Single-Cell RNA Sequencing Analysis of Steroidogenesis and Spermatogenesis Impairment in the Testis of db/db Mice.

Objective: The mechanism of steroidogenesis and spermatogenesis impairment in men with type 2 diabetes remains unclear. We aimed to explore the local changes of steroidogenesis and spermatogenesis in the testis of db/db mice. Research Design and Methods. We performed single-cell RNA sequencing analysis in the testis of db/db and C57BL/6J mice. The differentially expressed genes were then confirmed by real-time PCR. The histopathological characteristics of testis in db/db mice and C57BL/6J control were also performed. Results: The 20-week-old db/db mice had significantly higher blood glucose and body weight (both p < 0.001). The serum testosterone levels (4.4 ± 0.8 vs. 9.8 ± 0.7 ng/ml, p=0.001) and weight of the testis (0.16 ± 0.01 vs. 0.24 ± 0.01 g, p < 0.001) were significantly lower in db/db mice than that in C57BL/6J controls. db/db mice had a lower cross-sectional area of seminiferous tubules and thickness of the cell layer (both p < 0.05). The numbers of Sertoli cells and Leydig cells decreased in db/db mice (both p < 0.01). Single-cell RNA sequencing analysis showed that compared with the control group, the percentage of spermatogonia was significantly higher in the db/db mouse (p < 0.001), while the proportions of spermatocytes, round and elongating spermatids, and sperms were all lower in the db/db mouse (p all < 0.001). The most differentially expressed genes were found in round spermatids (n = 86), which were not found in spermatogonia, spermatocyte, and sperm. Igfbp5 was the most significantly decreased gene in Leydig cells of the db/db mouse, while the expression of Cd74, H2-Aa, and H2-Eb1 was elevated. Ccl7 and Ptgds were the most significantly increased and decreased genes in Sertoli cells of the db/db mouse. Conclusions: The present study indicates spermiogenesis and steroidogenesis defects in db/db mice. The mechanism of steroidogenesis impairment in the testis of db/db mice deserves further investigation.

Sex Hormone Binding Globulin is an Independent Predictor for Insulin Resistance in Male Patients with Newly Diagnosed Type 2 Diabetes Mellitus.

INTRODUCTION: This study explored the correlation between sex hormones, sex hormone binding globulin (SHBG), and insulin resistance in male patients with newly diagnosed type 2 diabetes mellitus (T2DM). METHODS: A total of 48 male patients with newly diagnosed T2DM were enrolled in this study between March 2022 and December 2022. Clinical characteristics, sex hormones, and SHBG levels were collected. All enrolled subjects received intensive hypoglycemic treatment with insulin pump for 1 week to achieve glycemic control, then the steady-state glucose infusion rate (GIR), an indicator of insulin sensitivity, was determined by the hyperinsulinemic-euglycemic clamp. Correlation analysis and multivariate logistic regression analysis were performed to explore the association of clinical characteristics, sex hormones, and SHBG with insulin sensitivity. The optimal cutoff value to predict insulin resistance was calculated using receiver operating characteristic (ROC) curve. RESULTS: According to the GIR cut-point value of 5.700 mg/(kg min), there were 40 patients with insulin resistance (IR group) and 8 patients without (non-IR group). The IR group exhibited lower testosterone and SHBG levels than the non-IR group (all p < 0.050). Correlation analysis showed that insulin sensitivity was positively associated with testosterone and SHBG, while negatively associated with body mass index, fasting blood glucose, alanine aminotransferase, aspartate aminotransferase, total cholesterol, triglyceride, and apolipoprotein B (all p < 0.050). Multivariate logistic regression analysis demonstrated that SHBG is an independent predictor for insulin resistance (p = 0.029). Further ROC curve analysis revealed that the optimal cutoff value of SHBG to predict insulin resistance is 17.200 nmol/L, with the corresponding area under the curve (AUC) and its 95% confidence interval (CI) being 0.813 and 0.691-0.934. CONCLUSIONS: SHBG is an independent predictor for insulin resistance in male patients with newly diagnosed T2DM. TRIAL REGISTRATION NUMBER: KY20220314-01.

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.

Increased Glycemic Variability Evaluated by Continuous Glucose Monitoring is Associated with Osteoporosis in Type 2 Diabetic Patients.

Background: Subjects with type 2 diabetes mellitus (T2DM) are susceptible to osteoporosis. This study was conducted to evaluate the association between glycemic variability evaluated by continuous glucose monitoring (CGM) and osteoporosis in type 2 diabetic patient. Methods: A total of 362 type 2 diabetic subjects who underwent bone mineral density (BMD) measurement and were monitored by a CGM system from Jan 2019 to May 2020 were enrolled in this cross-sectional study. Glycemic variability was calculated with the Easy GV software, including 24-hour mean blood glucose (24-h MBG), the standard deviation of 24-h MBG (SDBG), coefficient of variation (CV), mean amplitude of glycemic excursions (MAGE), and time in range between 3.9 and 10.0 mmol/L (TIR). Other potential influence factors for osteoporosis were also examined. Results: Based on the T-scores of BMD measurement, there were 190 patients with normal bone mass, 132 patients with osteopenia and 40 patients with osteoporosis. T2DM patients with osteoporosis showed a higher 24-h MBG, SDBG, CV, and MAGE, but a lower TIR (all p < 0.05). Multivariate logistic regression analysis revealed that age, female gender, body mass index (BMI), low-density lipoprotein cholesterol (LDL-C), serum uric acid (SUA) and MAGE independently contribute to osteoporosis, and corresponding odds ratio [95% confidence interval (CI)] was 1.129 (1.072-1.190), 4.215 (1.613-11.012), 0.801 (0.712-0.901), 2.743 (1.385-5.431), 0.993 (0.988-0.999), and 1.380 (1.026-1.857), respectively. Further receiver operating characteristic analysis with Youden index indicated that the area under the curve and its 95% CI were 0.673 and 0.604-0.742, with the optimal cut-off value of MAGE predicting osteoporosis being 4.31 mmol/L. Conclusion: In addition to conventional influence factors including age, female gender, BMI, LDL-C and SUA, increased glycemic variability assessed by MAGE is associated with osteoporosis in type 2 diabetic patients.

Real-Time Flash Glucose Monitoring Had Better Effects on Daily Glycemic Control Compared With Retrospective Flash Glucose Monitoring in Patients With Type 2 Diabetes on Premix Insulin Therapy.

Background and Aims: To compare the effects of real-time and retrospective flash glucose monitoring (FGM) on daily glycemic control and lifestyle in patients with type 2 diabetes on premix insulin therapy. Methods and Results: A total of 172 patients using premix insulin, with HbA1c ≥ 7.0% (56 mmol/mol), or the time below the target (TBR) ≥ 4%, or the coefficient of variation (CV) ≥36% during the screening period, were randomly assigned to retrospective FGM (n = 89) or real-time FGM group (n = 83). Another two retrospective or real-time 14-day FGMs were performed respectively, 1 month apart. Both groups received educations and medication adjustment after each FGM. Time in range (3.9~10.0 mmol/l, TIR) increased significantly after 3 months in the real-time FGM group (6.5%) compared with the retrospective FGM group (-1.1%) (p = 0.014). HbA1c decreased in both groups (both p < 0.01). Real-time FGMs increased daily exercise time compared with the retrospective group (p = 0.002). Conclusions: Real-time FGM with visible blood glucose improves daily glycemic control and diabetes self-care behaviors better than retrospective FGM in patients with type 2 diabetes on premix insulin therapy. Clinical Trial Registration: https://clinicaltrials.gov/NCT04847219.

Ethnicity Differences in the Association of UCP1-3826A/G, UCP2-866G/A and Ala55Val, and UCP3-55C/T Polymorphisms with Type 2 Diabetes Mellitus Susceptibility: An Updated Meta-Analysis.

BACKGROUND: The relationship between uncoupling protein (UCP) 1-3 polymorphisms and susceptibility to type 2 diabetes mellitus (T2DM) has been extensively studied, while conclusions remain contradictory. Thus, we performed this meta-analysis to elucidate whether the UCP1-3826A/G, UCP2-866G/A, Ala55Val, and UCP3-55C/T polymorphisms are associated with T2DM. METHODS: Eligible studies were searched from PubMed, Cochrane Library, and Web of Science database before 12 July 2020. Pooled odds ratios (ORs) with corresponding 95% confidence intervals (CIs) were calculated to evaluate the strength of the association. Heterogeneity analysis, subgroup analysis, sensitivity analysis, and publication bias were also performed. RESULTS: A total of 38 case-control studies were included in this meta-analysis. The overall results revealed significant association between T2DM and the UCP2 Ala55Val polymorphism (recessive model: OR = 1.25, 95% CI 1.12-1.40, P < 0.01; homozygous model: OR = 1.33, 95% CI 1.03-1.72, P = 0.029, respectively). In subgroup analysis stratified by ethnicity, T2DM risk was increased with the UCP2 Ala55Val polymorphism (allele model: OR = 1.17, 95% CI 1.02-1.34, P = 0.023; recessive model: OR = 1.28, 95% CI 1.13-1.45, P < 0.01; homozygous model: OR = 1.39, 95% CI 1.05-1.86, P = 0.023, respectively), while decreased with the UCP2-866G/A polymorphism in Asians (dominant model: OR = 0.86, 95% CI 0.74-1.00, P = 0.045). CONCLUSIONS: Our results demonstrate that the UCP2-866G/A polymorphism is protective against T2DM, while the UCP2 Ala55Val polymorphism is susceptible to T2DM in Asians.

Association of Acarbose with Decreased Muscle Mass and Function in Patients with Type 2 Diabetes: A Retrospective, Cross-Sectional Study.

INTRODUCTION: Prevalence of sarcopenia has increased in patients with type 2 diabetes. The influence of glucose-lowering drugs on muscles in these patients remains unclear. We aimed to investigate the association between muscle mass/function and glucose-lowering drugs. METHODS: Data of 1042 hospitalized patients with type 2 diabetes were included in this retrospective, cross-sectional study. All the patients had stable hypoglycemic therapy in the last 3 months, and performed bioelectrical impedance analysis, grip strength, and gait speed tests on admission. RESULTS: Skeletal muscle index [6.81 (95% CI 6.67, 6.94) vs. 7.17 (7.09, 7.24) kg/m2], handgrip strength [23.41 (22.24, 24.58) vs. 26.93 (26.33, 27.54) kg], and gait speed [1.19 (1.15, 1.22) vs. 1.27 (1.25, 1.28) m/s] decreased in patients using acarbose compared with the others (all p < 0.001). Gait speed and skeletal muscle index remained lower in patients using acarbose compared to their matched patients in propensity score matching (p = 0.036 and 0.010, respectively). Among drug-naïve patients and patients using insulin, metformin, sulfonylureas, or acarbose monotherapy, the acarbose group had lowest skeletal muscle index and handgrip strength [6.81 (6.52, 7.11) kg/m2 and 22.54 (19.28, 25.79) kg, p = 0.028 and 0.001, respectively]. CONCLUSION: Acarbose treatment was associated with decreased muscle mass and strength. Assessment and exercise of muscles in patients with long-term acarbose treatment should be considered.

Effects of Dapagliflozin Adjunct to Insulin on Glycemic Variations in Patients with Newly Diagnosed Type 2 Diabetes: A Randomized, Controlled, Open-Labeled Trial.

BACKGROUND: This study is aimed at investigating whether dapagliflozin adjunct to insulin therapy further improves glycemic control compared to insulin therapy alone in patients with newly diagnosed type 2 diabetes (T2D). METHODS: This single-centre, randomized, controlled, open-labeled trial recruited newly diagnosed T2D patients. Subjects were randomized 1 : 1 to the dapagliflozin add-on to continuous subcutaneous insulin infusion (CSII) group (DAPA) or the CSII therapy group for 5 weeks. Standard meal tests were performed 3 times at days -3, 7, and 35 for glucose, C-peptide, and insulin level determination. Two-time continuous glucose monitoring (CGM) was performed at baseline and at the end of the study. The primary endpoint was the difference in the mean amplitude of glycemic excursions (MAGEs) between the groups. RESULTS: A total of 66 subjects completed the study, with 34 and 32 patients in the DAPA and CSII groups, respectively. Patients in the DAPA group exhibited significant decreases in MAGE levels at the endpoint. We also observed that patients in the DAPA group had a lower homoeostasis model assessment insulin resistance (HOMA-IR) and a higher homoeostasis model assessment B (HOMA-B) value at 1 week and 5 weeks compared to those with insulin therapy, respectively. In addition, our data showed that patients in the DAPA group showed a significantly lower insulin dose (0.07 U/kg) and weighed less than those in the CSII group. CONCLUSION: Our data indicate that dapagliflozin adjunct to insulin is a safe and effective therapy for improving glycemic variations, insulin sensitivity, and weight loss in newly diagnosed T2D patients.

Effectiveness of beinaglutide in a patient with late dumping syndrome after gastrectomy: A case report.

RATIONALE: Dumping syndrome is a frequent and potentially severe complication after gastric surgery. Beinaglutide, a recombinant human glucagon-like peptide-1 (GLP-1) which shares 100% homology with human GLP-1(7-36), has never been reported in the treatment of dumping syndrome before. PATIENT CONCERNS: The patient had undergone distal gastrectomy for gastric signet ring cell carcinoma 16 months ago. He presented with symptoms of paroxysmal palpitation, sweating, and dizziness for 4 months. DIAGNOSIS: He was diagnosed with late dumping syndrome. INTERVENTIONS AND OUTCOMES: The patient was treated with dietary changes and acarbose for 4 months before admitted to our hospital. The treatment with dietary changes and acarbose did not prevent postprandial hyperinsulinemia and hypoglycemia according to the 75 g oral glucose tolerance test (OGTT) and continuous glucose monitoring (CGM) on admission.Therefore, the patient was treated with beinaglutide 0.1 mg before breakfast and lunch instead of acarbose. After the treatment of beinaglutide for 1 month, OGTT showed a reduction in postprandial hyperinsulinemia compared with before starting treatment, and the time in the range of 3.9 to 10 mmol/L became 100% in CGM. No side effect was observed in this patient during beinaglutide treatment. LESSONS: These findings suggest that beinaglutide may be effective for treating post-gastrectomy late dumping syndrome.

Vitamin A and Its Multi-Effects on Pancreas: Recent Advances and Prospects.

Vitamin A (VA), which is stored in several forms in most tissues, is required to maintain metabolite homeostasis and other processes, including the visual cycle, energy balance, epithelial cell integrity, and infection resistance. In recent years, VA molecules, also known as retinoids, have been extensively explored and used in the treatment of skin disorders and immune-related tumors. To date, several observational and interventional studies have explored the relationship between VA status and the pathogenesis of diabetes. In particular, VA micronutrients have been shown to regulate pancreatic development, ß-cell function, pancreatic innate immune responses, and pancreatic stellate cells phenotypes through multiple mechanisms. However, there are still many problems to be proven or resolved. In this review, we summarize and discuss recent and available evidence on VA biological metabolism in the pancreas. Analysis of the effects of VA on metabolism in the pancreas will contribute to our understanding of the supportive physiological roles of VA in pancreas protection.

Rapid Changes in Serum Testosterone in Men With Newly Diagnosed Type 2 Diabetes With Intensive Insulin and Metformin.

OBJECTIVE: To investigate the effect of metformin on testosterone levels in men with type 2 diabetes mellitus (T2DM). RESEARCH DESIGN AND METHODS: Seventy men with newly diagnosed drug-naive T2DM and HbA1c >9.0% (75 mmol/mol) were treated with intensive insulin pump therapy for 5 days to achieve glucose normalization. They were randomized to control (continued on intensive insulin only) and metformin (plus metformin) groups (1:1) for 1 month. Testosterone was measured at baseline, randomization, and after 1-month treatment. RESULTS: Total, free, and bioavailable testosterone increased significantly within 5 days (all P < 0.001). After 1 month, compared with the control group, the metformin group had lower total (12.7 vs. 15.3 nmol/L), free (0.20 vs. 0.24 nmol/L), and bioavailable (4.56 vs. 5.31 nmol/L) testosterone (all P < 0.05). CONCLUSIONS: In men with T2DM, 1-month oral metformin may decrease serum testosterone levels independent of blood glucose control. The effects of long-term metformin on testosterone in men need further study.

Needle-free jet injection of insulin glargine improves glycemic control in patients with type 2 diabetes mellitus: a study based on the flash glucose monitoring system.

Background: To investigate the effects of insulin glargine injection given with a QS-P jet injector on the glucose profile using a professional mode flash glucose monitoring (FGM) system in patients with type 2 diabetes mellitus (T2DM).Research design and methods: In this randomized, controlled, cross-sectional study, 66 patients with T2DM who received insulin glargine (12-18 IU/day) injection were enrolled. The patients were randomly divided into group A (jet injector before insulin pen) and group B (insulin pen before jet injector). Each subject injected insulin daily before breakfast. We analyzed the changes in the glucose profile using a professional mode FGM system.Results: Treatment with a jet injector led to significantly lower 24-h mean glucose, maximum blood glucose, area under the curve (AUC) > 10.0 mmol/L, time above range and increased AUC < 3.9 mmol/L and time below range than those when using an insulin pen. There was no difference in glycemic variability between the two groups. We observed that patients using a jet injector had significantly lower mean glucose between 12:00 to 22:00.Conclusions: Needle-free jet injection of insulin glargine was more effective than use of an insulin pen for good glycemic control in patients with T2DM.Clinical trial registration: www.clinicaltrials.gov identifier is NCT04093284.

Effect of Metformin on Testosterone Levels in Male Patients With Type 2 Diabetes Mellitus Treated With Insulin.

Aim: To explore the chronic effects of metformin on testosterone levels in men with type 2 diabetes mellitus (T2DM). Methods: This is a secondary analysis of a real-world study evaluating the efficacy and safety of premixed insulin treatment in patients with T2DM via 3-month intermittent flash glucose monitoring. Male patients aged 18-60 who were using metformin during the 3-month study period were included as the metformin group. The control group included males without metformin therapy by propensity score matching analysis with age as a covariate. Testosterone levels were measured at baseline and after 3-month treatment. Results: After 3-month treatment, the control group had higher levels of total testosterone, free and bioavailable testosterone than those at baseline (P<0.05). Compared with the control group, the change of total (-0.82 ± 0.59 vs. 0.99 ± 0.59 nmol/L) and bioavailable (-0.13 ± 0.16 vs. 0.36 ± 0.16 nmol/L) testosterone levels in the metformin group significantly decreased (P=0.036 and 0.029, respectively). In Glycated Albumin (GA) improved subgroup, the TT, FT, and Bio-T levels in the control subgroup were higher than their baseline levels (P < 0.05). Compared with the metformin subgroup, TT level in the control subgroup also increased significantly (P=0.044). In GA unimproved subgroup, the change of TT level in the metformin subgroup was significantly lower than that in the control subgroup (P=0.040). Conclusion: In men with T2DM, 3-month metformin therapy can reduce testosterone levels, and counteract the testosterone elevation that accompanied with the improvement of blood glucose. Clinical Trial Registration: https://www.clinicaltrials.gov/ct2/show/NCT04847219?term=04847219&draw=2&rank=1.

Relationship Between Estimated Glycosylated Hemoglobin Using Flash Glucose Monitoring and Actual Measured Glycosylated Hemoglobin in a Chinese Population.

INTRODUCTION: The aim of this study was to investigate the relationship between actual measured glycated hemoglobin (HbA1c) and estimated glycated hemoglobin (EA1c) in the flash glucose monitoring (FGM) system in Chinese patients with type 2 diabetes. METHODS: This study was conducted in Nanjing First Hospital. Each patient used FGM twice in a 3-month period (during the first 14 days immediately after baseline and during a second 14-day period from days 76 to 90 after baseline). HbA1c measurements were made using a high-performance liquid chromatography assay before the start of the first FGM period (baseline) and at the end of the second FGM period. RESULTS: A total of 74 patients (35 men; mean age ± standard deviation [SD] 67.6 ± 5.2 years) were enrolled in the study. The mean (± SD) duration of diabetes was 11.9 ± 7.8 months. The first and second HbA1c measurements were both higher than the EA1c (both p < 0.001). Mean glucose (MG) gradually decreased over time and was the lowest on day 14. Linear regression showed that only HbA1c at baseline affected the gap between HbA1c and EA1c (ß = 0.319, p = 0.01) when the educational level, age, gender, duration of diabetes, body mass index, HbA1c at baseline, and number of scans daily were included as independent variables. The best model for calculating EA1c was EA1c% = MG mmol/L × 0.669 - 0.213 × 8th MG + 3.351 when MG > 9.7 mmol/L, and EA1c % = (MG mmol/L + 2.590)/1.590 when MG ≤ 9.7 mmol/L. The correlation coefficient for EA1c and HbA1c in this model (model 7) is higher than that reported the original model in the FGM system 1 (0.955 vs. 0.822, respectively; p < 0.001). CONCLUSIONS: The EA1c used by FreeStyle Libre™ is lower than the actual measured HbA1c. Improvement in the glucose levels during FGM in these patients may contribute to the lowering of EA1c. TRIAL REGISTRATION: The study is registered with ClinicalTrials.gov, number NCT03785301.

The Accuracy and Precision of the Continuously Stored Data from Flash Glucose Monitoring System in Type 2 Diabetes Patients during Standard Meal Tolerance Test.

BACKGROUND: The purpose of this study was to investigate the accuracy of the continuously stored data from the Abbott FreeStyle Libre flash glucose monitoring (FGM) system in Chinese diabetes patients during standard meal tests when glucose concentrations were rapidly changing. Subjects and Methods. Interstitial glucose levels were monitored for 14 days in 26 insulin-treated patients with type 2 diabetes using the FGM system. Standard meal tests were conducted to induce large glucose swings. Venous blood glucose (VBG) was tested at 0, 30, 60, and 120 min after standard meal tests in one middle day of the first and second weeks, respectively. The corresponding sensor glucose values were obtained from interpolating continuously stored data points. Assessment of accuracy was according to recent consensus recommendations with median absolute relative difference (MARD) and Clarke and Parkes error grid analysis (CEG and PEG). RESULTS: Among 208 paired sensor-reference values, 100% were falling within zones A and B of the Clarke and Parkes error grid analysis. The overall MARD was 10.7% (SD, 7.8%). Weighted least squares regression analysis resulted in high agreement between the FGM sensor glucose and VBG readings. The overall MTT results showed that FGM was lower than actual VBG, with MAD of 22.1 mg/dL (1.2 mmol/L). At VBG rates of change of -1 to 0, 0 to 1, 1 to 2, and 2 to 3 mg/dl/min, MARD results were 11.4% (SD, 8.7%), 9.4% (SD, 6.5%), 9.9% (SD, 7.5%), and 9.5% (SD, 7.7%). At rapidly changing VBG concentrations (>3 mg/dl/min), MARD increased to 19.0%, which was significantly higher than slow changing BG groups. CONCLUSIONS: Continuously stored interstitial glucose measurements with the FGM system were found to be acceptable to evaluate VBG in terms of clinical decision during standard meal tests. The continuously stored data from the FGM system appeared to underestimate venous glucose and performed less well during rapid glucose changes.

Contributions of Fasting and Postprandial Glucose Concentrations to Haemoglobin A1c in Drug-Naïve Mal-Glucose Metabolism in Chinese Population Using Continuous Glucose Monitoring System.

AIM: To clarify the contributions of fasting glucose (FG) and postprandial glucose (PG) to HbA1c in drug-naïve patients with type 2 diabetes (T2D) and impaired glucose tolerate (IGT)/impaired fasting glucose (IFG). METHODS: Continuous glucose monitoring (CGM) was performed in 305 drug-naïve Chinese patients with T2D or IGT/IFG. The incremental area under the curve (AUC) above a glucose value of 6.1 mmol/L or FG glucose levels were calculated to evaluate the contributions of PG or FG to HbA1c values. RESULTS: According to quintiles of HbA1c, T2D patients were divided into five groups (group 1 to 5), and patients with IGT/IFG were assigned into group 0. PG was the predominant contributor in the lower groups with HbA1c 4.9∼6.0% and 6.1∼7.8%. The relative contributions of FG and PG to HbA1c had no significance in the middle groups of HbA1c (7.9∼8.7% and 8.8∼9.5%). FG contributed significantly more than PG in the higher groups of HbA1c (9.6∼10.9% and 11.0∼14.6%). Regression analyses indicate that the contributions of FG and PG were equal (both 50%) when the level of HbA1c was 8.5%. CONCLUSIONS: In drug-naïve patients with T2D or IGT/IFG, PG contributed more in patients with HbA1c < 8.5%, whereas FG became the predominant contributor in the poorly controlled patients with HbA1c ≥ 8.5%. These results may help the health-care provider set appropriate plasma glucose testing goals with the expectation of achieving specific HbA1c values.

Glycemic variation in uncontrolled Graves' disease patients with normal glucose metabolism: Assessment by continuous glucose monitoring.

PURPOSE: To observe the glycemic variation (GV) in uncontrolled Graves' disease (GD) patients with normal glucose metabolism measured by continuous glucose monitoring (CGM). METHODS: This was a single-center, open-label, observational study. From January 2017 to October 2017, 20 GD patients with normal glucose metabolism and 24 healthy control subjects were recruited. Serum samples were obtained at 0, 30, and 120 min after oral glucose loading for glucose, insulin, and C-peptide level measurements. Fasting plasma fasting free triiodothyronine (FT3), free thyroxin (FT4), and thyroid stimulating hormone concentrations were also detected. All participants were subjected to a 3-day CGM after baseline data were collected. The primary endpoint was the difference in the mean amplitude of the glycemic excursions between the two groups. RESULTS: Compared with the healthy subjects, the GD patients had higher mean amplitude of glycemic excursions (MAGE) (P < 0.01). Multiple linear stepwise regression analysis showed that FT4 level was an independent factor for the MAGE. Interestingly, the GD patients had a significant prolongation in the time to peak glucose, especially after breakfast (P < 0.01), and the elevation in the incremental area under the curve of glucose after breakfast till 4 hours later. CONCLUSIONS: Uncontrolled GD patients with normal glucose metabolism had a greater GV, and the FT4 level may contributed to the increased GV.

Twenty Minute Moderate-Intensity Post-Dinner Exercise Reduces the Postprandial Glucose Response in Chinese Patients with Type 2 Diabetes.

BACKGROUND Postprandial hyperglycemia and glycemic fluctuations are significant cardiovascular disease risk factors for patients with type 2 diabetes. We investigated the effects of a single session of post-dinner moderate-intensity exercise on the postprandial glycemic response compared with a non-exercise condition in a study population of Chinese patients with type 2 diabetes. MATERIAL AND METHODS This randomized crossover self-controlled pilot study involved 29 patients with type 2 diabetes who participated in post-dinner exercise days using non-exercise days as a control. The interstitial glucose level was monitored using a continuous glucose monitoring system, with a standardized diet and medication. For the non-exercise control days, patients pursued normal daily activities but refrained from unusual strenuous physical activity. On the exercise days, participants walked on a treadmill for 20 minutes after dinner, with a heart rate reserve of 40%. RESULTS Post-dinner moderate-intensity exercise reduced the 2-hour postprandial glucose spike, mean glucose level, and peak glucose level compared to the control condition. The cumulative glucose total area under the curve during 1-hour post-exercise was lower with exercise than under the control condition. The 12-hour standard deviation of blood glucose and the coefficient variation of glucose were significantly lower in the with exercise day compared to the control day, although the 12-hour mean amplitude of glycemic fluctuations did not reach statistical significance. No nocturnal hypoglycemia subsequently occurred on the exercise day. CONCLUSIONS A short session of moderate-intensity post-dinner exercise can improve postprandial hyperglycemia and glycemic excursions in Chinese patients with type 2 diabetes, with no potential hypoglycemia risk at a later period.

Metformin add-on continuous subcutaneous insulin infusion on precise insulin doses in patients with type 2 diabetes.

To investigate whether metformin add-on to the continuous subcutaneous insulin infusion (Met + CSII) therapy leads to a significant reduction in insulin doses required by type 2 diabetes (T2D) patients to maintain glycemic control, and an improvement in glycemic variation (GV) compared to CSII only therapy. We analyzed data from our two randomized, controlled open-label trials. Newly diagnoses T2D patients were randomized assigned to receive either CSII therapy or Met + CSII therapy for 4 weeks. Subjects were subjected to a 4-day continuous glucose monitoring (CGM) at the endpoint. Insulin doses and GV profiles were analyzed. The primary endpoint was differences in insulin doses and GV between the two groups. A total of 188 subjects were admitted as inpatients. Subjects in metformin add-on therapy required significantly lower total, basal and bolus insulin doses than those of control group. CGM data showed that patients in Met + CSII group exhibited significant reduction in the 24-hr mean amplitude of glycemic excursions (MAGE), the standard deviation, and the coefficient of variation compared to those of control group. Our data suggest that metformin add-on to CSII therapy leads to a significant reduction in insulin doses required by T2D patients to control glycemic variations.

The real world of blood glucose point-of-care testing (POCT) system running in China teaching hospital.

BACKGROUND:  The blood glucose point-of-care testing (POCT) system is important in the decision-making process involving patients suspected of having hypoglycemia. To investigate the real world of the POCT system being used in teaching hospitals in China. METHODS: The survey was conducted by Hisend Research Group from May 2015 to July 2015 in four teaching hospitals in China. The survey questions were referred to the ISO 15197:2013 standard requirements for the use of the POCT system in a hospital setting. RESULTS: A total of 170 subjects were included from 4 hospitals, which included nursing staff, nurse unit managers, employees from the department of medical instruments, and staff members employed by the clinical laboratories in the Tianjin Metabolism Hospital, Nanjing First Hospital, First Affiliated Hospital of Dalian Medical University, and the First hospital affiliated with the Xi'an Transportation University. The average score for the four hospitals surveyed in this study was 66.6, which varied from 46.1 to 79.7. The main factors influencing the scores were the multiple choices of blood-glucose meters, and the quality control assessment. CONCLUSION: Our data indicates that the real world use of the POCT system in hospital settings in China needs more closer adherence to a quality management framework.