Continuous glycemic monitoring in managing diabetes in adult patients with wolfram syndrome.

AIMS: In this study we evaluated the use of Continuous Glucose Monitoring system in adults with insulin-dependent diabetes in the course of Wolfram syndrome (WFS) in comparison to patients with type 1 diabetes (T1D). METHODS: Individuals with WFS (N = 10) used continuous glucose monitoring for 14 days and were compared with 30 patients with T1D matched using propensity score for age and diabetes duration. Glycemic variability was calculated with Glyculator 3.0. RESULTS: We revealed significant differences in glycemic indices between adults with Wolfram syndrome-related diabetes and matched comparison group. Patients with Wolfram syndrome presented lower mean glucose in 24-h and nighttime records [24h: 141.1 ± 30.4mg/dl (N = 10) vs 164.9 ± 31.3mg/dl (N = 30), p = 0.0427; nighttime: 136.7 ± 39.6mg/dl vs 166.2 ± 32.1mg/dl (N = 30), p = 0.0442]. Moreover, they showed lower standard deviation of sensor glucose over all periods [24h: 50.3 ± 9.2mg/dl (N = 10) vs 67.7 ± 18.7 mg/dl (N = 30), p = 0.0075; daytime: 50.8 ± 8.7mg/dl (N = 10) vs 67.4 ± 18.0mg/dl (N = 30), p = 0.0082; nighttime: 45.1 ± 14.9mg/dl (N = 10) vs 65.8 ± 23.2mg/dl (n = 30), p = 0.0119] and coefficient of variation at night [33.3 ± 5.8% (N = 10) vs 40.5 ± 8.8% (N = 30), p = 0.0210]. Additionally, WFS patients displayed lower time in high-range hyperglycemia (> 250mg/dl) across all parts of day [24h: 4.6 ± 3.8% (N = 10) vs 13.4 ± 10.5% (N = 30), p = 0.0004; daytime: 4.7 ± 3.9% (N = 10) vs 13.8 ± 11.2% (N = 30), p = 0.0005; nighttime: 4.2 ± 5.5% (N = 10) vs 12.1 ± 10.3% (N = 30), p = 0.0272]. CONCLUSIONS: Adult patients with Wolfram syndrome show lower mean blood glucose, less extreme hyperglycemia, and lower glycemic variability in comparison to patients with type 1 diabetes.

Glycemic variability in chronic calcific pancreatitis with diabetes mellitus and its possible determinants.

AIMS: To study glycemic patterns and variability in patients with pancreatic diabetes or type 3c Diabetes mellitus (DM) due to chronic pancreatitis and its subtypes and assess the role of pancreatic enzyme replacement therapy (ERT) in modulating glycemic variability. METHODS: Patients having type 3c DM due to chronic pancreatitis, and on insulin underwent Flash continuous-glucose-monitoring (CGM) for 14 days. Parameters were compared between patients with fibrocalculous pancreatic diabetes (FCPD) and non-FCPD-chronic calcific pancreatitis (non-FCPD) and between the recipients and non-recipients of pancreatic enzyme-replacement-therapy (ERT). RESULTS: Out of 54 patients with pancreatic diabetes, 35 patients had chronic calcific pancreatitis. They underwent CGM, median HbA1c 9.20 % (77 mmol/mol) and mean Time-In-Range (TIR) being 41.21 % (23.48). Only 5 (15.2 %) patients achieved target TIR>70 % while 16 (48.5 %) patients had high glycemic-variability [Coefficient-of-variation (CV) > 36 %]. Patients with FCPD (n = 14) had higher hypoglycemia-indices like Time-Below-Range (18.92 % vs 8.20 %; p = 0.03) and Low-Blood-Glucose-Index (18.14 % vs 6.04 %; p = 0.02) compared to non-FCPD (n = 21). HbA1c% and hyperglycemic excursions were similar in both groups. Recipients of ERT (n = 20) had lower glycemic-variability [Standard Deviation (SD) 52.15 % vs 68.14 % and CV 32.59 % vs 41.79 %, p < 0.05 for both) than non-recipients. ERT-recipients had no serious hypoglycemia within the 14 days. On subgroup analysis, lower glycemic-variability and hypoglycemia with ERT were seen only in FCPD but not in non-FCPD subgroup (50.13 vs 77.91, 30.09 vs 48.36 for SD and CV respectively, p < 0.05). CONCLUSION: Patients with type 3c DM due to chronic pancreatitis have high frequency of hyperglycemic and hypoglycemic excursions, with those with FCPD having a particularly higher risk of hypoglycemia and glycemic-variability. Those receiving pancreatic ERT had lesser glycemic variability and hypoglycemia. The small sample size and lack of objective markers of documentation of exocrine pancreatic insufficiency like fecal elastase highlight the need for further larger studies in this field.

Continuous glucose monitoring versus conventional glucose monitoring in the ICU: A randomized controlled trial.

PURPOSE: This study evaluated the clinical utility of continuous glucose monitoring system (CGMS) in critically ill patients. METHODS: In this randomized controlled trial, we randomly assigned critically ill participants with diabetes or stress-induced hyperglycemia to the CGMS group (n = 48) or to the conventional point-of-care monitoring (POCM) group (n = 48). The glucose values and clinical outcome were compared between the two group. The primary endpoint was 28-day mortality after intensive care unit admission. RESULTS: The 28-day mortality was not significantly different between the CGMS and POCM group (20.8% vs 31.3%, P = 0.25). The mean glucose, time-weighted average glucose, glucose standard deviation and time in range (3.9-10.0) were significantly improved in the CGMS group (all P < 0.05). CONCLUSION: Compared with conventional POCM, CGMS did not decrease the 28-day mortality in critically ill participants with diabetes or stress-induced hyperglycemia. But CGMS may improve the glycemic control and may be increasingly used in critically ill patients.

Observational study on stability of within-day glycemic variability of type 2 diabetes inpatients treated with decoctions of traditional Chinese medicine.

Background: Within-day glycemic variability (GV), characterized by frequent and significant fluctuations in blood glucose levels, is a growing concern in hospitalized patients with type 2 diabetes mellitus (T2DM). It is associated with an increased risk of hypoglycemia and potentially higher long-term mortality rates. Robust clinical evidence is needed to determine whether traditional Chinese medicine (TCM) decoctions can be a beneficial addition to the management of within-day GV in this patient population. Methods: This retrospective cohort study utilized data from adult inpatients diagnosed with T2DM admitted to the Traditional Chinese Medicine Hospital of Kaifeng. The primary outcome investigated was the association between the use of TCM decoctions and improved stability of within-day GV. Blood glucose variability was assessed using the standard deviation of blood glucose values (SDBG). For each patient, the total number of hospitalization days with SDBG below 2 mmol/L was calculated to represent within-day GV stability. Hospitalization duration served as the secondary outcome, compared between patients receiving TCM decoctions and those who did not. The primary analysis employed a multivariable logistic regression model, with propensity score matching to account for potential confounding variables. Results: A total of 1,360 patients were included in the final analysis. The use of TCM decoctions was significantly associated with enhanced stability of within-day GV (OR = 1.77, 95% CI: 1.34-2.33, P < 0.01). This association was most prominent in patients with a diagnosis of deficiency syndrome (predominantly qi-yin deficiency, accounting for 74.8% of cases) and a disease duration of less than 5 years (OR = 2.28, 95% CI: 1.21-4.29, P = 0.03). However, TCM decoctions did not exert a statistically significant effect on hospitalization duration among patients with T2DM (OR = 0.96, 95% CI: 0.91-1.01, P = 0.22). Conclusion: This study suggests that TCM decoctions may be effective in improving within-day GV stability in hospitalized patients with T2DM. This effect appears to be most pronounced in patients diagnosed with deficiency syndrome, particularly those with qi-yin deficiency and a shorter disease course. Further investigation is warranted to confirm these findings and elucidate the underlying mechanisms.

Glycemic variability through the perspective of the glycemia risk index and time in range and their association with glycated hemoglobin A1c in pediatric patients on sensor-augmented pump therapy.

Introduction: From the introduction of continuous glucose monitoring (CGM) in treatments of type 1 diabetes, particularly its integration with insulin pumps, there has been a quest for new parameters that describe optimal glycemic control. As of the consensus reached in 2019, the ambulatory glucose profile (AGP) has become the standard, with time in range (TIR) emerging as a fundamental parameter for metabolic control assessment. However, with technological advancements, new parameters, such as the glycemia risk index (GRI), have been introduced and clinically utilized. Therefore, exploring the relationships between traditional and novel parameters to understand metabolic control comprehensively is imperative. Materials and methods: This study was conducted at the Pediatric Clinic of the University Hospital of the Republic of Srpska Banja Luka between January and July 2023. The participants were randomly selected, with the inclusion criteria specifying an age greater than eight years and a diabetes type 1 duration exceeding two years. All participants were required to use a sensor-augmented insulin pump for the next three months (90 days), irrespective of prior use, with the suspend-before-low option activated. Results: Of the 35 participants, 30 completed the study, 14 (46.7%) of whom were male. The mean age of the subjects was 14.90 ± 2.88 years, and the mean duration of diabetes was 7.83 ± 4.76 years. Over the 90-day period, HbA1c increased to an average of 7.31%. The analysis revealed significant effects of TIR (ß=-0.771) and GRI (ß=0.651) on HbA1c. Furthermore, GRI and TIR strongly correlated (ß=-0.953). Discussion and conclusion: New parameters generated from the ambulatory glucose profile (AGP) can help clinicians create a complete picture of a patient's metabolic control in relation to HbA1c levels. Additionally, the GRI is a mathematically tailored parameter that incorporates all components of the ambulatory glucose profile and demonstrates strong correlations with laboratory-measured HbA1c and TIR. The GRI potentially can become a valuable statistical parameter for evaluating and managing patients in routine clinical practice.

Comparison of admission glycemic variability and glycosylated hemoglobin in predicting major adverse cardiac events among type 2 diabetes patients with heart failure following acute ST-segment elevation myocardial infarction.

Background and Objectives: Hyperglycemia is associated with adverse outcomes in patients with acute myocardial infarction (AMI) as well as in patients with heart failure. However, the significance of admission glycemic variability (GV) in predicting outcomes among diabetes patients with heart failure (HF) following acute ST-segment elevation myocardial infarction (ASTEMI) remains unclear. This study aims to explore the prognostic value of admission GV and admission glycosylated hemoglobin (HbA1c) levels in individuals diagnosed with type 2 diabetes and HF following ASTEMI. Methods: We measured GV and HbA1c upon admission in 484 consecutive patients diagnosed with type 2 diabetes and HF following ASTEMI. GV, indicated as the mean amplitude of glycemic excursions (MAGE), was assessed utilizing a continuous glucose monitoring system (CGMS). admission MAGE values were categorized as < 3.9 or ≥ 3.9 mmol/L, while HbA1c levels were classified as < 6.5 or ≥ 6.5%. Participants were followed up prospectively for 12 months. The relationship of admission MAGE and HbA1c to the major adverse cardiac event (MACE) of patients with type 2 diabetes and HF following ASTEMI was analyzed. Results: Among the 484 enrolled patients, the occurrence of MACE differed significantly based on MAGE categories (< 3.9 vs. ≥ 3.9 mmol/L), with rates of 13.6% and 25.3%, respectively (P = 0.001). While MACE rates varied by HbA1c categories (< 6.5 vs. ≥ 6.5%) at 15.7% and 21.8%, respectively (P = 0.086). Patients with higher MAGE levels exhibited a notably elevated risk of cardiac mortality and an increased incidence of HF rehospitalization. The Kaplan-Meier curves analysis demonstrated a significantly lower event-free survival rate in the high MAGE level group compared to the low MAGE level group (log-rank test, P < 0.001), while HbA1c did not exhibit a similar distinction. In multivariate analysis, high MAGE level was significantly associated with incidence of MACE (hazard ratio 3.645, 95% CI 1.287-10.325, P = 0.015), whereas HbA1c did not demonstrate a comparable association (hazard ratio 1.075, 95% CI 0.907-1.274, P = 0.403). Conclusions: Elevated admission GV emerges as a more significant predictor of 1-year MACE in patients with type 2 diabetes and HF following ASTEMI, surpassing the predictive value of HbA1c.

Continuous Glucose Monitoring Captures Glycemic Variability After Roux-en-Y Gastric Bypass in Patients with and Without Type 2 Diabetes Mellitus: A Prospective Cohort Study.

PURPOSE: To evaluate glycemic variability (GV) using continuous glucose monitoring (CGM) in individuals with and without type 2 diabetes mellitus (T2DM) undergoing Roux-en-Y gastric bypass (RYGB). METHODS: This prospective cohort study compared the CGM data of fourteen patients with T2DM (n = 7) and without T2DM (n = 7) undergoing RYGB. After 6 months, these patients were compared to a non-operative control group (n = 7) matched by BMI, sex, and age to the T2DM group. RESULTS: Fourteen patients underwent RYGB, with a mean BMI of 46.9 ± 5.3 kg/m2 and an average age of 47.9 ± 8.9 years; 85% were female. After 6 months post-surgery, the total weight loss (TWL) was 27.1 ± 6.3%, with no significant differences between the groups. Patients without diabetes had lower mean interstitial glucose levels (81 vs. 94 and 98 mg/dl, p < 0.01) and lower glucose management indicator (GMI) (5.2 vs. 5.6 and 5.65%, p = 0.01) compared to the control and T2DM groups, respectively. The coefficient of variation (CV) significantly increased only in patients with diabetes (17% vs. 26.7%, p < 0.01). Both groups with (0% vs. 2%, p = 0.03) and without (3% vs. 22%, p = 0.03) T2DM experienced an increased time below range with low glucose (54-69 mg/dL). However, patients without T2DM had significantly less time in rage (70-180 mg/dL) (97% vs. 78%, p = 0.04). CONCLUSION: Significant differences in CGM metrics among RYGB patients suggest an increase in glycemic variability after surgery, with a longer duration of hypoglycemia, especially in patients without T2DM.

Current landscape and comprehensive management of glycemic variability in diabetic retinopathy.

Diabetic retinopathy (DR), a well-known microvascular complication of diabetes mellitus, remains the main cause of vision loss in working-age adults worldwide. Up to now, there is a shortage of information in the study regarding the contributing factors of DR in diabetes. Accumulating evidence has identified glycemic variability (GV), referred to fluctuations of blood glucose levels, as a risk factor for diabetes-related complications. Recent reports demonstrate that GV plays an important role in accounting for the susceptibility to DR development. However, its exact role in the pathogenesis of DR is still not fully understood. In this review, we highlight the current landscape and relevant mechanisms of GV in DR, as well as address the mechanism-based therapeutic strategies, aiming at better improving the quality of DR management in clinical practice.

Diabetes Telemedicine Mediterranean Diet (DiaTeleMed) Study: study protocol for a fully remote randomized clinical trial evaluating personalized dietary management in individuals with type 2 diabetes.

Background: The Diabetes Telemedicine Mediterranean Diet (DiaTeleMed) Study is a fully remote randomized clinical trial evaluating personalized dietary management in individuals with type 2 diabetes (T2D). The study aims to test the efficacy of a personalized behavioral approach for dietary management of moderately-controlled T2D, versus a standardized behavioral intervention that uses one-size-fits-all dietary recommendations, versus a usual care control (UCC). The primary outcome will compare the impact of each intervention on the mean amplitude of glycemic excursions (MAGE). Methods: Eligible participants are between 21 to 80 years of age diagnosed with moderately-controlled T2D (HbA1c: 6.0-8.0%), and managed on lifestyle alone or lifestyle plus metformin. Participants must be willing and able to attend virtual counseling sessions and log meals into a dietary tracking smartphone application (DayTwo), and wear a continuous glucose monitor (CGM) for up to 12 days. Participants are randomized with equal allocation (n = 255, n = 85 per arm) to one of three arms: 1) Personalized, 2) Standardized, or 3) UCC. Measurements occur at 0 (baseline), 3, and 6 months. All participants receive isocaloric energy and macronutrients targets to meet Mediterranean diet guidelines plus 14 intervention contacts over 6 months (4 weekly then 10 biweekly) to cover diabetes self-management education. The first 4 UCC intervention contacts are delivered via synchronous videoconferences followed by educational video links. Participants in Standardized receive the same education content as UCC on the same schedule. However, all intervention contacts are conducted via synchronous videoconferences, paired with Social Cognitive Theory (SCT)-based behavioral counseling, plus dietary self-monitoring of planned meals using a mobile app that provides real-time feedback on calories and macronutrients. Participants in the Personalized arm receive all elements of the Standardized intervention, plus real-time feedback on predicted post-prandial glycemic response (PPGR) to meals and snacks logged into the mobile app. Discussion: The DiaTeleMed study will address an important gap in the current landscape of precision nutrition by determining the contributions of behavioral counseling and personalized nutrition recommendations on glycemic control in individuals with T2D. The fully remote methodology of the study allows for scalability and innovative delivery of personalized dietary recommendations at a population level. Trial registration: The DiaTeleMed Study is registered with ClinicalTrials.gov (Identifier: NCT05046886).

Diabetes Telemedicine Mediterranean Diet (DiaTeleMed) Study: study protocol for a fully remote randomized clinical trial evaluating personalized dietary management in individuals with type 2 diabetes.

BACKGROUND: The Diabetes Telemedicine Mediterranean Diet (DiaTeleMed) Study is a fully remote randomized clinical trial evaluating personalized dietary management in individuals with type 2 diabetes (T2D). The study aims to test the efficacy of a personalized behavioral approach for dietary management of moderately controlled T2D, versus a standardized behavioral intervention that uses one-size-fits-all dietary recommendations, versus a usual care control (UCC). The primary outcome will compare the impact of each intervention on the mean amplitude of glycemic excursions (MAGE). METHODS: Eligible participants are between 21 and 80 years of age diagnosed with moderately controlled T2D (HbA1c: 6.0 to 8.0%) and managed on lifestyle alone or lifestyle plus metformin. Participants must be willing and able to attend virtual counseling sessions and log meals into a dietary tracking smartphone application (DayTwo), and wear a continuous glucose monitor (CGM) for up to 12 days. Participants are randomized with equal allocation (n = 255, n = 85 per arm) to one of three arms: (1) Personalized, (2) Standardized, or (3) UCC. Measurements occur at 0 (baseline), 3, and 6 months. All participants receive isocaloric energy and macronutrient targets to meet Mediterranean diet guidelines, in addition to 14 intervention contacts over 6 months (4 weekly then 10 biweekly) to cover diabetes self-management education. The first 4 UCC intervention contacts are delivered via synchronous videoconferences followed by educational video links. Participants in Standardized receive the same educational content as those in the UCC arm, following the same schedule. However, all intervention contacts are conducted via synchronous videoconferences, paired with Social Cognitive Theory (SCT)-based behavioral counseling, plus dietary self-monitoring of planned meals using a mobile app that provides real-time feedback on calories and macronutrients. Participants in the Personalized arm receive all elements of the Standardized intervention, in addition to real-time feedback on predicted post-prandial glycemic response (PPGR) to meals and snacks logged into the mobile app. DISCUSSION: The DiaTeleMed Study aims to address an important gap in the current landscape of precision nutrition by determining the contributions of behavioral counseling and personalized nutrition recommendations on glycemic control in individuals with T2D. The fully remote methodology of the study allows for scalability and innovative delivery of personalized dietary recommendations at a population level. TRIAL REGISTRATION: ClinicalTrials.gov NCT05046886. Registered on September 16, 2021.

Metabolic Dysregulation and Its Multifaceted Impact on Cardiovascular Autonomic Control in Type 2 Diabetes Mellitus: Insights From Comprehensive Assessment.

BACKGROUND: Type 2 diabetes mellitus (T2DM) is associated with a spectrum of metabolic dysfunctions that significantly elevate the risk of cardiovascular disorders. Understanding the intricate relationship between metabolic control and cardiovascular autonomic function in individuals with T2DM is crucial for effective management and the prevention of associated complications. This insight is foundational in developing targeted strategies that can mitigate the heightened cardiovascular risks inherent to this condition, thereby enhancing patient outcomes and quality of life. AIM: The primary aim of the study was to explore the interconnections between various aspects of metabolic control in individuals with T2DM. This includes examining how glycemic variability, lipid profiles, body mass index (BMI), duration of diabetes, inflammatory markers, and cardiovascular autonomic function are interrelated. METHODS: A cross-sectional study was conducted involving 100 individuals with T2DM and 100 control participants. HbA1C levels, glycemic variability, lipid profile, BMI, duration of diabetes, and inflammatory markers were assessed. Cardiovascular autonomic function parameters, including resting heart rate and blood pressure responses, were evaluated using standardized tests. RESULTS: People with T2DM had significantly higher levels of glycosylated hemoglobin (HbA1C) compared to controls (mean difference = 2.95%, p < 0.001). Elevated HbA1C levels were correlated with increased resting heart rate (mean difference = 10 bpm, p < 0.001) and aberrant blood pressure responses during autonomic function assessments (p < 0.01 for systolic blood pressure; p < 0.05 for diastolic blood pressure). Glycemic variability (correlation coefficient (𝑟) = 0.75, p < 0.001) and dyslipidemia (elevated triglycerides and LDL cholesterol, reduced HDL cholesterol) were associated with cardiovascular autonomic dysfunction. Higher BMI values in T2DM individuals were independently correlated with alterations in autonomic function (𝑟 = 0.60, p < 0.001). The prolonged duration of diabetes was linked to greater impairment in autonomic function (mean decrease = 0.5 points per year, p < 0.01). In the T2DM group, higher levels of inflammatory markers (C-reactive protein and interleukin-6) were seen, which may have led to problems with the autonomic nervous system. CONCLUSION: Metabolic dysregulation, such as high HbA1C levels, glycemic variability, dyslipidemia, obesity, having diabetes for a long time, and inflammation, is linked to cardiovascular autonomic dysfunction in T2DM. Early intervention targeting these metabolic abnormalities may mitigate the risk of cardiovascular complications in individuals with T2DM.

An Update on the iglu Software Package for Interpreting Continuous Glucose Monitoring Data.

Background: Continuous glucose monitors (CGMs) are increasingly used to provide detailed quantification of glycemic control and glucose variability. An open-source R package iglu has been developed to assist with automatic CGM metrics computation and data visualization, providing a comprehensive list of implemented CGM metrics. Motivated by the recent international consensus statement on CGM metrics and recommendations from recent reviews of available CGM software, we present an updated version of iglu with improved accessibility and expanded functionality. Methods: The functionality was expanded to include automated computation of hypo- and hyperglycemia episodes with corresponding visualizations, composite metrics of glycemic control (glycemia risk index and personal glycemic state), and glycemic metrics associated with postprandial excursions. The algorithm for mean amplitude of glycemic excursions has been updated for improved accuracy, and the corresponding visualization has been added. Automated hierarchical clustering capabilities have been added to facilitate statistical analysis. Accessibility was improved by providing support for the automatic processing of common data formats, expanding the graphical user interface, and providing mirrored functionality in Python. Results: The updated version of iglu has been released to the Comprehensive R Archive Network (CRAN) as version 4. The corresponding Python wrapper has been released to the Python Package Index (PyPI) as version 1. The new functionality has been demonstrated using CGM data from 19 subjects with prediabetes and type 2 diabetes. Conclusions: An updated version of iglu provides comprehensive and accessible software for analyses of CGM data that meets the needs of researchers with varying levels of programming experience. It is freely available on CRAN and on GitHub at https://github.com/irinagain/iglu.

Perspective of Continuous Glucose Monitoring-Based Interventions at the Various Stages of Type 2 Diabetes.

Continuous glucose monitoring (CGM) is now advocated for the clinical management of individuals with type 1 diabetes (T1D). However, this glucose monitoring strategy is not routinely used in type 2 diabetes (T2D), given the large population, significant cost implications and relatively limited supporting evidence. T2D is a more heterogenous condition compared with T1D with various glucose lowering therapies that do not necessarily require CGM to ensure within target glucose levels. While all individuals with T2D may benefit from CGM at certain time points, the whole T2D population does not necessarily require this technology continuously, which should be prioritized based on patient benefit and cost effectiveness. In this pragmatic opinion piece, we describe the rationale and evidence for CGM use in different subgroups of individuals with T2d, divided according to the stage of the condition, glycemic therapies, presence of diabetes complications, or associated co-morbidities. We discuss a total of 16 T2D subgroups and provide a clinical view on CGM use in each, based on current evidence while also highlighting areas of knowledge gaps. This work provides health care professionals with a simple guide to CGM use in different T2D groups and gives suggestion for future studies to justify expansion of this technology.

Diabetic peripheral neuropathy and glycemic variability assessed by continuous glucose monitoring: A systematic review and meta-analysis.

Continuous glucose monitoring (CGM)-derived metrics have been used to accurately assess glycemic variability (GV) to facilitate management of diabetes mellitus, yet their relationship with diabetic peripheral neuropathy (DPN) is not fully understood. We performed a systematic review and meta-analysis to evaluate the association between GV metrics and the risk of developing DPN. Nine studies totaling 3,649 patients with type 1 and type 2 diabetes mellitus were included. A significant association was found between increased GV, as indicated by metrics including standard deviation (SD) with OR and 95% CI of 2.58 (1.45-4.57), mean amplitude of glycemic excursions (MAGE) with OR and 95% CI of 1.90 (1.01-3.58), mean of daily difference (MODD) with OR and 95% CI of 2.88 (2.17-3.81) and the incidence of DPN. Our findings support a link between higher GV and an increased risk of DPN in patients with diabetes. These findings highlight the potential of GV metrics as indicators for the development of DPN, advocating for their inclusion in diabetes management strategies to potentially mitigate neuropathy risk. Longitudinal studies with longer observation periods and larger sample sizes are necessary to validate these associations across diverse populations.

Correlation Between Blood Urea Nitrogen and Short- and Long-Term Glycemic Variability in Elderly Patients with Type 2 Diabetes Mellitus Who Were hospitalized:A Retrospective Study.

Objective: Type 2 diabetes mellitus (T2DM) is a metabolic disease characterized by insulin resistance and progressively impaired insulin secretion resulting in dynamic fluctuations in glucose levels.High blood urea nitrogen (BUN) levels have been linked to decreased insulin sensitivity, suppressed insulin synthesis and increased risk of incident diabetes mellitus in humans as well as insulin use in patients with T2DM.This study characterize the association between BUN levels and short-term and long-term glycemic variability(GV) in the elderly patients with T2DM who were hospitalized. Methods: A total of 927 elderly patients with T2DM were included in the study. The short-term GV was quantified using parameters such as standard deviation (SD), coefficient of variation (CV), time in range (TIR), and mean amplitude of glycemic excursions (MAGE), based on multi-point fingertip blood glucose monitoring. The long-term GV was quantified using parameters such as SD, CV, variation independent of the mean (VIM), and average successive variability (ARV), based on fasting blood glucose(FPG). The relationship between BUN levels and short-term and long-term GV in elderly T2DM who were hospitalized was explored using methods such as Spearman correlation coefficient, linear regression analysis, logistic regression analysis, and interaction tests. Results: In elderly patients with T2DM were hospitalized, there is a significant correlation between BUN levels and both short-term and long-term GV. BUN is negatively correlated with the GV parameter TIR (r=-0.12, P=0.000), and positively correlated with SD (r=0.12, P=0.000), CV (r=0.07, P=0.026), MAGE (r=0.11, P=0.001), FPG-SD (r=0.08, P=0.013), and FPG-CV (r=0.08, P=0.014).Furthermore, the association remains consistent across different age, gender, BMI, and haemoglobin A1c (HbA1c) subgroups (P interaction > 0.05). Conclusion: In elderly patients with T2DM were hospitalized, BUN levels were positively associated with GV.Therefore, monitoring BUN levels were beneficial in assessing the degree of GV.

Pre-hospital glycemia as a biomarker for in-hospital all-cause mortality in diabetic patients - a pilot study.

BACKGROUND: Type 2 Diabetes Mellitus (T2DM) presents a significant healthcare challenge, with considerable economic ramifications. While blood glucose management and long-term metabolic target setting for home care and outpatient treatment follow established procedures, the approach for short-term targets during hospitalization varies due to a lack of clinical consensus. Our study aims to elucidate the impact of pre-hospitalization and intra-hospitalization glycemic indexes on in-hospital survival rates in individuals with T2DM, addressing this notable gap in the current literature. METHODS: In this pilot study involving 120 hospitalized diabetic patients, we used advanced machine learning and classical statistical methods to identify variables for predicting hospitalization outcomes. We first developed a 30-day mortality risk classifier leveraging AdaBoost-FAS, a state-of-the-art ensemble machine learning method for tabular data. We then analyzed the feature relevance to identify the key predictive variables among the glycemic and routine clinical variables the model bases its predictions on. Next, we conducted detailed statistical analyses to shed light on the relationship between such variables and mortality risk. Finally, based on such analyses, we introduced a novel index, the ratio of intra-hospital glycemic variability to pre-hospitalization glycemic mean, to better characterize and stratify the diabetic population. RESULTS: Our findings underscore the importance of personalized approaches to glycemic management during hospitalization. The introduced index, alongside advanced predictive modeling, provides valuable insights for optimizing patient care. In particular, together with in-hospital glycemic variability, it is able to discriminate between patients with higher and lower mortality rates, highlighting the importance of tightly controlling not only pre-hospital but also in-hospital glycemic levels. CONCLUSIONS: Despite the pilot nature and modest sample size, this study marks the beginning of exploration into personalized glycemic control for hospitalized patients with T2DM. Pre-hospital blood glucose levels and related variables derived from it can serve as biomarkers for all-cause mortality during hospitalization.

Day-to-Day Glycemic Variability Using Continuous Glucose Monitors in Endurance Athletes.

OBJECTIVES: The application of continuous glucose monitors (CGMs) to measure interstitial glucose in athletic populations is limited by the lack of accepted athlete-specific reference values. The aim of this study was to develop athlete-specific reference ranges for glycemic variability under standardized diet and exercise conditions. METHODS: A total of 12 elite racewalkers (n = 7 men, 22.4 ± 3.5 years, VO2max 61.6 ± 7.3 mL kg-1 min-1) completed two 4-d trials separated by 4-d. Athletes were provided a high-energy, high-carbohydrate diet (225 ± 1.6 kJ kg-1 day-1, 8.4 ± 0.3 g kg-1 day-1 carbohydrate) and completed standardized daily exercise. The timing of food consumed and exercise undertaken were matched each day across the 4-d trials. Interstitial glucose data were collected via Freestyle Libre 2 CGMs. Glycemic variability was calculated as the mean amplitude of glycemic excursions (MAGEs), mean of daily differences (MODD), and standard deviation (SD). RESULTS: Twenty-four hour MODD, MAGE, and SD for interstitial glucose were 12.6 ± 1.8 mg/dL (0.7 ± 0.1 mmol/L), 36.0 ± 5.4 mg/dL (2.0 ± 0.3 mmol/L), and 16.2 ± 1.8 mg/dL (0.9 ± 0.1 mmol/L), respectively. Twenty-four hour mean glucose (MG; 102.6 ± 5.4 mg/dL [5.7 ± 0.3 mmol/L]) was higher than overnight (91.8 ± 5.4 mg/dL [5.1 ± 0.3 mmol/L]; P < .0001) and was lower in women than men (99.0 ± 3.6 mg/dL [5.5 ± 0.2 mmol/L] vs 104.4 ± 3.6 mg/dL [5.8 ± 0.2 mmol/L]; P = .059, d = 1.4). CONCLUSIONS: This study provides reference indices under standardized diet and exercise conditions for glycemic variability derived from CGMs in endurance athletes which are similar than previously reported for healthy individuals, despite strenuous daily training and a high daily energy and carbohydrate diet.

Association between continuous glucose monitoring metrics and clinical outcomes in adults with type 1 diabetes in a real-world setting.

AIMS: Continuous glucose monitoring (CGM) metrics can assist diabetes management. Consensus statements recommend > 70 % time in range (TIR) and ≤ 36 % glucose coefficient of variation (CV). However, how these targets perform in clinical practice is unknown. This retrospective, longitudinal cohort study analyzed relationships between TIR, CV, glycated hemoglobin (HbA1c), and hypoglycemia in a real-world setting. METHODS: Data of 542 adults with type 1 diabetes who used CGM (January 2014-July 2020) were analyzed. Associations between TIR and HbA1c at the same and subsequent visits, incidence rate ratios (IRRs) for hypoglycemia at different CVs, and number of hypoglycemic events at cross-sections of HbA1c and CV were estimated by regression. RESULTS: TIR was inversely related to HbA1c; for every 10 % increase in TIR, HbA1c was significantly reduced by 0.34 % (4 mmol/mol) and 0.20 % (2 mmol/mol) at the same and subsequent visits, respectively. Level 2 hypoglycemia was significantly reduced at CV < 30 %, 30-33 %, 33.1-36 %, and 36.1-40 %: adjusted IRRs vs CV ≥ 40.1 % of 0.14, 0.28, 0.32, and 0.50, respectively. Hypoglycemic events were reduced at lower CV across HbA1c levels and at higher HbA1c across CV levels. CONCLUSION: This study quantifies HbA1c improvements with increased TIR and hypoglycemia reductions with improved CV in clinical practice.

Impact of acute glycemic variability on short-term outcomes in patients with ST-segment elevation myocardial infarction: a multicenter population-based study.

BACKGROUND: Given the increasing attention to glycemic variability (GV) and its potential implications for cardiovascular outcomes. This study aimed to explore the impact of acute GV on short-term outcomes in Chinese patients with ST-segment elevation myocardial infarction (STEMI). METHODS: This study enrolled 7510 consecutive patients diagnosed with acute STEMI from 274 centers in China. GV was assessed using the coefficient of variation of blood glucose levels. Patients were categorized into three groups according to GV tertiles (GV1, GV2, and GV3). The primary outcome was 30-day all-cause death, and the secondary outcome was major adverse cardiovascular events (MACEs). Cox regression analyses were conducted to determine the independent correlation between GV and the outcomes. RESULTS: A total of 7136 patients with STEMI were included. During 30-days follow-up, there was a significant increase in the incidence of all-cause death and MACEs with higher GV tertiles. The 30-days mortality rates were 7.4% for GV1, 8.7% for GV2 and 9.4% for GV3 (p = 0.004), while the MACEs incidence rates was 11.3%, 13.8% and 15.8% for the GV1, GV2 and GV3 groups respectively (p < 0.001). High GV levels during hospitalization were significantly associated with an increased risk of 30-day all-cause mortality and MACEs. When analyzed as a continuous variable, GV was independently associated with a higher risk of all-cause mortality (hazard ratio [HR] 1.679, 95% confidence Interval [CI] 1.005-2.804) and MACEs (HR 2.064, 95% CI 1.386-3.074). Additionally, when analyzed as categorical variables, the GV3 group was found to predict an increased risk of MACEs, irrespective of the presence of diabetes mellitus (DM). CONCLUSION: Our study findings indicate that a high GV during hospitalization was significantly associated with an increased risk of 30-day all-cause mortality and MACE in Chinese patients with STEMI. Moreover, acute GV emerged as an independent predictor of increased MACEs risk, regardless of DM status.