Sleep duration and food intake in people with type 2 diabetes mellitus and factors affecting confectionery intake.

AIMS/INTRODUCTION: We carried out a cross-sectional study of people with type 2 diabetes mellitus to elucidate the association between sleep duration and food intake. MATERIALS AND METHODS: Overall, 2,887 participants with type 2 diabetes mellitus (mean age 63.0 years; 61.1% men; mean glycated hemoglobin level 7.5%) were included in this study. The participants' self-reported dietary habits and sleep duration were evaluated using a brief self-administered dietary history questionnaire and Pittsburgh Sleep Quality Index, respectively. The participants were categorized into the following four groups based on sleep duration: <6, 6-6.9, 7-7.9 (reference) and ≥8 h. RESULTS: No significant differences were observed between the groups regarding energy intake (kcal/day), absolute intake (g/day) or relative intake (% energy) of carbohydrates, total fat, proteins and fibers. However, confectionery intake was higher in the <6 h group and lower in the ≥8 h group than in the reference group after adjustment for confounding factors. In multivariate analysis, sleep durations <6 h and ≥8 h significantly correlated with increased (95% confidence interval 0.55 to 3.6; P = 0.0078) and decreased (95% confidence interval -4.0 to -0.32; P = 0.021) confectionery intake, respectively. Confectionery intake was positively correlated with female sex, glycated hemoglobin level and dyslipidemia, whereas it was negatively correlated with alcohol consumption and current smoking status. CONCLUSIONS: Short sleep duration is associated with high confectionery intake in people with type 2 diabetes mellitus; this might disturb their glycemic control. Therefore, short sleepers with type 2 diabetes mellitus could improve their glycemic control by avoiding confectionery intake and maintaining adequate sleep duration.

A cross-sectional study of the relationship between quality of life and sleep quality in Japanese patients with type 1 diabetes mellitus.

This study aimed to reveal the relationship between quality of life (QOL) and sleep quality in patients with type 1 diabetes mellitus (T1DM). Overall, 202 patients with T1DM were registered in our study, and 192 were eligible for analysis. Baseline characteristics and laboratory values were determined. Patients completed the Japanese versions of the Pittsburgh Sleep Quality Index (PSQI) and Diabetes Therapy-Related QOL (DTR-QOL) questionnaires. We investigated the relationship between the global PSQI and DTR-QOL total scores by using linear regression analysis. In univariate regression analysis, DTR-QOL total scores were associated with body mass index, alcohol consumption, hypertension, hemoglobin A1c (HbA1c), and global PSQI score (all p-value <0.05) but not with sleep duration. When the association between PSQI subscales and DTR-QOL total scores was examined, DTR-QOL total scores were significantly related to subjective sleep quality and daytime dysfunction. In a multivariate regression analysis, the global PSQI score was negatively related to DTR-QOL total scores. Patients with an HbA1c concentration ≥8.0% had significantly lower DTR-QOL total scores. We revealed a relationship between QOL and sleep quality in T1DM patients and showed that the relationship between QOL and PSQI subscales in T1DM patients may be different from that in patients with type 2 diabetes mellitus. Assessing and managing sleep quality may be necessary for patients with diabetes to improve QOL.

Risk of hypoglycemia associated with repaglinide combined with clopidogrel, a retrospective cohort study.

BACKGROUND: Repaglinide is widely prescribed to reduce postprandial hyperglycemia and elevated glycated hemoglobin (HbA1c) levels associated with type 2 diabetes, and clopidogrel is a thienopyridine antiplatelet agent and widely used in cardiovascular and cerebrovascular diseases. It has been suggested that the concomitant use of repaglinide with clopidogrel may inhibit repaglinide metabolism, because repaglinide is a substrate of cytochrome P450 2C8 (CYP2C8) and the main metabolite of clopidogrel acyl-ß-D-glucuronide inhibits CYP2C8 activity. In this study, we retrospectively investigated the effect of clopidogrel with repaglinide on plasma glucose and the risk of hypoglycemia associated with the combination of both drugs. METHOD: Patients were taking clopidogrel (75 mg/day) and started taking glinide (1.5 mg/day repaglinide or 30 mg/day mitiglinide) for the first time from April 2012 to March 2017. We targeted subjects who were hospitalized at the start of glinide and whose preprandial plasma glucose was measured by a nurse. The glucose levels were collected for up to 5 days before and after the glinide start date. RESULTS: Average fasting plasma glucose levels (before breakfast) in the repaglinide and clopidogrel group before and after starting repaglinide were 180.1±35.5 and 136.5 ± 44.1 mg/dL, with a mean decrease of 43.6 ± 33.6 mg/dL. In contrast, there was only a moderate decrease of 11.6 ± 30.0 mg/dL in the mitiglinide and clopidogrel group. Minimum plasma glucose levels in the repaglinide and clopidogrel group before and after starting repaglinide were 145.2 ± 42.9 and 93.3 ± 36.3 mg/dL, respectively. Decrease in minimum levels after starting glinide in the repaglinide and clopidogrel group (51.9 ± 47.5 mg/dL) was more significant than those in the mitiglinide and clopidogrel group (only 2.1 ± 29.1 mg/dL), and the repaglinide group (without clopidogrel, 15.5 ± 20.0 mg/dL). Hypoglycemia was observed in 6 of 15 patients in the repaglinide and clopidogrel group, but only 1 of 15 patients in the mitiglinide and clopidogrel group, and no patients in the repaglinide group. CONCLUSION: These findings indicate that minimum plasma glucose levels were significantly decreased in patients taking repaglinide and clopidogrel. Considering the risk of hypoglycemia associated with taking repaglinide and clopidogrel, when a glinide is required in patients taking clopidogrel, mitiglinide may be a better choice.

Efficacy and safety of insulin degludec U100 and insulin glargine U100 in combination with meal-time bolus insulin in hospitalized patients with type 2 diabetes: an open-label, randomized controlled study.

The short-term efficacy and safety of insulin degludec U100 (IDeg) in patients with type 2 diabetes have not been reported widely. We compared insulin IDeg and insulin glargine U100 (IGla) for glycemic control and glucose variability in hospitalized patients with type 2 diabetes. In an open-label, multicenter, randomized controlled trial, 74 patients were randomly assigned to either the IDeg (36 patients) or IGla (38 patients) group and were administered with basal-bolus therapy during hospitalization. Following the start of the treatment, on day 11, glucose variability was assessed by continuous glucose monitoring. A fasting blood glucose level of 110 mg/dL and 2-hour postprandial blood glucose level of 180 mg/dL throughout at least one day during the observation period were achieved in 31.3% (10/32) and 30.6% (11/36) of the patients in the IDeg and IGla groups, respectively. The 6-point self-monitoring of blood glucose profiles showed a significant difference between the two groups. On day 7, the intra-day variation was larger in the IDeg group than in the IGla group. The incidence of hypoglycemia or glucose variability was comparable in the two groups. This study suggests that short-term efficacy and safety of IDeg and IGla in patients with type 2 diabetes during the initial phase of basal-bolus therapy were comparable, and these results can help in deciding which treatment to opt for.

Dietary survey in Japanese patients with type 2 diabetes and the influence of dietary carbohydrate on glycated hemoglobin: The Sleep and Food Registry in Kanagawa study.

AIMS/INTRODUCTION: The present study investigated the relationship between the macronutrient energy ratio, dietary carbohydrate and glycated hemoglobin levels in Japanese patients with type 2 diabetes, to generate a potential optimal dietary intake of macronutrients for such patients. MATERIALS AND METHODS: In total, 3,032 patients participating in the Sleep and Food Registry in Kanagawa study were evaluated. Their diets were assessed for macronutrient content through a brief self-administered dietary history questionnaire. Relevant biochemical assays were carried out. RESULTS: The mean energy intake (±standard deviation) was 1,711 ± 645 kcal/day. The proportion of energy supplied by protein, fat and carbohydrate were 16.3, 26.8 and 52.3%, respectively. Total fiber intake was 12.6 ± 5.7 g/day. The high glycated hemoglobin (HbA1c) group (HbA1c >8%) had significantly lower protein and higher carbohydrate intake than the low HbA1c group (HbA1c <6.5%). Higher HbA1c levels were positively correlated with unfavorable metabolic factors, including elevated body mass index and excess carbohydrate intake, and negatively correlated with age, protein intake and fiber intake. Multiple regression analysis showed a significant association between HbA1c and carbohydrate intake after adjusting for sex, age and body mass index (0.104, P < 0.0001). Additionally, patients within the uppermost tertile for the percentage of total energy intake from carbohydrate (>60%) were most likely to have high HbA1c levels. HbA1c was significantly correlated with carbohydrate (%E) in all age groups and in patients taking one or two antidiabetic drugs. CONCLUSIONS: The dietary carbohydrate:energy ratio has a positive correlation with HbA1c, suggesting that avoiding excessive carbohydrate intake (>60%) might help foster glycemic control.

Association of usual sleep quality and glycemic control in type 2 diabetes in Japanese: A cross sectional study. Sleep and Food Registry in Kanagawa (SOREKA).

OBJECTIVES: Excessively short and long sleep durations are associated with type 2 diabetes, but there is limited information about the association between sleep quality and diabetes. Accordingly, the present study was performed to investigate this relationship. MATERIALS AND METHODS: The subjects were 3249 patients with type 2 diabetes aged 20 years or older. Sleep quality was assessed by using the Pittsburgh Sleep Quality Index (PSQI). A higher global PSQI score indicates worse sleep quality, and a global PSQI score >5 differentiates poor sleepers from good sleepers. RESULTS: The mean global PSQI score was 5.94 ± 3.33, and 47.6% of the patients had a score of 6 or higher. Regarding the components of the PSQI, the score was highest for sleep duration, followed by subjective sleep quality and then sleep latency in decreasing order. When the patients were assigned to HbA1c quartiles (≤ 6.5%, 6.6-7.0%, 7.1-7.8%, and ≥ 7.9%), the top quartile had a significantly higher global PSQI score than the other quartiles. The top HbA1c quartile had a sleep duration of only 6.23 ± 1.42 hours, which was significantly shorter than in the other quartiles. Also, sleep latency was 25.3 ± 31.8 minutes in the top quartile, which was significantly longer (by approximately 20 minutes) than in the other quartiles. When analysis was performed with adjustment for age, gender, BMI, smoking, and other confounders, the global PSQI score was still significantly higher and sleep duration was shorter in the top HbA1c quartile (HbA1c ≥ 7.9%). CONCLUSIONS: Japanese patients with type 2 diabetes were found to have poor subjective sleep quality independently of potential confounders, especially those with inadequate glycemic control. Impairment of sleep quality was associated with both increased sleep latency and a shorter duration of sleep.

Incretin Kinetics Before and After Miglitol in Japanese Patients With Late Dumping Syndrome.

BACKGROUND: In patients with late dumping syndrome following gastrectomy, it has been reported that hypoglycemia occurs due to inhibition of glucagon secretion as a result of excessive insulin production facilitated by an increase in glucagon-like peptide-1 (GLP-1). METHODS: To determine the kinetics of incretins in Japanese patients with late dumping syndrome, an oral glucose tolerance test was carried out before and after miglitol administration, and the kinetics of insulin and incretins were analyzed. RESULTS: After miglitol administration, there was improvement of hypoglycemia and early phase insulin secretion, with persistent excessive insulin secretion being minimized. These findings revealed that miglitol inhibited rapid excessive influx of carbohydrates into the blood and persistent elevation of GLP-1, resulting in improvement of early phase insulin secretion and minimizing persistent excessive insulin secretion. CONCLUSIONS: Eating frequent small meals is generally effective for late dumping syndrome, but patients often find it difficult to continue such a regimen. Based on the present analysis of incretin kinetics, miglitol may be a useful treatment option for late dumping syndrome.

A Randomized Controlled Trial of Vildagliptin Versus Alogliptin: Effective Switch From Sitagliptin in Patients With Type 2 Diabetes.

BACKGROUND: We investigated the effects of vildagliptin or alogliptin on blood glucose and hemoglobin A1c (HbA1c) in patients with type 2 diabetes inadequately controlled by sitagliptin. METHODS: In a single-center open-label trial, 35 patients with inadequate glycemic control on sitagliptin therapy (50 mg once daily) were randomly switched to treatment with vildagliptin (50 mg twice daily) or alogliptin (25 mg once daily). After 12 weeks, patients who failed to achieve the target HbA1c level of < 7.0% with vildagliptin or alogliptin treatment were switched to high-dose sitagliptin (100 mg once daily) and the effect on glycemic control was assessed. RESULTS: Vildagliptin did not significantly alter the mean plasma glucose level (175.5 ± 54.4 mg/dL vs. 179.1 ± 73.4 mg/dL) or HbA1c (8.01% vs. 8.02%) after 12 weeks. With alogliptin, mean plasma glucose increased from 175.4 ± 50.9 mg/dL to 195.3 ± 55.0 mg/dL after 12 weeks and HbA1c increased significantly from 8.0% to 8.3% (P < 0.05). At 12 weeks after switching from vildagliptin to high-dose sitagliptin (100 mg daily), HbA1c was increased to 8.3%, but it was significantly (P < 0.05) reduced to the baseline level of 8.0% after switching from alogliptin. The reduction of HbA1c was significantly greater in the vildagliptin group than the alogliptin group (P = 0.008), but the response rate (achieving the target HbA1c < 7.0%) did not differ significantly between the two groups. CONCLUSION: The glucose-lowering effects of these three dipeptidyl peptidase-4 (DPP-4) inhibitors (vildagliptin, alogliptin, and sitagliptin) were different, and the effects of vildagliptin and sitagliptin were stronger than that of alogliptin.

Efficacy of switching from insulin glargine to insulin degludec in patients with type 1 diabetes: a 16-week retrospective study.

We retrospectively investigated the effect of switching from insulin glargine (IGlar) to insulin degludec (IDeg) on glycemic control in Japanese patients with type 1 diabetes mellitus. We also evaluated the dose of IDeg, and assessed weight gain and the risk of hypoglycemia after switching. Forty-five patients with type 1 diabetes were switched from IGlar (once daily or twice daily) to IDeg (once daily) during routine medical care. Data were collected for 16 weeks after switching from IGlar to IDeg. The mean HbA1c (%) in weeks 4, 8, 12, and 16 was lower than it was in week 0 (8.0 ± 1.0, 8.0 ± 1.4, 7.9 ± 1.1, 7.6 ± 1.0 vs. 8.3 ± 1.3 %, p < 0.01). The total basal insulin dose (TBD) was significantly lower after 16 weeks of IDeg as compared to IGlar treatment (0.30 ± 0.12 vs. 0.24 ± 0.11 U/kg/day, p = 0.001). In the twice-daily IGlar group, TBD showed a significant decrease from 0.33 ± 0.12 to 0.26 ± 0.11 U/kg/day (p < 0.001) after switching to IDeg. In the once-daily IGlar group, TBD showed a slight but not significant decrease from 0.23 ± 0.08 to 0.20 ± 0.09 U/kg/day (p = 0.97). Hypoglycemic episodes were transiently increased, but the change was not significant. The blood glucose fluctuation was evaluated from self-monitoring data and the coefficient of variation (CV) was calculated. The CV showed only a minimal change from 48.3 ± 17.1 to 48.6 ± 14.2 % at 12 weeks after switching to IDeg (p = 0.73). In conclusion, once-daily IDeg improved glycemic control in patients with type 1 diabetes compared to the control achieved with IGlar, without increasing the risk of hypoglycemia. When switching from IGlar (especially twice daily), it is recommended that the initial dose of IDeg should be reduced in order to decrease the risk of hypoglycemia.

Effects of exenatide and liraglutide on 24-hour glucose fluctuations in type 2 diabetes.

We evaluated the influence of short-term treatment with exenatide twice daily or liraglutide once daily on daily blood glucose fluctuations in 40 patients with type 2 diabetes inadequately controlled by sulfonylureas. The patients in a multicenter, open-label trial were randomly assigned to receive add-on exenatide (10 µg/day, n = 21) or add-on liraglutide (0.3-0.9 mg/day, n = 19), and underwent 24-hour continuous subcutaneous glucose monitoring. There was no significant between-group difference in glucose fluctuations during the day, as assessed by calculating mean amplitude of glycemic excursion (MAGE) and standard deviation (SD). However, the mean blood glucose levels at 3 hours after breakfast and dinner were significantly lower in the exenatide group than the liraglutide group (breakfast: 127.3 ± 24.1 vs. 153.4 ± 28.7 mg/dL; p = 0.006, dinner: 108.7 ± 17.3 vs. 141.9 ± 24.2 mg/dL; p < 0.001). In contrast, mean blood glucose levels and their SD were significantly lower between 0000 h and 0600 h in the liraglutide group than the exenatide group (average glucose: 126.9 ± 27.1 vs. 107.1 ± 24.0 mg/dL; p = 0.029, SD: 15.2 ± 10.5 vs. 8.7 ± 3.8; p = 0.020). Both groups had similar glucose fluctuations despite differences in 24-hour blood glucose profiles. Therefore, each of these agents may have advantages or disadvantages and should be selected according to the blood glucose profile of the patient.

Effect of sitagliptin on lipid profile in patients with type 2 diabetes mellitus.

BACKGROUND: Animal studies have demonstrated that an inhibition of DPP-4 has an impact on the secretion of cholesterol and apoB by the small intestine. However, there is no consensus about the changes of the lipid profile following administration of sitagliptin. METHODS: Accordingly, we treated patients who had type 2 diabetes complicated by dyslipidemia with sitagliptin and evaluated its effects on the profile of lipid parameters. A total of 248 outpatients with type 2 diabetes complicated by dyslipidemia were treated with sitagliptin at a daily dose of 50 mg. The levels and percent changes of lipid and glucose metabolism markers were measured at baseline and at 12 weeks after the initiation of treatment. RESULTS: Both plasma glucose and HbA1c were significantly decreased. Among the lipid parameters, total cholesterol (TC) and non-high-density lipoprotein cholesterol (non-HDL-C) showed a significant decrease (TC 3.6±15.6%, non-HDL-C 2.9±19.7%; P < 0.05). Stratified analysis revealed a significant decrease of TC, low-density lipoprotein cholesterol (LDL-C) and non-HDL-C in the high triglyceride (TG) group (≥ 150 mg/dL) (P < 0.05). Analysis stratified by demographic factors demonstrated significant differences in the changes of TC, LDL-C and non-HDL-C. Multivariate analysis showed a significant decrease of the TC, LDL-C and non-HDL-C levels in the high TG group (≥ 150 mg/dL), as well as a significant decrease of TC and LDL-C in patients using strong statins. CONCLUSIONS: The results suggested that sitagliptin caused a significant decrease of TC, LDL-C and non-HDL-C, particularly in patients with high baseline TG levels and those using strong statins.

Second-line treatments for dyslipidemia in patients at risk of cardiovascular disease.

Previous studies have shown that approximately 50% patients at risk of cardiovascular disease do not achieve lipid management goals. Thus, improvements dyslipidemia management are needed. We investigated the clinical choice and efficacy of second-line treatments for dyslipidemia in the Japanese clinical setting. Using a retrospective cohort design, we collected lipid profile data from patients who had been treated with hypolipidemic agents at a stable dosage for at least 12 weeks. These patients had then been administered a second-line treatment for dyslipidemia because they had not achieved the low-density lipoprotein cholesterol (LDL-C) management goals. We included data from 641 patients in our analysis. The top three choices for second-line treatment were adding ezetimibe, switching to strong statins (statin switching), and doubling the original statin dosage (statin doubling). Adding ezetimibe, statin switching, and statin doubling decreased LDL-C levels by 28.2 ± 14.5%, 23.2 ± 24.4%, and 23.5 ± 17.2%, respectively. Among these three strategies, adding ezetimibe decreased LDL-C levels to the maximum extent. In patients with dysglycemia, baseline-adjusted change in hemoglobin A1c (HbA1c) levels decreased slightly in the adding-ezetimibe, statin-switching, and statin-doubling groups, but the differences were not statistically significant among the groups (-0.10 ± 0.62%, -0.22 ± 0.54%, and -0.12 ± 0.52%, p = 0.19). In conclusion, the most common second-line treatment options for dyslipidemia were adding ezetimibe, statin switching, or statin doubling. Adding ezetimibe resulted in the highest reduction in LDL-C levels. These strategies did not increase HbA1c levels when administered with conventional diabetes treatment.

Efficacy of ezetimibe is associated with gender and baseline lipid levels in patients with type 2 diabetes.

AIM: The combination of ezetimibe and a statin provides greater LDL-C reduction by inhibiting both intestinal cholesterol absorption and endogenous production of cholesterol. The present study was designed to examine the influence of ageing, gender, BMI, levels of LDL-C, and HbA1c on the response to ezetimibe add-on therapy. METHODS: Patients who had been taking a statin for >3 months at the usual dose and whose LDL-C was >120 mg/dL were eligible for this study. Patients were assigned to receive add-on ezetimibe at 10 mg once daily for 12 weeks. RESULTS: Adding ezetimibe to basal statin therapy resulted in a further 15.0% reduction of TC, 20.5% reduction of LDL-C, and 19.7% reduction of non-HDL-C. The change in TC was significantly greater in males than in females. The change in TG was significantly greater in patients with a baseline TG level ≥150 mg/dL. Multivariate regression analysis showed that male sex and LDL-C ≥140 mg/dL were independent predictors of TC reduction after adjustment for age, BMI, and HbA1c. A baseline TG ≥150 mg/dL was also an independent predictor of TG reduction. CONCLUSION: Addition of ezetimibe to ongoing statin therapy was effective in patients with type 2 diabetes. Male sex and baseline LDL-C levels are independent predictors of marked TC reduction by ezetimibe treatment.

Pravastatin potentiates increases in serum adiponectin concentration in dyslipidemic patients receiving thiazolidinedione: the DOLPHIN study.

AIM: A reduced risk of type 2 diabetes has been reported following treatment with pravastatin. Adiponectin is an adipocyte-derived protein that has an antidiabetic property. The objective of this study was to evaluate the effect of pravastatin on serum adiponectin concentration and other influencing factors. METHODS: This study was a multicenter observational study: Dyslipidemia Open-labeled observational study by Lipid-lowering therapy with Pravastatin of the effect on High-molecular weight adiponectin in Nippon Yokohama (DOLPHIN). The protocol was registered in the UMIN Clinical Trial Registry as UMIN000000791. All patients received pravastatin 10 mg/day for 6 months and the change in concentration of total and high molecular weight adiponectin was assessed before and after follow-up. The difference in the change in total adiponectin concentration by patient characteristics was analyzed by an unpaired t-test. Influences of continuous variable factors on the change in total adiponectin concentration were estimated by simple linear regression analyses. Finally, in order to estimate the influences of factors that potentially affect the change in total adiponectin concentration induced by pravastatin, multiple linear regression analysis was conducted. RESULTS: After 6 months, total adiponectin concentration was increased significantly by 23.2% from 11.7±6.4 to 13.7±8.6 µg/mL (p=0.002). The use of thiazolidinedione as a concomitant medication was the only significant influencing factor (ß=0.580, p<0.001). CONCLUSION: Pravastatin increased the serum adiponectin concentration in Japanese dyslipidemic patients without previous coronary artery disease. Interestingly, this effect was seen synergistically in combination with thiazolidinedione.