Recently, a role for uncoupling protein-3 (UCP3) in carbohydrate metabolism and in type 2 diabetes has been suggested. Mice overexpressing UCP3 in skeletal muscle showed reduced fasting plasma glucose levels, improved glucose tolerance after an oral glucose load, and reduced fasting plasma insulin levels. However, data regarding the expression of UCP3 in patients with type 2 diabetes is inconsistent, and so far, there have been no reports of UCP3 protein content. Here we compared, for the first time, the protein levels of UCP3 in vastus lateralis muscle in 14 male type 2 diabetic patients (age 49.8 +/- 2.1 years; BMI 27.2 +/- 1.2 kg/m(2); mean +/- SE) with 16 male control subjects (age 48.0 +/- 1.9 years; BMI 23.4 +/- 0.6 kg/m(2)). We found that UCP3 protein levels were twice as low in patients with type 2 diabetes compared with control subjects (117 +/- 16 vs. 58 +/- 12 AU; P = 0.007). There was no correlation between UCP3 content and BMI. In conclusion, UCP3 content is lower in type 2 diabetic patients compared with healthy control subjects. These results are consistent with a role for UCP3 in glucose homeostasis and suggest a role for UCP3 in type 2 diabetes.
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From the publisher's site: "Trial design: Self-management plays a central role in diabetes management. However, not all patients are able to translate the health care providers’ recommendations for effective self-management in daily life. Diabetes Education and Self-management to Increase Empowerment (DESTINE) primarily investigates the effects of group education program Proactive Interdisciplinary Self-Management (PRISMA) in primary care treated people with Type 2 Diabetes Mellitus (T2DM) on the use of an online care platform. Methods: The DESTINE study has a randomized controlled design (1:1). 200 patients with T2DM using an online care platform called e-Vita will receive either PRISMA in addition to usual care or usual care only. The primary endpoint of this study is usage of the e-Vita platform. The secondary endpoints are participation in the consultation with the care provider, adherence to oral diabetes medications, and a selection of self-reported and clinical measures. After six months, both groups will receive PRISMA in a 6 month extension phase. Discussion: PRISMA focuses on aligning treatment goals from different health care providers while the individual patient remains in the lead. The goal is to shift patients from being an information receiver towards applying self-management and becoming empowered health care participants. Though recognized as important; theoretically based group education is still not routinely offered in the Netherlands. In the future, depending on the study results, e-Vita and PRISMA could be implemented in regular diabetes care. Trial registration: Current Controlled Trials NTR4693. (aut. ref.)"
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Comparisons of visual perception, response-selection, and response-execution performance were made between Type 2 diabetes mellitus patients and a matched nondiabetic control group. 10 well-controlled male patients with Type 2 diabetes without diabetic complications (M age 58 yr.) and an age and IQ-matched non-diabetic control group consisting of 13 male healthy volunteers (M age 57 yr.) were included. Significant differences were found only between the two groups on response-selection performance, which concerns the selection and preparation of an appropriate motor action.
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The studies in this thesis aim to increase understanding of the effects of various characteristics of scientific news about a common chronic disease, i.e., diabetes, on the cognitive responses (e.g., emotions, attitudes, intentions) of diabetes patients. The research questions presented in this thesis are guided by the Health Belief Model, a theoretical framework developed to explain and predict healthrelated behaviours based on an individual’s beliefs and attitudes. The model asserts that perceived barriers to a recommended health behavior, advantages of the behavior, self-efficacy in executing the behavior, and disease severity and personal susceptibility to the disease are important predictors of a health behavior. Communication is one of the cues to action (i.e., stimuli) that may trigger the decision-making process relating to accepting a medical or lifestyle recommendation.
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OBJECTIVE: Our aim was to determine whether the impact of upward and downward social comparison information on individuals' motivation to manage their diabetes is dependent on their regulatory focus (promotion or prevention focus) and self-efficacy.DESIGN: The hypotheses were examined in a cross-sectional study. Patients with diabetes (N = 234) read a fictitious interview with a fellow patient, either an upward or a downward target, and they filled out questionnaires.MAIN OUTCOME MEASURES: Motivation to work on diabetes regulation.RESULTS: High promotion-focused patients reported more motivation than low promotion-focused patients when confronted with the upward target (positive role model). High prevention-focused patients reported more motivation than low prevention-focused patients when confronted with the downward target (negative role model). This latter finding was qualified by patients' self-efficacy, as it applied only to patients with relatively high levels of self-efficacy.CONCLUSION: The current study highlights the importance of considering individual differences when using role models to encourage self-care activities in persons with diabetes.
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The prevalence of type 2 diabetes (T2D) is relatively high among people with a low socioeconomic status (SES). As lifestyle is crucial in T2D management, patients are advised to live healthily, but incorporating lifestyle changes in daily life is not easy. It may be even more difficult for people with a low SES, as they often struggle with more urgent issues in daily life that supersede healthy lifestyle. How to promote a healthy lifestyle such that the needs of low SES patients are met? A boundary condition is a thorough understanding of the target group, and of the differences between individuals in this group. Too often, people with a low SES receive either general advice, or advice targeted to literacy level or ethnic background, whereas the diversity within the low SES population is much wider than that. We developed personas to identify archetypes of the target group, each reflecting a distinct pattern in goals, attitudes and behaviours, to help grasp the diversity of the target group. Ten interviews with low SES T2D-patients revealed their perceptions and experiences related to what is important in life, a healthy lifestyle, living with diabetes, and lifestyle advice. Following Goodwin’s persona development methodology (2011), three groups were qualitatively extracted from the data. In short, the personas are: 1) the worrisome caregiver: wants to live healthier, but is incapable of incorporating advices into one’s life; caring for others is first priority; 2) the conscious self-confident: willing and able to follow up advice in order to reduce medication use; 3) the selfwilled survivor: dealing with multiple (health) issues, and dedicated to solve things one’s own way. Each persona likely responds differently to health promoting strategies. Additional research is needed to enrich the set of personas, for example by verifying them with the target group’s family or health professionals.
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Sodium-glucose co-transporter 2 (SGLT2) inhibitors, including canagliflozin, reduce the risk of cardiovascular and kidney outcomes in patients with and without type 2 diabetes, albeit with a large interindividual variation. The underlying mechanisms for this variation in response might be attributed to differences in SGLT2 occupancy, resulting from individual variation in plasma and tissue drug exposure and receptor availability. We performed a feasibility study for the use of [18F]canagliflozin positron emission tomography (PET) imaging to determine the association between clinical canagliflozin doses and SGLT2 occupancy in patients with type 2 diabetes. We obtained two 90-minute dynamic PET scans with diagnostic intravenous [18F]canagliflozin administration and a full kinetic analysis in 7 patients with type 2 diabetes. Patients received 50, 100, or 300 mg oral canagliflozin (n = 2:4:1) 2.5 hours before the second scan. Canagliflozin pharmacokinetics and urinary glucose excretion were measured. The apparent SGLT2 occupancy was derived from the difference between the apparent volume of distribution of [18F]canagliflozin in the baseline and post-drug PET scans. Individual canagliflozin area under the curve from oral dosing until 24-hours (AUCP0-24h) varied largely (range 1,715–25,747 μg/L*hour, mean 10,580 μg/L*hour) and increased dose dependently with mean values of 4,543, 6,525, and 20,012 μg/L*hour for 50, 100, and 300 mg, respectively (P = 0.046). SGLT2 occupancy ranged between 65% and 87%, but did not correlate with canagliflozin dose, plasma exposure, or urinary glucose excretion. We report the feasibility of [18F]canagliflozin PET imaging to determine canagliflozin kidney disposition and SGLT2 occupancy. This suggests the potential of [18F]canagliflozin as a tool to visualize and quantify clinically SGLT2 tissue binding.
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The angiotensin receptor blocker telmisartan slows progression of kidney disease in patients with type 2 diabetes (T2D), yet many patients remain at high risk for progressive kidney function loss. The underlying mechanisms for this response variation might be attributed to differences in angiotensin-1 receptor occupancy (RO), resulting from individual variation in plasma drug exposure, tissue drug exposure, and receptor availability. Therefore, we first assessed the relationship between plasma telmisartan exposure and urinary-albumin-to-creatinine-ratio (UACR) in 10 patients with T2D and albuminuria (mean age 66 years, median UACR 297 mg/g) after 4 weeks treatment with 80 mg telmisartan once daily. Increasing telmisartan exposure associated with a larger reduction in UACR (Pearson correlation coefficient (PCC) = −0.64, P = 0.046, median change UACR: −40.1%, 95% confidence interval (CI): −22.9 to −77.4%, mean telmisartan area under the curve (AUC) = 2927.1 ng·hour/mL, 95% CI: 723.0 to 6501.6 ng·hour/mL). Subsequently, we assessed the relation among plasma telmisartan exposure, kidney distribution, and angiotensin-1 RO in five patients with T2D (mean age 60 years, median UACR 72 mg/g) in a separate positron emission tomography imaging study with [11C]Telmisartan. Individual plasma telmisartan exposure correlated with telmisartan distribution to the kidneys (PCC = 0.976, P = 0.024). A meaningful RO could be calculated in three patients receiving 120 mg oral telmisartan, and although high exposure seems related to higher RO, with AUC0–last of 31, 840, and 274 ng·hour/mL and corresponding RO values 5.5%, 44%, and 59%, this was not significant (P = 0.64). Together these results indicate, for the first time, a relationship among interindividual differences in plasma exposure, kidney tissue distribution, RO, and ultimately UACR response after telmisartan administration.
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The purpose of this study was to determine the efficacy of an online self-tracking program on physical activity, glycated hemoglobin, and other health measures in patients with type 2 diabetes. Seventy-two patients with type 2 diabetes were randomly assigned to an intervention or control group. All participants received usual care. The intervention group received an activity tracker (Fitbit Zip) connected to an online lifestyle program. Physical activity was analyzed in average steps per day from week 0 until 12. Health outcome measurements occurred in both groups at baseline and after 13 weeks. Results indicated that the intervention group significantly increased physical activity with 1.5 ± 3 days per week of engagement in 30 minutes of moderate-vigorous physical activity versus no increase in the control group (P = .047). Intervention participants increased activity with 1255 ± 1500 steps per day compared to their baseline (P < .010). No significant differences were found in glycated hemoglobin A1c, with the intervention group decreasing -0.28% ± 1.03% and the control group showing -0.0% ± 0.69% (P = .206). Responders (56%, increasing minimally 1000 steps/d) had significantly decreased glycated hemoglobin compared with nonresponders (-0.69% ± 1.18% vs 0.22% ± 0.47%, respectively; P = .007). To improve effectiveness of eHealth programs, additional strategies are needed.This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal.
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A substantial proportion of chronic disease patients do not respond to self-management interventions, which suggests that one size interventions do not fit all, demanding more tailored interventions. To compose more individualized strategies, we aim to increase our understanding of characteristics associated with patient activation for self-management and to evaluate whether these are disease-transcending. A cross-sectional survey study was conducted in primary and secondary care in patients with type-2 Diabetes Mellitus (DM-II), Chronic Obstructive Pulmonary Disease (COPD), Chronic Heart Failure (CHF) and Chronic Renal Disease (CRD). Using multiple linear regression analysis, we analyzed associations between self-management activation (13-item Patient Activation Measure; PAM-13) and a wide range of socio-demographic, clinical, and psychosocial determinants. Furthermore, we assessed whether the associations between the determinants and the PAM were disease-transcending by testing whether disease was an effect modifier. In addition, we identified determinants associated with low activation for self-management using logistic regression analysis. We included 1154 patients (53% response rate); 422 DM-II patients, 290 COPD patients, 223 HF patients and 219 CRD patients. Mean age was 69.6±10.9. Multiple linear regression analysis revealed 9 explanatory determinants of activation for selfmanagement: age, BMI, educational level, financial distress, physical health status, depression, illness perception, social support and underlying disease, explaining a variance of 16.3%. All associations, except for social support, were disease transcending. This study explored factors associated with varying levels of activation for self-management. These results are a first step in supporting clinicians and researchers to identify subpopulations of chronic disease patients less likely to be engaged in self-management. Increased scientific efforts are needed to explain the greater part of the factors that contribute to the complex nature of patient activation for self-management.
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