Effect of postprandial moderate-intensity walking for 15-min on glucose homeostasis in type 2 diabetes mellitus patients.

AIM: Diabetes patients usually have a low activity level and complain about lack of time. Therefore, we investigated the effect of short time, postprandial moderate-intensity exercise on glucose homeostasis in type 2 diabetes patients. METHODS: Eleven patients with type 2 diabetes were recruited. Patients spent the first day of the study without exercise (non-exercise day; NE day). In the second day, they walked at moderate-intensity (40% of the maximum heart rate reserve) for 15 min, 30 min after each meal (exercise day; E day). Glucose homeostasis was estimated by a continuous glucose monitor (CGM). All meals during the study were of standard composition. We compared NE day and E day concerning 24-h glucose homeostasis and 3 h postprandial glucose levels by the incremental area under the curve (iAUC) method. Medications were not changed during the study. RESULTS: The number of patients under basal supported oral therapy, intensive insulin therapy and oral hypoglycemic agents (OHA) were 5, 4 and 2, respectively. The blood glucose standard deviation over 24 h and the iAUC for the 24-h glycemic variability (NE day vs. E day; 34,765 [21,424-56,014] vs. 23,205 [15,323-39,779]) were smaller in E day than in NE day. CONCLUSION: These results suggest that postprandial moderate-intensity walking, easily performable in daily life activities, was effective for improving glucose homeostasis. Further study should be performed to clarify the relationship between postprandial walk and drug therapy (insulin and OHA), including insulin secretory ability.

Comparison of morning basal + 1 bolus insulin therapy (insulin glulisine + insulin glargine 300 U/mL vs insulin lispro + insulin glargine biosimilar) using continuous glucose monitoring: A randomized crossover study.

INTRODUCTION: We compared the effects of morning administration of insulin glulisine + insulin glargine 300 U/mL (G + G300) with that of insulin lispro + insulin glargine biosimilar (L + GB). MATERIALS AND METHODS: A total of 30 patients with type 2 diabetes who wore a continuous glucose monitoring device on admission after glucose levels were stabilized by morning long-acting and ultra-rapid-acting insulins were randomly allocated to groups who received G + G300 on days 1 and 2, and the same dose L + GB on days 3 and 4, or vice versa. Data collected on days 2 and 4 (mean amplitude of glycemic excursion, mean of daily differences: all days) were analyzed. Insulin was injected at 08.00 h. A day was defined as the period from 08.00 h one day, to 08.00 h the next day. Test meals were given. RESULTS: Increased post-breakfast glucose level, post-breakfast glucose gradient, mean glucose level, standard deviation and M-value (24 h, 00.00-06.00 h), mean amplitude of glycemic excursion, and mean of daily differences were significantly lower in patients taking G + G300 than those taking L + GB (P ≤ 0.0001-0.04). The area over the glucose curve (<70 mg/dL) was not significantly different between groups. Pre-lunch - pre-breakfast glucose levels were significantly lower in patients taking L + GB than those taking G + G300 (P < 0.0001). The difference in the highest post-breakfast glucose level between groups (Δ = G + G300 - L + GB) was significantly correlated to 24-h mean glucose level (r = 0.40, P = 0.03). CONCLUSIONS: Compared with L + GB, G + G300 decreases post-breakfast glucose level reducing rate of rise of that, nocturnal and 24-h glucose variability and level without causing hypoglycemia, and daily variance.

Comparison of tofogliflozin 20 mg and ipragliflozin 50 mg used together with insulin glargine 300 U/mL using continuous glucose monitoring (CGM): A randomized crossover study.

To investigate whether sodium glucose co-transporter 2 inhibitors (SGLT2i), tofogliflozin or ipragliflozin, achieve optimal glycemic variability, when used together with insulin glargine 300 U/mL (Glargine 300). Thirty patients with type 2 diabetes were randomly allocated to 2 groups. For the first group: After admission, tofogliflozin 20 mg was administered; Fasting plasma glucose (FPG) levels were titrated using an algorithm and stabilized at 80 mg/dL level with Glargine 300 for 5 days; Next, glucose levels were continuously monitored for 2 days using continuous glucose monitoring (CGM); Tofogliflozin was then washed out over 5 days; Subsequently, ipragliflozin 50 mg was administered; FPG levels were titrated using the same algorithm and stabilized at 80 mg/dL level with Glargine 300 for 5 days; Next, glucose levels were continuously monitored for 2 days using CGM. For the second group, ipragliflozin was administered prior to tofogliflozin, and the same regimen was maintained. Glargine 300 and SGLT2i were administered at 8:00 AM. Data collected on the second day of measurement (mean amplitude of glycemic excursion [MAGE], average daily risk range [ADRR]; on all days of measurement) were analyzed. Area over the glucose curve (<70 mg/dL; 0:00 to 6:00, 24-h), M value, standard deviation, MAGE, ADRR, and mean glucose levels (24-h, 8:00 to 24:00) were significantly lower in patients on tofogliflozin than in those on ipragliflozin. Tofogliflozin, which reduces glycemic variability by preventing nocturnal hypoglycemia and decreasing postprandial glucose levels, is an ideal SGLT2i when used together with Glargine 300 during basal insulin therapy.

Investigating the Relationship between Morning Glycemic Variability and Patient Characteristics Using Continuous Glucose Monitoring Data in Patients with Type 2 Diabetes.

Objective To investigate the relationship between patient characteristics and morning glycemic variability. Methods We retrospectively evaluated 106 patients with type 2 diabetes who underwent continuous glucose monitoring during admission. The highest postprandial glucose level (within 3 hours after breakfast; 'highest level'), the time from the start of breakfast to the highest postprandial glucose level ('highest time'), the difference between the pre-breakfast and highest postprandial breakfast glucose level ('increase'), the area under the curve (AUC; ≥180 mg/dL) for the glycemic variability within 3 hours after breakfast ('morning AUC'), and the post-breakfast glucose gradient ('gradient') were calculated. We analyzed the associations between these factors and nocturnal hypoglycemia and the patients' characteristics by using a regression analysis. Results After stepwise multivariate adjustment, significant independent associations were found between 'highest level' and high age, low BMI, and high HbA1c; 'highest time' and high HbA1c, low C-peptide immunoreactivity (CPR), and low fasting plasma glucose (FPG); the 'increase' and high age, low BMI, high HbA1c, low FPG and hypoglycemia; 'morning AUC' and high age, high HbA1c and hypoglycemia; and 'gradient' and long duration of diabetes and low BMI. Conclusion Higher age and lower BMI are associated with higher 'highest' and 'increase' levels. Higher HbA1c levels were linked to a longer 'highest time', and longer durations of the diabetes, while lower BMI values were related to a higher 'gradient'.

Major Increases between Pre- and Post-breakfast Glucose Levels May Predict Nocturnal Hypoglycemia in Type 2 Diabetes.

Objective The aim of this study was to determine whether nocturnal hypoglycemia may be predicted according to morning glucose levels. Methods We retrospectively evaluated 106 patients with type 2 diabetes who underwent continuous glucose monitoring during admission. The pre-breakfast glucose level (Pre-breakfast level), highest postprandial glucose level within 3 hours after breakfast (Highest level), time from the start of breakfast to the highest postprandial glucose level (Highest time), difference between the pre-breakfast and highest postprandial breakfast glucose levels (Increase), area under the glucose curve (≥180 mg/dL) within 3 hours after breakfast (Morning AUC), post-breakfast glucose gradient (Gradient), and the increase-to-pre-breakfast ratio (Increase/Pre-breakfast) were calculated. The subjects were divided into hypoglycemic and non-hypoglycemic patients and compared for the above parameters using the t-test. A receiver operating characteristic analysis was used to determine the optimal cut-off values to predict nocturnal hypoglycemia (Hypoglycemia). Results Twenty-eight patients (26.4%) had hypoglycemia. The Pre-breakfast levels were significantly lower in patients with hypoglycemia than those without (p=0.03). The Increases were significantly higher in patients with hypoglycemia than those without (p=0.047). The Increase/Pre-breakfast ratio were significantly larger in patients with hypoglycemia than those without (p=0.0002). Their cut-off values were as follows (level, sensitivity, specificity, and area under the curve): 123 mg/dL, 0.89, 0.55, and 0.78 (p<0.0001); 90.5 mg/dL, 0.75, 0.64, and 0.76 (p<0.0001); and 90.2%, 0.75, 0.76, and 0.78 (p<0.0001), respectively. Conclusion Major increases between the pre- and post-breakfast glucose levels may predict nocturnal hypoglycemia in patients with type 2 diabetes.

Evaluation of safety of insulin degludec on undergoing total colonoscopy using continuous glucose monitoring.

AIMS/INTRODUCTION: There is little information regarding how to use insulin degludec (D) when diabetic patients are preparing for total colonoscopy (TCS). MATERIALS AND METHODS: A total of 12 patients with type 2 diabetes treated with insulin D and scheduled to undergo TCS were enrolled in the present study. A continuous glucose monitoring device was attached to each patient for 4 days, from two evenings before TCS to the morning after the procedure. The patients fasted for 24 h, starting after 18.00 h the day before TCS. Insulin D was only discontinued the morning of the day TCS was carried out. RESULTS: No patients experienced hypoglycemia during the daytime fasting period (08.00-18.00 h the day of TCS); the hypoglycemic index, mean glucose level, and standard deviation were 0, 141.3 ± 31.5 mg/dL and 15.6 ± 6.5 mg/dL. The mean glucose level and standard deviation during the daytime fasting period were significantly lower than during the daytime control period (08.00-18.00 h the day before TCS; P = 0.003, P = 0.001, respectively). The mean fasting glucose and fasting plasma glucose levels were significantly correlated (r = 0.78, P = 0.002), as were both the mean glucose level and standard deviation during the daytime control period, and the change in the mean glucose level (fasting period minus control period; r = -0.79, P = 0.002, and r = -0.69, P = 0.01, respectively). CONCLUSIONS: Patients can safely undergo TCS when insulin D is discontinued only once on the day of the procedure.

Hypoglycemia and glycemic variability are associated with mortality in non-intensive care unit hospitalized infectious disease patients with diabetes mellitus.

AIMS/INTRODUCTION: We aimed to identify factors - glycemic control, reactive inflammatory biomarkers or vital signs - associated with mortality in diabetic patients admitted to hospital for various infections (non-intensive care unit). MATERIALS AND METHODS: We retrospectively analyzed the cases of 620 diabetic patients admitted to hospital for various infections (non-intensive care unit) who underwent glucose monitoring >3 times per day. We extracted data regarding reactive inflammatory biomarkers and vital signs recorded on day 1 of hospital stay, and data on bacteremia and hypoglycemia status, glycemic variability (GV; coefficient of variation and standard deviation) and mean glucose concentrations during the entire hospital stay. Univariate and stepwise multivariate logistic regression analyses were carried out to determine the association between these factors and mortality. RESULTS: The mortality rate was 10.1%. Reactive inflammatory biomarkers, vital signs and bacteremia were not associated with mortality. According to the results of the adjusted analysis, hypoglycemia showed a significant positive association with mortality, increasing death risk by 266% (odds ratio [OR] 2.66, 95% confidence interval [95% CI] 1.22-5.83; P = 0.0006). High coefficient of variation and standard deviation values were significantly associated with increased mortality, increasing death risk by 18% (OR 1.18, 95% CI 1.01-1.38; P = 0.03) and 9% (OR 1.09, 95% CI 1.01-1.18; P = 0.03), respectively. Mean glucose concentrations were also significantly associated with mortality, increasing death risk by 5% (OR 1.05, 95% CI 1.02-1.08; P = 0.0008). CONCLUSIONS: Glycemic indices (especially hypoglycemia and GV), rather than reactive inflammatory biomarkers or vital signs, were associated with mortality in non-intensive care unit diabetes mellitus patients with infections.