Nonlinear modeling of oral glucose tolerance test response to evaluate associations with aging outcomes.

As people age, their ability to maintain homeostasis in response to stressors diminishes. Physical frailty, a syndrome characterized by loss of resilience to stressors, is thought to emerge due to dysregulation of and breakdowns in communication among key physiological systems. Dynamical systems modeling of these physiological systems aims to model the underlying processes that govern response to stressors. We hypothesize that dynamical systems model summaries are predictive of age-related declines in health and function. In this study, we analyze data obtained during 75-gram oral-glucose tolerance tests (OGTT) on 1,120 adults older than 50 years of age from the Baltimore Longitudinal Study on Aging. We adopt a two-stage modeling approach. First, we fit OGTT curves with the Ackerman model-a nonlinear, parametric model of the glucose-insulin system-and with functional principal components analysis. We then fit linear and Cox proportional hazards models to evaluate whether usual gait speed and survival are associated with the stage-one model summaries. We also develop recommendations for identifying inadequately-fitting nonlinear model fits in a cohort setting with numerous heterogeneous response curves. These recommendations include: (1) defining a constrained parameter space that ensures biologically plausible model fits, (2) evaluating the relative discrepancy between predicted and observed responses of biological interest, and (3) identifying model fits that have notably poor model fit summary measures, such as [Formula: see text], relative to other fits in the cohort. The Ackerman model was unable to adequately fit 36% of the OGTT curves. The stage-two regression analyses found no associations between Ackerman model summaries and usual gait speed, nor with survival. The second functional principal component score was associated with faster gait speed (p<0.01) and improved survival (p<0.01).

Predictive modeling of multi-class diabetes mellitus using machine learning and filtering iraqi diabetes data dynamics.

Diabetes is a persistent metabolic disorder linked to elevated levels of blood glucose, commonly referred to as blood sugar. This condition can have detrimental effects on the heart, blood vessels, eyes, kidneys, and nerves as time passes. It is a chronic ailment that arises when the body fails to produce enough insulin or is unable to effectively use the insulin it produces. When diabetes is not properly managed, it often leads to hyperglycemia, a condition characterized by elevated blood sugar levels or impaired glucose tolerance. This can result in significant harm to various body systems, including the nerves and blood vessels. In this paper, we propose a multiclass diabetes mellitus detection and classification approach using an extremely imbalanced Laboratory of Medical City Hospital data dynamics. We also formulate a new dataset that is moderately imbalanced based on the Laboratory of Medical City Hospital data dynamics. To correctly identify the multiclass diabetes mellitus, we employ three machine learning classifiers namely support vector machine, logistic regression, and k-nearest neighbor. We also focus on dimensionality reduction (feature selection-filter, wrapper, and embedded method) to prune the unnecessary features and to scale up the classification performance. To optimize the classification performance of classifiers, we tune the model by hyperparameter optimization with 10-fold grid search cross-validation. In the case of the original extremely imbalanced dataset with 70:30 partition and support vector machine classifier, we achieved maximum accuracy of 0.964, precision of 0.968, recall of 0.964, F1-score of 0.962, Cohen kappa of 0.835, and AUC of 0.99 by using top 4 feature according to filter method. By using the top 9 features according to wrapper-based sequential feature selection, the k-nearest neighbor provides an accuracy of 0.935 and 1.0 for the other performance metrics. For our created moderately imbalanced dataset with an 80:20 partition, the SVM classifier achieves a maximum accuracy of 0.938, and 1.0 for other performance metrics. For the multiclass diabetes mellitus detection and classification, our experiments outperformed conducted research based on the Laboratory of Medical City Hospital data dynamics.

U-shaped association between fasting blood glucose and suicide attempts in Chinese patients with first-episode drug-naïve major depressive disorder.

BACKGROUND: Evidence regarding the relationship between fasting blood glucose (FBG) and suicide attempts (SA) in patients with major depressive disorder (MDD) was limited. Therefore, the objective of this research was to investigate whether FBG was independently related to SA in Chinese patients with first-episode drug-naïve (FEDN) MDD after adjusting for other covariates. METHODS: The present study was a cross-sectional study. A total of 1718 participants (average age: 34.9 ± 12.4 years, 65.8% females) with FEDN MDD were involved in a hospital in China from September 2016 to December 2018. Multiple logistic regression analysis and smooth curve fitting were used to estimate the association between FBG and the risk of SA. The threshold effect was examined by the two-piecewise linear regression model. Interaction and stratified analyses were conducted according to sex, education, marital status, comorbid anxiety, and psychotic symptoms. RESULTS: The prevalence of SA in patients with FEDN MDD was 20.1%. The result of fully adjusted binary logistic regression showed FBG was positively associated with the risk of SA (odds ratio (OR) = 1.62, 95% CI: 1.13-2.32). Smoothing plots also revealed a nonlinear relationship between FBG and SA, with the inflection point of FBG being 5.34 mmol/l. The effect sizes and the confidence intervals on the left and right sides of the inflection point were 0.53 (0.32-0.88, P = 0.014) and 1.48 (1.04-2.10, P = 0.030), respectively. CONCLUSIONS: A U-shaped relationship between FBG and SA in FEDN MDD patients was found, with the lowest risk of SA at a FBG of 5.34 mmol/l, indicating that both the lower and higher FBG levels may lead to an increased risk of SA.

Association of the triglyceride-glucose index and its related parameters with frailty.

BACKGROUND: Frailty is a dynamic geriatric condition. Limited studies have examined the association of the triglyceride-glucose (TyG) index and its related indicators [TyG index, triglyceride glucose-waist to height ratio (TyG-WHtR), triglyceride glucose-waist circumference (TyG-WC), and triglyceride glucose-body mass index (TyG-BMI)] with frailty, and the potential links among them remain unclear. On the basis of data from the National Health and Nutrition Examination Survey (NHANES), this study investigated the potential relationships of the TyG index and its related indices with frailty. METHODS: This research included 7,965 participants from NHANES 2003-2018. The relationship of the TyG index and its related indices with frailty was investigated with binary logistic regression analyses, restricted cubic spline (RCS), and receiver operating characteristic (ROC) curve. Potential influences were further investigated through stratified analyses and interaction tests. RESULTS: The prevalence of frailty in the participants of this study was 25.59%, with a average frailty index of 0.16 (0.00). In the three regression analysis models, the continuous TyG index and its associated indices were positively associated with frailty. In addition, quartiles of TyG, TyG-WC, TyG-WHtR, and TyG-BMI were significantly associated with increased frailty prevalence in the fully adjusted models (TyG Q4 vs. Q1, OR = 1.58, 95% CI: 1.19, 2.09, P = 0.002; TyG-WC Q4 vs. Q1, OR = 2.40, 95% CI: 1.90, 3.04, P < 0.001; TyG-WHtR Q4 vs. Q1, OR = 2.26, 95% CI: 1.82, 2.81, P < 0.001; TyG- BMI Q4 vs. Q1, OR = 2.16, 95% CI: 1.76, 2.64, P < 0.001). According to RCS analysis, TyG, TyG-WC, TyG-WHtR, and TyG-BMI were linearly and positively associated with frailty. ROC curves revealed that TyG-WHtR (AUC: 0.654) had greater diagnostic value for frailty than TyG (AUC: 0.604), TyG-BMI (AUC: 0.621), and TyG-WC (AUC: 0.629). All of the stratified analyses and interaction tests showed similar results. CONCLUSIONS: Elevated TyG and its associaed indices are associated with an increased prevalence of frailty. Reasonable control of blood glucose and blood lipids, and avoidance of obesity, may aid in reducing the occurrence of frailty in middle-aged and older adults.

Implementation research: a protocol for two three-arm pragmatic randomised controlled trials on continuous glucose monitoring devices in people with type 1 diabetes in South Africa and Kenya.

BACKGROUND: Self-monitoring of glucose is an essential component of type 1 diabetes (T1D) management. In recent years, continuous glucose monitoring (CGM) has provided an alternative to daily fingerstick testing for the optimisation of insulin dosing and general glucose management in people with T1D. While studies have been conducted to evaluate the impact of CGM on clinical outcomes in the US, Europe and Australia, there are limited data available for low- and middle-income countries (LMICs) and further empirical evidence is needed to inform policy decision around their use in these countries. METHODS: This trial was designed as a pragmatic, parallel-group, open-label, multicentre, three-arm, randomised (1:1:1) controlled trial of continuous or periodic CGM device use versus standard of care in people with T1D in South Africa and Kenya. The primary objective of this trial will be to assess the impact of continuous or periodic CGM device use on glycaemic control as measured by change from baseline glycosylated haemoglobin (HbA1c). Additional assessments will include clinical outcomes (glucose variation, time in/below/above range), safety (adverse events, hospitalisations), quality of life (EQ-5D, T1D distress score, Glucose Monitoring Satisfaction Survey for T1D), and health economic measures (incremental cost-effectiveness ratios, quality adjusted life years). DISCUSSION: This trial aims to address the substantial evidence gap on the impact of CGM device use on clinical outcomes in LMICs, specifically South Africa and Kenya. The trial results will provide evidence to inform policy and treatment decisions in these countries. TRIAL REGISTRATION: NCT05944731 (Kenya), July 6, 2023; NCT05944718 (South Africa), July 13, 2023.

Ultra rapid lispro improves postprandial glucose control versus lispro in combination with basal insulin: a study based on CGM in type 2 diabetes in China.

Aim: To evaluate the efficacy and safety of URLi (ultra rapid lispro insulin) compared to insulin lispro as bolus insulin with basal insulin using CGM in the individuals with type 2 diabetes(T2D) in China. Methods: This was a double-blind, randomized, parallel, prospective, phase 3 study. Subjects with uncontrolled T2D were recruited and randomized 1:2 into the insulin lispro and URLi groups. Subjects received a consistent basal insulin regimen during the study and self-administered insulin lispro or URLi before each meal throughout the treatment period. Subjects underwent a 3-day continuous glucose monitoring (CGM) at the baseline and endpoint respectively, and then CGM data were analyzed. The primary endpoint was to compare the difference in postprandial glucose (PPG) control using CGM between the two groups. Results: A total of 57 subjects with T2D completed the study. Our CGM data showed that postprandial glucose excursions after breakfast (BPPGE) in the URLi group was lower than that in the insulin lispro group (1.59 ± 1.57 mmol/L vs 2.51 ± 1.73 mmol/L, p = 0.046). 1-hour PPG was observed to decrease more in the URLi group than that in the insulin lispro group (-1.37 ± 3.28 mmol/L vs 0.24 ± 2.58 mmol/L, p = 0.047). 2-hour PPG was observed to decrease more in the URLi group than that in the insulin lispro group (-1.12 ± 4.00 mmol/L vs 1.22 ± 2.90 mmol/L, p = 0.021). The mean HbA1c level decreased by 1.1% in the URLi group and 0.99% in the insulin lispro group, with no treatment difference (p = 0.642). In the CGM profile, TBR was not significantly different between the two groups (p = 0.743). The weight gain also did not differ between the two groups (p = 0.303). Conclusion: URLi can control breakfast PPG better than insulin lispro in adults with T2D in China, while it is non-inferior in improving HbA1c. The incidence of hypoglycemic and weight gain were similar between the two groups.

Measuring the effectiveness of hybrid diabetes care over 90 days through continuous data monitoring in type 2 diabetic patients.

Background: Diabetes Mellitus, a global health challenge, affects 537 million individuals. Traditional management relies on periodic clinic visits, but technological advancements, including remote monitoring, offer transformative changes. Telemedicine enhances access, convenience, adherence, and glycemic control. Challenges include trust-building and limitations in face-to-face interactions. Integrating remote monitoring with in-person healthcare creates a hybrid approach. This study evaluates the impact on Type 2 Diabetes patients over 3 months. Methods: A retrospective case-control observational study. Inclusion criteria involved previous Type 2 Diabetes diagnosis and a minimum 3-month GluCare model period with two physical visits. Patients in the case group had in-clinic visits, bi-weekly app engagement, and monthly body weight readings. Control group had in-clinic visits only. Outcomes measured included HbA1c, lipid profile, CV risk, eGFR, urine Albumin/Creatinine Ratio, Uric Acid, and CRP. Results: Case group showed significant HbA1c improvements (-2.19%), especially in higher baseline levels. Weight, BMI, LDL, total cholesterol, and CVD risk also improved. Controls showed smaller improvements. Higher digital interactions correlated with better outcomes. Patients with ≥11 interactions showed significant reductions in HbA1c (-2.38%) and weight (-6.00 kg). Conclusion: The GluCare.Health hybrid model demonstrates promising outcomes in Type 2 diabetes management. The integration of in-clinic consultations with continuous remote monitoring leads to substantial improvements in glycemic control and clinical parameters. The study highlights the importance of patient engagement in achieving positive outcomes, with higher digital interactions associated with greater reductions in HbA1c and weight. The hybrid approach proves more effective than digital-only interventions, emphasizing the need for comprehensive, end-to-end solutions in diabetes care.

Early feasibility study with an implantable near-infrared spectroscopy sensor for glucose, ketones, lactate and ethanol.

OBJECTIVE: To evaluate the safety and performance of an implantable near-infrared (NIR) spectroscopy sensor for multi-metabolite monitoring of glucose, ketones, lactate, and ethanol. RESEARCH DESIGN AND METHODS: This is an early feasibility study (GLOW, NCT04782934) including 7 participants (4 with type 1 diabetes (T1D), 3 healthy volunteers) in whom the YANG NIR spectroscopy sensor (Indigo) was implanted for 28 days. Metabolic challenges were used to vary glucose levels (40-400 mg/dL, 2.2-22.2 mmol/L) and/or induce increases in ketones (ketone drink, up to 3.5 mM), lactate (exercise bike, up to 13 mM) and ethanol (4-8 alcoholic beverages, 40-80g). NIR spectra for glucose, ketones, lactate, and ethanol levels analyzed with partial least squares regression were compared with blood values for glucose (Biosen EKF), ketones and lactate (GlucoMen LX Plus), and breath ethanol levels (ACE II Breathalyzer). The effect of potential confounders on glucose measurements (paracetamol, aspartame, acetylsalicylic acid, ibuprofen, sorbitol, caffeine, fructose, vitamin C) was investigated in T1D participants. RESULTS: The implanted YANG sensor was safe and well tolerated and did not cause any infectious or wound healing complications. Six out 7 sensors remained fully operational over the entire study period. Glucose measurements were sufficiently accurate (overall mean absolute (relative) difference MARD of 7.4%, MAD 8.8 mg/dl) without significant impact of confounders. MAD values were 0.12 mM for ketones, 0.16 mM for lactate, and 0.18 mM for ethanol. CONCLUSIONS: The first implantable multi-biomarker sensor was shown to be well tolerated and produce accurate measurements of glucose, ketones, lactate, and ethanol. TRIAL REGISTRATION: Clinical trial identifier: NCT04782934.

Summary of clinical investigation plan for The DIATEC trial: in-hospital diabetes management by a diabetes team and continuous glucose monitoring or point of care glucose testing - a randomised controlled trial.

BACKGROUND: Worldwide, up to 20 % of hospitalised patients have diabetes mellitus. In-hospital dysglycaemia increases patient mortality, morbidity, and length of hospital stay. Improved in-hospital diabetes management strategies are needed. The DIATEC trial investigates the effects of an in-hospital diabetes team and operational insulin titration algorithms based on either continuous glucose monitoring (CGM) data or standard point-of-care (POC) glucose testing. METHODS: This is a two-armed, two-site, prospective randomised open-label blinded endpoint (PROBE) trial. We recruit non-critically ill hospitalised general medical and orthopaedic patients with type 2 diabetes treated with basal, prandial, and correctional insulin (N = 166). In both arms, patients are monitored by POC glucose testing and diabetes management is done by ward nurses guided by in-hospital diabetes teams. In one of the arms, patients are monitored in addition to POC glucose testing by telemetric CGM viewed by the in-hospital diabetes teams only. The in-hospital diabetes teams have operational algorithms to titrate insulin in both arms. Outcomes are in-hospital glycaemic and clinical outcomes. DISCUSSION: The DIATEC trial will show the glycaemic and clinical effects of in-hospital CGM handled by in-hospital diabetes teams with access to operational insulin titration algorithms in non-critically ill patients with type 2 diabetes. The DIATEC trial seeks to identify which hospitalised patients will benefit from CGM and in-hospital diabetes teams compared to POC glucose testing. This is essential information to optimise the use of healthcare resources before broadly implementing in-hospital CGM and diabetes teams. TRIAL REGISTRATION: Prospectively registered at ClinicalTrials.gov with identification number NCT05803473 on March 27th 2023.

Nonenzymatic dual glucose sensing on boronic acid modified zeolitic imidazolate framework-67 nanoparticles for diabetes management.

For early diabetes identification and management, the progression of an uncomplicated and exceedingly responsive glucose testing technology is crucial. In this study, we present a new sensor incorporating a composite of metal organic framework (MOF) based on cobalt, coated with boronic acid to facilitate selective glucose binding. Additionally, we successfully employed a highly sensitive electro-optical immunosensor for the detection of subtle changes in concentration of the diabetes biomarker glycated haemoglobin (HbA1c), using zeolitic imidazolate framework-67 (ZIF-67) coated with polydopamine which further modified with boronic acid. Utilizing the polymerization characteristics of dopamine and the NH2 groups, a bonding structure is formed between ZIF-67 and 4-carboxyphenylboronic acid. ZIF-67 composite served as an effective substrate for immobilising 4-carboxyphenylboronic acid binding agent, ensuring precise and highly selective glucose identification. The sensing response was evaluated through both electrochemical and optical methods, confirming its efficacy. Under optimized experimental condition, the ZIF-67 based sensor demonstrated a broad detection range of 50-500 mg dL-1, a low limit of detection (LOD) of 9.87 mg dL-1 and a high correlation coefficient of 0.98. Furthermore, the 4-carboxyphenylboronic acid-conjugated ZIF-67-based sensor platform exhibited remarkable sensitivity and selectivity in optical-based detection for glycated haemoglobin within the clinical range of 4.7-11.3%, achieving a LOD of 3.7%. These findings highlight the potential of the 4-carboxyphenylboronic acid-conjugated ZIF-67-based electro-optical sensor as a highly sensitive platform for diabetes detection.

Surrogate indices of insulin resistance using the Matsuda index as reference in adult men-a computational approach.

Background: Overweight and obesity, high blood pressure, hyperglycemia, hyperlipidemia, and insulin resistance (IR) are strongly associated with non-communicable diseases (NCDs), including type 2 diabetes, cardiovascular disease, stroke, and cancer. Different surrogate indices of IR are derived and validated with the euglycemic-hyperinsulinemic clamp (EHC) test. Thus, using a computational approach to predict IR with Matsuda index as reference, this study aimed to determine the optimal cutoff value and diagnosis accuracy for surrogate indices in non-diabetic young adult men. Methods: A cross-sectional descriptive study was carried out with 93 young men (ages 18-31). Serum levels of glucose and insulin were analyzed in the fasting state and during an oral glucose tolerance test (OGTT). Additionally, clinical, biochemical, hormonal, and anthropometric characteristics and body composition (DEXA) were determined. The computational approach to evaluate the IR diagnostic accuracy and cutoff value using difference parameters was examined, as well as other statistical tools to make the output robust. Results: The highest sensitivity and specificity at the optimal cutoff value, respectively, were established for the Homeostasis model assessment of insulin resistance index (HOMA-IR) (0.91; 0.98; 3.40), the Quantitative insulin sensitivity check index (QUICKI) (0.98; 0.96; 0.33), the triglyceride-glucose (TyG)-waist circumference index (TyG-WC) (1.00; 1.00; 427.77), the TyG-body mass index (TyG-BMI) (1.00; 1.00; 132.44), TyG-waist-to-height ratio (TyG-WHtR) (0.98; 1.00; 2.48), waist-to-height ratio (WHtR) (1.00; 1.00; 0.53), waist circumference (WC) (1.00; 1.00; 92.63), body mass index (BMI) (1.00; 1.00; 28.69), total body fat percentage (TFM) (%) (1.00; 1.00; 31.07), android fat (AF) (%) (1.00; 0.98; 40.33), lipid accumulation product (LAP) (0.84; 1.00; 45.49), leptin (0.91; 1.00; 16.08), leptin/adiponectin ratio (LAR) (0.84; 1.00; 1.17), and fasting insulin (0.91; 0.98; 16.01). Conclusions: The computational approach was used to determine the diagnosis accuracy and the optimal cutoff value for IR to be used in preventive healthcare.

Clinical variables influencing the severity of diabetes ketoacidosis.

OBJECTIVES: To evaluate clinical indicators in order to examine the intensity of diabetes ketoacidosis (DKA) episodes in children and adolescents diagnosed with type 1 diabetes mellitus (T1DM). METHODS: Data from 156 T1DM patients aged 6 months to 14 years, who presented with DKA to the emergency room, were retrospectively reviewed from 2018 to 2022. Data on demographic characteristics, economic status, initial clinical presentation, glycemic control, DKA severity, and laboratory evaluations were also collected. RESULTS: Diabetes ketoacidosis episodes were more prevalent among male patients during the middle childhood age group. Notably, these episodes displayed seasonal patterns. The severity was found to be inversely associated with economic status and positively correlated with early adolescence. Newly diagnosed T1DM patients constituted 52.9%, with a statistically significant connection observed between severe DKA and this subgroup. Furthermore, there was a significant escalation in poor glycemic control with episode severity. Prolonged episode duration also exhibited a statistically significant association with more severity. Gastrointestinal symptoms were commonly reported during the presentation. Moreover, several clinical signs and symptoms, including decreased consciousness, reduced activity, drowsiness, Kussmaul breathing, shortness of breath, vomiting, tachycardia, and severe dehydration, were significantly correlated with the severity of DKA (p<0.05). Hypernatremia was more frequent among children with severe DKA. CONCLUSION: Diabetes ketoacidosis was observed to occur more frequently among males in middle childhood with seasonal variations. Furthermore, the severity of DKA was associated with lower economic status, early adolescence, and the presence of hypernatremia.

Study of Glycemic Variability in Well-controlled Type 2 Diabetic Patients Using Continuous Glucose Monitoring System.

INTRODUCTION: The world has changed tremendously for patients suffering from diabetes mellitus with the development of cutting-edge technologies like continuous glucose monitoring and flash glucose monitoring systems. Now, the details of constant fluctuations of glucose in their blood can be monitored not only by medical professionals but also by patients, and this is called glycemic variability (GV). Traditional metrics of glycemic control measurement, such as glycated hemoglobin (HbA1c), fail to reflect various short-term glycemic changes like postprandial hyperglycemia and hypoglycemic episodes, paving the way to the occurrence of various diabetic complications even in asymptomatic, well-controlled diabetic patients. This need for advanced management of diabetes and effective monitoring of these swings in blood glucose can be met by using a continuous glucose monitoring system (CGMS). AIM AND OBJECTIVE: To evaluate the extent of GV in well-controlled type 2 diabetes mellitus (T2DM) patients using a flash CGMS and to assess the correlation between GV and HbA1c. MATERIALS AND METHODS: A hospital-based prospective observational study was carried out from May 2020 to Oct 2021 at the Department of Medicine, SMS Hospital, Jaipur, Rajasthan (India), after approval from the Ethics Committee of the institution. A total of 30 patients with well-controlled T2DM (HbA1c was ≥6.5, but ≤7.5) were included in the study using simple random techniques after written informed consent from patients. Patients were studied for glycemic excursions over a period of 7 days by using FreeStyle® Libre Pro™, which is a flash glucose monitoring system. The CGM sensor was attached to the left upper arm of the patient on day 0 and removed on day 7. The data recorded in the sensor was then retrieved using pre-installed computer software and analyzed using standard CGM metrics like standard deviation (SD), percentage coefficient of variation (%CV), time above range (TAR), time below range (TBR), and time in range (TIR), out of which %CV was used to quantify GV. %CV has been used to cluster patients into four cohorts from best to worst, namely: best/low CV ≤ 10%, intermediate CV from 10 to 20%, high CV from 20 to 30%, and very high CV of >30%. Scatterplots are used to establish correlations between various parameters. RESULT: Data from a total of 30 patients were analyzed using CGMS and thus used for calculating standard CGM metrics; glucose readings every 15 minutes were recorded consecutively for 7-day periods, making it a total of 672 readings for each patient. Interpreting the CGM data of all 30 patients, the following results were found: the mean blood glucose of all cases is 134.925 ± 22.323 mg/dL, the mean SD of blood glucose of all cases is 35.348 ± 9.388 mg/dL, the mean of %CV of all cases is 26.376 ± 6.193%. CGM parameters of time are used in the form of percentages, and the following results were found: the mean of TAR, TBR, and TIR is 14.425 ± 13.211, 5.771 ± 6.808, and 82.594 ± 12.888%, respectively. Clustering the patients into cohorts, the proportion of patients exhibiting best/low %CV (10%) is 0, intermediate %CV (10-20%) is 16.67% (five out of 30 patients), high %CV (20-30%) is 50% (15 out of 30 patients) and very high %CV (>30%) is 33.33% (10 out of 30 patients). Also, there is no significant correlation found between HbA1c and %CV (ρ = 0.076, p-value = 0.690); a significant negative correlation was found between %CV and TIR (ρ = -0.604, p < 0.001S); a positive correlation of %CV with TAR and TBR is significant (ρ = 0.816, p-value of <0.001). CONCLUSION: Using a flash CGMS device and considering %CV as the parameter and primary measure of GV, the study demonstrated the overall instability of a person's glycemic control, making note of unrecognized events of hypoglycemia and hyperglycemia in asymptomatic well-controlled T2DM patients, revealing the overall volatile glycemic control. The most important finding of this study is that even those diabetics who are considered well-controlled experience a great degree of GV as assessed by CGM-derived metrics. This study also demonstrated that there is no significant correlation between HbA1c and GV, suggesting that patients may not have optimal control of their diabetes despite having "normal HbA1c" values; hence, GV can be considered an HbA1c-independent danger factor, having more harmful effects than sustained hyperglycemia in the growth of diabetic complications. So, by using CGM-derived metrics, the measurement of GV has the potential to complement HbA1c data. In this manner, a more comprehensive assessment of glycemic excursions can be provided for better treatment decisions, thereby facilitating optimal glycemic control, which is essential for reducing overall complications and promoting good quality of life.

Randomized, Double-blind, Phase III Trial of Lobeglitazone Add-on to Metformin in Type 2 Diabetes (SENSITIZE INDIA).

BACKGROUND: The efficacy and safety of lobeglitazone sulfate has been reported only in the Korean population, and no study has been conducted in India. MATERIALS AND METHODS: In this 16-week randomized, double-blind, and multicenter study, the efficacy and safety of lobeglitazone sulfate 0.5 mg were evaluated with pioglitazone 15 mg. Type 2 diabetes mellitus (T2DM) patients with ≥7.5% glycated hemoglobin (HbA1c) ≤10.5% and on stable metformin dose were assigned to both treatment arms. The primary outcome was a mean change in HbA1c. Safety assessments included adverse events (AE), home-based glucose monitoring, vital parameters, electrocardiogram (ECG), and laboratory assessments. RESULTS: A total of 328 subjects were randomized equally in two groups. A statistically significant reduction in HbA1c at week 16 in the lobeglitazone group with the least square (LS) mean change: 1.01 [standard error (SE): 0.09] (p < 0.0001) was seen. The LS mean difference between the two groups was 0.05 (SE: 0.12) [95% confidence interval (CI): -0.18, 0.27], which was statistically significant (p = 0.0013). Statistically significant reductions were also observed in fasting and postprandial glucose. Treatment-emergent Aes (TEAE) were comparable between both groups. CONCLUSION: Lobeglitazone 0.5 mg once daily was found to be efficacious and safe in the treatment of T2DM in the Indian population. Lobeglitazone significantly improved glycemic parameters and was noninferior to pioglitazone; hence, it could be a promising insulin sensitizer in T2DM management in India.

Efficacy of Triglyceride Glucose Index-Neck Circumference and Triglyceride Glucose Index-Neck-to-Height Ratio in the Diagnosis of Cardiovascular Diseases and Metabolic Syndrome.

BACKGROUND: A group of characteristics known as metabolic syndrome raises the chance of developing diabetes and cardiovascular disease. Insulin resistance (IR) and obesity are regarded as critical metabolic syndrome pathophysiology. OBJECTIVES: The diagnostic accuracy of IR indicators, triglyceride (TG) glucose index-neck circumference (TyG-NC), and TG glucose index-neck-to-height ratio (TyG-NHtR) to be evaluated for the detection of cardiovascular diseases and metabolic syndrome in nondiabetic individuals. MATERIALS AND METHODS: A cross-sectional study was conducted and passed by the Ethics Committee of the institute. The age should be 18 years or older, and subjects should not have diabetes. Each patient's clinical information was gathered, and lab tests were run. The study was done for a period of 1 year. RESULTS: The study has 100 participants. Around 74% of the group was women. Only 26.5% of the group had an obesity diagnosis. Poor fasting plasma glucose levels were found in 19.4% of the research team. Receiver operating characteristic (ROC)-area under the curve (AUC) testing revealed that all examined IR indices can differentiate individuals with metabolic syndrome from those who are healthy. Our analysis laid out the soaring high area under the ROC curve for TyG index and the low stunted area under the ROC curve for TyG-NC. For obesity, all indices showed appreciable diagnostic efficacy, indicating the maximum achieved area under the ROC curve for TyG index and the minimum recorded metabolic score for IR. The AUC in the case of the metabolic score for IR (METS-IR) male sample population was found to be not statistically compelling. CONCLUSION: The exploration of indirect indices, the proposed ones, namely TyG-NC and TyG-NHtR, emphasized an intricate link between cardiovascular diseases and metabolic syndrome.

A Study of Relationships between the HbA1c Level and Inflammatory Markers, Neutrophil-to-Lymphocyte Ratio, and Monocyte-to-Lymphocyte Ratio in Controlled and Uncontrolled Type 2 Diabetes Mellitus.

AIM AND OBJECTIVE: To assess the relationship between glycated hemoglobin (HbA1c) with inflammatory markers, neutrophil-to-lymphocytes ratio (NLR), and monocyte-to-lymphocytes ratio (MLR) in controlled and uncontrolled type 2 diabetes patients. MATERIALS AND METHODS: This was a hospital-based cross-sectional study conducted at the Department of Medicine, SMS Hospital, and an attached group of hospitals (Jaipur, Rajasthan, India) after informed consent from the Ethics Committee of the institute. After obtaining informed consent from patients who met the inclusion and exclusion criteria, 200 diabetic patients were included in the study using the simple randomization method. Following a detailed history and diagnosis, vital demographic information, and blood tests were collected from patients via a predesigned preliminary questionnaire. The following blood tests were collected: white blood cell (WBC), Hb, hematocrit (HCT), red cell distribution width (RDW), neutrophils, lymphocytes, HbA1c, blood glucose, NLR ratio, and MLR ratio. Data were entered and analyzed using Statistical Package for the Social Sciences version 22. RESULTS: The mean age of patients with controlled diabetes mellitus was 54.10 years, while that of patients with uncontrolled diabetes mellitus was 55.3 years. Glycemic control was more in the age group of 51-60 years. Around 54% of males and 46% of females were included in the present study, and no association was found between the two genders with poor and good glycemic control. Around 63.29% of participants with uncontrolled diabetes have an increased NLR, and 61.39% of participants with uncontrolled diabetes have an increased MLR. A strong association was found between the NLR and MLR with the glycemic control. CONCLUSION: Uncontrolled diabetes mellitus had a positive association with inflammatory markers, that is, NLR and MLR. STATEMENT OF SIGNIFICANCE: Diabetes mellitus is the most common metabolic disorder in Asian countries. It leads to many acute and chronic complications in uncontrolled diabetes. Markers like the NLR ratio and MLR ratio are inexpensive and easily available for blood investigation. Hence, these markers are quite useful in differentiating controlled and uncontrolled diabetes and, therefore, useful in predicting blood sugar control in type 2 diabetes mellitus.

Acute pharmacodynamic responses to sitagliptin: Drug-induced increase in early insulin secretion in oral glucose tolerance test.

DPP4 inhibitors are widely prescribed as treatments for type 2 diabetes. Because drug responses vary among individuals, we initiated investigations to identify genetic variants associated with the magnitude of drug responses. Sitagliptin (100 mg) was administered to 47 healthy volunteers. Several endpoints were measured to assess clinically relevant responses - including the effect of sitagliptin on glucose and insulin levels during an oral glucose tolerance test (OGTT). This pilot study confirmed that sitagliptin (100 mg) decreased the area under the curve for glucose during an OGTT (p = 0.0003). Furthermore, sitagliptin promoted insulin secretion during the early portion of the OGTT as reflected by an increase in the ratio of plasma insulin at 30 min divided by plasma insulin at 60 min (T30:T60) from mean ± SEM 0.87 ± 0.05 to 1.62 ± 0.36 mU/L (p = 0.04). The magnitude of sitagliptin's effect on insulin secretion (as judged by the increase in the T30:T60 ratio for insulin) was correlated with the magnitude of sitagliptin-induced increase in the area under the curve for intact plasma GLP1 levels during the first hour of the OGTT. This study confirmed previously reported sex differences in glucose and insulin levels during an OGTT. Specifically, females exhibited higher levels of glucose and insulin at the 90-180 min time points. However, we did not detect significant sex-associated differences in the magnitude of sitagliptin-induced changes in T30:T60 ratios for either glucose or insulin. In conclusion, T30:T60 ratios for insulin and glucose during an OGTT provide useful indices to assess pharmacodynamic responses to DPP4 inhibitors.

The reliability of using gingival crevicular blood to measure blood glucose and hba1c levels in the dental setting: a systematic review and meta-analysis.

OBJECTIVE: There are 500 million patients living with diabetes mellitus worldwide and 50% of them remain undiagnosed. Routine periodontal probing provides gingival crevicular blood in patients with gingivitis. Gingival blood may be useful for diabetes screening without the need for any expensive, painful or time-consuming method by using convenient glucometers. Therefore, the objective of this systematic review and meta-analysis is to answer the question to "is there a difference in glucose or HbA1c levels (O) in patients with positive gingival bleeding (P) measured on gingival crevicular blood (GCB) (I) compared to finger prick capillary blood (CB) (C). MATERIALS AND METHODS: The authors performed an electronic search of six databases using identical MeSH phrases. Only human clinical studies without limitations on the year of publication were considered. Data extraction was done by using standardized data collection sheets. Risk of bias assessment were conducted using QUADAS-2 and QUADAS-C. Meta-analyses were carried out with the random effects model to aggregate the correlation coefficients and the difference between the means between gingival and capillary blood reading, using 95% confidence intervals. RESULTS: The database and manual search yielded 268 articles, from which the selection procedure provided 36 articles for full-text screening, and the final pool of eligible articles composed of 23 studies with 1680 patients. Meta-analysis results on glycemic levels showed differences between the GCB and CB procedures in patients with and without diabetes with values of -6.80 [-17.35; 3.76] and - 4.36 [-9.89; 1.18], respectively. Statistically significant correlations were found (p = 0.001) between GCB and CB measurements in patients with (0.97 [0.927; 0.987]) and without diabetes (0.927 [0.873; 0.958]). CONCLUSION: Gingival blood could prove to be useful to identify patients with undiagnosed diabetes when the necessary amount of uncontaminated blood is present. However, this technique is limited by the possibility of contamination, prandial status and inaccuracies, so it is unsuited to address the patient's glycemic control accurately.

TYG Index as a Novel Predictor of Clinical Outcomes in Advanced Chronic Heart Failure with Renal Dysfunction Patients.

Background: The triglyceride-glucose (TYG) index is a novel and reliable marker reflecting insulin resistance. Its predictive ability for cardiovascular disease onset and prognosis has been confirmed. However, for advanced chronic heart failure (acHF) patients, the prognostic value of TYG is challenged due to the often accompanying renal dysfunction (RD). Therefore, this study focuses on patients with aHF accompanied by RD to investigate the predictive value of the TYG index for their prognosis. Methods and Results: 717 acHF with RD patients were included. The acHF diagnosis was based on the 2021 ESC criteria for acHF. RD was defined as the eGFR < 90 mL/(min/1.73 m2). Patients were divided into two groups based on their TYG index values. The primary endpoint was major adverse cardiovascular events (MACEs), and the secondary endpoints is all-cause mortality (ACM). The follow-up duration was 21.58 (17.98-25.39) months. The optimal cutoff values for predicting MACEs and ACM were determined using ROC curves. Hazard factors for MACEs and ACM were revealed through univariate and multivariate COX regression analyses. According to the univariate COX regression analysis, high TyG index was identified as a risk factor for MACEs (hazard ratio = 5.198; 95% confidence interval [CI], 3.702-7.298; P < 0.001) and ACM (hazard ratio = 4.461; 95% CI, 2.962-6.718; P < 0.001). The multivariate COX regression analysis showed that patients in the high TyG group experienced 440.2% MACEs risk increase (95% CI, 3.771-7.739; P < 0.001) and 406.2% ACM risk increase (95% CI, 3.268-7.839; P < 0.001). Kaplan-Meier survival analysis revealed that patients with high TyG index levels had an elevated risk of experiencing MACEs and ACM within 30 months. Conclusion: This study found that patients with high TYG index had an increased risk of MACEs and ACM, and the TYG index can serve as an independent predictor for prognosis.

Correspondence to "association of sleep patterns and cardiovascular disease risk is modified by glucose tolerance status".

After reading the article written by Wang et al., we have encountered several concerns that may compromise the credibility of the article. There are some factors, such as changes in sleep patterns, glucose tolerance status, and the use of hypnotics, which may interfere with the research results. Additionally, the design of the sleep pattern could lead to biased outcomes. Therefore, we are writing this letter to recommend that further research should take these concerns into consideration.