Psychological risk factors of micro- and macrovascular outcomes in primary care patients with type 2 diabetes:Rationale and design of the DiaDDZoB Study

BACKGROUND: Depression is a common psychiatric complication of diabetes, but little is known about the natural course and the consequences of depressive symptoms in primary care patients with type 2 diabetes. While depression has been related to poor glycemic control and increased risk for macrovascular disease, its association with microvascular complications remains understudied. The predictive role of other psychological risk factors such as Type D (distressed) personality and the mechanisms that possibly link depression and Type D personality with poor vascular outcomes are also still unclear. METHODS/DESIGN: This prospective cohort study will examine: (1) the course of depressive symptoms in primary care patients with type 2 diabetes; (2) whether depressive symptoms and Type D personality are associated with the development of microvascular and/or macrovascular complications and with the risk of all-cause or vascular mortality; and (3) the behavioral and physiological mechanisms that may mediate these associations. The DiaDDZoB Study is embedded within the larger DIAZOB Primary Care Diabetes study, which covers a comprehensive cohort of type 2 diabetes patients treated by over 200 primary care physicians in South-East Brabant, The Netherlands. These patients will be followed during their lifetime and are assessed annually for demographic, clinical, lifestyle and psychosocial factors. Measurements include an interviewer-administered and self-report questionnaire, regular care laboratory tests and physical examinations, and pharmacy medication records. The DiaDDZoB Study uses data that have been collected during the original baseline assessment in 2005 (M(0); N = 2,460) and the 2007 (M(1); N = 2,225) and 2008 (M(2); N = 2,032) follow-up assessments. DISCUSSION: The DiaDDZoB Study is expected to contribute to the current understanding of the course of depression in primary care patients with type 2 diabetes and will also test whether depressed patients or those with Type D personality are at increased risk for (further) development of micro- and cardiovascular disease. More knowledge about the mechanisms behind this association is needed to guide new intervention studies

Patient-reported outcomes in primary care patients with COPD:Psychometric properties and usefulness of the Clinical COPD Questionnaire (CCQ). A cross-sectional study

Background Remote patient monitoring is a safe and effective alternative for the in-clinic follow-up of patients with cardiovascular implantable electronic devices (CIEDs). However, evidence on the patient perspective on remote monitoring is scarce and inconsistent. Objectives The primary objective of the REMOTE-CIED study is to evaluate the influence of remote patient monitoring versus in-clinic follow-up on patient-reported outcomes. Secondary objectives are to: 1) identify subgroups of patients who may not be satisfied with remote monitoring; and 2) investigate the cost-effectiveness of remote monitoring. Methods The REMOTE-CIED study is an international randomised controlled study that will include 900 consecutive heart failure patients implanted with an implantable cardioverter defibrillator (ICD) compatible with the Boston Scientific LATITUDE® Remote Patient Management system at participating centres in five European countries. Patients will be randomised to remote monitoring or in-clinic follow-up. The In-Clinic group will visit the outpatient clinic every 3–6 months, according to standard practice. The Remote Monitoring group only visits the outpatient clinic at 12 and 24 months post-implantation, other check-ups are performed remotely. Patients are asked to complete questionnaires at five time points during the 2-year follow-up. Conclusion The REMOTE-CIED study will provide insight into the patient perspective on remote monitoring in ICD patients, which could help to support patient-centred care in the future. Keywords: REMOTE-CIED, Cardiovascular implantable electronic devices, Remote monitoring, Patient-reported outcomes, Cost-effectivenes

Associations between physical activity and depressive symptoms by weight status among adults with type 2 diabetes: Results from diabetes miles-Australia

© 2017 Human Kinetics, Inc. Background: To examine associations between physical activity (PA) and depressive symptoms among adults with type 2 diabetes mellitus (Type 2 DM), and whether associations varied according to weight status. Methods: Diabetes MILES-Australia is a national survey of adults with diabetes, focused on behavioral and psychosocial issues. Data from 705 respondents with Type 2 DM were analyzed, including: demographic and clinical characteristics, PA (IPAQ-SF), depressive symptoms (PHQ-9), and BMI (self-reported height and weight). Data analysis was performed using ANCOVA. Results: Respondents were aged 59 ± 8 years; 50% women. PA was negatively associated with depressive symptoms for the overall sample (?p 2= 0.04,P < .001) and all weight categories separately: healthy (?p 2 0.11 P = .041,), overweight (?p 2= 0.04, P = .025) and obese (?p 2 = 0.03, P = .007). For people who were healthy (BMI 18.5 to 24.9) or overweight (BMI 25 to 29.9), high amounts of PA were significantly associated with fewer depressive symptoms; for adults who were obese (BMI ? 30) however, both moderate and high amounts were associated with fewer depressive symptoms. Conclusions: PA is associated with fewer depressive symptoms among adults with Type 2DM, however the amount of PA associated with fewer depressive symptoms varies according to weight status. Lower amounts of PA might be required for people who are obese to achieve meaningful reductions in depressive symptoms compared with those who are healthy weight or overweight. Further research is needed to establish the direction of the relationship between PA and depressive symptoms

Reducing the burden of hypoglycaemia in people with diabetes through increased understanding:design of the Hypoglycaemia Redefining Solutions for Better Lives (Hypo-RESOLVE) project

Background Hypoglycaemia is the most frequent complication of treatment with insulin or insulin secretagogues in people with diabetes. Severe hypoglycaemia, i.e. an event requiring external help because of cognitive dysfunction, is associated with a higher risk of adverse cardiovascular outcomes and all‐cause mortality, but underlying mechanism(s) are poorly understood. There is also a gap in the understanding of the clinical, psychological and health economic impact of ‘non‐severe’ hypoglycaemia and the glucose level below which hypoglycaemia causes harm. Aim To increase understanding of hypoglycaemia by addressing the above issues over a 4‐year period. Methods Hypo‐RESOLVE is structured across eight work packages, each with a distinct focus. We will construct a large, sustainable database including hypoglycaemia data from >100 clinical trials to examine predictors of hypoglycaemia and establish glucose threshold(s) below which hypoglycaemia constitutes a risk for adverse biomedical and psychological outcomes, and increases healthcare costs. We will also investigate the mechanism(s) underlying the antecedents and consequences of hypoglycaemia, the significance of glucose sensor‐detected hypoglycaemia, the impact of hypoglycaemia in families, and the costs of hypoglycaemia for healthcare systems. Results The outcomes of Hypo‐RESOLVE will inform evidence‐based definitions regarding the classification of hypoglycaemia in diabetes for use in daily clinical practice, future clinical trials and as a benchmark for comparing glucose‐lowering interventions and strategies across trials. Stakeholders will be engaged to achieve broadly adopted agreement. Conclusion Hypo‐RESOLVE will advance our understanding and refine the classification of hypoglycaemia, with the ultimate aim being to alleviate the burden and consequences of hypoglycaemia in people with diabetes

Modeling Interactions Between Latent Variables in Research on Type D Personality: A Monte Carlo Simulation and Clinical Study of Depression and Anxiety

Item does not contain fulltextSeveral approaches exist to model interactions between latent variables. However, it is unclear how these perform when item scores are skewed and ordinal. Research on Type D personality serves as a good case study for that matter. In Study 1, we fitted a multivariate interaction model to predict depression and anxiety with Type D personality, operationalized as an interaction between its two subcomponents negative affectivity (NA) and social inhibition (SI). We constructed this interaction according to four approaches: (1) sum score product; (2) single product indicator; (3) matched product indicators; and (4) latent moderated structural equations (LMS). In Study 2, we compared these interaction models in a simulation study by assessing for each method the bias and precision of the estimated interaction effect under varying conditions. In Study 1, all methods showed a significant Type D effect on both depression and anxiety, although this effect diminished after including the NA and SI quadratic effects. Study 2 showed that the LMS approach performed best with respect to minimizing bias and maximizing power, even when item scores were ordinal and skewed. However, when latent traits were skewed LMS resulted in more false-positive conclusions, while the Matched PI approach adequately controlled the false-positive rate