The study primarily aims to compare alterations in the daily patterns of glucose fluctuations across individuals with different kinds of diabetes in pregnancy and secondly investigate influencing factors that may react with glucose variations.

We conducted a retrospective cohort study of 776 pregnant women in Shanghai General Hospital. We grouped participants who were exposed to gestational hyperglycemia into 5 sub-groups [Type 1 diabetes (T1DM), Type 2 diabetes (T2DM), Overt diabetes, Gestational diabetes (GDMA1 and GDMA2). Demographic variables and GV parameters were compared among 5 groups through ANOVA-test and Chi-square test. We estimated odd ratios (ORs) for the association between glucose coefficient of variation (CV) and possible influencing variables.

A final total of 776 pregnant women were analyzed. The proportion of pregnant women with pre-gestational diabetes was 31.83% (T1DM: 3.35%,T2DM: 28.48%), ODM 26.68%, and GDM was 41.49% (GDMA1:18.04%, GDMA2: 23.45%). T1DM group performed greatest glucose fluctuations with a CV value 35.02% whereas the number in all the other groups was no more than 22.82% (ODM group). In terms of achieving glycemic control target, only 57.70% participants hit the goal while all the other groups achieved the standard with at least a percentage of 94.20% (ODM group). Other parameters (GMI < 6.0%, GA < 15.70% and HbA1c < 6.0%) showed similar trends in each group. On multivariate logistic regression analysis of possible factors influencing CV, only body mass index (BMI) (OR: 0.754, 95% CI: 0.585-0.971; P = 0.029), HOMA- β (OR:0.969, 95%CI: 0.959-0.976; P = 0.037) and fasting plasma glucose (FPG) (OR: 1.832, 95% CI: 1.170-2.870; P = 0.008) reached statistical significance.

Pregnant women with type 1 or type 2 diabetes exhibit significantly greater glycemic variability compared to those with gestational diabetes, with the ODM group showing intermediate variability, and BMI, HOMA-β, and FPG identified as independent risk factors for unstable glucose variability.

The preservation of islet β-cell function in elderly patients with type 2 diabetes mellitus (T2DM) is a top priority for diabetic control.

To assess the preservation of islet β-cell function among elderly Chinese patients with T2DM after different anti-diabetic treatments.

In this longitudinal observational study, elderly patients with T2DM treated with insulin, oral antidiabetic drugs or a combination of both were enrolled to disclose their islet β-cell function between baseline and follow-up. Islet β-cell function was determined by the plasma Homeostasis Model for β-cell function (HOMA-β), C-peptide and area under the curve (AUC) based on oral glucose tolerance test. Changes in β-cell function (decrement or increment from baseline) between different therapy groups were the outcomes.

In total, 745 elderly patients (≥ 60 years) with T2DM [insulin monotherapy, n = 105; oral anti-diabetic drugs (OAD) monotherapy, n = 321; insulin plus OAD, n = 319] had their baseline and follow-up β-cell function assessed during a median observation period of 4.5 years (range, 3.0-7.2 years). Overall, islet β-cell function (HOMA-β, fasting C-peptide, fasting insulin, AUCc-pep, AUCins, AUCc-pep/AUCglu, AUCins/AUCglu) consistently deteriorated over time regardless of the three different antidiabetic treatments. No statistical differences in decrement were observed among the three groups regarding the islet β-cell function indices. All three groups showed an increased ratio of delayed insulin secretion response after 4.5 years of observation.

In Chinese elderly patients with T2DM, islet β-cell function progressively declines regardless of insulin supplement or insulin plus OAD treatments.

To evaluate whether the intense simplified strategy, which comprises short term intensive insulin therapy (SIIT) followed by subsequent oral antihyperglycaemic regimens, could improve long term glycaemic outcomes in patients with newly diagnosed type 2 diabetes mellitus and severe hyperglycaemia.

Multicentre, open label, randomised trial.

15 hospitals in China between December 2017 and December 2020.

412 patients with newly diagnosed type 2 diabetes and significant hyperglycaemia (HbA1c ≥8.5%).

All randomised participants initially received SIIT for 2-3 weeks, followed by linagliptin 5 mg/day, metformin 1000 mg/day, combination linagliptin plus metformin, or lifestyle modification alone (control) for 48 weeks.

The primary outcome was the percentage of participants achieving HbA1c <7.0% at week 48 after SIIT. Secondary outcomes included glycaemic control, β cell function, and variations in insulin sensitivity.

412 participants were randomised. At baseline, the mean age was 46.8 (standard deviation 11.2) years, mean body mass index was 25.8 (2.9), and mean HbA1c was 11.0% (1.9%). At week 48, 80% (78/97), 72% (63/88), and 73% (69/95) of patients in the linagliptin plus metformin, linagliptin, and metformin groups, respectively, achieved HbA1c <7.0%, compared with 60% (56/93) in the control group (P=0.02 overall; P=0.003 for linagliptin plus metformin versus control; P=0.12 for linagliptin versus control; P=0.09 for metformin versus control). Additionally, 70% (68/97), 68% (60/88), and 68% (65/95) of patients in the linagliptin plus metformin, linagliptin, and metformin group, respectively, achieved HbA1c <6.5% compared with 48% (45/93) in the control group (P=0.005 overall; P=0.005 for linagliptin plus metformin versus control; P=0.01 for linagliptin versus control; P=0.008 for metformin versus control; all were significant after adjustment for multiple comparisons). Thus, compared with the control group, participants in the linagliptin plus metformin group were more likely to achieve HbA1c <7.0% at week 48 (odds ratio 2.78, 95% confidence interval 1.37 to 5.65; P=0.005). Moreover, the linagliptin plus metformin group showed the most significant improvement in fasting plasma glucose and β cell function indices. All treatments were well tolerated.

The intense simplified strategy using subsequent oral therapies post-SIIT, especially the linagliptin plus metformin combination, sustainably improved glycaemic control and β cell function in patients with newly diagnosed type 2 diabetes mellitus and severe hyperglycaemia. This approach offers a promising direction for decision making in the clinical management of type 2 diabetes mellitus.

ClinicalTrials.gov NCT03194945.

To explore parameters that may determine the improvement in C-peptide levels in patients with type 2 diabetes (T2D) receiving continuous subcutaneous insulin infusion (CSII) therapy.

The trial included a lead-in period for collecting baseline parameters and correcting hyperglycemia, a 4-day CGM period, and a 2-3 weeks treatment period. After screening, patients were hospitalized and randomized to the metformin add-on NovoRapid group or the Prandilin group. Once the glycemic target was reached, all patients underwent a 4-day CGM, with treatments maintained for 2-3 weeks. OGTTs were performed at baseline and endpoint. The primary endpoint was identifying factors contributing to better β-cell function recovery after CSII therapy.

A total of 99 recruited patients were admitted as inpatients and achieved glycemic control within 3.8 ± 1.1 days. Of these, 83 (84 %) patients showed improvement in C-peptide levels, while 16 (16 %) did not show any change in C-peptide levels at the endpoint. Pearson analysis showed a negative correlation between the incremental AUC of glucose concentration (from 0700 to 1000) and the increase in incremental AUC of C-peptide levels (r = -0.199, P < 0.05).

Drug-naïve T2D patients with lower postprandial glucose concentration during CSII therapy exhibit better β-cell function recovery.

There is little information on factors that influence the glycemic variability (GV) during the nocturnal and diurnal periods. We aimed to examine the relationship between clinical factors and GV during these two periods.

This cross-sectional study included 134 patients with type 2 diabetes. 24-h changes in blood glucose were recorded by a continuous glucose monitoring system. Nocturnal and diurnal GV were assessed by standard deviation of blood glucose (SDBG), coefficient of variation (CV), and mean amplitude of glycemic excursions (MAGE), respectively. Robust regression analyses were performed to identify the factors associated with GV. Restricted cubic splines were used to determine dose-response relationship.

During the nocturnal period, age and glycemic level at 12:00 A.M. were positively associated with GV, whereas alanine aminotransferase was negatively associated with GV. During the diurnal period, homeostatic model assessment 2-insulin sensitivity (HOMA2-S) was positively associated with GV, whereas insulin secretion-sensitivity index-2 (ISSI2) was negatively associated with GV. Additionally, we found a J-shape association between the glycemic level at 12:00 A.M. and MAGE, with 9.0 mmol/L blood glucose level as a cutoff point. Similar nonlinear associations were found between ISSI2 and SDBG, and between ISSI2 and MAGE, with ISSI2 value of 175 as a cutoff point.

Factors associated with GV were different between nocturnal and diurnal periods. The cutoff points we found in this study may provide the therapeutic targets for beta-cell function and pre-sleep glycemic level in clinical practice.

To assess whether the beta-cell function of inpatients undergoing antidiabetic treatment influences achieving time in range (TIR) and time above range (TAR) targets.

This cross-sectional study included 180 inpatients with type 2 diabetes. TIR and TAR were assessed by a continuous glucose monitoring system, with target achievement defined as TIR more than 70% and TAR less than 25%. Beta-cell function was assessed by the insulin secretion-sensitivity index-2 (ISSI2).

Following antidiabetic treatment, logistic regression analysis showed that lower ISSI2 was associated with a decreased number of inpatients achieving TIR (OR = 3.10, 95% CI: 1.19-8.06) and TAR (OR = 3.40, 95% CI: 1.35-8.55) targets after adjusting for potential confounders. Similar associations still existed in those participants treated with insulin secretagogues (TIR: OR = 2.91, 95% CI: 0.90-9.36, P = .07; TAR, OR = 3.14, 95% CI: 1.01-9.80) or adequate insulin therapy (TIR: OR = 2.84, 95% CI: 0.91-8.81, P = .07; TAR, OR = 3.24, 95% CI: 1.08-9.67). Furthermore, receiver operating characteristic curves showed that the diagnostic value of the ISSI2 for achieving TIR and TAR targets was 0.73 (95% CI: 0.66-0.80) and 0.71 (95% CI: 0.63-0.79), respectively.

Beta-cell function was associated with achieving TIR and TAR targets. Stimulating insulin secretion or exogenous insulin treatment could not overcome the disadvantage of lower beta-cell function on glycaemic control.

Elevated C-peptide has been suggested as a risk factor for coronary artery disease (CAD). Elevated urinary C-peptide to creatinine ratio (UCPCR) as an alternative measurement is shown to be related to insulin secretion dysfunction; however, data regarding UCPCR predictive value for CAD in diabetes mellitus (DM) are scarce. Therefore, we aimed to assess the UCPCR association with CAD in type 1 DM (T1DM) patients.

279 patients previously diagnosed with T1DM included and categorized into two groups of CAD (n = 84) and without-CAD (n = 195). Furthermore, each group was divided into obese (body mass index (BMI) ≥ 30) and non-obese (BMI < 30) groups. Four models utilizing the binary logistic regression were designed to evaluate the role of UCPCR in CAD adjusted for well-known risk factors and mediators.

Median level of UCPCR was higher in CAD group compared to non-CAD group (0.07 vs. 0.04, respectively). Also, the well-acknowledged risk factors including being active smoker, hypertension, duration of diabetes, and body mass index (BMI) as well as higher levels of haemoglobin A1C (HbA1C), total cholesterol (TC), low-density lipoprotein (LDL) and estimated glomeruli filtration rate (e-GFR) had more significant pervasiveness in CAD patients. Based on multiple adjustments by logistic regression, UCPCR was a strong risk factor of CAD among T1DM patients independent of hypertension, demographic variables (gender, age, smoking, alcohol consumption), diabetes-related factors (diabetes duration, FBS, HbA1C), lipid profile (TC, LDL, HDL, TG) and renal-related indicators (creatinine, e-GFR, albuminuria, uric acid) in both patients with BMI≥30 and BMI < 30.

UCPCR is associated with clinical CAD, independent of CAD classic risk factors, glycaemic control, insulin resistance and BMI in type 1 DM patients.

Patients with type 2 diabetes mellitus (T2DM) usually have higher blood viscosity attributed to high blood glucose that can decrease blood supply to the pancreas. A mild increase in blood pressure (BP) has been reported as a potential compensatory response that can maintain blood perfusion in the islet. However, how BP influences beta-cell function in T2DM subjects remains inconsistent. This study aimed to examine the relationship between BP and beta-cell function in patients with T2DM under different HbA1c levels.

This is a cross-sectional study of 615 T2DM patients, whose clinical data were extracted from hospital medical records. Beta-cell function was assessed by insulin secretion-sensitivity index-2 (ISSI2). Multivariable linear regression analysis and restricted cubic splines (RCS) analysis were performed to identify the association between systolic BP (SBP) and ISSI2. Mediation analysis was performed to determine whether higher SBP could reduce blood glucose by enhancing beta-cell function.

After adjustment of potential confounders, in participants with HbA1c ≥ 10%, the SBP between 140 to150 mmHg had the highest log ISSI2 (b = 0.227, 95% CI 0.053-0.402), an association specific to participants with < 1 year duration of diabetes. RCS analyses demonstrated an inverted U-shaped association between SBP and ISSI2 with the SBP at 144 mmHg corresponding to the best beta-cell function. This higher SBP was "paradoxically" associated with lower 2 h postprandial blood glucose (PBG) when SBP < 150 mmHg that was almost exclusively mediated by ISSI2 (mediating effect = - 0.043, 95%CI - 0.067 to - 0.018; mediating effect percentage = 94.7%, P < 0.01). SBP was however not associated with improvement in ISSI2 or 2 h PBG in participants with HbA1c < 10%.

In early stage of diabetes, a slightly elevated SBP (140-150 mmHg) was transiently associated with better beta-cell function in T2DM patients with HbA1c ≥ 10% but not in those with HbA1c < 10%.

To examine the effect of different patterns of durable glycemic control on the development of comorbidities among youth with type 2 diabetes (T2D) and to assess the impact of fasting glucose (FG) variability on the clinical course of T2D.

From the Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) study, 457 participants (mean age, 14 years) with mean diabetes duration <2 years at entry and a minimum study follow-up of 10 years were included in these analyses. HbA1c, FG concentrations, and β-cell function estimates from oral glucose tolerance tests were measured longitudinally. Prevalence of comorbidities by glycemic control status after 10 years in the TODAY study was assessed.

Higher baseline HbA1c concentration, lower β-cell function, and maternal history of diabetes were strongly associated with loss of glycemic control in youth with T2D. Higher cumulative HbA1c concentration over 4 years and greater FG variability over a year within 3 years of diagnosis were related to higher prevalence of dyslipidemia, nephropathy, and retinopathy progression over the subsequent 10 years. A coefficient of variability in FG ≥8.3% predicted future loss of glycemic control and development of comorbidities.

Higher baseline HbA1c concentration and FG variability during year 1 accurately predicted youth with T2D who will experience metabolic decompensation and comorbidities. These values may be useful tools for clinicians when considering early intensification of therapy.

We performed a comprehensive review of recent publications about type 2 diabetes mellitus (T2DM) in Peru, including studies among people living at high altitude above the sea level. An increase in the prevalence of T2DM in Peru has been reported, the reasons are multifactorial and coinciding with the strong economic growth that our country has experienced over the last 20 years along with migration from the Andean regions to the coast and the adoption of a lifestyle that is a known to be a risk factor for obesity and insulin resistance. Scarce information is available in Peru about the prevalence of chronic complications of T2DM such as retinopathy, neuropathy, and nephropathy. There is a need for a health care plan based on early diagnosis of T2DM to reduce social and economic problems, as recommended by the WHO and the United Nations.

We estimated the hazards of cardiovascular diseases (CVDs) and early all-cause mortality in Korean adults according to the presence of recently diagnosed type 2 diabetes (type 2 diabetes for <5 years) and insulin use.

We used the Korean National Health Insurance Service-National Sample Cohort database (2002-2015) for this longitudinal population-based study. Among adults aged ≥40 years without baseline CVD, individuals without diabetes or with recently diagnosed type 2 diabetes were selected (N = 363,919). The hazard ratios (HRs) for myocardial infarction (MI), stroke, and all-cause mortality during follow-up were analyzed according to three groups categorized by the presence of type 2 diabetes and insulin use.

Within a mean 7.8 years, there were 5,275 MIs, 7,220 strokes, and 15,834 deaths. The hazards for outcomes were higher in the insulin-treated type 2 diabetes group than in the non-diabetes group [HR (95% CI): 2.344 (1.870-2.938) for MI, 2.420 (1.993-2.937) for stroke, and 3.037 (2.706-3.407) for death], higher in the non-insulin-treated type 2 diabetes group than in the non-diabetes group [HR (95% CI): 1.284 (1.159-1.423) for MI, 1.435 (1.320-1.561) for stroke, and 1.135 (1.067-1.206) for death], and higher in the insulin-treated type 2 diabetes group than in the non-insulin-treated type 2 diabetes group [HR (95% CI): 1.914 (1.502-2.441) for MI, 1.676 (1.363-2.060) for stroke, and 2.535 (2.232-2.880) for death].

Recently diagnosed type 2 diabetes patients showed increased risks of incident CVDs and premature mortality, and insulin-treated group demonstrated an additional increase in the risks of these outcomes in adults with recently diagnosed type 2 diabetes, suggesting the need for intensified cardio-protective interventions for adults with insulin-treated type 2 diabetes.

Deterioration of sleep quality has been reported to contribute to the incidence of diabetes and may be responsible for glycemic status in diabetes. The present study explored the relationship between sleep quality and glycemic variability in patients with type 2 diabetes (T2D).

We recruited 111 patients with T2D for this cross-sectional study. Each patient underwent flash glucose monitoring for 14 days to obtain glycemic variability parameters, such as standard deviation of glucose (SD), coefficient of variation of glucose (CV), mean amplitude of glycemic excursions (MAGE), mean of daily differences (MODD), and time in glucose range of 3.9-10 mmol/L (TIR_3.9-10). After 14 days of flash glucose monitoring, each patient received a questionnaire on the Pittsburgh Sleep Quality Index (PSQI) to evaluate subjective sleep quality. HbA1c was also collected to assess average glucose.

HbA1c was comparable among the subgroups of PSQI score tertiles. Across ascending tertiles of PSQI scores, SD, CV and MAGE were increased, while TIR_3.9-10 was decreased (p for trend  <  0.05), but not MODD (p for trend  =  0.090). Moreover, PSQI scores were positively correlated with SD, CV, MODD and MAGE (r =  0.322, 0.361, 0.308 and 0.354, respectively, p  <  0.001) and were inversely correlated with TIR_3.9-10 (r  =  - 0.386, p  <  0.001). After adjusting for other relevant data by multivariate linear regression analyses, PSQI scores were independently responsible for SD (β  =  0.251, t  =  2.112, p  =  0.041), CV (β  =  0.286, t  =  2.207, p  =  0.033), MAGE (β  =  0.323, t  =  2.489, p  =  0.018), and TIR_3.9-10 (β  =  - 0.401, t  =  - 3.930, p  <  0.001) but not for MODD (β  =  0.188, t  =  1.374, p  =  0.177).

Increased glycemic variability assessed by flash glucose monitoring was closely associated with poor subjective sleep quality evaluated by the PSQI in patients with T2D.

Oscillating glucose levels can increase oxidative stress and may contribute to β-cell dysfunction. We tested the hypothesis that increased glycemic variability contributes to β-cell dysfunction by experimentally altering glucose variability with controlled diets varying in glycemic index (GI). Fifty-two adults with prediabetes received a 2-week moderate GI (GI = 55-58) control diet followed by randomization to a four-week low GI (LGI: GI < 35) or high GI (HGI HI > 70) diet. Those on the HGI diet were randomized to placebo or the antioxidant N-acetylcysteine (NAC). Participants underwent blinded CGMS, fasting oxidative stress markers and an intravenous glucose tolerance test to estimate β-cell function (disposition index: DI). On the control diet, DI was inversely correlated with SD glucose (r = -0.314, p = 0.03), but neither DI nor glucose variability were associated with oxidative stress markers. The LGI diet decreased SD glucose (Control 0.96 ± 0.08 vs. LGI 0.79 ± 0.06, p = 0.02) while the HGI diet increased it (Control 0.88 ± 0.06 vs. HGI 1.06 ± 0.07, p = 0.03). Neither DI nor oxidative stress markers changed after the LGI or HGI diets. NAC had no effect on DI, glucose variability or oxidative stress markers. We conclude small changes in glucose variability induced by dietary GI in adults with pre-diabetes are unlikely to contribute to β-cell dysfunction.

Glycemic control plays an important role in diabetes management, and self-monitoring of blood glucose (SMBG) is critical to achieving good glycemic control. However, there are few studies about the relationship between SMBG-estimated glycemic indices and β-cell function. Here we investigated the association between glucose variation indices estimated by SMBG and β-cell function among Chinese patients with type 2 diabetes mellitus (T2DM).

In this cross‑sectional study, 397 patients with T2DM were recruited from February 2015 to October 2016. β-cell function was monitored using the Homeostasis Model Assessment 2 (HOMA2)-%β index. The parameters evaluated by SMBG were the mean blood glucose (MBG), standard deviation of MBG (SDBG), largest amplitude of glycemic excursions (LAGE), and postprandial glucose excursion (PPGE).

HOMA2-%β was negatively correlated with SDBG, LAGE, PPGE, and MBG (r = -0.350, -0.346, -0.178, and -0.631, respectively; all p < 0.01). After adjusting for confounding characteristics (diabetic duration, triglyceride, total cholesterol, fasting C-peptide, HOMA2-insulin resistance index, hypoglycemia, and diabetic treatments) and glycated hemoglobin A1c on a continuous scale, odds ratios of SDBG, LAGE, PPGE, and MBG between the patients in the lowest and highest HOMA2-%β quartiles were 2.02 (1.14-3.57), 1.24 (1.04-1.49), 1.13 (0.86-1.51), and 2.26 (1.70-3.00). HOMA2-%β was independently associated with SDBG, LAGE, and MBG.

Increased SDBG and LAGE assessed by SMBG are associated with β-cell dysfunction in Chinese patients with T2DM.

The association between β-cell function and glycemic variability remains to be clarified in insulin-treated patients with type 2 diabetes. Therefore, the study sought to examine the association of various indices of β-cell function with glycemic variability in Chinese insulin-treated patients with type 2 diabetes.

Glycemic variability was assessed by the coefficient of variation (CV) of glucose levels with the use of continuous glucose monitoring (CGM). Basal β-cell function was evaluated by fasting C-peptide (FCP) and the homeostasis model assessment 2 for β-cell function (HOMA2-%β). Postload β-cell function was measured by 2-hour C-peptide (2hCP) and the acute C-peptide response (ACPR) to arginine.

When a cutoff value of CV ≥ 36% was used to define unstable glucose, the multivariable-adjusted odds ratios for labile glycemic control were 0.34 (95% CI 0.18-0.64) for each 1 ng/mL increase in ACPR, 0.47 (95% CI 0.27-0.81) for each 1 ng/mL increase in FCP, 0.77 (95% CI 0.61-0.97) for each 1 ng/mL increase in 2hCP, and 1.00 (95% CI 0.98-1.01) for each 1% increase in HOMA2-%β. When we further adjusted for 2hCP and HOMA2-%β in the ACPR and FCP analyses, and adjusted for ACPR or FCP in the 2hCP analyses, only ACPR but not FCP or 2hPC remained to be a significant and inverse predictor for labile glycemic control.

ACPR evaluated by the arginine stimulation test may be superior to other commonly used β-cell function parameters to reflect glycemic fluctuation in insulin-treated patients with type 2 diabetes.

Our aim was to investigate the effects of add-on canagliflozin with glimepiride dose adjustment or glimepiride dose adjustment on pancreatic beta cell function in patients with type 2 diabetes mellitus and inadequate glycemic control despite stable triple therapy (metformin, teneligliptin, and glimepiride) plus diet/exercise therapy.

Forty patients on stable triple therapy were randomized to glimepiride dose adjustment without (glimepiride group) or with add-on canagliflozin 100 mg (canagliflozin group) for 24 weeks. The glimepiride dose was adjusted every 4 weeks based on continuous glucose monitoring over the previous 2 weeks according to a prespecified algorithm. After the 24-week treatment period, the patients returned to the pre-intervention regimen for 1 week (wash-out period). Patients underwent 75 g OGTTs at the start of the run-in period and at the end of the wash-out period. The primary endpoint was the change in disposition index (DI).

Thirty-nine patients completed the study (canagliflozin, n = 19; glimepiride, n = 20). The change in DI was +5.1% and -11.0% in the canagliflozin and glimepiride groups, respectively, with a between-group difference ratio of 18.0% (P = 0.330). HbA1c, fasting plasma glucose, body weight, and daily-life continuous glucose monitoring-derived parameters improved in the canagliflozin group. Hypoglycemia occurred in 60% (44 episodes) and 70% (79 episodes) of patients in the canagliflozin and glimepiride groups, respectively. The change in DI was significantly correlated with the changes in glycemic control and variability in overall cohort.

Adding canagliflozin to the triple therapy improved beta cell function by 18%, but it did not reach statistical significance. This study also demonstrated a correlation between the change in DI and glycemic control. As canagliflozin improved both glucose level and variability with relatively lower risk of hypoglycemia compared with glimepiride dose adjustment, adding canagliflozin to the triple therapy may be clinically beneficial.

UMIN000030208/jRCTs051180036.

Testosterone affects insulin resistance, but the effect of testosterone treatment on type 2 diabetes (T2D) remains controversial. We aimed to investigate the association between circulating total testosterone (TT) and glycaemic variability using continuous glucose monitoring (CGM) in patients with T2D.

A total of 248 men with T2D were enrolled in the study. Clinical characteristics and plasma for glycated haemoglobin (HbA1c) and C-peptide assessment were collected. TT was measured using a chemiluminescent immunometric assay. All patients were subjected to a 3-day CGM before making adjustments for hypoglycaemic therapy.

TT positively correlated with the standard deviation of mean blood glucose (SDBG) (P < 0.05), especially in older patients. Linear regression analysis showed that SDBG was associated with HbA1c (β = 0.354, P < 0.001) and TT (β = 0.164, P = 0.008) after adjusting for age, duration of diabetes, body mass index, fasting/postprandial C-peptide, and use of different hypoglycaemic drugs. The cut-off value of TT for predicting glycaemic variability was 14.76 mmol/L according to receiver operating characteristic (ROC) analysis. SDBG, the coefficient of variation, the incremental area under the curve of glucose (AUC) > 10 mmol/L, and AUC night were increased in the group with TT > 14.76 nmol/L (P < 0.01 for all variables). Body mass index and fasting/postprandial C-peptide were lower in the group with TT > 14.76 nmol/L than in the group with TT ≤ 14.76 nmol/L (P < 0.05).

Circulating TT levels should be assessed in patients with T2D in addition to HbA1c for predicting glycaemic variability. More frequent blood glucose monitoring or CGM is suggested for patients with T2D and high testosterone levels.

NCT03519529, ClinicalTrials.gov.

Short-term intensive insulin therapy (IIT) early in the course of type 2 diabetes acutely improves beta-cell function with long-lasting effects on glycemic control. However, conventional measures cannot determine which patients are better suited for IIT, and little is known about the molecular mechanisms determining response. Therefore, this study aimed to develop a model that could accurately predict the response to IIT and provide insight into molecular mechanisms driving such response in humans.

Twenty-four patients with early type 2 diabetes were assessed at baseline and four weeks after IIT, consisting of basal detemir and premeal insulin aspart. Twelve individuals had a beneficial beta-cell response to IIT (responders) and 12 did not (nonresponders). Beta-cell function was assessed by multiple methods, including Insulin Secretion-Sensitivity Index-2. MicroRNAs (miRNAs) were profiled in plasma samples before and after IIT. The response to IIT was modeled using a machine learning algorithm and potential miRNA-mediated regulatory mechanisms assessed by differential expression, correlation, and functional network analyses (FNA).

Baseline levels of circulating miR-145-5p, miR-29c-3p, and HbA1c accurately (91.7%) predicted the response to IIT (OR = 121 [95% CI: 6.7, 2188.3]). Mechanistically, a previously described regulatory loop between miR-145-5p and miR-483-3p/5p, which controls TP53-mediated apoptosis, appears to also occur in our study population of humans with early type 2 diabetes. In addition, significant (fold change > 2, P < 0.05) longitudinal changes due to IIT in the circulating levels of miR-138-5p, miR-192-5p, miR-195-5p, miR-320b, and let-7a-5p further characterized the responder group and significantly correlated (|r| > 0.4, P < 0.05) with the changes in measures of beta-cell function and insulin sensitivity. FNA identified a network of coordinately/cooperatively regulated miRNA-targeted genes that potentially drives the IIT response through negative regulation of apoptotic processes that underlie beta cell dysfunction and concomitant positive regulation of proliferation.

Responses to IIT in people with early type 2 diabetes are associated with characteristic miRNA signatures. This study represents a first step to identify potential responders to IIT (a current limitation in the field) and provides important insight into the pathophysiologic determinants of the reversibility of beta-cell dysfunction. ClinicalTrial.gov identifier: NCT01270789.

Although increasing evidence suggests the association between short-term variability of fasting plasma glucose (FPG) and diabetic complications or mortality, the impact of visit-to-visit variability of FPG on the development of type 2 diabetes (T2D) has not been evaluated.

Our analysis included 131,744 Korean men and women without diabetes using the Korean National Health Insurance System cohort with periodic health examination program. FPG variability was calculated using the coefficient of variation (FPG-CV), SD (FPG-SD), and variability independent of the mean (FPG-VIM).

During the median follow-up time of 8.3 years, Kaplan-Meier curves demonstrated lower disease-free probability in the higher FPG variability group compared with the lower FPG variability group. Multivariable Cox proportional hazards analysis exhibited that the hazard ratio for incident T2D was 1.67 (95% CI 1.58-1.77, P < 0.001) in the highest quartile of FPG-CV compared with the lowest quartile of FPG-CV after adjusting for confounding variables, including mean FPG. The association between FPG variability and the risk of T2D was consistent when modeling using FPG-SD and FPG-VIM in both normal and impaired fasting glucose groups. A 1 SD increase in the FPG-CV was associated with a 24% increased risk of T2D in the fully adjusted model.

Increased variability of FPG is associated with the development of T2D independently of diverse risk factors.

Diabetes mellitus represents a major risk factor for the development of coronary artery disease and other vascular complications. Glycated haemoglobin, fructosamine, and fasting blood glucose levels are partial parameters to exhaustively describe patient dysglycemic status. Thus, recently the new concept of glycemic variability has emerged, including information about two major aspects: the magnitude of blood glucose excursions (from nadir to peak, thus lower and higher spikes) and the time intervals in which these fluctuations occur. Despite the lack of consensus regarding the most appropriate definition and tools for its assessment, glycemic variability seems to have more deleterious effects than sustained hyperglycemia in the pathogenesis of diabetic cardiovascular complications. This manuscript aimed to review the most recent evidence on glycemic variability and its potential use in everyday clinical practice to identify diabetic patients at higher risk of cardiovascular complications and thus needing stricter monitoring and treatment.

To assess and compare the effect of small doses of fructose and allulose on postprandial blood glucose regulation in type 2 diabetes.

A double-blind, multiple-crossover, randomized, controlled, acute feeding, equivalence trial in 24 participants with type 2 diabetes was conducted. Each participant was randomly assigned six treatments separated by >1-week washouts. Treatments consisted of fructose or allulose at 0 g (control), 5 g or 10 g added to a 75-g glucose solution. A standard 75-g oral glucose tolerance test protocol was followed with blood samples at -30, 0, 30, 60, 90 and 120 minutes. The primary outcome measure was plasma glucose incremental area under the curve (iAUC).

Allulose significantly reduced plasma glucose iAUC by 8% at 10 g compared with 0 g (717.4 ± 38.3 vs. 777.5 ± 39.9 mmol × min/L, P = 0.015) with a linear dose response gradient between the reduction in plasma glucose iAUC and dose (P = 0.016). Allulose also significantly reduced several related secondary and exploratory outcome measures at 5 g (plasma glucose absolute mean and total AUC) and 10 g (plasma glucose absolute mean, absolute and incremental maximum concentration [Cmax ], and total AUC) (P < .0125). There was no effect of fructose at any dose. Although allulose showed statistically significant reductions in plasma glucose iAUC compared with fructose at 5 g, 10 g and pooled doses, these reductions were within the pre-specified equivalence margins of ±20%.

Allulose, but not fructose, led to modest reductions in the postprandial blood glucose response to oral glucose in individuals with type 2 diabetes. There is a need for long-term randomized trials to confirm the sustainability of these improvements.

High-normal thyrotropin (TSH) is related to reduced insulin sensitivity and may contribute to glycemic disorders in diabetes. We investigated the relationship between normal serum TSH levels and glycemic variability in euthyroid type 2 diabetic patients.

A total of 432 newly diagnosed type 2 diabetic patients with euthyroid function and normal serum TSH levels were recruited between March 2013 and February 2017. Insulin sensitivity was evaluated by the Matsuda index (ISI_Matsuda) following a 75-g oral glucose tolerance test. Multiple glycemic variability indices, including the mean amplitude of glycemic excursions (MAGE), mean of daily differences (MODD), and standard deviation of glucose (SD), were calculated from glucose data obtained with a continuous glucose monitoring system. Average glucose accessed by 24-h mean glucose (24-h MG) was also calculated.

A normal serum TSH level was positively correlated with MAGE, MODD, SD, and 24-h MG (r = 0.206, 0.178, 0.186, and 0.132, respectively, p < 0.01). After adjusting for somatometric parameters, lipid profiles, ISI_Matsuda, and HbA1c via multiple linear regression analysis, mean differences [B(95% CI)] in MAGE, MODD, SD, and 24-h MG between the patients in the lowest and highest quartiles of TSH levels were 0.128(0.031, 0.226), 0.085(0.022, 0.148), 0.039(0.001, 0.078), and 0.002(-0.264, 0.267) mmol/L, respectively. High-normal TSH was independently associated with MAGE, MODD, and SD, but not 24-h MG.

High-normal serum TSH is a significant additional risk factor for increased glycemic variability in type 2 diabetic patients.

Previous studies have indicated that the pathogenesis of diabetes differs between obese and lean patients. We investigated whether newly diagnosed Chinese diabetic patients with different body mass indices (BMIs) have different glycemic variability, and we assessed the relationship between BMI and glycemic variability. This was a cross-sectional study that included 169 newly diagnosed and drug-naïve type 2 diabetic patients (mean age, 51.33 ± 9.83 years; 110 men). The clinical factors and results of the 75-g oral glucose tolerance test were all recorded. Glycemic variability was assessed using continuous glucose monitoring. Compared with overweight or obese patients (BMI ≥ 24 kg/m2), underweight or normal-weight patients (BMI < 24 kg/m2) had higher levels of blood glucose fluctuation parameters, particularly in terms of mean amplitude of glycemic excursion (MAGE 6.64 ± 2.38 vs. 5.67 ± 2.05; P = 0.007) and postprandial glucose excursions (PPGEs) (PPGE at breakfast, 7.72 ± 2.79 vs. 6.79 ± 2.40, P = 0.028; PPGE at lunch, 5.53 ± 2.70 vs. 5.07 ± 2.40, P = 0.285; PPGE at dinner, 5.96 ± 2.24 vs. 4.87 ± 2.50, P = 0.008). BMI was negatively correlated with glycemic variability (r = -0.243, P = 0.002). On multiple linear regression analyses, BMI (β = -0.231, P = 0.013) and Insulin Secretion Sensitivity Index-2 (β = -0.204, P = 0.048) were two independent predictors of glycemic variability. In conclusion, lower BMI was associated with increased glycemic variability, characterized by elevated PPGEs, in newly diagnosed Chinese type 2 diabetic patients.

Continuous glucose monitoring (CGM) is a tool that allows constant evaluation of glycemic control, providing data such as the trend and fluctuation of interstitial glucose levels over time. In clinical practice, there are two modalities: the professional or retrospective and the personal or real-time CGM (RT-CGM). The latest-generation sensors are more accurate and sensitive for hypoglycemia, improving adherence to self-monitoring, which has allowed optimizing glycemic control. The development of algorithms that allow the suspension of the infusion of insulin during hypoglycemia gave rise to the integrated therapy or sensor-augmented insulin pump therapy with low glucose suspend, which has proven to be an effective and safe alternative in the treatment of diabetic patients with high risk of hypoglycemia. The objective of this review is to present the evidence of the advantages of RT-CGM, the clinical impact of integrated therapy, and cost-effectiveness of its implementation in the treatment of patients with diabetes mellitus.

Glucagon-like peptide-1 agonists acutely lower serum glucagon. However, in the Liraglutide and β-Cell Repair (LIBRA) Trial, 48-week treatment with liraglutide yielded lower/unchanged fasting glucagon but, surprisingly, enhanced postchallenge glucagonemia [measured by R&D Systems (Minneapolis, MN) assay].

Because differences between glucagon assays potentially could explain these unexpected findings, we have remeasured glucagon in all 1222 samples from this trial using the highly-sensitive/specific Mercodia assay to compare the findings between assays.

In LIBRA, 51 patients with type 2 diabetes of 2.6 ± 1.9 years duration were randomized to daily subcutaneous liraglutide or placebo injection and followed for 48 weeks, with serial oral glucose tolerance test (OGTT) every 12 weeks (with liraglutide/placebo last administered ∼24 hours earlier).

Serum glucagon was measured every 30 minutes on each OGTT, enabling determination of the area under the glucagon curve (AUCglucagon).

With the Mercodia assay, fasting glucagon was higher in the liraglutide arm than placebo at 12 weeks (P = 0.01), with no between-group differences at 24, 36, and 48 weeks. There was no difference in AUCglucagon between the groups at any visit. Mercodia and R&D Systems glucagon measurements correlated at postchallenge time points but not at fasting.

The Mercodia assay did not replicate the R&D Systems glucagon findings. Although neither assay demonstrated lower postchallenge glucagonemia with chronic liraglutide last administered ∼24 hours earlier, the differential response reported by these assays precludes definitive conclusion and highlights the critical role of assay selection when measuring glucagon in clinical studies.

C-peptide is a widely used measure of pancreatic beta cell function. It is produced in equimolar amounts to endogenous insulin but is excreted at a more constant rate over a longer time. Methods of estimation include urinary and unstimulated and stimulated serum sampling. Modern assays detect levels of c-peptide which can be used to guide diabetes diagnosis and management. We explore the evidence behind the various tests available. We recommend the glucagon stimulation c-peptide testing owing to its balance of sensitivity and practicality. C-peptide levels are associated with diabetes type and duration of disease. Specifically a c-peptide level of less than 0.2 nmol/l is associated with a diagnosis of type 1 diabetes mellitus (T1DM). C-peptide level may correlate with microvascular and macrovascular complications and future use of insulin therapy, as well as likely response to other individual therapies. We explore the potential uses of c-peptide measurement in clinical practice.

Sustained exogenous stimulation of a hormone-specific receptor can affect endogenous hormonal regulation. In this context, little is known about the impact of chronic treatment with glucagon-like peptide-1 (GLP-1) agonists on the endogenous GLP-1 response. We therefore evaluated the impact of chronic liraglutide therapy on endogenous GLP-1 and glucose-dependent insulinotropic polypeptide (GIP) response to an oral glucose challenge. A total of 51 people with type 2 diabetes of 2.6 ± 1.9 years' duration were randomized to daily subcutaneous liraglutide or placebo injection and followed for 48 weeks, with an oral glucose tolerance test (OGTT) every 12 weeks. GLP-1 and GIP responses were assessed according to their respective area under the curve (AUC) from measurements taken at 0, 30, 60, 90 and 120 minutes during each OGTT. There were no differences in AUC_GIP between the groups. By contrast, although fasting GLP-1 was unaffected, the liraglutide arm had ~2-fold higher AUC_GLP-1 at 12 weeks ( P  < .001), 24 weeks ( P  < .001), 36 weeks ( P  = .03) and 48 weeks ( P  = .03), as compared with placebo. Thus, chronic liraglutide therapy induces a previously unrecognized, robust and durable enhancement of the endogenous GLP-1 response, highlighting the need for further study of the long-term effects of incretin mimetics on L-cell physiology.

Obesity and Type 2 diabetes mellitus are on rise with cause-effect relationship. Diabetics monitor blood sugar, neglecting qualitative body composition, leaving residual threat of ectopic fat unattended. We tried to correlate glycemic triad with parameters of body composition derived objectively by bioelectrical impedance analysis (BIA).

A sample of 78 under treatment sedentary Type 2 diabetics of either sex with known glycemic and lipidemic control from our city. Following baseline assessment measurement was done by instrument Omron Karada Scan (Model HBF-510, China) using the principle of tetra poplar BIA to derive parameters of body composition. We tried to correlate glycemic triad with these parameters, both directly as well as after defining them as per established cutoff norms.

We found poor glycemic control in the study group (20% for Hb1AC), high body mass index, subcutaneous fat, visceral fat (VF), total body fat (TBF), and lesser mass of skeletal muscle in Type 2 diabetics. However, there were small, insignificant, and inconsistent difference of these parameters while directly correlating with the fasting blood sugar, postprandial blood sugar, and glycosylated hemoglobin. On qualitative assessment, the impact of glycemic control as per standard norms, the risk of high VF, high TBF, low skeletal muscle mass was though high (between 1 and 2) in Type 2 diabetics with poor glycemic control as compared to good glycemics, but each strength lacks statistical significance.

BIA reveals that Type 2 diabetics have more ectopic fat on expense of skeletal muscle that do not correlate with current glycemic status, both quantitatively and qualitatively. Measurement of body composition can be included and subjects can be motivated for lifestyle modification strategies while managing metabolic derangements of Type 2 diabetes.

In early type 2 diabetes (T2DM), short-term intensive insulin therapy (IIT) for 2-4 weeks can decrease insulin resistance, reduce glucagonemia, improve β-cell function, and even induce a remission of diabetes that can last up to 1 year in some patients. However, little is known about the predictors of such a sustained remission.

We evaluated data from the placebo arm of a double-blind randomized controlled trial in which patients with early T2DM (≤7 years duration) underwent 4 weeks of IIT (basal detemir, bolus aspart), followed by placebo therapy for 48 weeks (n=25). Participants underwent an oral glucose tolerance test every 12 weeks, enabling serial assessment of insulin sensitivity, α-cell response, and β-cell function. Diabetes remission was defined as A1c<6.5% on no medication for T2DM.

At 48 weeks post-IIT, 56% of the participants remained in remission. Comparison of remitters to non-remitters revealed no differences in waist, body mass index, insulin sensitivity (Matsuda index), or glucagon profile, either at baseline or over 48 weeks. Compared to non-remitters, the remission group had lower baseline A1c (p=0.006) and better baseline β-cell function (Insulin Secretion-Sensitivity Index-2) (p=0.01) that was then sustained across 48 weeks post-IIT (p=0.006). On logistic regression analyses, however, shorter duration of diabetes supplanted baseline A1c (p=0.24) and β-cell function (p=0.19) as an independent predictor of remission (p=0.04). In particular, diabetes duration <2 years predicted persistence of remission (p=0.006).

The key determinant of the likelihood of inducing sustained drug-free diabetes remission with short-term IIT is early intervention, particularly within the first 2 years after diagnosis.

ClinicalTrials.Gov NCT01270789; Post-results.

Short-term intensive insulin therapy is unique amongst therapies for type 2 diabetes because it offers the potential to preserve and improve beta-cell function without additional pharmacological treatment. On the basis of clinical experience and the promising results of a series of studies in newly diagnosed patients, mostly in Asian populations, an expert workshop was convened to assess the available evidence and the potential application of short-term intensive insulin therapy should it be advocated for inclusion in clinical practice. Participants included primary care physicians and endocrinologists. We endorse the concept of short-term intensive insulin therapy as an option for some patients with type 2 diabetes at the time of diagnosis and have identified the following six areas where additional knowledge could help clarify optimal use in clinical practice: (1) generalizability to primary care, (2) target population and biomarkers, (3) follow-up treatment, (4) education of patients and providers, (5) relevance of ethnicity, and (6) health economics.

Prediabetes and diabetes are rising worldwide. Control of blood glucose is crucial to prevent or delay diabetic complications that frequently result in increased morbidity and mortality. Most strategies include medical treatment and changes in lifestyle and diet. Some nutraceutical compounds have been recognized as adjuvants in diabetes control. Many of them can activate the nuclear factor (erythroid-derived 2)-like 2 (Nrf2), which has been recognized as a master regulator of the antioxidant response. Recent studies have described the role of Nrf2 in obesity, metabolic syndrome, nephropathy, retinopathy and neuropathy, where its activation prevents the development of diabetes and its complications. It has been demonstrated that natural compounds derived from plants, vegetables, fungi and micronutrients (such as curcumin, sulforaphane, resveratrol and vitamin D among others) can activate Nrf2 and, thus, promote antioxidant pathways to mitigate oxidative stress and hyperglycemic damage. The role of some natural Nrf2 activators and its effect in diabetes is discussed.

In patients with Type 2 diabetes, a short course of intensive insulin therapy can improve β-cell function and even induce transient remission of diabetes. However, not all patients respond to this therapy. Although the achievement of fasting glucose  < 7.0 mmol/l one day after stopping intensive insulin therapy can identify patients in whom β-cell function has improved, we sought to determine clinical predictors for the early identification of such responders and the time course of response.

We pooled data from two studies in which 97 patients with Type 2 diabetes mellitus (median 3 years duration) and HbA1c 51 ± 8.7 mmol/mol (6.8 ± 0.8%) underwent 4-8 weeks of intensive insulin therapy, consisting of basal detemir and pre-meal insulin aspart. They were classified as responders (n = 74) or non-responders (n = 23), defined by the achievement of fasting glucose  < 7.0 mmol/l after stopping intensive insulin therapy.

On logistic regression analyses, duration of diabetes (odds ratio [OR] = 0.72, 95% confidence interval [CI] 0.56-0.92, P = 0.009) and baseline fasting glucose (OR = 0.40, 95% CI 0.24-0.68, P = 0.001) emerged as predictors of the likelihood of responding. Ninety per cent of patients with duration ≤ 4 years and fasting glucose ≤ 8.0 mmol/l responded to intensive insulin therapy. Despite having lower glucose levels during intensive insulin therapy, responders had less hypoglycaemia than non-responders (median 0.3 vs. 1.6 episodes/week, P < 0.0001), with rates of hypoglycaemia diverging sharply from the third week onwards.

At baseline, shorter duration of diabetes and lower fasting glucose can identify patients most likely to benefit from short-term intensive insulin therapy. Most importantly, during therapy, responders had less hypoglycaemia from the third week onwards, despite lower glycaemia, suggesting that 2 weeks of intensive insulin therapy may be needed to improve endogenous islet function.

Glycemic variability (GV) has been proposed as contributor to diabetes-related macrovascular complications. This randomized control trial evaluated a new combination therapy with continuous subcutaneous insulin infusion (CSII) plus sitagliptin (CSII + sitagliptin) vs. CSII only in terms of metabolic control, GV and β-cell function in patients with newly diagnosed type 2 diabetes (T2DM). 217 patients were randomized to two weeks of CSII (n = 108) or CSII + sitagliptin (n = 109) therapy. As a measure of GV, the coefficient of variation (CV) was computed from capillary blood glucose during the first and second week, respectively. β-cell function before and after treatment was determined with the Insulin Secretion-Sensitivity Index-2 (ISSI-2). Good metabolic controls were established with both therapies. CSII + sitagliptin therapy resulted in greater improvements in CV and ISSI-2 than CSII alone (all P = 0.000). For each group, change in CV was inversely correlated with change in ISSI-2 (r = -0.529, P = 0.000 and r = -0.433, P = 0.000, respectively). The multivariate regression analysis demonstrated that improved ISSI-2 was the only independent contributor to reduced CV in both groups (standardized β = -0.388, P = 0.004 and standardized β = -0.472, P = 0.000, respectively). Correction of β-cell function in newly diagnosed T2DM patients via use of either CSII or CSII + sitagliptin therapy was feasible in controlling GV to prevent secondary complications of T2DM. Moreover, CSII + sitagliptin therapy was superior to CSII monotherapy in terms of GV.