Continuous Glucose Monitoring Research Articles

Diabetic Peripheral Neuropathy and Glycemia Risk Index in Type 2 Diabetes: A Cross-Sectional Study.

Diabetic peripheral neuropathy (DPN) is a prevalent chronic complication of diabetes which is linked to chronic hyperglycemia and glycemic variability. This study aimed to investigate the association between the glycemia risk index (GRI) and DPN in patients with type 2 diabetes mellitus (T2DM) using continuous glucose monitoring (CGM) data. From 2019 to 2023, 862 adults diagnosed with T2DM were enrolled at a tertiary care diabetes center in Ningbo, China. The medical history and laboratory parameters were recorded. Neurophysiological examinations were performed to evaluate DPN. The CGM data were recorded for 14 days, and the GRI was calculated based on these data. Multivariate logistic regression analyses were conducted to assess the odds ratio (OR) for DPN with an increased GRI. The prevalence of DPN in the ascending GRI quartiles was 41.6%, 47.9%, 49.1%, and 59.5%, respectively (P for trend < 0.001). In the multivariable logistic analysis, the highest GRI quartile exhibited a 63% greater risk of DPN (OR 1.631, 95% CI: 1.071 to 2.484, P = 0.023) than the lowest quartile after adjusted for age, sex, body mass index, diabetes duration, blood pressure, creatinine, urinary albumin-to-creatinine ratio, lipid profile and glycated hemoglobin. High GRI levels, as measured by CGM, were associated with a greater likelihood of DPN in T2DM patients.

Personalized management of hepatic glycogen storage disorders: The role of continuous glucose monitoring.

Glycogen storage disorders (GSD), inherent disorders of carbohydrate metabolism, feature hypoglycemia as a hallmark. Normoglycemia and glucose monitoring are pivotal in disease management. Conventional glucometer-based monitoring may overlook hypoglycemic trends. This study assesses glycemic control in Asian Indian GSD children using continuous glucose monitoring (CGM) and its role in facilitating dietary adjustments. A pre-post study enrolled molecularly confirmed GSDI, GSDIII, GSDVI, and GSDIX patients for baseline dietary compliance and CGM-based glycemic status evaluation. Hypoglycemic patients were stratified into diet-compliant and diet-noncompliant groups. Noncompliant patients received dietary reinforcement; compliant individuals underwent dietary adjustments. Repeat CGM (rCGM) was performed 6 weeks to 6 months postadjustments. Clinical and metabolic parameters were re-evaluated at 6 months. Of the 20 patients assessed at baseline, 11 were diet compliant. Six among these exhibited hypoglycemia, prompting diet adjustments. Among nine noncompliant patients, eight experienced hypoglycemia and received diet reinforcement. rCGM in 10 patients (five GSDI, three GSDIII, and two GSDIXc) showed a significant reduction in hypoglycemia duration in all. An improvement in height and body mass index was observed in all GSDI and GSDIII patients. Triglyceride levels, raised at baseline in two GSDI and one GSDIII, showed a substantial decline in one GSDI patient. Hepatic transaminase levels decreased in both GSDIXc patients. Plasma lactate levels decreased in all GSDI patients. CGM is an efficacious adjunct in the personalized management of hepatic GSD patients, in the Asian Indian population. The study also underscores the need for long-term follow-up to determine the role of glycemic management in growth, general well-being, and metabolic control in the GSD subtypes.

Continuous glucose monitoring profile in COVID-19 patients with and without diabetes receiving methylprednisolone.

Methylprednisolone is widely used during the COVID-19 epidemic. We aimed to evaluate the glucose profile of COVID-19 patients with and without diabetes receiving methylprednisolone. 36 patients with COVID-19 admitted to hospital were included: 17 with and 19 without diabetes. Methylprednisolone 40 mg was administered at about 9:00 a.m. Glucose levels were assessed by blinded intermittently scanned continuous glucose monitoring (isCGM) for an average of 6.8 ± 2.4 days. Excess hyperglycemia was defined as time above range (TAR) > 10.0 mmol/L (TAR>10.0) ≥ 25%, or TAR > 13.9 mmol/L (TAR>13.9) ≥ 10%. Glucose management indicator (GMI) was significantly higher than the admission glycated hemoglobin A1c (HbA1c) level in patients without diabetes [6.7 (6.1-7.0) % vs. 5.9 (5.9-6.1) %, P < 0.001], while no significant difference was found in patients with diabetes [9.0 (7.5-9.5) % vs. 8.9 (7.5-10.2) %, P > 0.05]. The difference between GMI and HbA1c (∆GMI-HbA1c) in patients without diabetes was significantly higher than in patients with diabetes [0.7 (0.2-1.0) % vs. -0.2 (-1.5-0.5) %, P = 0.005]. The circadian patterns of glucose were similar in the two groups. In patients without diabetes, excess hyperglycemia occurred in 31.6% (6/19) of participants, with 31.6% (6/19) having a TAR>10.0 ≥ 25%, while 21.1% (4/19) had a TAR>13.9 ≥ 10%. The impact of methylprednisolone on glycemia was more pronounced in COVID-19 patients without diabetes, compared to those with diabetes. A significant burden of methylprednisolone-induced hyperglycemia was observed in patients without diabetes.

Efficacy of Lisosan G (fermented wheat) on reactive hypoglycemia after bariatric surgery.

post-bariatric hypoglycemia (PBH) is considered a chronic complication after gastric bypass (RYGB) impacting roughly 30% of patients. Current treatments often focus on nutritional interventions to reduce the frequency of episodes. This prospective study evaluated the effectiveness of Lisosan G (LG), a fermented wheat-based supplement added to the diet, in mitigating PBH episodes and elucidating its mechanism of action on the gut-pancreas axis. twenty subjects with PBH, who had undergone RYGB between 2015 and 2018, were enrolled. Subjects underwent clinical examination, blood test, and a 3-hour oral glucose load test (OGTT). Then, they were monitored for 2-weeks on a free diet with continuous glucose monitoring (CGM), which was extended for another 2-weeks after introduction of LG supplementation (5g, twice daily) on the same diet. Finally, subjects repeated OGTT and blood test. PBH was defined as interstitial glucose ≤54mg/dl. after treatment, a marked reduction in PBH time was observed (75[23-113] vs 16 [0-33], minutes, p<0.001). During OGTT, there was an increase in glucose nadir (44±11 vs 56±10, mg/dl, p=0.038), and a significantly decrease in total GLP-1 AUC (7.6±4.1 vs 6.5±3.8, nmol/L*min, p=0.043), in potentiation factor ratio (p=0.037) and in total insulin AUC (57±12 vs 49±9, nmol/L*min, p=0.043). LG effectively reduces PBH frequency and duration, probably by attenuating GLP-1 concentrations and leading to a decrease in the second phase of insulin secretion in response to glucose. These findings underscore the promise of LG as a novel adjunct therapy for PBH, particularly when added to the diet, and emphasize the need for further exploration into its microbiota-modulating and anti-inflammatory effects.

Potential of Near-Infrared Optical Techniques for Non-invasive Blood Glucose Measurement: A Pilot Study

BackgroundDiabetes mellitus manifested by escalated blood glucose, demands periodic or continuous glucose monitoring in the pursuit of improved control, optimal management, and appropriate medication. The existing state-of-the-art for blood glucose estimation are invasive methodologies necessitating the acquisition of blood sample through either a finger-stick or venipuncture. MethodsWe propose a dual Near-infrared wavelength integrated in a 3D printed enclosure as the optical prototype for non-invasive glucose estimation. We acquired data from both diabetic and healthy subjects with the developed system and subsequently validated the system. ResultsThe system demonstrated commendable clinical accuracy, as evidenced by the alignment of data pairs representing actual blood glucose levels and blood glucose levels predicted by our optical system within the A+B zones of the Parkes error grid and zones of no-risk and lower risk as defined by the surveillance error grid. We achieved compliant pairs percentage of 95.6%, which satisfies the accuracy requirements of the blood glucose monitoring surveillance study. The mean absolute percentage error attained with the proposed device (5.99%) was significant in predicting the blood glucose. ConclusionWe successfully deployed the NIR wavelengths functionality as the promising approach for glucose monitoring, offering new possibilities for improved medical interventions.

Continuous Glucose Data Construction and Risk Assessment Application of Diabetic Retinopathy Complications for Patients with Type 2 Diabetes Mellitus

Managing diabetes mellitus (DM) includes achieving acceptable blood glucose levels and minimizing the risk of complications from DM. The appropriate glucose sensing method is continuous glucose monitoring (CGM). Effective evaluation metrics that reflect glucose fluctuations can be realized. However, compared with self-monitoring of blood glucose (SMBG), CGM data are not easy to obtain. Therefore, this article studies a fusion model to achieve this objective, including Gaussian process regression (GPR) and long short-term memory (LSTM). Compared with the three commonly used LSTM, GPR, and support vector machine, the proposed model can construct accurate results. By using the constructed CGM data, the conventional metrics, such as the mean amplitude of glycemic excursion (MAGE), mean blood glucose (MBG), standard deviation (SD), and time in range (TIR), are calculated. These metrics and other variables are input into statistical methods to realize diabetic retinopathy risk assessment. In this way, the relationship between the glycemic variability of the constructed CGM data by the mathematical model and DR could be achieved. The utilized statistical methods include single-factor analysis and binary multivariate logistic regression analysis. Results show that fasting blood glucose, disease course, history of hypertension, MAGE and TIR are independent risk factors for DR.

Short-term intermittent fasting and energy restriction do not impair rates of muscle protein synthesis: A randomised, controlled dietary intervention

BackgroundIntermittent fasting (IF) is an effective energy restricted dietary strategy to reduce body and fat mass and improve metabolic health in individuals with either an overweight or obese status. However, dietary energy restriction may impair muscle protein synthesis (MPS) resulting in a concomitant decline in lean body mass. Due to periods of prolonged fasting combined with irregular meal intake, we hypothesised that IF would reduce rates of MPS compared to an energy balanced diet with regular meal patterns. AimsWe assessed the impact of a short-term (ten days) alternate day fasting or a continuous energy restricted diet to a control diet on integrated rates of skeletal MPS in middle-aged males with overweight or obesity. MethodsTwenty-seven middle-aged males with overweight or obesity (age: 44.6±5.4 y; BMI: 30.3±2.6 kg/m2) consumed a three-day lead-in diet, followed by a ten-day controlled dietary intervention matched for protein intake, as alternate day fasting (ADF: 62.5 energy (En)%, days of 25 En% alternated with days of 100 En% food ingestion), continuous energy restriction (CER: 62.5 En%), or an energy balanced, control diet (CON: 100 En%). Deuterated water (D2O) methodology with saliva, blood, and skeletal muscle sampling were used to assess integrated rates of MPS over the ten-day intervention period. Secondary measures included fasting plasma glucose, insulin, and gastrointestinal hormone concentrations, continuous glucose monitoring, and assessment of body composition. ResultsThere were no differences in daily rates of MPS between groups (ADF: 1.18±0.13, CER: 1.13±0.16, and CON: 1.18±0.18%/day, P>0.05). The reductions in body mass were greater in ADF and CER compared to CON (P<0.001). Lean and fat mass were decreased by a similar magnitude across groups (main time effect, P<0.001; main group effect, P>0.05). Fasting plasma leptin concentrations decreased in ADF and CER (P<0.001), with no differences in fasting plasma glucose or insulin concentrations between groups. ConclusionShort-term alternate day fasting does not lower rates of MPS compared to continuous energy restriction or an energy balanced, control diet with matched protein intake. The prolonged effects of IF and periods of irregular energy and protein intake patterns on muscle mass maintenance remain to be investigated. This trial was registered under Australian New Zealand Clinical Trial Registry (https://www.anzctr.org.au), identifier no. ACTRN12619000757112.

Analytical Accuracy of a Continuous Glucose Monitor in Adult Diabetic Ketoacidosis

Analytical Accuracy of a Continuous Glucose Monitor in Adult Diabetic Ketoacidosis

Cost-Utility of Real-Time Continuous Glucose Monitoring versus Self-Monitoring of Blood Glucose in People with Insulin-Treated Type 2 Diabetes in Spain.

Management of advanced type 2 diabetes (T2D) typically involves daily insulin therapy alongside frequent blood glucose monitoring, as treatments such as oral antidiabetic agents are therapeutically insufficient. Real-time continuous glucose monitoring (rt-CGM) has been shown to facilitate greater reductions in glycated hemoglobin (HbA1c) levels and improvements in patient satisfaction relative to self-monitoring of blood glucose (SMBG). This study aimed to investigate the cost-utility of rt-CGM versus SMBG in Spanish patients with insulin-treated T2D.. The analysis was conducted using the IQVIA Core Diabetes Model (CDM V9.5). Baseline characteristics of the simulated patient cohort and treatment efficacy data were sourced from a large-scale, United States-based retrospective cohort study. Costs were obtained from Spanish sources and inflated to 2022 Euros (EUR) where required. A remaining lifetime horizon (maximum 50 years) was used, alongside an annual discount rate of 3% for future costs and health effects. A willingness-to-pay (WTP) threshold of EUR 30,000 per quality-adjusted life year (QALY) was adopted, based on precedent across previous cost-effectiveness studies set in Spain. A Spanish payer perspective was adopted. Over patient lifetimes, rt-CGM yielded 9.933 QALYs, versus 8.997 QALYs with SMBG, corresponding to a 0.937 QALY gain with rt-CGM. Total costs in the rt-CGM arm were EUR 2347higher with rt-CGM versus SMBG (EUR 125,365 versus EUR123,017). The base case incremental cost-utility ratio was therefore EUR 2506 per QALY gained, substantially lower than the WTP threshold of EUR 30,000 per QALY. The analysis also projected a reduction in cumulative incidence of ophthalmic, renal, neurological, and cardiovascular events in rt-CGM users, with reductions of 16.03%, 13.07%, 7.34%, and 9.09%, respectively. Compared to SMBG, rt-CGM is highly likely to be a cost-effective intervention for patients living with insulin-treated T2D in Spain.

Factors associated with Glycemia Risk Index in a cohort of patients with type 1 Diabetes Mellitus and Latent Autoimmune Diabetes In Adults (LADA).

To analyze the degree of control based on classical glucometric parameters and Glycemia Risk Index (GRI) in real-life conditions in a cohort of patients with type 1 Diabetes Mellitus (DM) and Latent Autoimmune Diabetes in Adults (LADA) and to assess the factors that are associated with GRI. Cross-sectional study. 447 adult patients with type 1 DM and LADA users of Intermittent Continuous Glucose Monitoring (iCGM) with an adherence ≥ 70% were included. GRI was calculated with its Hypoglycemia (CHypo) and Hyperglycemia (CHyper) Components. Multivariate linear regression analysis was performed to evaluate the factors associated with GRI. Mean age 44.6 years (SD 13.7); 57.7% men; 83.9% type 1 DM; 16.1% LADA; time of evolution 20.6 years (SD 12.3). In patients with type 1 DM vs. LADA, differences were observed in relation to age [-11.1 years (SD 1.7)], age of onset [-21.9 years (DE 1.5)], time of evolution [11.7 years (DE 1.5)], treatment modality (p < 0.001), Time in Range (TIR) [-6.3% (SD 2.2)], Time Below Range (TBR) [1.9% (SD 0.6)], TBR level 1 (TBR1) [1.4% (SD 0.5)], Time Above Range (TAR) level 2 (TAR2) [4.7% (SD 1.3)], Coefficient of Variation (CV) [4.6% (SD 0.9)], GRI [11.3% (SD 2.8)], CHypo [1.3% (SD 0.5)] and CHyper [4.8% (SD 1.7)]. The variables that were independently associated with GRI were TIR (β = -1.34; CI 95% -1.43 to -1.25; p < 0.001), Glucose Management Indicator (GMI) (β = -5.82; CI 95% -7.59 to -4.05; p < 0.001), CV (β = 0.67; CI 95% 0.57 to 0.77; p < 0.001) and adherence to sensor usage (β = -0.16; CI 95% -1.27 to -0.06; p < 0.002). LADA present better control according to some glucometric parameters and a low GRI. However, the type of DM is not a factor that is independently associated with GRI.

Evaluation of the Effects of Non-Invasive Auricular Acupoint Stimulation on Postprandial Blood Glucose Regulation using a CGM Device

Background: Postprandial blood glucose regulation is critical for diabetes management. Non-invasive auricular acupoint stimulation may influence metabolic functions through the autonomic nervous system. This study aimed to evaluate its effects on postprandial glucose regulation using Continuous Glucose Monitoring (CGM). Methods: Thirteen healthy Japanese adults (10 males, 3 females) had 1.5 mm gold beads applied to six acupoints. Glucose levels were monitored over seven days using CGM. Key metrics included postprandial peak, 2-hour glucose levels, time to peak, and normalization time. Results: Auricular acupoint stimulation reduced time to glucose peak after breakfast (-14.6 min, p = 0.01) and glucose normalization time for breakfast and lunch combined (-20.8 min, p = 0.04). A significant reduction in 2-hour postprandial glucose was observed after lunch (-10.8 mg/dL, p = 0.03). No significant effect was found on peak glucose levels. Conclusion: Auricular acupoint stimulation may promote postprandial glucose normalization, particularly after breakfast and lunch, and could serve as a complementary approach to glucose management.

Use of Technology in the Management and Treatment of Prediabetes, A New Era: A Case Report Series

Introduction: The escalating prevalence of prediabetes has positioned it as a silent precursor to a looming public health crisis, particularly as it paves the way for type 2 diabetes mellitus (T2DM). This case series report explores the transformative role of technology, specifically the Sugar Fit’s Diabetes Reversal and Management Program (SDRMP), in the treatment and management of prediabetic patients. Methods: The case series follows the progress of two patients aged 31-44 with prediabetes utilizing the SDRMP to prevent the progression to diabetes. The interventions for both patients involved continuous glucose monitoring, personalized nutrition plans, fitness strategies, and behavioral modifications. The patients also engaged in regular communication with their life coaches through the Sugar Fit application, ensuring ongoing support and adherence to the program. Results: The results revealed significant improvements in glycemic control, lipid profiles, and overall well-being. The first patient, a 44-year-old male, demonstrated a successful return to normal glycemic control in 177 days through a comprehensive approach involving dietary changes, exercise, and lifestyle modifications. The second patient, a 31-year-old male, achieved normal glycemic control in a comparable timeframe, showcasing the effectiveness of the SDRMP. Discussion and Conclusion: These cases demonstrate that patients were able to adhere to the goals of care, preventing the progression of prediabetes to diabetes and improving insulin resistance. The study also underscores the potential impact of technology on public health outcomes, bridging the gap between traditional interventions and the evolving needs of a tech-savvy population. The synergy between healthcare expertise and technological innovation not only arrests the progression of prediabetes but also contributes to a broader societal shift towards metabolic well-being, paving the way for a healthier future. Future monitoring is essential to ensure the maintenance of lifestyle modifications and continued success in preventing diabetes.

Characterising impaired awareness of hypoglycaemia and associated risks through HypoA-Q: findings from a T1D Exchange cohort.

We aimed to: (1) externally validate the five-item Hypoglycaemia Awareness Questionnaire (HypoA-Q) impaired awareness subscale (HypoA-Q IA); (2) examine how impaired awareness of hypoglycaemia (IAH) relates to the risk of severe hypoglycaemia and level 2 hypoglycaemia; and (3) identify factors associated with IAH. Nationwide survey of T1D Exchange registrants was conducted to collect data on demographics, 6 month severe-hypoglycaemia history, hypoglycaemia awareness status (via HypoA-Q IA, the Gold instrument and the Clarke instrument) and continuous glucose monitor (CGM) measures. The Clarke hypoglycaemia awareness factor (Clarke-HAF) was calculated to exclude severe-hypoglycaemia history items. Analyses included Cronbach's α, Spearman correlations and logistic regression. Valid survey responses were collected from N=1580 adults with type 1 diabetes (median age, 44 years; 52% female participants; median HbA1c, 48 mmol/mol [6.5%]). Of these, 94% of participants were using CGMs and 69% were using hybrid closed-loop (HCL) systems; 30% had at least one severe-hypoglycaemia episode in the past 6 months. The HypoA-Q IA had satisfactory internal reliability (α=0.79) and construct validity. Higher HypoA-Q IA scores were independently associated with greater risk of severe hypoglycaemia (p<0.001), performing comparably to the Gold instrument and the Clarke-HAF instrument. HypoA-Q IA-determined IAH was independently associated with 88% higher odds of developing severe hypoglycaemia (p<0.001) and twofold higher odds for spending ≥1% of time in level 2 hypoglycaemia (p=0.011). Higher age and longer diabetes duration were associated with higher IAH risk (p<0.001). CGM and HCL use was associated with lower IAH risk (p<0.001). The HypoA-Q IA is a brief, valid and reliable tool for assessing IAH in today's technology-oriented era. IAH was independently associated with severe hypoglycaemia and level 2 hypoglycaemia in a cohort with high prevalence of advanced diabetes technology use and HbA1c within the recommended range. CGM and HCL use was related to lower IAH risk.

Effect of fenofibrate on residual beta cell function in adults and adolescents with newly diagnosed type 1 diabetes: a randomised clinical trial.

Fenofibrate, a peroxisome proliferator-activated receptor alpha agonist, shows some promise in alleviating beta cell stress and preserving beta cell function in preclinical studies of type 1 diabetes. The aim of this phase 2, placebo-controlled, double-blinded, randomised clinical trial was to investigate the efficacy and safety of fenofibrate in adults and adolescents with newly diagnosed type 1 diabetes. We enrolled 58 individuals (aged 16 to 40 years old) with newly diagnosed type 1 diabetes and randomised them to daily oral treatment with fenofibrate 160 mg or placebo for 52 weeks (in a block design with a block size of 4, assigned in a 1:1 ratio). Our primary outcome was change in beta cell function after 52 weeks of treatment, assessed by AUC for C-peptide levels following a 2h mixed-meal tolerance test. Secondary outcomes included glycaemic control (assessed by HbA1c and continuous glucose monitoring), daily insulin use, and proinsulin/C-peptide (PI/C) ratio as a marker of beta cell stress. We assessed outcome measures before and after 4, 12, 26 and 52 weeks of treatment. Blinding was maintained for participants, their healthcare providers and all staff involved in handling outcome samples and assessment. The statistical analyses for the primary outcome included 56 participants (n=27 in the fenofibrate group, after two withdrawals, and n=29 in the placebo group). We found no significant differences between the groups in either 2h C-peptide levels (mean difference of 0.08 nmol/l [95% CI -0.05, 0.23]), insulin use or glycaemic control after 52 weeks of treatment. On the contrary, the fenofibrate group showed a higher PI/C ratio at week 52 compared with placebo (mean difference of 0.024 [95% CI 0.000, 0.048], p<0.05). Blood lipidome analysis revealed that fenofibrate repressed pathways involved in sphingolipid metabolism and signalling at week 52 compared with placebo. The 52 week intervention evoked few adverse events and no serious adverse events. Follow-up in vitro experiments in human pancreatic islets demonstrated a stress-inducing effect of fenofibrate. Contrary to the beneficial effects of fenofibrate found in preclinical studies, this longitudinal, randomised, placebo-controlled trial does not support the use of fenofibrate for preserving beta cell function in individuals with newly diagnosed type 1 diabetes. EudraCT number: 2019-004434-41 FUNDING: This study was funded by the Sehested Hansens Foundation.

The benefits and accuracy of real-time continuous glucose monitoring in children and adolescents with type 1 diabetes attending a summer camp.

This study evaluated the usability, satisfaction, and accuracy of a real-time continuous glucose monitoring (rt-CGM) in children and adolescents with type 1 diabetes (T1D) attending a summer camp. Seven children and adolescents with T1D (camper) and 31 of healthcare providers (HCPs) participating in a 2-day summer camp in Kumamoto, Japan were enrolled. The usability and satisfaction were evaluated by tailored questionnaire. The accuracy of rt-CGM was evaluated using self-monitoring of blood glucose (BG) and sensor glucose (SG) values before or after (off camp) and during (on camp) the camp. The score of the usefulness of rt-CGM showed 3.29 ± 0.90 in campers and 4.23 ± 0.87 in HCPs (P = 0.017). The degree of recommendation score for rt-CGM was 3.29 ± 1.11 in campers and 4.23 ± 0.79 in HCPs (P = 0.013). Time in range (TIR) off camp was 45.9% and that on camp was 57.0%. Time above range (TAR) off camp was 53.4% and that on camp was 42.4%. The mean absolute relative difference (MARD) off camp was 19.7% ± 25.2%, whereas that on camp was 16.0% ± 14.8% (P = 0.367). Clinically acceptable zones of the error grid analyses were approximately 96% in total. Rt-CGM exhibited higher usability and recommendation scores in HCPs than those in campers. This may be related to relatively lower accuracy in rt-CGM. Overall usability and recommendation are clinically satisfactory, but due to relatively low accuracy, no decision should be made based on a single, non-verified SG value alone.

Evaluation of Glycemic Control in Patients With Diabetes by a Continuous Glucose Monitoring System During the Month of Ramadan

Evaluation of Glycemic Control in Patients With Diabetes by a Continuous Glucose Monitoring System During the Month of Ramadan

Machine Learning Algorithms Based on Time Series Pre-Clustering for Nocturnal Glucose Prediction in People with Type 1 Diabetes.

Background: Machine learning offers new options for glucose prediction and real-time glucose management. The aim of this study was to develop a machine learning-based algorithm that takes into account glucose dynamics patterns for predicting nocturnal glucose in individuals with type 1 diabetes. Methods: To identify glucose patterns, we applied a hierarchical clustering algorithm to real-time continuous glucose monitoring data obtained from 570 adult patients. Machine learning algorithms with or without pre-clustering were used for modeling. Results: Eight clusters without nocturnal hypoglycemia and six clusters with at least one low-glucose episode were identified by the cluster analysis. When forecasting time series without hypoglycemia with a prediction horizon (PH) of 15 or 30 min, gradient boosting trees (GBTs) with pre-clustering and random forest (RF) with pre-clustering outperformed algorithms based on medoids of time series clusters, the Holt model, and GBTs without pre-clustering. When forecasting time series with low-glucose episodes, a model based on the pre-clustering and GBTs provided the highest predictive accuracy at PH = 15 min, and a model based on RF with pre-clustering was the best at PH = 30 min. Conclusions: The results indicate that the clustering of glucose dynamics can enhance the efficacy of machine learning algorithms used for glucose prediction.

Nanomedicine Innovations for Diabetes Management: Revolutionizing Diagnosis, Treatment, and Monitoring

Diabetes mellitus, a widespread metabolic disease characterized by high blood sugar levels, affects many people globally. The limitations of conventional diagnostic and therapeutic approaches necessitate exploring innovative strategies. Nanotechnology shows remarkable potential for revolutionizing the field of diabetes theranostics (combined diagnosis and treatment) by enabling accurate diagnosis and precise treatment delivery. This article provides a comprehensive review of the latest advancements in nanomaterials for diagnosing and treating diabetes. It explores the applications of various nanomaterials, including inorganic and organic nanoparticles, nanocomposites, and nanostructured biosensors, in biomarker detection, glucose monitoring, insulin delivery, and addressing diabetes-related complications. The study focuses on the synthesis and functionalization of nanomaterials for diabetes, covering both traditional and environmentally friendly synthesis methods. This study looks into how nanomaterials can be used to carry natural antidiabetic extracts, recombinant insulin, and other antidiabetic drugs, to make them more bioavailable, targetable, and effective. However, the review also talks about the problems that come with using nanosensors to diagnose diabetes. It also looks at the newest developments in nanosensors for biomarker detection, implantable devices, and continuous glucose monitoring. Additionally, the review examines the potential of nanomaterials in the management of diabetic sequelae, including diabetic nephropathy, cardiovascular disorders, retinopathy, and wound healing. We underscore the significance of nanomaterials in islet transplantation, as they provide immunological protection and enhance the viability and efficacy of islets. This study provides useful insights into the prospects and challenges connected with the rapidly growing field of nanotechnology in diabetic theranostics through a comprehensive examination of the current landscape. Academics, clinicians, and stakeholders engaged in developing innovative nanomaterial-based approaches to accurately diagnose and effectively manage diabetes will find this resource highly helpful.

Identification of gut microbiome features associated with host metabolic health in a large population-based cohort

The complex relationship between the gut microbiome and host metabolic health has been an emerging research area. Several recent studies have highlighted the potential effects of the microbiome’s diversity, composition and metabolic production capabilities on Body Mass Index (BMI), liver health, glucose homeostasis and Type-2 Diabetes (T2D). The majority of these studies were constrained by relatively small cohorts, mostly focusing on individuals with metabolic disorders, limiting a comprehensive understanding of the microbiome’s role in metabolic health. Leveraging a large-scale, comprehensive cohort of nearly 9000 individuals, measured using Continuous Glucose Monitoring (CGM), Dual-energy X-ray absorptiometry (DXA) scan and liver Ultrasound (US) we examined the functional profile of the gut microbiome, and its relation to 38 metabolic health measures. We identified 145 unique bacterial pathways significantly correlated with metabolic health measures, with 86.9% of these showing significant associations with more than one metabolic health measure. Furthermore, 87,678 unique bacterial gene families were found to be significantly associated with at least one metabolic health measure. Notably, “key” bacterial pathways such as purine ribonucleosides degradation and anaerobic energy metabolism demonstrated multiple robust associations across various metabolic health measures, highlighting their potential roles in regulating metabolic processes. Our results remained largely unchanged after adjustments for nutritional habits and for BMI they were replicated in a geographically independent cohort. These insights pave the way for future research and potentially the development of microbiome-targeted interventions to enhance metabolic health.

Exploration of micro-miniature venturi pump for continuous glucose monitoring through interstitial fluid (ISF) extraction

Interstitial Fluid (ISF) is a naturally occurring body fluid that surrounds cells and tissues and contains certain markers useful for continuously monitoring glucose levels in the blood without constantly extracting it. Miniaturizing can reduce its cost and timescale. In this study, for continuous glucose monitoring the numerical analysis of a Polymethyl methacrylate (PMMA) based Micro-miniature venturi pump was carried out to extract Interstitial Fluid (ISF). The numerical study was carried out using COMSOL Multiphysics software by employing the k-ε turbulence model to obtain output as a vacuum at the throat of the pump. The micro-miniature venturi pump was numerically analyzed for several key parameters, including the dimensions of the throat, the convergent angle, and the divergent angle. This study obtained a minimum pressure of 49.41 kPa numerically and 70 kPa experimentally when an input pressure of 252 kPa of compressed air was given to the system. Further influence of turbulence kinetic energy and turbulence dissipation rate on throat pressure output have been notified. Notably, the pressure output reaches its minimum value of 49.41 kPa when the turbulent kinetic energy and the turbulent dissipation rate reach maximum values of 5.0 × 109 m2/s3 and 7000 m2/s2 respectively. As per the previous research findings, for continuous glucose monitoring through ISF extraction, a pressure level of 95 kPa is deemed adequate hence the designed micro-miniature venturi pump is suitable for this application.