108 research outputs found

    Use of mental health services among disaster survivors: predisposing factors

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    <p>Abstract</p> <p>Background</p> <p>Given the high prevalence of mental health problems after disasters it is important to study health services utilization. This study examines predictors for mental health services (MHS) utilization among survivors of a man-made disaster in the Netherlands (May 2000).</p> <p>Methods</p> <p>Electronic records of survivors (n = 339; over 18 years and older) registered in a mental health service (MHS) were linked with general practice based electronic medical records (EMRs) of survivors and data obtained in surveys. EMR data were available from 16 months pre-disaster until 3 years post-disaster. Symptoms and diagnoses in the EMRs were coded according to the International Classification of Primary Care (ICPC). Surveys were carried out 2–3 weeks and 18 months post-disaster, and included validated questionnaires on psychological distress, post-traumatic stress reactions and social functioning. Demographic and disaster-related variables were available. Predisposing factors for MHS utilization 0–18 months and 18–36 months post-disaster were examined using multiple logistic regression models.</p> <p>Results</p> <p>In multiple logistic models, adjusting for demographic and disaster related variables, MHS utilization was predicted by demographic variables (young age, immigrant, public health insurance, unemployment), disaster-related exposure (relocation and injuries), self-reported psychological problems and pre- and post-disaster physician diagnosed health problems (chronic diseases, musculoskeletal problems). After controlling for all health variables, disaster intrusions and avoidance reactions (OR:2.86; CI:1.48–5.53), hostility (OR:2.04; CI:1.28–3.25), pre-disaster chronic diseases (OR:1.82; CI:1.25–2.65), injuries as a result of the disaster (OR:1.80;CI:1.13–2.86), social functioning problems (OR:1.61;CI:1.05–2.44) and younger age (OR:0.98;CI:0.96–0.99) predicted MHS utilization within 18 months post-disaster. Furthermore, disaster intrusions and avoidance reactions (OR:2.29;CI:1.04–5.07) and hostility (OR:3.77;CI:1.51–9.40) predicted MHS utilization following 18 months post-disaster.</p> <p>Conclusion</p> <p>This study showed that several demographic and disaster-related variables and self-reported and physician diagnosed health problems predicted post-disaster MHS-use. The most important factors to predict post-disaster MHS utilization were disaster intrusions and avoidance reactions and symptoms of hostility (which can be identified as symptoms of PTSD) and pre-disaster chronic diseases.</p

    A graphical vector autoregressive modelling approach to the analysis of electronic diary data

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    <p>Abstract</p> <p>Background</p> <p>In recent years, electronic diaries are increasingly used in medical research and practice to investigate patients' processes and fluctuations in symptoms over time. To model dynamic dependence structures and feedback mechanisms between symptom-relevant variables, a multivariate time series method has to be applied.</p> <p>Methods</p> <p>We propose to analyse the temporal interrelationships among the variables by a structural modelling approach based on graphical vector autoregressive (VAR) models. We give a comprehensive description of the underlying concepts and explain how the dependence structure can be recovered from electronic diary data by a search over suitable constrained (graphical) VAR models.</p> <p>Results</p> <p>The graphical VAR approach is applied to the electronic diary data of 35 obese patients with and without binge eating disorder (BED). The dynamic relationships for the two subgroups between eating behaviour, depression, anxiety and eating control are visualized in two path diagrams. Results show that the two subgroups of obese patients with and without BED are distinguishable by the temporal patterns which influence their respective eating behaviours.</p> <p>Conclusion</p> <p>The use of the graphical VAR approach for the analysis of electronic diary data leads to a deeper insight into patient's dynamics and dependence structures. An increasing use of this modelling approach could lead to a better understanding of complex psychological and physiological mechanisms in different areas of medical care and research.</p

    Canagliflozin and Renal Outcomes in Type 2 Diabetes and Nephropathy

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    BACKGROUND Type 2 diabetes mellitus is the leading cause of kidney failure worldwide, but few effective long-term treatments are available. In cardiovascular trials of inhibitors of sodium–glucose cotransporter 2 (SGLT2), exploratory results have suggested that such drugs may improve renal outcomes in patients with type 2 diabetes. METHODS In this double-blind, randomized trial, we assigned patients with type 2 diabetes and albuminuric chronic kidney disease to receive canagliflozin, an oral SGLT2 inhibitor, at a dose of 100 mg daily or placebo. All the patients had an estimated glomerular filtration rate (GFR) of 30 to 300 to 5000) and were treated with renin–angiotensin system blockade. The primary outcome was a composite of end-stage kidney disease (dialysis, transplantation, or a sustained estimated GFR of <15 ml per minute per 1.73 m 2), a doubling of the serum creatinine level, or death from renal or cardiovascular causes. Prespecified secondary outcomes were tested hierarchically. RESULTS The trial was stopped early after a planned interim analysis on the recommendation of the data and safety monitoring committee. At that time, 4401 patients had undergone randomization, with a median follow-up of 2.62 years. The relative risk of the primary outcome was 30% lower in the canagliflozin group than in the placebo group, with event rates of 43.2 and 61.2 per 1000 patient-years, respectively (hazard ratio, 0.70; 95% confidence interval [CI], 0.59 to 0.82; P=0.00001). The relative risk of the renal-specific composite of end-stage kidney disease, a doubling of the creatinine level, or death from renal causes was lower by 34% (hazard ratio, 0.66; 95% CI, 0.53 to 0.81; P<0.001), and the relative risk of end-stage kidney disease was lower by 32% (hazard ratio, 0.68; 95% CI, 0.54 to 0.86; P=0.002). The canagliflozin group also had a lower risk of cardiovascular death, myocardial infarction, or stroke (hazard ratio, 0.80; 95% CI, 0.67 to 0.95; P=0.01) and hospitalization for heart failure (hazard ratio, 0.61; 95% CI, 0.47 to 0.80; P<0.001). There were no significant differences in rates of amputation or fracture. CONCLUSIONS In patients with type 2 diabetes and kidney disease, the risk of kidney failure and cardiovascular events was lower in the canagliflozin group than in the placebo group at a median follow-up of 2.62 years

    Canagliflozin and renal outcomes in type 2 diabetes and nephropathy

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    BACKGROUND Type 2 diabetes mellitus is the leading cause of kidney failure worldwide, but few effective long-term treatments are available. In cardiovascular trials of inhibitors of sodium–glucose cotransporter 2 (SGLT2), exploratory results have suggested that such drugs may improve renal outcomes in patients with type 2 diabetes. METHODS In this double-blind, randomized trial, we assigned patients with type 2 diabetes and albuminuric chronic kidney disease to receive canagliflozin, an oral SGLT2 inhibitor, at a dose of 100 mg daily or placebo. All the patients had an estimated glomerular filtration rate (GFR) of 30 to &lt;90 ml per minute per 1.73 m2 of body-surface area and albuminuria (ratio of albumin [mg] to creatinine [g], &gt;300 to 5000) and were treated with renin–angiotensin system blockade. The primary outcome was a composite of end-stage kidney disease (dialysis, transplantation, or a sustained estimated GFR of &lt;15 ml per minute per 1.73 m2), a doubling of the serum creatinine level, or death from renal or cardiovascular causes. Prespecified secondary outcomes were tested hierarchically. RESULTS The trial was stopped early after a planned interim analysis on the recommendation of the data and safety monitoring committee. At that time, 4401 patients had undergone randomization, with a median follow-up of 2.62 years. The relative risk of the primary outcome was 30% lower in the canagliflozin group than in the placebo group, with event rates of 43.2 and 61.2 per 1000 patient-years, respectively (hazard ratio, 0.70; 95% confidence interval [CI], 0.59 to 0.82; P=0.00001). The relative risk of the renal-specific composite of end-stage kidney disease, a doubling of the creatinine level, or death from renal causes was lower by 34% (hazard ratio, 0.66; 95% CI, 0.53 to 0.81; P&lt;0.001), and the relative risk of end-stage kidney disease was lower by 32% (hazard ratio, 0.68; 95% CI, 0.54 to 0.86; P=0.002). The canagliflozin group also had a lower risk of cardiovascular death, myocardial infarction, or stroke (hazard ratio, 0.80; 95% CI, 0.67 to 0.95; P=0.01) and hospitalization for heart failure (hazard ratio, 0.61; 95% CI, 0.47 to 0.80; P&lt;0.001). There were no significant differences in rates of amputation or fracture. CONCLUSIONS In patients with type 2 diabetes and kidney disease, the risk of kidney failure and cardiovascular events was lower in the canagliflozin group than in the placebo group at a median follow-up of 2.62 years

    Wind Power Persistence Characterized by Superstatistics

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    Mitigating climate change demands a transition towards renewable electricity generation, with wind power being a particularly promising technology. Long periods either of high or of low wind therefore essentially define the necessary amount of storage to balance the power system. While the general statistics of wind velocities have been studied extensively, persistence (waiting) time statistics of wind is far from well understood. Here, we investigate the statistics of both high- and low-wind persistence. We find heavy tails and explain them as a superposition of different wind conditions, requiring q-exponential distributions instead of exponential distributions. Persistent wind conditions are not necessarily caused by stationary atmospheric circulation patterns nor by recurring individual weather types but may emerge as a combination of multiple weather types and circulation patterns. This also leads to Fréchet instead of Gumbel extreme value statistics. Understanding wind persistence statistically and synoptically may help to ensure a reliable and economically feasible future energy system, which uses a high share of wind generation

    Sectionalizing distribution networks concept and system framework

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    The increasing dependency of society on electricity motivates the research for more reliable and resilient distribution networks. Self-healing of networks is one of the key elements of the Smart Grid concept. Conventional self-healing networks (CSHNs) recover part of the network by rerouting power with automated switchgear. By utilizing microgrids (MGs), the sectionalizing distribution networks (SDNs) concept is an extension of CSHNs which utilizes both automated switchgear and distributed energy resources (DERs) to create both grid-connected and islanded microgrids (MGs). The SDN concept provides more resilience against faults than CSHNs and allows local bottom-up blackout restoration. This paper provides a high-level conceptual and operation states description, a system framework and the operational sequence of SDNs in case of faults. Finally, several future research directions are proposed

    Cerebral tissue oxygenation index in very premature infants

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    Aim: To describe normal values of the cerebral tissue oxygenation index (TOI) in premature infants. Methods: TOI was measured by spatially resolved spectroscopy in preterm infants on the first 3 days of life. Infants with an abnormal cranial ultrasound were excluded. Other simultaneously measured variables were PaO(2), PaCO(2), pH, mean arterial blood pressure, heart rate, haemoglobin, glycaemia, and peripheral oxygen saturation. Results: Fifteen patients with a median postmenstrual age of 28 weeks were measured. There was a significant increase in median TOI over the first 3 days of life: 57% on day 1, 66.1% on day 2, and 76.1% on day 3. Multiple regression analysis showed no correlation between TOI and postmenstrual age, peripheral oxygen saturation, mean arterial blood pressure, PaO(2), PaCO(2), and haemoglobin concentration. Conclusion: Cerebral TOI increases significantly in the first 3 days of life in premature babies. This increase probably reflects the increase in cerebral blood flow at this time
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