Expert clinical reasoning and pain assessment in mechanically ventilated patients: A descriptive study.

BACKGROUND: Pain assessment in mechanically ventilated patients is challenging, because nurses need to decode pain behaviour, interpret pain scores, and make appropriate decisions. This clinical reasoning process is inherent to advanced nursing practice, but is poorly understood. A better understanding of this process could contribute to improved pain assessment and management. OBJECTIVE: This study aimed to describe the indicators that influence expert nurses' clinical reasoning when assessing pain in critically ill nonverbal patients. METHODS: This descriptive observational study was conducted in the adult intensive care unit (ICU) of a tertiary referral hospital in Western Switzerland. A purposive sample of expert nurses, caring for nonverbal ventilated patients who received sedation and analgesia, were invited to participate in the study. Data were collected in "real life" using recorded think-aloud combined with direct non-participant observation and brief interviews. Data were analysed using deductive and inductive content analyses using a theoretical framework related to clinical reasoning and pain. RESULTS: Seven expert nurses with an average of 7.85 (±3.1) years of critical care experience participated in the study. The patients had respiratory distress (n=2), cardiac arrest (n=2), sub-arachnoid bleeding (n=1), and multi-trauma (n=2). A total of 1344 quotes in five categories were identified. Patients' physiological stability was the principal indicator for making decision in relation to pain management. Results also showed that it is a permanent challenge for nurses to discriminate situations requiring sedation from situations requiring analgesia. Expert nurses mainly used working knowledge and patterns to anticipate and prevent pain. CONCLUSIONS: Patient's clinical condition is important for making decision about pain in critically ill nonverbal patients. The concept of pain cannot be assessed in isolation and its assessment should take the patient's clinical stability and sedation into account. Further research is warranted to confirm these results.

Biological impact assessment of nanomaterial used in nanomedicine. Introduction to the NanoTEST project.

Therapeutic nanoparticles (NPs) are used in nanomedicine as drug carriers or imaging agents, providing increased selectivity/specificity for diseased tissues. The first NPs in nanomedicine were developed for increasing the efficacy of known drugs displaying dose-limiting toxicity and poor bioavailability and for enhancing disease detection. Nanotechnologies have gained much interest owing to their huge potential for applications in industry and medicine. It is necessary to ensure and control the biocompatibility of the components of therapeutic NPs to guarantee that intrinsic toxicity does not overtake the benefits. In addition to monitoring their toxicity in vitro, in vivo and in silico, it is also necessary to understand their distribution in the human body, their biodegradation and excretion routes and dispersion in the environment. Therefore, a deep understanding of their interactions with living tissues and of their possible effects in the human (and animal) body is required for the safe use of nanoparticulate formulations. Obtaining this information was the main aim of the NanoTEST project, and the goals of the reports collected together in this special issue are to summarise the observations and results obtained by the participating research teams and to provide methodological tools for evaluating the biological impact of NPs.

Mercury analysis in hair: comparability and quality assessment within the transnational COPHES/DEMOCOPHES project

Human biomonitoring (HBM) is an effective tool for assessing actual exposure to chemicals that takes into account all routes of intake. Although hair analysis is considered to be an optimal biomarker for assessing mercury exposure, the lack of harmonization as regards sampling and analytical procedures has often limited the comparison of data at national and international level. The European-funded projects COPHES and DEMOCOPHES developed and tested a harmonized European approach to Human Biomonitoring in response to the European Environment and Health Action Plan. Herein we describe the quality assurance program (QAP) for assessing mercury levels in hair samples from more than 1800 mother-child pairs recruited in 17 European countries. To ensure the comparability of the results, standard operating procedures (SOPs) for sampling and for mercury analysis were drafted and distributed to participating laboratories. Training sessions were organized for field workers and four external quality-assessment exercises (ICI/EQUAS), followed by the corresponding web conferences, were organized between March 2011 and February 2012. ICI/EQUAS used native hair samples at two mercury concentration ranges (0.20-0.71 and 0.80-1.63) per exercise. The results revealed relative standard deviations of 7.87-13.55% and 4.04-11.31% for the low and high mercury concentration ranges, respectively. A total of 16 out of 18 participating laboratories the QAP requirements and were allowed to analyze samples from the DEMOCOPHES pilot study. Web conferences after each ICI/EQUAS revealed this to be a new and effective tool for improving analytical performance and increasing capacity building. The procedure developed and tested in COPHES/DEMOCOPHES would be optimal for application on a global scale as regards implementation of the Minamata Convention on Mercury.

Multi-scale support vector algorithms for hot spot detection and modelling

The algorithmic approach to data modelling has developed rapidly these last years, in particular methods based on data mining and machine learning have been used in a growing number of applications. These methods follow a data-driven methodology, aiming at providing the best possible generalization and predictive abilities instead of concentrating on the properties of the data model. One of the most successful groups of such methods is known as Support Vector algorithms. Following the fruitful developments in applying Support Vector algorithms to spatial data, this paper introduces a new extension of the traditional support vector regression (SVR) algorithm. This extension allows for the simultaneous modelling of environmental data at several spatial scales. The joint influence of environmental processes presenting different patterns at different scales is here learned automatically from data, providing the optimum mixture of short and large-scale models. The method is adaptive to the spatial scale of the data. With this advantage, it can provide efficient means to model local anomalies that may typically arise in situations at an early phase of an environmental emergency. However, the proposed approach still requires some prior knowledge on the possible existence of such short-scale patterns. This is a possible limitation of the method for its implementation in early warning systems. The purpose of this paper is to present the multi-scale SVR model and to illustrate its use with an application to the mapping of Cs137 activity given the measurements taken in the region of Briansk following the Chernobyl accident.

Treatment motivation in adolescents with psychosis or at high risk: Determinants and impact on improvements in symptoms and cognitive functioning, preliminary results.

Abstract Low motivation is frequent in chronic disorders such as psychosis and may limit treatment efficacy. Although some evidence supports this view in adults, few studies so far have focused on adolescents. We assessed the impact of baseline symptoms, cognitive deficits and cognitive treatment characteristics on treatment motivation (TM), and examined whether TM affected treatment outcome. Twenty-eight adolescents with psychotic disorders participated in 16 sessions of computerized cognitive remediation or games. TM was assessed for each session. Lower TM was predicted by more severe symptoms at baseline, and was associated with smaller improvements in symptoms and both cognitive and psychosocial functioning at the end of the intervention. Experiencing success in the treatment exercises enhanced TM in all patients.

Development and preclinical assessment of a bioartificial pancreas.

Transplantation of insulin secreting cells is regarded as a possible treatment for type 1 diabetes. One major difficulty in this approach is, however, that the transplanted cells are exposed to the patient's inflammatory and autoimmune environment, which originally destroyed their own beta-cells. Therefore, even if a good source of insulin-secreting cells can be identified for transplantation therapy, these cells need to be protected against these destructive influences. The aim of this project was to evaluate, using a clonal mouse beta-cell line, whether genetic engineering of protective genes could be a viable option to allow these cells to survive when transplanted into autoimmune diabetic mice. We demonstrated that transfer of the Bcl-2 anti-apoptotic gene and of several genes specifically interfering with cytokines intracellular signalling pathways, greatly improved resistance of the cells to inflammatory stresses in vitro. We further showed that these modifications did not interfere with the capacity of these cells to correct hyperglycaemia for several months in syngeneic or allogeneic streptozocin-diabetic mice. However, these cells were not protected against autoimmune destruction when transplanted into type 1 diabetic NOD mice. This suggests that in addition to inflammatory attacks by cytokines, autoimmunity very efficiently kills the transplanted cells, indicating that multiple protective mechanisms are required for efficient transplantation of insulin-secreting cells to treat type 1 diabetes.

Eosinophilie sanguine: quel bilan, quel cheminement diagnostique [Peripheral blood eosinophilia: diagnostic value and further assessment].

Although not specific, an increased in peripheral blood eosinophils may contribute substantially to the diagnosis of numerous infectious, allergic and inflammatory diseases. The scope of this article is to detail pathologies associated with peripheral eosinophilia by order of frequency and to guide further investigations.

Ventricular arrhythmia in coronary artery disease: limits of a risk stratification strategy based on the ejection fraction alone and impact of infarct localization.

AIMS: Estimates of the left ventricular ejection fraction (LVEF) in patients with life-threatening ventricular arrhythmias related to coronary artery disease (CAD) have rarely been reported despite it has become the basis for determining patient's eligibility for prophylactic defibrillator. We aimed to determine the extent and distribution of reduced LVEF in patients with sustained ventricular tachycardia or ventricular fibrillation. METHODS AND RESULTS: 252 patients admitted for ventricular arrhythmia related to CAD were included: 149 had acute myocardial infarction (MI) (Group I, 59%), 54 had significant chronic obstructive CAD suggestive of an ischaemic arrhythmic trigger (Group II, 21%) and 49 patients had an old MI without residual ischaemia (Group III, 19%). 34% of the patients with scar-related arrhythmias had an LVEF > or =40%. Based on pre-event LVEF evaluation, it can be estimated that less than one quarter of the whole study population had a known chronic MI with severely reduced LVEF. In Group III, the proportion of inferior MI was significantly higher than anterior MI (81 vs. 19%; absolute difference, -62; 95% confidence interval, -45 to -79; P < or = 0.0001), though median LVEF was higher in inferior MI (0.37 +/- 10 vs. 0.29 +/- 10; P = 0.0499). CONCLUSION: Patients included in defibrillator trials represent only a minority of the patients at risk of sudden cardiac death. By applying the current risk stratification strategy based on LVEF, more than one third of the patients with old MI would not have qualified for a prophylactic defibrillator. Our study also suggests that inferior scars may be more prone to ventricular arrhythmia compared to anterior scars.

Prevalence of frailty indicators and association with socioeconomic status in middle-aged and older adults in a swiss region with universal health insurance coverage : a population-based cross-sectional study

Frailty prevalence in older adults has been reported but is largely unknown in middle-aged adults. We determined the prevalence of frailty indicators among middle-aged and older adults from a general Swiss population characterized by universal health insurance coverage and assessed the determinants of frailty with a special focus on socioeconomic status. Participants aged 50 and more from the population-based 2006-2010 Bus Santé study were included (N = 2,930). Four frailty indicators (weakness, shrinking, exhaustion, and low activity) were measured according to standard definitions. Multivariate logistic regressions were used to determine associations. Overall, 63.5%, 28.7%, and 7.8% participants presented no frailty indicators, one frailty indicator, and two or more frailty indicators, respectively. Among middle-aged participants (50-65 years), 75.1%, 22.2%, and 2.7% presented 0, 1, and 2 or more frailty indicators. The number of frailty indicators was positively associated with age, hypertension, and current smoking and negatively associated with male gender, body mass index, waist-to-hip ratio, and serum total cholesterol level. Lower income level but not education was associated with higher number of frailty indicators. Frailty indicators are frequently encountered in both older and middle-aged adults from the Swiss general population. Despite universal health insurance coverage, household income is independently associated with frailty.

Aspects génétiques de la consommation de tabac et prise en charge clinique [Genetic aspects of smoking and impact on clinical care]

Tobacco smoking is a major public health issue and a better understanding of tobacco addiction represents an important challenge. Many factors are involved in tobacco addiction, including genetic factors. Taking them into account in smoking cessation programs would allow to better adapt these programs to individual characteristics and improve their rate of success. Given enzymatic induction by tobacco smoke, smoking cessation can nevertheless have important consequences on the metabolism of some drugs, that have to be taken into consideration. Here we present different clinical and genetic aspects of smoking and of smoking cessation. A dose adjustment of drugs influenced by tobacco smoke is proposed when quitting smoking.

Adiposity indicators and blood pressure in children: nothing beyond body mass index?

Obesity is a major risk factor for elevated blood pressure in children. For instance, in a school-based study of 5207 children aged 10-12 years, the prevalence of hypertension, which is sustained elevated blood pressure over several visits, was 1.5%, 3.9% and 17.5% in normal weight, overweight and obese children, respectively. High body mass index (BMI) is commonly used to define overweight and obesity. However, because BMI is merely a proxy for adiposity, there is a longstanding debate about its performance to predict elevated blood pressure (or any other health conditions associated with adiposity) and whether other adiposity indicators, such as waist circumference, waist-to-hip ratio or hip circumference, should not be preferred... In this study, 7.4% of boys and 6.4% of girls had elevated blood pressure. The adiposity indicators were highly correlated to each other, apart from weight, waist-to-hip ratio and skinfold thickness z-scores. All indicators were associated with blood pressure. The ability to identify children with elevated blood pressure, assessed by the area under the receiver operating curve (AUC) statistic, was superior for BMI, body adiposity index and waist-to-height ratio z-scores compared with other indicators. BMI z-scores had a slightly higher AUC than other indicators. The authors concluded that BMIz-scores could be a better predictor of elevated blood pressure in children than other adiposity indicators.

Three Essays on the Formation and Impact of Economic Policy

Introduction In my thesis I argue that economic policy is all about economics and politics. Consequently, analysing and understanding economic policy ideally has at least two parts. The economics part, which is centered around the expected impact of a specific policy on the real economy both in terms of efficiency and equity. The insights of this part point into which direction the fine-tuning of economic policies should go. However, fine-tuning of economic policies will be most likely subject to political constraints. That is why, in the politics part, a much better understanding can be gained by taking into account how the incentives of politicians and special interest groups as well as the role played by different institutional features affect the formation of economic policies. The first part and chapter of my thesis concentrates on the efficiency-related impact of economic policies: how does corporate income taxation in general, and corporate income tax progressivity in specific, affect the creation of new firms? Reduced progressivity and flat-rate taxes are in vogue. By 2009, 22 countries are operating flat-rate income tax systems, as do 7 US states and 14 Swiss cantons (for corporate income only). Tax reform proposals in the spirit of the "flat tax" model typically aim to reduce three parameters: the average tax burden, the progressivity of the tax schedule, and the complexity of the tax code. In joint work, Marius Brülhart and I explore the implications of changes in these three parameters on entrepreneurial activity, measured by counts of firm births in a panel of Swiss municipalities. Our results show that lower average tax rates and reduced complexity of the tax code promote firm births. Controlling for these effects, reduced progressivity inhibits firm births. Our reading of these results is that tax progressivity has an insurance effect that facilitates entrepreneurial risk taking. The positive effects of lower tax levels and reduced complexity are estimated to be significantly stronger than the negative effect of reduced progressivity. To the extent that firm births reflect desirable entrepreneurial dynamism, it is not the flattening of tax schedules that is key to successful tax reforms, but the lowering of average tax burdens and the simplification of tax codes. Flatness per se is of secondary importance and even appears to be detrimental to firm births. The second part of my thesis, which corresponds to the second and third chapter, concentrates on how economic policies are formed. By the nature of the analysis, these two chapters draw on a broader literature than the first chapter. Both economists and political scientists have done extensive research on how economic policies are formed. Thereby, researchers in both disciplines have recognised the importance of special interest groups trying to influence policy-making through various channels. In general, economists base their analysis on a formal and microeconomically founded approach, while abstracting from institutional details. In contrast, political scientists' frameworks are generally richer in terms of institutional features but lack the theoretical rigour of economists' approaches. I start from the economist's point of view. However, I try to borrow as much as possible from the findings of political science to gain a better understanding of how economic policies are formed in reality. In the second chapter, I take a theoretical approach and focus on the institutional policy framework to explore how interactions between different political institutions affect the outcome of trade policy in presence of special interest groups' lobbying. Standard political economy theory treats the government as a single institutional actor which sets tariffs by trading off social welfare against contributions from special interest groups seeking industry-specific protection from imports. However, these models lack important (institutional) features of reality. That is why, in my model, I split up the government into a legislative and executive branch which can both be lobbied by special interest groups. Furthermore, the legislative has the option to delegate its trade policy authority to the executive. I allow the executive to compensate the legislative in exchange for delegation. Despite ample anecdotal evidence, bargaining over delegation of trade policy authority has not yet been formally modelled in the literature. I show that delegation has an impact on policy formation in that it leads to lower equilibrium tariffs compared to a standard model without delegation. I also show that delegation will only take place if the lobby is not strong enough to prevent it. Furthermore, the option to delegate increases the bargaining power of the legislative at the expense of the lobbies. Therefore, the findings of this model can shed a light on why the U.S. Congress often practices delegation to the executive. In the final chapter of my thesis, my coauthor, Antonio Fidalgo, and I take a narrower approach and focus on the individual politician level of policy-making to explore how connections to private firms and networks within parliament affect individual politicians' decision-making. Theories in the spirit of the model of the second chapter show how campaign contributions from lobbies to politicians can influence economic policies. There exists an abundant empirical literature that analyses ties between firms and politicians based on campaign contributions. However, the evidence on the impact of campaign contributions is mixed, at best. In our paper, we analyse an alternative channel of influence in the shape of personal connections between politicians and firms through board membership. We identify a direct effect of board membership on individual politicians' voting behaviour and an indirect leverage effect when politicians with board connections influence non-connected peers. We assess the importance of these two effects using a vote in the Swiss parliament on a government bailout of the national airline, Swissair, in 2001, which serves as a natural experiment. We find that both the direct effect of connections to firms and the indirect leverage effect had a strong and positive impact on the probability that a politician supported the government bailout.

Structural characterization of Turtle Mountain anticline (Alberta, Canada) and impact on rock slope failure

his paper proposes a structural investigation of the Turtle Mountain anticline (Alberta, Canada) to better understand the role of the different tectonic features on the development of both local and large scale rock slope instabilities occurring in Turtle Mountain. The study area is investigated by combining remote methods with detailed field surveys. In particular, the benefit of Terrestrial Laser Scanning for ductile and brittle tectonic structure interpretations is illustrated. The proposed tectonic interpretation allows the characterization of the fracturing pattern, the fold geometry and the role of these tectonic features in rock slope instability development. Ten discontinuity sets are identified in the study area, their local variations permitting the differentiation of the study zone into 20 homogenous structural domains. The anticline is described as an eastern verging fold that displays considerable geometry differences along its axis and developed by both flexural slip and tangential longitudinal strain folding mechanisms. Moreover, the origins of the discontinuity sets are determined according to the tectonic phases affecting the region (pre-folding, folding, post-folding). The localization and interpretation of kinematics of the different instabilities revealed the importance of considering the discrete brittle planes of weakness, which largely control the kinematic release of the local instabilities, and also the rock mass damage induced by large tectonic structures (fold hinge, thrust).

Involvement of environmental mercury and lead in the etiology of neurodegenerative diseases.

The incidence of neurodegenerative disease like Parkinson's disease and Alzheimer's disease (AD) increases dramatically with age; only a small percentage is directly related to familial forms. The etiology of the most abundant, sporadic forms is complex and multifactorial, involving both genetic and environmental factors. Several environmental pollutants have been associated with neurodegenerative disorders. The present article focuses on results obtained in experimental neurotoxicology studies that indicate a potential pathogenic role of lead and mercury in the development of neurodegenerative diseases. Both heavy metals have been shown to interfere with a multitude of intracellular targets, thereby contributing to several pathogenic processes typical of neurodegenerative disorders, including mitochondrial dysfunction, oxidative stress, deregulation of protein turnover, and brain inflammation. Exposure to heavy metals early in development can precondition the brain for developing a neurodegenerative disease later in life. Alternatively, heavy metals can exert their adverse effects through acute neurotoxicity or through slow accumulation during prolonged periods of life. The pro-oxidant effects of heavy metals can exacerbate the age-related increase in oxidative stress that is related to the decline of the antioxidant defense systems. Brain inflammatory reactions also generate oxidative stress. Chronic inflammation can contribute to the formation of the senile plaques that are typical for AD. In accord with this view, nonsteroidal anti-inflammatory drugs and antioxidants suppress early pathogenic processes leading to Alzheimer's disease, thus decreasing the risk of developing the disease. The effects of lead and mercury were also tested in aggregating brain-cell cultures of fetal rat telencephalon, a three-dimensional brain-cell culture system. The continuous application for 10 to 50 days of non-cytotoxic concentrations of heavy metals resulted in their accumulation in brain cells and the occurrence of delayed toxic effects. When applied at non-toxic concentrations, methylmercury, the most common environmental form of mercury, becomes neurotoxic under pro-oxidant conditions. Furthermore, lead and mercury induce glial cell reactivity, a hallmark of brain inflammation. Both mercury and lead increase the expression of the amyloid precursor protein; mercury also stimulates the formation of insoluble beta-amyloid, which plays a crucial role in the pathogenesis of AD and causes oxidative stress and neurotoxicity in vitro. Taken together, a considerable body of evidence suggests that the heavy metals lead and mercury contribute to the etiology of neurodegenerative diseases and emphasizes the importance of taking preventive measures in this regard.