Value of Glycemic Dispersion Index in Predicting Major Adverse Cardiovascular Events in Diabetic Patients with Concomitant Acute Coronary Syndrome.

Aim: This investigation aims to assess the predictive value of the glycemic dispersion index (GDI), calculated by incorporating glycated hemoglobin, fasting plasma glucose, and 2-hour postprandial plasma glucose, in predicting major adverse cardiovascular events (MACE) within a 12-month timeframe for diabetic patients with concomitant acute coronary syndrome (ACS). Methods: A retrospective study was conducted on 3261 diabetic patients with ACS who were hospitalized in the Department of Cardiology, the Sixth Affiliated Hospital of Kunming Medical University, from January 2016 to July 2022. Based on the inclusion and exclusion criteria, 512 patients were ultimately enrolled in the study. Their general information and laboratory test indicators were collected, and the occurrence of MACE within 12 months after admission was followed up and recorded for the enrolled patients, With the last follow-up having been concluded on July 31, 2023. The enrolled patients were stratified into four groups (Q1, Q2, Q3, Q4) based on their GDI values, from the lowest to the highest. Cox proportional hazards regression analysis and Kaplan-Meier survival analysis were employed to investigate the risk factors associated with MACE occurrence across these groups and to assess the cumulative risk of MACE over time within each group. Results: The percentages of enrolled patients experiencing MACE in groups Q1 to Q4 were 10.16%, 12.50%, 15.63%, and 16.41%, respectively. GDI independently predicted the hazards for MACE in enrolled patients. The cumulative risk of MACE over time was considerably more significant in those with a GDI>4.21 than those with a GDI≤4.21. Conclusion: The elevated GDI is correlated with an augmented risk of MACE in diabetic patients with concomitant ACS, thereby serving as an early indicator for assessing the unfavorable clinical prognosis of patients. This study offers novel insights into glycemic variability monitoring, enhancing prevention and treatment strategies for cardiovascular disease in people with diabetes.

Glycemic Variability and Disordered Eating Among Adolescents and Young Adults with Type 1 Diabetes: The Role of Disinhibited Eating.

Background and Aims: Disordered eating behaviors (DEB) are common among individuals with type 1 diabetes (T1D). Glycemic variability, potentially harmful in T1D, may reveal distinct characteristics between those with higher versus lower variability, particularly concerning DEB. Our aim was to evaluate the prevalence of DEB and associated risk factors among adolescents and young adults with T1D and to investigate unique factors associated with DEB across different levels of glycemic variability. Methods: An observational, cross-sectional study was conducted with 147 individuals with T1D, aged 13-21 years. Data were collected from medical charts, personal technological devices for assessing glycemic variability, and self-reported questionnaires, including assessments of DEB. Results: DEB were found in 62 (42.1%) individuals, and 41.5% achieved the glycemic variability (% coefficient of variation) target ≤36%. Among individuals with low glycemic variability, DEB were positively associated with diabetes distress (odds ratio [OR]: 1.14 [95% confidence interval or CI: 1.05-1.22], P < 0.001), longer diabetes duration (OR: 1.34 [95% CI: 1.05-1.70], P = 0.016) and lower socioeconomic-status (OR: 0.53 [95% CI: 0.31-0.90], P = 0.019). Among those with high glycemic variability, body mass index Z score (OR: 3.82 [95% CI: 1.48-9.85], P = 0.005), HbA1c (OR: 4.12 [95% CI: 1.33-12.80], P = 0.014), disinhibited eating (OR: 1.57 [95% CI: 1.14-2.15], P = 0.005), and tendency to lower socioeconomic status (OR: 0.75 [95% CI: 0.56-1.01], P = 0.065). Discussion: DEB are prevalent among adolescents and young adults with T1D and are associated with various risk factors. Factors associated with DEB vary across different levels of glycemic variability. Both low and high glycemic variability are associated with specific risk factors for DEB. One notable risk factor is diabetes-specific disinhibited eating among individuals with high glycemic variability, in contrast to those with low glycemic variability. Given these different risk factors, it may be prudent to adjust intervention programs to reduce DEB among T1D adolescents according to their glycemic variability levels.

Evaluation of Glycemic Variability and Discharge Outcomes in Patients with Ischemic Stroke Following Thrombolysis.

Background and Purpose: Hyperglycemia following acute ischemic stroke (AIS) is associated with adverse outcomes including, hemorrhagic conversion and increased length of stay; however, the impact of glycemic variability is largely unknown. This study aims to evaluate the effect of glycemic variability on discharge outcomes in patients treated with alteplase for AIS. Methods: A retrospective review of ischemic stroke patients who presented within 4.5 hours from symptom onset and received alteplase was completed. Patients hospitalized for at least 48 hours were included. Glycemic variability was measured using J-index. Groups were defined by normal or abnormal J-indices. Logistic regression models were developed to determine odds ratios for select clinical characteristics, NIHSS score, mRS, and disposition at discharge. Results: Of the 229 patients, 97 (42%) had an abnormal J-index. In the univariate analysis, abnormal J-index was associated with worse outcomes in terms of NIHSS score, mRS, and discharge disposition compared to a normal J-index. In the unadjusted multivariate analysis, abnormal J-index was associated with higher odds of unfavorable mRS (3-6) at discharge (OR 2.1; 95% CI 1.2 - 3.5, P = .009). In the adjusted multivariate analysis, patients with an abnormal J-index had higher odds of hemorrhagic transformation (OR 5.7; 95% CI 2.1 - 15.6, P < .0001). There was no difference in mortality. Conclusion: Glycemic variability with abnormal J-index following AIS is associated with adverse functional outcomes at discharge and increased odds of hemorrhagic conversion in patients treated with alteplase. Additional studies validating glycemic variability indices post-ischemic stroke are needed to determine the full clinical impact.

Glycemic Variability in Pancreatogenic Diabetes Mellitus: characteristics, Risks, Potential Mechanisms, and Treatment Possibilities.

In recent years, pancreatogenic diabetes mellitus has garnered significant attention due to its high incidence, complications, and mortality rates. Glycemic variability (GV) can increase the risk of pancreatogenic diabetes mellitus and its associated complications; however, the precise mechanism remains unclear. The effective control of GV is crucial for preventing the onset of pancreatic diabetes mellitus and improving prognosis. Both diet and antidiabetic medications have substantial effects on GV. However, many patients are prescribed suboptimal or even harmful drugs. Therefore, to provide a comprehensive treatment basis for clinicians to prevent and treat pancreatogenic diabetes mellitus, this study aimed to elucidate the relationship between GV and pancreatogenic diabetes mellitus; investigate the potential mechanisms (such as oxidative stress, inflammatory response, insulin resistance, and lipid metabolism disorders); provide lifestyle guidance; and recommend drug selections to reduce the GV in patients with pancreatogenic diabetes mellitus.

Characteristics of Nocturnal Hypoglycaemic Events and Their Impact on Glycaemia.

BACKGROUND: Nocturnal hypoglycaemia is a burden for people with diabetes, particularly when treated with multiple daily injections (MDI) therapy. However, the characteristics of nocturnal hypoglycaemic events in this patient group are only poorly described in the literature. METHOD: Continuous glucose monitoring (CGM) data from 185 study participants with type 1 diabetes using MDI therapy were collected under everyday conditions for up to 13 weeks. Hypoglycaemic events were identified as episodes of consecutive CGM readings <70 mg/dl or <54 mg/dl for at least 15 minutes. Subsequently, the time <54 mg/dl (TB54), time below range (TBR), time in range (TIR), time above range (TAR), glucose coefficient of variation (CV), and incidence of hypoglycaemic events were calculated for diurnal and nocturnal periods. Furthermore, the effect of nocturnal hypoglycaemic events on glucose levels the following day was assessed. RESULTS: The incidence of hypoglycaemic events <70 mg/dl was significantly lower during the night compared to the day, with 0.8 and 3.8 events per week, respectively, while the TBR, TB54, and incidence of events with CGM readings <54 mg/dl was not significantly different. Nocturnal hypoglycaemic events <70 mg/dl were significantly longer (60 vs 35 minutes) and enveloped by less rapidly changing glucose levels. On days following nights containing hypoglycaemic events, there was a decrease in TAR, mean CGM glucose level and morning glucose levels and an increase in TB54, TBR, and CV. CONCLUSIONS: The results showed that nocturnal hypoglycaemic events are a common occurrence in persons with type 1 diabetes using MDI with significant differences between the characteristics of nocturnal and diurnal events.

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.

Twenty-Four Hour Glucose Profiles and Glycemic Variability during Intermittent Religious Dry Fasting and Time-Restricted Eating in Subjects without Diabetes: A Preliminary Study.

Intermittent religious fasting increases the risk of hypo- and hyperglycemia in individuals with diabetes, but its impact on those without diabetes has been poorly investigated. The aim of this preliminary study was to examine the effects of religious Bahá'í fasting (BF) on glycemic control and variability and compare these effects with time-restricted eating (TRE). In a three-arm randomized controlled trial, 16 subjects without diabetes were assigned to a BF, TRE, or control group. Continuous glucose monitoring and food intake documentation were conducted before and during the 19 days of the intervention, and the 24 h mean glucose and glycemic variability indices were assessed. The BF and TRE groups, but not the control group, markedly reduced the daily eating window while maintaining macronutrient composition. Only the BF group decreased caloric intake (-677.8 ± 357.6 kcal, p = 0.013), body weight (-1.92 ± 0.95 kg, p = 0.011), and BMI (-0.65 ± 0.28 kg, p = 0.006). Higher maximum glucose values were observed during BF in the within-group (+1.41 ± 1.04, p = 0.039) and between-group comparisons (BF vs. control: p = 0.010; TRE vs. BF: p = 0.022). However, there were no alterations of the 24 h mean glucose, intra- and inter-day glycemic variability indices in any group. The proportions of time above and below the range (70-180 mg/dL) remained unchanged. BF and TRE do not exhibit negative effects on glycemic control and variability in subjects without diabetes.

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.

Preoperative Carbohydrate Load Does Not Alter Glycemic Variability in Diabetic and Non-Diabetic Patients Undergoing Major Gynecological Surgery: A Retrospective Study.

Background/Objectives: Elevated glycemic variability (GV) has been associated with postoperative morbidity. Traditional preoperative fasting guidelines may contribute to high GV by driving the body into catabolism. Enhanced recovery after surgery (ERAS) protocols that include a preoperative carbohydrate load (PCL) reduce hospital length of stay and healthcare costs; however, it remains unclear whether PCL improves GV in surgical patients. The aim of this retrospective study was to determine the effect of a PCL on postoperative GV in diabetic and non-diabetic patients having gynecological surgery. Methods: Retrospective data were collected on patients who had gynecological surgery before and after the rollout of an institutional ERAS protocol that included PCL ingestion. The intervention group included patients who underwent surgery in 2019 and were enrolled in the ERAS protocol and, therefore, received a PCL. The control group included patients who underwent surgery in 2016 and, thus, were not enrolled in the protocol. The primary endpoint was GV, calculated by the coefficient of variance (CV) and glycemic lability index (GLI). Results: A total of 63 patients in the intervention group and 45 in the control were analyzed. GV was not statistically significant between the groups for CV (19.3% vs. 18.6%, p = 0.65) or GLI (0.58 vs. 0.54, p = 0.86). Postoperative pain scores (4.5 vs. 5.2 p = 0.23) and incentive spirometry measurements (1262 vs. 1245 p = 0.87) were not significantly different. A subgroup analysis of patients with and without type 2 diabetes mellitus revealed no significant differences in GV for any of the subgroups. Conclusions: This retrospective review highlights the need for additional GV research, including consensus agreement on a gold standard GV measurement. Large-scale prospective studies are needed to test the effectiveness of the PCL in reducing GV.

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.

From Stability to Variability: Classification of Healthy Individuals, Prediabetes, and Type 2 Diabetes Using Glycemic Variability Indices from Continuous Glucose Monitoring Data.

Objective: This study aims to investigate the continuum of glucose control from normoglycemia to dysglycemia (HbA1c ≥ 5.7%/39 mmol/mol) using metrics derived from continuous glucose monitoring (CGM). In addition, we aim to develop a machine learning-based classification model to classify dysglycemia based on observed patterns. Methods: Data from five distinct studies, each featuring at least two days of CGM, were pooled. Participants included individuals classified as healthy, with prediabetes, or with type 2 diabetes mellitus (T2DM). Various CGM indices were extracted and compared across groups. The data set was split 70/30 for training and testing two classification models (XGBoost/Logistic Regression) to differentiate between prediabetes or dysglycemia and the healthy group. Results: The analysis included 836 participants (healthy: n = 282; prediabetes: n = 133; T2DM: n = 432). Across all CGM indices, a progressive shift was observed from the healthy group to those with diabetes (P < 0.001). Statistically significant differences (P < 0.01) were noted in mean glucose, time below range, time above 140 mg/dl, mobility, multiscale complexity index, and glycemic risk index when transitioning from health to prediabetes. The XGBoost models achieved the highest receiver operating characteristic area under the curve values on the test data set ranging from 0.91 [confidence interval (CI): 0.87-0.95] (prediabetes identification) to 0.97 [CI: 0.95-0.98] (dysglycemia identification). Conclusion: Our findings demonstrate a gradual deterioration of glucose homeostasis and increased glycemic variability across the spectrum from normo- to dysglycemia, as evidenced by CGM metrics. The performance of CGM-based indices in classifying healthy individuals and those with prediabetes and diabetes is promising.

Commonly Used Indicators of Low Energy Availability Risk Fail to Identify Female Amateur Soccer Players With Measured Low Energy Availability During Preseason.

This study aimed to determine energy availability (EA) and within-day energy balance (WDEB) in female soccer players during preseason and also explored eating disorder risk and athlete food choice. We hypothesized commonly used indicators of low energy availability (LEA) risk would correlate with measured EA and WDEB variables, and that food choice determinants would differ according to EA. Eleven National Premier League female soccer players participated in this observational cross-sectional study over 3 weeks. Assessment of resting metabolic rate and physique traits, including bone mineral density, was conducted during Weeks 1 or 3. During Week 2, dietary intake, energy expenditure, and continuous monitor-derived glucose were measured for 5 days. EA was calculated daily and WDEB calculated hourly with deficits/surpluses carried continuously. Questionnaires were administered throughout the 3 weeks, including the Athlete Food Choice Questionnaire, the Eating Disorders Screen for Athletes, and the Low Energy Availability in Females Questionnaire. Resting metabolic rate ratio, bone mineral density, Low Energy Availability in Females Questionnaire, and Eating Disorders Screen for Athletes scores were used as indicators of LEA risk. EA averaged 30.7 ± 7.5 kcals·kg fat-free mass-1·day-1. Approximately one-third (36%) of athletes were at risk of an eating disorder, while approximately half (45%) were identified at risk of the female athlete triad via Low Energy Availability in Females Questionnaire, compared with approximately one-third (36%) of athletes identified with EA < 30 kcal·kg fat-free mass-1·day-1. No athlete achieved EA >45 kcal·kg fat-free mass-1·day-1, and no indicator of LEA risk was associated with calculated EA or WDEB. However, overnight glycemic variability was positively correlated with measured EA (r = .722, p = .012).

Two-week continuous glucose monitoring-derived metrics and degree of hepatic steatosis: a cross-sectional study among Chinese middle-aged and elderly participants.

BACKGROUND: Continuous glucose monitoring (CGM) devices provide detailed information on daily glucose control and glycemic variability. Yet limited population-based studies have explored the association between CGM metrics and fatty liver. We aimed to investigate the associations of CGM metrics with the degree of hepatic steatosis. METHODS: This cross-sectional study included 1180 participants from the Guangzhou Nutrition and Health Study. CGM metrics, covering mean glucose level, glycemic variability, and in-range measures, were separately processed for all-day, nighttime, and daytime periods. Hepatic steatosis degree (healthy: n = 698; mild steatosis: n = 242; moderate/severe steatosis: n = 240) was determined by magnetic resonance imaging proton density fat fraction. Multivariate ordinal logistic regression models were conducted to estimate the associations between CGM metrics and steatosis degree. Machine learning models were employed to evaluate the predictive performance of CGM metrics for steatosis degree. RESULTS: Mean blood glucose, coefficient of variation (CV) of glucose, mean amplitude of glucose excursions (MAGE), and mean of daily differences (MODD) were positively associated with steatosis degree, with corresponding odds ratios (ORs) and 95% confidence intervals (CIs) of 1.35 (1.17, 1.56), 1.21 (1.06, 1.39), 1.37 (1.19, 1.57), and 1.35 (1.17, 1.56) during all-day period. Notably, lower daytime time in range (TIR) and higher nighttime TIR were associated with higher steatosis degree, with ORs (95% CIs) of 0.83 (0.73, 0.95) and 1.16 (1.00, 1.33), respectively. For moderate/severe steatosis (vs. healthy) prediction, the average area under the receiver operating characteristic curves were higher for the nighttime (0.69) and daytime (0.66) metrics than that of all-day metrics (0.63, P < 0.001 for all comparisons). The model combining both nighttime and daytime metrics achieved the highest predictive capacity (0.73), with nighttime MODD emerging as the most important predictor. CONCLUSIONS: Higher CGM-derived mean glucose and glycemic variability were linked with higher steatosis degree. CGM-derived metrics during nighttime and daytime provided distinct and complementary insights into hepatic steatosis.

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.

Acute Effect of Imeglimin Add-on Therapy on 24-h Glucose Profile and Glycemic Variability in Patients with Type 2 Diabetes Receiving Metformin.

INTRODUCTION: Imeglimin is a novel antidiabetic drug with insulinotropic and insulin-sensitizing effects that targets mitochondrial bioenergetics. We investigated acute effects of add-on therapy with imeglimin to preceding metformin on the 24-h glucose profile and glycemic variability assessed by continuous glucose monitoring (CGM) in patients with type 2 diabetes. METHODS: We studied 30 outpatients with type 2 diabetes inadequately controlled with metformin. CGM was used for 14 days straight during the research period. Imeglimin 2,000 mg/day was started on day 7 after initiating CGM. Several CGM parameters were compared between days 4-6 (prior to imeglimin treatment) and 11-13 (following the initiation of imeglimin treatment). RESULTS: After treatment with imeglimin, 24-h mean glucose was acutely decreased from 161.6 ± 48.0 mg/dL to 138.9 ± 32.2 mg/dL (p < 0.0001), while time in range (i.e., at a glucose level of 70-180 mg/dL) was significantly increased from 69.9 ± 23.9% to 80.6 ± 21.0% (p < 0.0001). Addition of imeglimin to metformin significantly decreased the standard deviation (SD) of 24-h glucose and mean amplitude of glycemic excursions, 2 indexes of glycemic variability. Baseline serum high-density lipoprotein (HDL) cholesterol was negatively correlated with changes in mean 24-h glucose (r = -0.3859, p = 0.0352) and those in SD (r = -0.4015, p = 0.0309). CONCLUSIONS: Imeglimin add-on therapy to metformin acutely lowered 24-h glucose levels and improved glycemic variability in patients with type 2 diabetes on metformin. A higher serum HDL cholesterol at baseline was associated with a better response to acute effects of imeglimin on 24-h glucose levels and glycemic variability.

Glycemic Control in Diabetic Patients Receiving a Diabetes-Specific Nutritional Enteral Formula: A Case Series in Home Care Settings.

BACKGROUND AND AIM: In patients with Diabetes Mellitus (DM), Enteral Nutrition (EN) is associated with less hyperglycemia and lower insulin requirements compared to Parenteral Nutrition (PN). The primary aim of this study was to assess changes in glycemic control (GC) in DM patients on EN therapy. The secondary objectives included evaluating the impact of the specialized formula on various clinical parameters and the tolerability of the nutritional formula by monitoring potential gastrointestinal side effects. METHODS: We report a case series on the effects of a Diabetes-Specific Formula (DSF) on GC, lipid profile (LP), and renal and hepatic function in a DM cohort receiving EN support. RESULTS: Twenty-two DM subjects with total dysphagia (thirteen men, nine women) on continuous EN were observed. The use of a DSF in EN was associated with an improvement in glycemic indices across all patients studied, leading to a reduction in average insulin demand. No hospitalizations were reported during the study period. CONCLUSION: The study demonstrated that the use of DSFs in a multi-dimensional home care management setting can improve glycemic control, reduce glycemic variability and insulin need, and positively impact the lipid profile of the DM cohort. The metabolic improvements were supported by the clinical outcomes observed.

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.

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).