24 hours are also subject to circadian rhythm, i.e. maximal concentration is observed during the daytime, minimal one at night. Such diurnal rhythms are characteristic for patients without complicated arterial hypertension. However, circadian rhythms disturbances of humoral factors may further violate the circadian profile of blood pressure. It is pointed out that chronotherapy promote further development of the principle of individual treating approach.

Impact of Overnight Glucose on Next-Day Functioning in Adults With Type 1 Diabetes: An Exploratory Intensive Longitudinal Study.

While there is evidence that functioning, or ability to perform daily life activities, can be adversely influenced by type 1 diabetes, the impact of acute fluctuations in glucose levels on functioning is poorly understood. Using dynamic structural equation modeling, we examined whether overnight glucose (coefficient of variation[CV], percent time <70 mg/dL, percent time >250 mg/dL) predicted seven next-day functioning outcomes (mobile cognitive tasks, accelerometry-derived physical activity, self-reported activity participation) in adults with type 1 diabetes. We examined mediation, moderation, and whether short-term relationships were predictive of global patient-reported outcomes. Overall next-day functioning was significantly predicted from overnight CV (P = 0.017) and percent time >250 mg/dL (P = 0.037). Pairwise tests indicate that higher CV is associated with poorer sustained attention (P = 0.028) and lower engagement in demanding activities (P = 0.028), time <70 mg/dL is associated with poorer sustained attention (P = 0.007), and time >250 mg/dL is associated with more sedentary time (P = 0.024). The impact of CV on sustained attention is partially mediated by sleep fragmentation. Individual differences in the effect of overnight time <70 mg/dL on sustained attention predict global illness intrusiveness (P = 0.016) and diabetes-related quality of life (P = 0.036). Overnight glucose predicts problems with objective and self-reported next-day functioning and can adversely impact global patient-reported outcomes. These findings across diverse outcomes highlight the wide-ranging effects of glucose fluctuations on functioning in adults with type 1 diabetes.

Effect of Mobile-Based Application Usage on Time in Range and Time above Range in Patients with Diabetes Mellitus: A Pilot Cohort Retrospective Study

Achieving recommended glucose targets is challenging for many people with diabetes. An application that assists in self-management through continuous glucose monitoring may help reduce glycemic variability and help people with diabetes reach glucose targets. We aimed to evaluate how a digital collection of meal photos and postprandial continuous glucose monitoring data may impact glycemic stability. We assessed people with type 1 or type 2 diabetes and a time in range of &lt;70%. Glucose parameters were measured at the beginning of application usage and after 14 days. To exclude time in range improvement due to continuous glucose monitoring use, the preceding glucose data of each user were collected in a control cohort. The intervention was via a photo-based food diary combined with continuous glucose monitoring data history. Users (n=21) demonstrated significant improvements in time in range (11.0%±5.0, P=.001) and time above range (-12.0%±5.0, P=.001). Combining continuous glucose monitoring data with meal photos in a mobile application could help improve time in range and time above range. A photo-based diabetes management application with visualized continuous glucose monitoring data and connection to specific meals allows better understanding of different meal-related decisions among individuals, thus decreasing fluctuations in glucose levels. Further research is needed to evaluate time in range and time above range changes caused by the regular use of the digital food diary combined with continuous glucose monitoring data.

Artificial Sweeteners Perturbed Liver Enzymes in Rat Model

In the recent time there has been an increased demand of low-fat or low calorie diet universally. In the mean while the availability of low calorie products has also increased like sugar free drinks, beverages, biscuits, jams and jellies. On contrary to this, some studies suggest that the prolong use of non-nutritive sweeteners alters the homeostasis of glucose and insulin. It results in fluctuation of glucose level in blood and increase in bodyweight. This study intends to evaluate the effect of non-nutritive sweeteners on the liver function test and record the alteration in the levels of ALP, AST and ALT. Seventy rats were divided into seven equal groups, controlled group received distilled water and the rest six were given NNS Sucrose, Stevia, Sucralose, Saccharine Aspartame and Acesulfame-k, respectively. On the evaluation of Alanine aminotransferase ALT, saccharine and aspartame markedly increased the level of ALT from 40U/L to 80 U/L. Both of these NNS have shown the most raised level of Alanine aminotransferase. This represents the stress on the liver associated with the use of NNS and suggests the use to be controlled in humans.

Prolonged insulin-induced hypoglycaemia reduces ß-cell activity rather than number in pancreatic islets in non-diabetic rats

Pancreatic β-cells have an extraordinary ability to adapt to acute fluctuations in glucose levels by rapid changing insulin production to meet metabolic needs. Although acute changes have been characterised, effects of prolonged metabolic stress on β-cell dynamics are still unclear. Here, the aim was to investigate pancreatic β-cell dynamics and function during and after prolonged hypoglycaemia. Hypoglycaemia was induced in male and female rats by infusion of human insulin for 8 weeks, followed by a 4-week infusion-free recovery period. Animals were euthanized after 4 or 8 weeks of infusion, and either 2 days and 4 weeks after infusion-stop. Total volumes of pancreatic islets and β-cell nuclei, islet insulin and glucagon content, and plasma c-peptide levels were quantified. Prolonged hypoglycaemia reduced c-peptide levels, islet volume and almost depleted islet insulin. Relative β-cell nuclei: total pancreas volume decreased, while being unchanged relative to islet volume. Glucagon: total pancreas volume decreased during hypoglycaemia, whereas glucagon: islet volume increased. Within two days after infusion-stop, plasma glucose and c-peptide levels normalised and all remaining parameters were fully reversed after 4 weeks. In conclusion, our findings indicate that prolonged hypoglycaemia inactivates β-cells, which can rapidly be reactivated when needed, demonstrating the high plasticity of β-cells even following prolonged suppression.

Experiences of Using Wearable Continuous Glucose Monitors in Adults With Diabetes: A Qualitative Descriptive Study.

The purpose of the study was to understand the experiences of adults with diabetes wearing a continuous glucose monitor (CGM). This qualitative, descriptive study included 19 adults with type 1 diabetes or type 2 diabetes, who had used the FreeStyle Libre CGM for at least 4 weeks, from an outpatient clinic at a university-affiliated hospital in Korea. Data were collected through in-depth interviews and analyzed using an inductive content analysis approach. The content analysis revealed 3 major themes-navigating glucose level fluctuations, reframing diabetes self-care and improving quality of life, and device improvement and service quality. Participants reported that CGMs offered convenient glucose level monitoring, allowed early response to rapid glucose changes, and facilitated effective patient-clinician communication. Participants expressed concerns about the financial burden and limited services, recommending improvements for devices, consumer services, and health insurance coverage. Study findings indicated that using wearable CGMs could improve self-care and quality of life in adults with diabetes. Using CGMs could improve patients' understanding of how diabetes self-care management affects real-time glucose levels. Health care providers could support patients' self-care by using device data. Improvements in quality, services, and insurance coverage could increase user satisfaction and promote self-care.