Glucose fluctuations aggravate cardiomyocyte apoptosis by enhancing the interaction between Txnip and Akt.

BACKGROUND: Glucose fluctuations may be involved in the pathophysiological process of cardiomyocyte apoptosis, but the exact mechanism remains elusive. This study focused on exploring the mechanisms related to glucose fluctuation-induced cardiomyocyte apoptosis. METHODS: Diabetic rats established via an injection of streptozotocin were randomized to five groups: the controlled diabetic (CD) group, the uncontrolled diabetic (UD) group, the glucose fluctuated diabetic (GFD) group, the GFD group rats with the injection of 0.9% sodium chloride (NaCl) (GFD + NaCl) and the GFD group rats with the injection of N-acetyl-L-cysteine (NAC) (GFD + NAC). Twelve weeks later, cardiac function and apoptosis related protein expressions were tested. Proteomic analysis was performed to further analyze the differential protein expression pattern of CD and GFD. RESULTS: The left ventricular ejection fraction levels and fractional shortening levels were decreased in the GFD group, compared with those in the CD and UD groups. Positive cells tested by DAB-TUNEL were increased in the GFD group, compared with those in the CD group. The expression of Bcl-2 was decreased, but the expressions of Bax, cleaved caspase-3 and cleaved caspase-9 were increased in response to glucose fluctuations. Compared with CD, there were 527 upregulated and 152 downregulated proteins in GFD group. Txnip was one of the differentially expressed proteins related to oxidative stress response. The Txnip expression was increased in the GFD group, while the Akt phosphorylation level was decreased. The interaction between Txnip and Akt was enhanced when blood glucose fluctuated. Moreover, the application of NAC partially reversed glucose fluctuations-induced cardiomyocyte apoptosis. CONCLUSIONS: Glucose fluctuations lead to cardiomyocyte apoptosis by up-regulating Txnip expression and enhancing Txnip-Akt interaction.

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.

A real-world observational study on the effect of Qingre Lishi decoction on glycemic profile using continuous glucose monitoring in obese type 2 diabetes adults.

Objective: To observe the clinical efficacy and safety of the Qingre Lishi decoction in treating of newly diagnosed overweight and obese patients with type 2 diabetes mellitus (T2DM) from an evidence-based medical perspective. Methods: 70 cases of overweight and obese patients with newly diagnosed T2DM treated in the outpatient clinic of the Department of Endocrinology of the Affiliated Hospital of Liaoning University of Traditional Chinese Medicine from December 2021 to November 2022 were selected, of which 35 cases were in the observation group and 35 cases were in the control group. The observation group was treated with the Qingre Lishi decoction add lifestyle intervention, and the control group was treated with lifestyle intervention only. We compared and analyzed the fasting blood glucose (FPG), 2-hour postprandial glucose (2hPG), the occurrence of adverse reactions, and the related indexes provided by wearing the CGM device during the observation period of the patients in the two groups. Results: 53 participants completed the clinical trial. In relation of glycemic control, a decreasing trend has shown in both groups, with the decreases in FPG, 2hPG, eHbA1c, and MG in the observation group being higher than those in the control group (P<0.05). In regard to blood glucose attainment, at the 28d, the attainment rate of patients in the observation group with TIR>80% was 87.10%, and the magnitude of changes in the rise of TIR and the fall of TAR was significantly better than that in the control group (P<0.01). In terms of blood glucose fluctuation, CV and SD of the patients in the observation group decreased compared with the 0d; the magnitude of daytime blood glucose fluctuation was significantly alleviated compared with that of the control group. The degree of decrease in LAGE, MAGE, and MODD was significantly lower than that of the control group (P<0.01). Conclusion: The Qingre Lishi decoction can effectively improve the hyperglycemic condition of overweight and obese patients with newly diagnosed T2DM. It can reduce blood glucose, alleviate blood glucose fluctuations, reduce the incidence of hypoglycemia, and improve patients' adherence and self-confidence in controlling blood glucose. Clinical Trial Registration: https://itmctr.ccebtcm.org.cn/, identifier ITMCTR2024000006.

Influence of blood glucose fluctuations on chemotherapy efficacy and safety in type 2 diabetes mellitus patients complicated with lung carcinoma.

BACKGROUND: Patients with type 2 diabetes mellitus (T2DM) have large fluctuations in blood glucose (BG), abnormal metabolic function and low immunity to varying degrees, which increases the risk of malignant tumor diseases and affects the efficacy of tumor chemotherapy. Controlling hyperglycemia may have important therapeutic implications for cancer patients. AIM: To clarify the influence of BG fluctuations on chemotherapy efficacy and safety in T2DM patients complicated with lung carcinoma (LC). METHODS: The clinical data of 60 T2DM + LC patients who presented to the First Affiliated Hospital of Ningbo University between January 2019 and January 2021 were retrospectively analyzed. All patients underwent chemotherapy and were grouped as a control group (CG; normal BG fluctuation with a mean fluctuation < 3.9 mmol/L) and an observation group (OG; high BG fluctuation with a mean fluctuation ≥ 3.9 mmol/L) based on their BG fluctuations, with 30 cases each. BG-related indices, tumor markers, serum inflammatory cytokines and adverse reactions were comparatively analyzed. Pearson correlation analysis was performed to analyze the correlation between BG fluctuations and tumor markers. RESULTS: The fasting blood glucose and 2-hour postprandial blood glucose levels in the OG were notably elevated compared with those in the CG, together with markedly higher mean amplitude of glycemic excursions (MAGE), mean of daily differences, largest amplitude of glycemic excursions and standard deviation of blood glucose (P < 0.05). In addition, the OG exhibited evidently higher levels of carbohydrate antigen 19-9, carbohydrate antigen 125, carcinoembryonic antigen, neuron-specific enolase, cytokeratin 19, tumor necrosis factor-α, interleukin-6, and high-sensitivity C-reactive protein than the CG (P < 0.05). Pearson analysis revealed a positive association of MAGE with serum tumor markers. The incidence of adverse reactions was significantly higher in the OG than in the CG (P < 0.05). CONCLUSION: The greater the BG fluctuation in LC patients after chemotherapy, the more unfavorable the therapeutic effect of chemotherapy; the higher the level of tumor markers and inflammatory cytokines, the more adverse reactions the patient experiences.

Effect of 24†h glucose fluctuations on 30-day and 1-year mortality in patients with acute myocardial infarction: an analysis from the MIMIC-III database.

Background: It is recognized that patients' blood glucose fluctuates over time during acute disease episodes, especially during the outbreak of cardiovascular events, regardless of the presence of an abnormal blood glucose profile prior to admission to the hospital. Glucose fluctuations in patients with acute myocardial infarction (AMI) in the intensive care unit (ICU) are currently not adequately monitored and studied. We focused on blood glucose fluctuation values within 24 h of admission to assess their association with 30-day and 1-year mortality. Methods: Data of patients with AMI aged 18 years or older from the Critical Care Medical Information Marketplace database III V1.4 were available for analysis in this research. Glucose data were obtained by measurement. A total of 390 of them were treated with PCI. The principal consequence was 30-day and 1-year mortality in patients with AMI. The effect of different glucose fluctuations within 24 h of admission on mortality was predicted by constructing a multivariate Cox regression model with four model adjustments and Kaplan-Meier survival curves. Additionally, we performed curve-fitting analyses to show the correlation between blood glucose fluctuations and risk of death. Results: We selected 1,699 AMI patients into our study through screening. The included population was categorized into three groups based on the tertiles of blood glucose fluctuation values within 24 h of admission to the ICU. The three groups were <25 mg/dl, 25-88 mg/dl and >88 mg/dl. By cox regression analysis, the group with the highest blood glucose fluctuation values (>88 mg/dl) had the most significant increase in 30-day and 1-year mortality after excluding confounding factors (30-day mortality adjusted HR = 2.11; 95% CI = 1.49-2.98 p < 0.001; 1-year mortality adjusted HR = 1.83; 95% CI = 1.40-2.39 p < 0.001). As demonstrated by the Kaplan-Meier survival curves, the group with the greatest fluctuations in blood glucose has the worst 30-day and 1-year prognosis. Conclusions: The extent of glucose fluctuations in patients with AMI in the first 24 h after ICU admission is an essential predictor as to 30-day as well as 1-year mortality. When blood glucose fluctuates more than 88 mg/dl within 24 h, mortality increases significantly with the range of blood glucose fluctuations.

Clinical application of real-time continuous glucose monitoring system during postoperative enteral nutrition therapy in esophageal cancer patients.

BACKGROUND: Enteral nutrition (EN) support therapy increases the risk of abnormal blood glucose (BG). The aim of this study is to evaluate the clinical value of a real-time continuous glucose monitoring (rt-CGM) system in BG monitoring during postoperative EN support therapy in patients with esophageal cancer. METHODS: Patients without diabetes mellitus (DM) with esophageal cancer who planned to receive postoperative EN were enrolled. With the self-monitoring of BG value as the reference BG, the accuracy of rt-CGM was evaluated by the mean absolute relative difference (MARD) value, correlation efficient, agreement analysis, and Parkes and Clarke error grid plot. Finally, paired t tests were used to compare the differences in glucose fluctuations between EN and non-EN days and slow and fast days. RESULTS: The total MARD value of the rt-CGM system was 13.53%. There was a high correlation between interstitial glucose and fingertip capillary BG (consistency correlation efficient = 0.884 [95% confidence interval, 0.874-0.894]). Results of 15/15%, 20/20%, 30/30% agreement analysis were 58.51%, 84.71%, and 99.65%, respectively. The Parkes and Clarke error grid showed that the proportion of the A and B regions were 100% and 99.94%, respectively. The glucose fluctuations on EN days vs non-EN days and on fast days vs slow days were large, and the difference was statistically significant (P < 0.001). CONCLUSION: The rt-CGM system achieved clinical accuracy and can be used as a new option for glucose monitoring during postoperative EN therapy. The magnitude of glucose fluctuation during EN therapy remains large, even in the postoperative population without DM.

Glucose fluctuations aggravated the late sodium current induced ventricular arrhythmias via the activation of ROS/CaMKII pathway.

BACKGROUND: Recent evidence revealed that glucose fluctuation might be more likely to cause arrhythmia than persistent hyperglycemia, whereas its mechanisms were elusive. We aimed to investigate the effect of glucose fluctuation on the occurrence of ventricular arrhythmia and its mechanism. METHODS: Streptozotocin (STZ) induced diabetic rats were randomized to five groups: the controlled blood glucose (C-STZ) group, uncontrolled blood glucose (U-STZ) group, fluctuated blood glucose (GF-STZ) group, and GF-STZ rats with 100 mg/kg Tempol (GF-STZ + Tempol) group or with 5 mg/kg KN93 (GF-STZ + KN93) group. Six weeks later, the susceptibility of ventricular arrhythmias and the electrophysiological dysfunctions of ventricular myocytes were evaluated using electrocardiogram and patch-clamp technique, respectively. The levels of reactive oxygen species (ROS) and oxidized CaMKII (ox-CaMKII) were determined by fluorescence assay and Western blot, respectively. Neonatal rat cardiomyocytes and H9C2 cells in vitro were used to explore the underlying mechanisms. RESULTS: The induction rate of ventricular arrhythmias was 10%, 55%, and 90% in C-STZ group, U-STZ group, and GF-STZ group, respectively (P < 0.05). The electrophysiological dysfunctions of ventricular myocytes, including action potential duration at repolarization of 90% (APD90), APD90 short-term variability (APD90-STV), late sodium current (INa-L), early after depolarization (EAD) and delayed after depolarizations (DAD), as well as the levels of ROS and ox-CaMKII, were significantly increased in GF-STZ group. In vivo and ex vivo, inhibition of ROS or ox-CaMKII reversed these effects. Inhibition of INa-L also significantly alleviated the electrophysiological dysfunctions. In vitro, inhibition of ROS increase could significantly decrease the ox-CaMKII activation induced by glucose fluctuations. CONCLUSIONS: Glucose fluctuations aggravated the INa-L induced ventricular arrhythmias though the activation of ROS/CaMKII pathway.

Time in Range Estimation in Patients with Type 2 Diabetes is Improved by Incorporating Fasting and Postprandial Glucose Levels.

INTRODUCTION: Time in range (TIR) as assessed by continuous glucose monitoring (CGM) measures an individual's glucose fluctuations within set limits in a time period and is increasingly used together with HbA1c in patients with diabetes. HbA1c indicates the average glucose concentration but provides no information on glucose fluctuation. However, before CGM becomes available for patients with type 2 diabetes (T2D) worldwide, especially in developing nations, fasting plasma glucose (FPG) and postprandial plasma glucose (PPG) are still the common biomarkers used for monitoring diabetes conditions. We investigated the importance of FPG and PPG to glucose fluctuation in patients with T2D. We used machine learning to provide a new estimate of TIR based on the HbA1c, together with FPG and PPG. METHODS: This study included 399 patients with T2D. (1) Univariate and (2) multivariate linear regression models and (3) random forest regression models were developed to predict the TIR. Subgroup analysis was performed in the newly diagnosed T2D population to explore and optimize the prediction model for patients with different disease history. RESULTS: Regression analysis suggests that FPG was strongly linked to minimum glucose, while PPG was strongly correlated with maximum glucose. After FPG and PPG were incorporated into the multivariate linear regression model, the prediction performance of TIR was improved compared with the univariate correlation between HbA1c and TIR, and the correlation coefficient (95% CI) increased from 0.62 (0.59, 0.65) to 0.73 (0.72, 0.75) (p < 0.001). The random forest model significantly outperformed the linear model (p < 0.001) in predicting TIR through FPG, PPG and HbA1c, with a stronger correlation coefficient 0.79 (0.79, 0.80). CONCLUSIONS: The results offered a comprehensive understanding of glucose fluctuations through FPG and PPG compared to HbA1c alone. Our novel TIR prediction model based on random forest regression with FPG, PPG, and HbA1c provides a better prediction performance than the univariate model with solely HbA1c. The results indicate a nonlinear relationship between TIR and glycaemic parameters. Our results suggest that machine learning may have the potential to be used in developing better models for understanding patients' disease status and providing necessary interventions for glycaemic control.

Effects of dulaglutide combined with insulin degludec on glucose fluctuations and appetite in type 2 diabetes.

Introduction: The aim of this study was to describe appetite and glucose fluctuation in type 2 diabetes mellitus patients initiating treatment with dulaglutide combined with insulin degludec. Methods: This retrospective study of patients identified adults starting treatment with once-weekly (QW) dulaglutide combined with insulin degludec (experimental group) or insulin degludec alone (control group). Patients were followed for up to 6 months from treatment initiation. The clinical characteristics of patients, treatment patterns, CGM data, and appetite scores were obtained for the two groups. Results: A total of 236 patients were included in this study. SDBG, MAGE, LAGE, and PPGE of the experimental group were lower than the control group's (P < 0.05). The proportions of patients achieving a time in range (TIR) of ≥70% in the experimental group were higher than in the control group, with 43% and 10% on the second day, 88% and 47% on the fourth day, 95% and 47% on the seventh day, and 100% and 67% on the tenth day, respectively. Significant associations existed between TIR and the prevalence of islet function. At six months, 89.2% of patients in the experimental group were still using dulaglutide. Appetite decreased significantly at 1 week and increased at 3 months after treatment with dulaglutide. Conclusion: Dulaglutide combined with insulin degludec significantly reduces glucose fluctuations in patients with type 2 diabetes mellitus and improves the TIR rate. However, the treatment on appetite could decrease in the first three months.

Higher glucose fluctuation is associated with a higher risk of cardiovascular disease: Insights from pooled results among patients with diabetes.

BACKGROUND: The relationship between glucose fluctuation and the risk of cardiovascular disease (CVD) in patients with diabetes remains elusive. Glycated hemoglobin (HbA1c) variability is a key parameter of glucose fluctuation. METHODS: PubMed, Cochrane Library, Web of Science, and Embase were searched up to 1 July 2022. Studies reporting associations of HbA1c variability (HbA1c-SD), coefficient of variation of HbA1c (HbA1c-CV), and HbA1c variability score [HVS] with the risk of CVD among patients with diabetes were included. We used three different insights (a high-low value meta-analysis, a study-specific meta-analysis, and a non-linear dose-response meta-analysis) to explore the relationship between HbA1c variability and CVD risk. A subgroup analysis was also performed to screen the potential confounding factors. RESULTS: A total of 14 studies with 254 017 patients with diabetes were eligible. The highest HbA1c variability was significantly associated with increased risks of CVD (HbA1c-SD, risk ratio [RR] 1.45; HbA1c-CV, RR 1.74; HVS, RR 2.46; all p < .001) compared to the lowest HbA1c variability. The RRs of CVD for per HbA1c variability were significantly >1 (all p < .001). The subgroup analysis for per HbA1c-SD found a significant exposure-covariate interaction in the types of diabetes (p = .003 for interaction). The dose-response analysis showed a positive association between HbA1c-CV and CVD risk (P for nonlinearity <.001). CONCLUSIONS: Our study suggests that the higher glucose fluctuation is significantly associated with the higher CVD risk in diabetes patients based on HbA1c variability. The CVD risk associated with per HbA1c-SD might be higher among patients type 1 diabetes than patients with type 2 diabetes.

Acute Coronary Syndrome Due to Intraplaque Hemorrhage in a Post-gastrectomy Patient with a Latent Severe Glycemic Disorder.

Glycemic disorders involving large glucose fluctuations and recurrent hypoglycemia may lead to adverse cardiovascular events, including acute coronary syndrome (ACS). Flash glucose monitoring (FGM) has reportedly been useful for detecting latent glycemic disorders. However, only a few studies have so far reported latent glycemic disorders in coronary artery disease. Thus, we herein present a unique case of ACS due to intraplaque hemorrhage in a post-gastrectomy patient who had no apparent coronary risk, except for a latent severe glycemic disorder detected via FGM. This masked etiology should be considered in ACS patients who have no apparent cardiovascular risks in order to improve their cardiovascular outcomes.

Effect of glycemic control and glucose fluctuation on in-hospital adverse outcomes after on-pump coronary artery bypass grafting in patients with diabetes: a retrospective study.

BACKGROUND: The optimal glycemic control level in diabetic patients undergoing coronary artery bypass grafting (CABG) with cardiopulmonary bypass (On-Pump) remains unclear. Therefore, this study aimed to investigate the effect of different blood glucose control levels and glucose fluctuations on in-hospital adverse outcomes in diabetic patients undergoing on-pump CABG. METHOD: A total of 3918 patients with diabetes undergoing CABG were reviewed in this study. A total of 1638 patients were eligible for inclusion and were categorized into strict, moderate and liberal glucose control groups based on post-operative mean blood glucose control levels of < 7.8 mmol/L, from 7.8 to 9.9 mmol/L and ≥ 10.0 mmoL/L, respectively. The primary endpoint was defined as a composite endpoint including in-hospital all-cause mortality and major cardiovascular complications. The secondary endpoint was defined as major cardiovascular complications including acute myocardial infarction, strokes and acute kidney injuries. To determine the associations between blood glucose fluctuations and adverse outcomes, patients with different glycemic control levels were further divided into subgroups according to whether the largest amplitude of glycemic excursion (LAGE) was ≥ 4.4 mmol/L or not. RESULTS: A total of 126 (7.7%) patients had a composite endpoint. Compared with moderate control, strict glucose control was associated with an increased risk of the primary endpoint (adjusted OR = 2.22, 95% CI 1.18-4.15, p = 0.01) and the secondary endpoint (adjusted OR = 1.95, 95% CI 1.01-3.77, p = 0.049). Furthermore, LAGE ≥ 4.4 mmol/L was significantly associated with the primary endpoint (adjusted OR = 1.67, 95% CI 1.12-2.50, p = 0.01) and the secondary endpoint (adjusted OR = 1.75, 95% CI 1.17-2.62, p = 0.01),respectively. Patients with LAGE ≥ 4.4 mmol/L had significantly higher rates of the composite endpoint and major vascular complications in both the strict-control (the primary endpoint, 66.7% vs 12.4%, p = 0.034, the secondary endpoint, 66.7% vs 10.3%, p = 0.03) and moderate-control groups (the primary endpoint, 10.2% vs 6.0%, p = 0.03, the secondary endpoint, 10.2% vs 5.8%, p = 0.02). CONCLUSIONS: After On-Pump CABG patients with diabetes, strict glucose control (< 7.8 mmol/L) and relatively large glucose fluctuations (LAGE ≥ 4.4 mmol/L) were independently associated with in-hospital adverse outcomes.

High glucose promotes apoptosis and autophagy of MC3T3-E1 osteoblasts.

Introduction: Diabetes and osteoporosis are common metabolic diseases. Abnormal high glucose can lead to the apoptosis of osteoblasts. Autophagy is a highly conserved cellular process that degrades proteins or organelles. In the present study, we comparatively analyzed the effects of high glucose and glucose fluctuation on apoptosis and autophagy of MC3T3-E1 osteoblasts. Material and methods: MC3T3-E1 cells were respectively treated with different concentrations of D-glucose: 5.5 mM for the control group, 25 mM for the high glucose group and 5.5/25 mM for the glucose fluctuation group. Results: High glucose and glucose fluctuation decreased MC3T3-E1 proliferation and activated autophagy. Also, high glucose and glucose fluctuation might induce the production of reactive oxygen species, decline the mitochondrial membrane potential and trigger apoptosis. The differences in the glucose fluctuation treatment group were more significant. Moreover, N-acetylcysteine, an antioxidant reagent, dramatically eliminated the intracellular reactive oxygen species induced by high glucose and glucose fluctuation, and significantly inhibited the autophagy and apoptosis in MC3T3-E1 osteoblasts. Furthermore, treatment with chloroquine, an inhibitor of autophagy, significantly increased the apoptosis of MC3T3-E1 osteoblasts. Conclusions: High glucose, especially high glucose fluctuation, inhibits proliferation and promotes apoptosis and autophagy of MC3T3-E1 osteoblasts. This may occur through inducing oxidative stress and mitochondrial damage in the osteoblasts.

Effect of dulaglutide and long-acting insulin combination therapy in patients with type 2 diabetes: a retrospective observational study.

Objective: The study aimed to evaluate the long-term effects of combination therapy comprising dulaglutide and long-acting insulin, on glycemic control in patients with type 2 diabetes. Methods: This retrospective observational study included 20 patients with type 2 diabetes who underwent blood glucose management with intensive insulin therapy for a limited period. All patients were switched from intensive insulin therapy to combination therapy comprising dulaglutide and long-acting insulin. Hemoglobin A1c was evaluated before and 4, 12, and 24 weeks after starting combination therapy. Continuous glucose monitoring was conducted before and 1 and 24 weeks after starting combination therapy. Results: Hemoglobin A1c levels were significantly reduced after 4, 12, and 24 weeks of combination therapy (- 2.2% ± 0.4%, P < 0.0001; - 3.7% ± 0.8%, P = 0.0003; and - 3.6% ± 0.8%, P = 0.0005, respectively). Glycemic variability (% coefficient of variation) was significantly decreased after 1 and 24 weeks of combination therapy (- 5.7% ± 2.1%, P = 0.011; and - 8.7% ± 2.4%, P = 0.003, respectively) and the percentage of readings and time > 250 mg/dL at 24 weeks was significantly improved (- 2.2% ± 0.8%, P = 0.019). Conclusion: Combination therapy with dulaglutide and long-acting insulin resulted in better blood glucose control than intensive insulin therapy, which persisted for 24 weeks. Combination therapy also reduced blood glucose fluctuations and the number of self-injections needed. Supplementary Information: The online version contains supplementary material available at 10.1007/s13340-022-00592-z.

Effect of needle-free jet injection of insulin glargine on glycaemic fluctuation in type 2 diabetic patients with uncontrolled glycemia / 中华内分泌代谢杂志

Objective:To investigate the effects of insulin glargine administration by jet injection versus conventional insulin pen on glucose profile using professional mode flash glucose monitoring(FGM) system in type 2 diabetic patients with poor glucose control.Methods:In this randomized, controlled, crossover study, 40 patients with T2DM who treated with insulin glargine were enrolled. The patients were randomly divided into group A(jet injector-conventional pen, n=20) and group B(conventional pen-jet injector, n=20). Each patient wore FreeStyle Libre sensor from day 4 to day 17. The specialist nurse instructed patients how to master the injection techniques. Professional FGM system was applied to assess glucose profile. Results:The fasting blood glucose(FBG) of the enrolled patients was(9.37±1.84) mmol/L. In contrast to conventional insulin pen, treatment with the jet injector significantly decreased the 24h MBG [(9.06±2.13 vs 9.98±2.67) mmol/L, P=0.001], MaxBG [(16.69±3.01 vs 17.95±3.48) mmol/L, P=0.001], AUC>10 mmol/L [95.93(21.12, 129.02) vs 142.66( 27.88, 198.46), P=0.002], TAR(31.10±21.89 vs 39.49±25.93, P=0.003), MAGE and SDBG. It was observed that patients using jet injector had significant increased TIR(65.94±20.47 vs 58.32±25.00, P=0.001). There were no difference in the risk of hypoglycaemia between two groups. Conclusion:Insulin jet injector was more effective than the insulin pen on glycaemic control and glucose fluctuation without increasing the risk of hypoglycemia in type 2 diabetic patients with uncontrolled glycemia.

Machine Learning-Based Time in Patterns for Blood Glucose Fluctuation Pattern Recognition in Type 1 Diabetes Management: Development and Validation Study.

BACKGROUND: Continuous glucose monitoring (CGM) for diabetes combines noninvasive glucose biosensors, continuous monitoring, cloud computing, and analytics to connect and simulate a hospital setting in a person's home. CGM systems inspired analytics methods to measure glycemic variability (GV), but existing GV analytics methods disregard glucose trends and patterns; hence, they fail to capture entire temporal patterns and do not provide granular insights about glucose fluctuations. OBJECTIVE: This study aimed to propose a machine learning-based framework for blood glucose fluctuation pattern recognition, which enables a more comprehensive representation of GV profiles that could present detailed fluctuation information, be easily understood by clinicians, and provide insights about patient groups based on time in blood fluctuation patterns. METHODS: Overall, 1.5 million measurements from 126 patients in the United Kingdom with type 1 diabetes mellitus (T1DM) were collected, and prevalent blood fluctuation patterns were extracted using dynamic time warping. The patterns were further validated in 225 patients in the United States with T1DM. Hierarchical clustering was then applied on time in patterns to form 4 clusters of patients. Patient groups were compared using statistical analysis. RESULTS: In total, 6 patterns depicting distinctive glucose levels and trends were identified and validated, based on which 4 GV profiles of patients with T1DM were found. They were significantly different in terms of glycemic statuses such as diabetes duration (P=.04), glycated hemoglobin level (P<.001), and time in range (P<.001) and thus had different management needs. CONCLUSIONS: The proposed method can analytically extract existing blood fluctuation patterns from CGM data. Thus, time in patterns can capture a rich view of patients' GV profile. Its conceptual resemblance with time in range, along with rich blood fluctuation details, makes it more scalable, accessible, and informative to clinicians.

The increased prevalence of depression and anxiety in T2DM patients associated with blood glucose fluctuation and sleep quality.

BACKGROUND: Current evidence demonstrates that blood glucose fluctuation can be associated with depression and anxiety. The association among blood glucose fluctuation, traditional risk factors and emotional disorders in T2DM should be studied and clarified. METHODS: A total of 182 diabetic patients including 81 patients with depression or anxiety and 101 patients without emotional disorder were enrolled into this study. Data were obtained through medical history and questionnaire survey. Data were analyzed using appropriate statistical methods. RESULTS: The comparison results of basic information between the two groups showed that the differences of the proportion of female were statistically significant (p = 0.002). There was no statistical difference in laboratory examination indexes between the two groups, however, standard deviation of blood glucose (SDBG) and postprandial glucose excursion (PPGE) of the comorbidity group were significantly higher than that of control group (p = 0.032 and p = 0.037). The results of questionnaire survey showed that there were statistically significant differences in sleep quality, PSQI and dietary habit between the two groups (p < 0.001, p < 0.001 and p < 0.001). Stratified analysis results according to gender showed that the percentage of cognitive disorder, anxiety and depression in female group was significantly higher than that in male group (p = 0.001, p < 0.001 and p < 0.001). Mini-mental state examination (MMSE), self-rating anxiety scale (SAS) and patient health questionnaire (PHQ-9) score in female group were also higher than male group (p = 0.001, p < 0.001 and p < 0.001). Logistic regression analysis results showed that SDBG and sleep quality were associated with emotional disorders in T2DM (p = 0.040 and p < 0.001) and the OR values of these factors were 7.588 (1.097-52.069) and 4.428 (2.649-7.401). CONCLUSIONS: Blood glucose fluctuation and sleep quality are associated with the increased prevalence of depression and anxiety disorders in T2DM.

Glucose fluctuation promotes cardiomyocyte apoptosis by triggering endoplasmic reticulum (ER) stress signaling pathway in vivo and in vitro.

Glucose fluctuation is more harmful than sustained hyperglycemia, but the effect on cardiomyocyte apoptosis have not yet been clarified. In this study, we aim to identify the effect of glucose fluctuation on cardiomyocyte apoptosis and explore the underlying mechanism. Sprague-Dawley rats were intraperitoneally injected with streptozotocin (STZ) and divided into three groups: controlled diabetic group (C-STZ); uncontrolled diabetic group (U-STZ) and glucose fluctuated diabetic group (GF-STZ). After twelve weeks, echocardiography, Hematoxylin-eosin (HE) staining, and Masson staining were adopted to assess the cardiac function and pathological changes. TUNEL staining was used to detect apoptotic cells. Expressions of apoptosis-related proteins and key molecules in the endoplasmic reticulum (ER) stress pathway were determined via western blots. Further, primary cardiomyocytes incubated in different glucose conditions were treated with the inhibitor of ER stress to explore the causative role of ER stress in glucose fluctuation-induced cardiomyocyte apoptosis. In vivo, we demonstrated that glucose fluctuation promoted cardiomyocyte apoptosis, and were more harmful to cardiomyocytes than sustained hyperglycemia. Moreover, glucose fluctuation significantly triggered ER stress signaling pathway. In vitro, primary cardiomyocyte apoptosis induced by glucose fluctuation and the activation of ER stress were significantly attenuated by 4-PBA, which is an ER stress inhibitor. Above all, glucose fluctuation can promote cardiomyocyte apoptosis through triggering the ER stress signaling pathway in diabetic rats and in primary cardiomyocytes.

Glucose Fluctuations Aggravate Myocardial Fibrosis via the Nuclear Factor-κB-Mediated Nucleotide-Binding Oligomerization Domain-Like Receptor Protein 3 Inflammasome Activation.

Background: Glucose fluctuations may be associated with myocardial fibrosis. This study aimed to investigate the underlying mechanisms of glucose fluctuation-related myocardial fibrosis. Methods: Streptozotocin (STZ)-injected type 1 diabetic rats were randomized to five groups: the controlled blood glucose (CBG) group, uncontrolled blood glucose (UBG) group, fluctuated blood glucose (FBG) group, FBG rats injected with 0.9% sodium chloride (NaCl) (FBG + NaCl) group, and FBG rats injected with MCC950 (FBG + MCC950) group. Eight weeks later, left ventricular function was evaluated by echocardiography and myocardial fibrosis was observed by Masson trichrome staining. The primary neonatal rat cardiac fibroblasts were cultured with different concentrations of glucose in vitro. Results: The left ventricular function was impaired and myocardial fibrosis was aggravated most significantly in the FBG group compared with the CBG and UBG groups. The levels of interleukin (IL)-1ß, IL-18, transforming growth factor-ß1 (TGF-ß1), collagen type 1 (collagen I), nuclear factor (NF)-κB, and nucleotide-binding oligomerization domain-like receptor protein 3 (NLRP3) inflammasome were significantly increased in the FBG group. In vitro, the inhibition of NF-κB and inflammasome reversed these effects. In vivo, NLRP3 inhibition with MCC950 reversed left ventricular systolic dysfunction and myocardial fibrosis induced by glucose fluctuations. Conclusion: Glucose fluctuations promote diabetic myocardial fibrosis by the NF-κB-mediated inflammasome activation.