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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Using stable isotope techniques, this study shows that plasma free fatty acid oxidation is not impaired during exercise in non-obese type II diabetic patients.
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The aim of the present study was to determine whether a diagnosis of diabetes mellitus (DM) in a primary setting is associated with an increased risk of subsequent depression. A retrospective cohort design was used based on the Registration Network Family Practice (RNH) database. Patients diagnosed with diabetes mellitus at or after the age of 40 and who were diagnosed between 01-01-1980 and 01-01-2007 (N = 6,140), were compared with age-matched controls from a reference group (N = 18,416) without a history of diabetes. Both groups were followed for an emerging first diagnosis of depression (and/or depressive feelings) until January 1, 2008. 2.0% of the people diagnosed with diabetes mellitus developed a depressive disorder, compared to 1.6% of the reference group. After statistical correction for confounding factors diabetes mellitus was associated with an increased risk of developing subsequent depression (HR 1.26; 95% CI: 1.12-1.42) and/or depressive feelings (HR 1.33; 95% CI: 1.18-1.46). After statistical adjustment practice identification code, age and depression preceding diabetes, were significantly related to a diagnosis of depression. Patients with diabetes mellitus are more likely to develop subsequent depression than persons without a history of diabetes. Results from this large longitudinal study based on a general practice population indicate that this association is weaker than previously found in cross-sectional research using self-report surveys. Several explanations for this dissimilarity are discussed
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(1) Background: Recent research showed that subtypes of patients with type 2 diabetes may differ in response to lifestyle interventions based on their organ-specific insulin resistance (IR). (2) Methods: 123 Subjects with type 2 diabetes were randomized into 13-week lifestyle intervention, receiving either an enriched protein drink (protein+) or an isocaloric control drink (control). Before and after the intervention, anthropometrical and physiological data was collected. An oral glucose tolerance test was used to calculate indices representing organ insulin resistance (muscle, liver, and adipose tissue) and β-cell functioning. In 82 study-compliant subjects (per-protocol), we retrospectively examined the intervention effect in patients with muscle IR (MIR, n = 42) and without MIR (no-MIR, n = 40). (3) Results: Only in patients from the MIR subgroup that received protein+ drink, fasting plasma glucose and insulin, whole body, liver and adipose IR, and appendicular skeletal muscle mass improved versus control. Lifestyle intervention improved body weight and fat mass in both subgroups. Furthermore, for the MIR subgroup decreased systolic blood pressure and increased VO2peak and for the no-MIR subgroup, a decreased 2-h glucose concentration was found. (4) Conclusions: Enriched protein drink during combined lifestyle intervention seems to be especially effective on increasing muscle mass and improving insulin resistance in obese older, type 2 diabetes patients with muscle IR.
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Aims: This systematic review and meta-analysis evaluates the additional effect of exercise to hypocaloric diet on body weight, body composition, glycaemic control and cardio-respiratory fitness in adults with overweight or obesity and type 2 diabetes. Methods: Embase, Medline, Web of Science and Cochrane Central databases were evaluated, and 11 studies were included. Random-effects meta-analysis was performed on body weight and measures of body composition and glycaemic control, to compare the effect of hypocaloric diet plus exercise with hypocaloric diet alone. Results: Exercise interventions consisted of walking or jogging, cycle ergometer training, football training or resistance training and duration varied from 2 to 52 weeks. Body weight and measures of body composition and glycaemic control decreased during both the combined intervention and hypocaloric diet alone. Mean difference in change of body weight (−0.77 kg [95% CI: −2.03; 0.50]), BMI (−0.34 kg/m2 [95% CI: −0.73; 0.05]), waist circumference (−1.42 cm [95% CI: −3.84; 1.00]), fat-free mass (−0.18 kg [95% CI: −0.52; 0.17]), fat mass (−1.61 kg [95% CI: −4.42; 1.19]), fasting glucose (+0.14 mmol/L [95% CI: −0.02; 0.30]), HbA1c (−1 mmol/mol [95% CI: −3; 1], −0.1% [95% CI: −0.2; 0.1]) and HOMA-IR (+0.01 [95% CI: −0.40; 0.42]) was not statistically different between the combined intervention and hypocaloric diet alone. Two studies reported VO2max and showed significant increases upon the addition of exercise to hypocaloric diet. Conclusions: Based on limited data, we did not find additional effects of exercise to hypocaloric diet in adults with overweight or obesity and type 2 diabetes on body weight, body composition or glycaemic control, while cardio-respiratory fitness improved.
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PURPOSE: To assess the association of clinical variables and the development of specified chronic conditions in ICU survivors.MATERIALS AND METHODS: A retrospective cohort study, combining a national health insurance claims database and a national quality registry for ICUs. Claims data from 2012 to 2014 were combined with clinical data of patients admitted to an ICU during 2013. To assess the association of clinical variables (ICU length of stay, mechanical ventilation, acute physiology score, reason for ICU admission, mean arterial pressure score and glucose score) and the development of chronic conditions (i.e. heart diseases, COPD or asthma, Diabetes mellitus type II, depression and kidney diseases), logistic regression was used.RESULTS: 49,004 ICU patients were included. ICU length of stay was associated with the development of heart diseases, asthma or COPD and depression. The reason for ICU admission was an important risk factor for the development of all chronic conditions with adjusted ORs ranging from 2.05 (CI 1.56; 2.69) for kidney diseases to 5.14 (CI 3.99; 6.62) for depression.CONCLUSIONS: Clinical variables, especially the reason for ICU admission, are associated with the development of chronic conditions after ICU discharge. Therefore, these clinical variables should be considered when organizing follow-up care for ICU survivors.
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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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Inhibition of the sodium−glucose cotransporter 2 (SGLT2) by canagliflozin in type 2 diabetes mellitus results in large between-patient variability in clinical response. To better understand this variability, the positron emission tomography (PET) tracer [18F]canagliflozin was developed via a Cu-mediated 18F-fluorination of its boronic ester precursor with a radiochemical yield of 2.0 ± 1.9% and a purity of >95%. The GMP automated synthesis originated [18F]canagliflozin with a yield of 0.5−3% (n = 4) and a purity of >95%. Autoradiography showed [18F]canagliflozin binding in human kidney sections containing SGLT2. Since [18F]canagliflozin is the isotopologue of the extensively characterized drug canagliflozin and thus shares its toxicological and pharmacological characteristics, it enables its immediate use in patients.
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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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