New glycemic targets for patients with diabetes from the Japan Diabetes Society

Laughter yoga as an enjoyable therapeutic approach for glycemic control in individuals with type 2 diabetes: A randomized controlled trial

BACKGROUND

Laughter has been reported to have various health benefits. However, data on the long-term effects of laughter interventions on diabetes are limited. This study aimed to investigate whether laughter yoga can improve glycemic control among individuals with type 2 diabetes.

METHODS

In a single-center, randomized controlled trial, 42 participants with type 2 diabetes were randomly assigned to either the intervention or the control group. The intervention consisted of a 12-week laughter yoga program. Hemoglobin A1c (HbA1c), body weight, waist circumference, psychological factors, and sleep duration were evaluated at baseline and week 12.

RESULTS

Intention-to-treat analysis showed that participants in the laughter yoga group experienced significant improvements in HbA1c levels (between-group difference: -0.31%; 95% CI -0.54, -0.09) and positive affect scores (between-group difference: 0.62 points; 95% CI 0.003, 1.23). Sleep duration tended to increase in the laughter yoga group with a between-group difference of 0.4 hours (95% CI -0.05, 0.86; P = 0.080). The mean attendance rate for laughter yoga program was high (92.9%).

CONCLUSIONS

A 12-week laughter yoga program is feasible for individuals with type 2 diabetes and improves glycemic control. These findings suggest that having fun could be a self-care intervention. Further studies with larger numbers of participants are warranted to better evaluate the effects of laughter yoga.

CLINICAL TRIAL REGISTRATION

http://www.chinadrugtrials.org.cn, identifier UMIN000047164.

Changes in Treatment Satisfaction Over 3 Years in Patients With Type 2 Diabetes After Initiating Second-line Treatment

CONTEXT

J-DISCOVER is a prospective observational cohort study aiming to understand the current management of patients with early-stage type 2 diabetes mellitus (T2DM) in Japan, enrolling patients initiating second-line treatment.

OBJECTIVE

The current analysis examined the change in treatment satisfaction during the study period and factors affecting this change among patients in J-DISCOVER.

METHODS

We used data from the J-DISCOVER study, in which 1798 patients with T2DM aged ≥ 20 years were enrolled from 142 sites across Japan. Treatment satisfaction was assessed using the Diabetes Treatment Satisfaction Questionnaire (DTSQ).

RESULTS

The mean DTSQ treatment satisfaction score increased from 25.9 points at baseline to 27.3 points at 6 months, which was maintained through 36 months. Among the baseline characteristics examined, higher baseline DTSQ treatment satisfaction scores (P < 0.0001), older age (≥ 75 vs < 65 years, P = 0.0096), living alone (P = 0.0356), and type of facility (clinics vs hospitals, P = 0.0044) had a significantly negative impact on the changes in DTSQ treatment satisfaction scores. Improvement in mean glycated hemoglobin (HbA1c) from baseline (7.7%) to 36 months (7.1%) was associated with positive changes in the DTSQ treatment satisfaction score (P = 0.0003).

CONCLUSION

Changes in DTSQ treatment satisfaction scores were related to HbA1c improvement, suggesting that the management strategy was appropriately planned for each patient. The results also suggest that the availability of social support for patients with T2DM who are elderly or living alone may be an important factor affecting treatment satisfaction, adherence, and clinical outcomes.

Relation of cardiac function to insulin resistance as evaluated by hyperinsulinemic-euglycemic clamp analysis in individuals with type 2 diabetes

AIMS

Whereas homeostasis model assessment of insulin resistance (HOMA-IR), an easily measured but limited index of insulin resistance, has been shown to correlate with impairment of cardiac function in individuals without diabetes, the pathological relevance of insulin resistance to the development of cardiac dysfunction in individuals with type 2 diabetes has remained unclear. Here we investigated the relation between left ventricular (LV) function as assessed by echocardiography and insulin resistance as evaluated by hyperinsulinemic-euglycemic clamp analysis, the gold standard for measurement of this parameter, in individuals with type 2 diabetes.

METHODS

This retrospective study included 34 individuals with type 2 diabetes who underwent both hyperinsulinemic-euglycemic clamp analysis and echocardiography. Both the insulin sensitivity index (ISI) as determined by glucose clamp analysis as well as HOMA-IR were determined as measures of insulin resistance. The ratio of the peak early- to late-diastolic mitral inflow velocities (E/A) and the LV ejection fraction (LVEF) were determined as measures of diastolic and systolic function, respectively.

RESULTS

The ISI was significantly correlated with both the E/A ratio and LVEF (correlation coefficients of 0.480 and 0.360, respectively), whereas HOMA-IR was not correlated with either cardiac parameter. Multivariate analysis revealed that ISI was an independent predictor for both a high log [E/A] (P = 0.031) and a high LVEF (P = 0.045).

CONCLUSIONS

Insulin resistance as evaluated by hyperinsulinemic-euglycemic clamp analysis may be causally related to LV diastolic and systolic dysfunction in individuals with type 2 diabetes.

Development and validation of an equation to predict the incidence of coronary heart disease in patients with type 2 diabetes in Japan

Objective

In the diabetes treatment policy after the Kumamoto Declaration 2013, it is difficult to accurately predict the incidence of complications in patients using the JJ risk engine. This study was conducted to develop a prediction equation suitable for the current diabetes treatment policy using patient data from Kitasato University Kitasato Institute Hospital (Hospital A) and to externally validate the developed equation using patient data from Kitasato University Hospital (Hospital B). Outlier tests were performed on the patient data from Hospital A to exclude the outliers. Prediction equation was developed using the patient data excluding the outliers and was subjected to external validation.

Results

By excluding outlier data, we could develop a new prediction equation for the incidence of coronary heart disease (CHD) as a complication of type 2 diabetes, incorporating the use of antidiabetic drugs with a high risk of hypoglycemia. This is the first prediction equation in Japan that incorporates the use of antidiabetic drugs. We believe that it will be useful in preventive medicine for treatment for people at high risk of CHD as a complication of diabetes or other diseases. In the future, we would like to confirm the accuracy of this equation at other facilities.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13104-021-05844-w.

A retrospective study on the usefulness of the JJ risk engine for predicting the incidence rate of coronary heart disease in type 2 diabetes patients

Objective

In 2018, we conducted a retrospective survey using the medical records of 484 patients with type 2 diabetes. The observed value of coronary heart disease (CHD) incidence after 5 years and the predicted value by the JJ risk engine as of 2013 were compared and verified using the discrimination and calibration values.

Results

Among the total cases analyzed, the C-statistic was 0.588, and the calibration was p < 0.05; thus, the JJ risk engine could not correctly predict the risk of CHD. However, in the group expected to have a low frequency of hypoglycemia, the C-statistic was 0.646; the predictability of the JJ risk engine was relatively accurate. Therefore, it is difficult to accurately predict the complication rate of patients using the JJ risk engine based on the diabetes treatment policy after the Kumamoto Declaration 2013. The JJ risk engine has several input items (variables), and it is difficult to satisfy them all unless the environment is well-equipped with testing facilities, such as a university hospital. Therefore, it is necessary to create a new risk engine that requires fewer input items than the JJ risk engine and is applicable to several patients.