Assessing psychosocial vulnerability and care needs of pretransplant patients by means of the INTERMED.

OBJECTIVE: We investigated whether the INTERMED, a generic instrument for assessing biopsychosocial case complexity and direct care, identifies organ transplant patients at risk of unfavourable post-transplant development by comparing it to the Transplant Evaluation Rating Scale (TERS), the established measure for pretransplant psychosocial evaluation. METHOD: One hundred nineteen kidney, liver, and heart transplant candidates were evaluated using the INTERMED, TERS, SF-36, EuroQol, Montgomery-Åsberg Depression Rating Scale (MADRS), and Hospital Anxiety & Depression Scale (HADS). RESULTS: We found significant relationships between the INTERMED and the TERS scores. The INTERMED highly correlated with the HADS,MADRS, and mental and physical health scores of the SF-36 Health Survey. CONCLUSIONS: The results demonstrate the validity and usefulness of the INTERMED instrument for pretransplant evaluation. Furthermore, our findings demonstrate the different qualities of INTERMED and TERS in clinical practice. The advantages of the psychiatric focus of the TERS and the biopsychosocial perspective of the INTERMED are discussed in the context of current literature on integrated care.

Improving the prediction of plant species distribution and community composition by adding edaphic to topo-climatic variables

Questions Soil properties have been widely shown to influence plant growth and distribution. However, the degree to which edaphic variables can improve models based on topo-climatic variables is still unclear. In this study, we tested the roles of seven edaphic variables, namely (1) pH; (2) the content of nitrogen and of (3) phosphorus; (4) silt; (5) sand; (6) clay and (7) carbon-to-nitrogen ratio, as predictors of species distribution models in an edaphically heterogeneous landscape. We also tested how the respective influence of these variables in the models is linked to different ecological and functional species characteristics. Location The Western Alps, Switzerland. Methods With four different modelling techniques, we built models for 115 plant species using topo-climatic variables alone and then topo-climatic variables plus each of the seven edaphic variables, one at a time. We evaluated the contribution of each edaphic variable by assessing the change in predictive power of the model. In a second step, we evaluated the importance of the two edaphic variables that yielded the largest increase in predictive power in one final set of models for each species. Third, we explored the change in predictive power and the importance of variables across plant functional groups. Finally, we assessed the influence of the edaphic predictors on the prediction of community composition by stacking the models for all species and comparing the predicted communities with the observed community. Results Among the set of edaphic variables studied, pH and nitrogen content showed the highest contributions to improvement of the predictive power of the models, as well as the predictions of community composition. When considering all topo-climatic and edaphic variables together, pH was the second most important variable after degree-days. The changes in model results caused by edaphic predictors were dependent on species characteristics. The predictions for the species that have a low specific leaf area, and acidophilic preferences, tolerating low soil pH and high humus content, showed the largest improvement by the addition of pH and nitrogen in the model. Conclusions pH was an important predictor variable for explaining species distribution and community composition of the mountain plants considered in our study. pH allowed more precise predictions for acidophilic species. This variable should not be neglected in the construction of species distribution models in areas with contrasting edaphic conditions.

External irradiation with or without long-term androgen suppression for prostate cancer with high metastatic risk: 10-year results of an EORTC randomised study.

BACKGROUND: We did a randomised phase 3 trial assessing the benefit of addition of long-term androgen suppression with a luteinising-hormone-releasing hormone (LHRH) agonist to external irradiation in patients with prostate cancer with high metastatic risk. In this report, we present the 10-year results. METHODS: For this open-label randomised trial, eligible patients were younger than 80 years and had newly diagnosed histologically proven T1-2 prostatic adenocarcinoma with WHO histological grade 3 or T3-4 prostatic adenocarcinoma of any histological grade, and a WHO performance status of 0-2. Patients were randomly assigned (1:1) to receive radiotherapy alone or radiotherapy plus immediate androgen suppression. Treatment allocation was open label and used a minimisation algorithm with institution, clinical stage of the disease, results of pelvic-lymph-node dissection, and irradiation fields extension as minimisation factors. Patients were irradiated externally, once a day, 5 days a week, for 7 weeks to a total dose of 50 Gy to the whole pelvis, with an additional 20 Gy to the prostate and seminal vesicles. The LHRH agonist, goserelin acetate (3·6 mg subcutaneously every 4 weeks), was started on the first day of irradiation and continued for 3 years; cyproterone acetate (50 mg orally three times a day) was given for 1 month starting a week before the first goserelin injection. The primary endpoint was clinical disease-free survival. Analysis was by intention to treat. The trial is registered at ClinicalTrials.gov, number NCT00849082. FINDINGS: Between May 22, 1987, and Oct 31, 1995, 415 patients were randomly assigned to treatment groups and were included in the analysis (208 radiotherapy alone, 207 combined treatment). Median follow-up was 9·1 years (IQR 5·1-12·6). 10-year clinical disease-free survival was 22·7% (95% CI 16·3-29·7) in the radiotherapy-alone group and 47·7% (39·0-56·0) in the combined treatment group (hazard ratio [HR] 0·42, 95% CI 0·33-0·55, p<0·0001). 10-year overall survival was 39·8% (95% CI 31·9-47·5) in patients receiving radiotherapy alone and 58·1% (49·2-66·0) in those allocated combined treatment (HR 0·60, 95% CI 0·45-0·80, p=0·0004), and 10-year prostate-cancer mortality was 30·4% (95% CI 23·2-37·5) and 10·3% (5·1-15·4), respectively (HR 0·38, 95% CI 0·24-0·60, p<0·0001). No significant difference in cardiovascular mortality was noted between treatment groups both in patients who had cardiovascular problems at study entry (eight of 53 patients in the combined treatment group had a cardiovascular-related cause of death vs 11 of 63 in the radiotherapy group; p=0·60) and in those who did not (14 of 154 vs six of 145; p=0·25). Two fractures were reported in patients allocated combined treatment. INTERPRETATION: In patients with prostate cancer with high metastatic risk, immediate androgen suppression with an LHRH agonist given during and for 3 years after external irradiation improves 10-year disease-free and overall survival without increasing late cardiovascular toxicity.

Evidence of climatic niche shift during biological invasion

Niche-based models calibrated in the native range by relating species observations to climatic variables are commonly used to predict the potential spatial extent of species' invasion. This climate matching approach relies on the assumption that invasive species conserve their climatic niche in the invaded ranges. We test this assumption by analysing the climatic niche spaces of Spotted Knapweed in western North America and Europe. We show with robust cross-continental data that a shift of the observed climatic niche occurred between native and non-native ranges, providing the first empirical evidence that an invasive species can occupy climatically distinct niche spaces following its introduction into a new area. The models fail to predict the current invaded distribution, but correctly predict areas of introduction. Climate matching is thus a useful approach to identify areas at risk of introduction and establishment of newly or not-yet-introduced neophytes, but may not predict the full extent of invasions.

Assessing alpine plant vulnerability to climate change: A modeling perspective

The potential ecological impact of ongoing climate change has been much discussed. High mountain ecosystems were identified early on as potentially very sensitive areas. Scenarios of upward species movement and vegetation shift are commonly discussed in the literature. Mountains being characteristically conic in shape, impact scenarios usually assume that a smaller surface area will be available as species move up. However, as the frequency distribution of additional physiographic factors (e.g., slope angle) changes with increasing elevation (e.g., with few gentle slopes available at higher elevation), species migrating upslope may encounter increasingly unsuitable conditions. As a result, many species could suffer severe reduction of their habitat surface, which could in turn affect patterns of biodiversity. In this paper, results from static plant distribution modeling are used to derive climate change impact scenarios in a high mountain environment. Models are adjusted with presence/absence of species. Environmental predictors used are: annual mean air temperature, slope, indices of topographic position, geology, rock cover, modeled permafrost and several indices of solar radiation and snow cover duration. Potential Habitat Distribution maps were drawn for 62 higher plant species, from which three separate climate change impact scenarios were derived. These scenarios show a great range of response, depending on the species and the degree of warming. Alpine species would be at greatest risk of local extinction, whereas species with a large elevation range would run the lowest risk. Limitations of the models and scenarios are further discussed.

MORM--a Petri net based model for assessing OH&S risks in industrial processes: modeling qualitative aspects.

Because of the increase in workplace automation and the diversification of industrial processes, workplaces have become more and more complex. The classical approaches used to address workplace hazard concerns, such as checklists or sequence models, are, therefore, of limited use in such complex systems. Moreover, because of the multifaceted nature of workplaces, the use of single-oriented methods, such as AEA (man oriented), FMEA (system oriented), or HAZOP (process oriented), is not satisfactory. The use of a dynamic modeling approach in order to allow multiple-oriented analyses may constitute an alternative to overcome this limitation. The qualitative modeling aspects of the MORM (man-machine occupational risk modeling) model are discussed in this article. The model, realized on an object-oriented Petri net tool (CO-OPN), has been developed to simulate and analyze industrial processes in an OH&S perspective. The industrial process is modeled as a set of interconnected subnets (state spaces), which describe its constitutive machines. Process-related factors are introduced, in an explicit way, through machine interconnections and flow properties. While man-machine interactions are modeled as triggering events for the state spaces of the machines, the CREAM cognitive behavior model is used in order to establish the relevant triggering events. In the CO-OPN formalism, the model is expressed as a set of interconnected CO-OPN objects defined over data types expressing the measure attached to the flow of entities transiting through the machines. Constraints on the measures assigned to these entities are used to determine the state changes in each machine. Interconnecting machines implies the composition of such flow and consequently the interconnection of the measure constraints. This is reflected by the construction of constraint enrichment hierarchies, which can be used for simulation and analysis optimization in a clear mathematical framework. The use of Petri nets to perform multiple-oriented analysis opens perspectives in the field of industrial risk management. It may significantly reduce the duration of the assessment process. But, most of all, it opens perspectives in the field of risk comparisons and integrated risk management. Moreover, because of the generic nature of the model and tool used, the same concepts and patterns may be used to model a wide range of systems and application fields.

A retrospective case-control study assessing the role of trabecular bone score in postmenopausal Caucasian women with osteopenia: analyzing the odds of vertebral fracture.

This case-control study assessed whether the trabecular bone score (TBS), determined from gray-level analysis of DXA images, might be of any diagnostic value, either alone or combined with bone mineral density (BMD), in the assessment of vertebral fracture risk among postmenopausal women with osteopenia. Of 243 postmenopausal Caucasian women, 50-80 years old, with BMD T-scores between -1.0 and -2.5, we identified 81 with osteoporosis-related vertebral fractures and compared them with 162 age-matched controls without fractures. Primary outcomes were BMD and TBS. For BMD, each incremental decrease in BMD was associated with an OR = 1.54 (95% CI = 1.17-2.03), and the AUC was 0.614 (0.550-0.676). For TBS, corresponding values were 2.53 (1.82-3.53) and 0.721 (0.660-0.777). The difference in the AUC for TBS vs. BMD was statistically significant (p = 0.020). The OR for (TBS + BMD) was 2.54 (1.86-3.47) and the AUC 0.732 (0.672-0.787). In conclusion, the TBS warrants a closer look to see whether it may be of clinical usefulness in the determination of fracture risk in postmenopausal osteopenic women.

Decision Support Model for Assessing Archaeological Survey Needs for Bridge Replacement Projects in Iowa, 2006

The Bridges Decision Support Model is a geographic information system (GIS) that assembles existing data on archaeological sites, surveys, and their geologic contexts to assess the risk of bridge replacement projects encountering 13,000- to 150-year-old Native American sites. This project identifies critical variables for assessing prehistoric sites potential, examines the quality of available data about the variables, and applies the data to creating a decision support framework for use by the Iowa Department of Transportation (Iowa DOT) and others. An analysis of previous archaeological surveys indicates that subsurface testing to discover buried sites became increasingly common after 1980, but did not become routine until after the adoption of guidelines recommending such testing, in 1993. Even then, the average depth of testing has been relatively shallow. Alluvial deposits of sufficient age, deposited in depositional environments conducive to human habitation, are considerably thicker than archaeologists have routinely tested.

Assessing small non-zero perceptions of chance: The case of H1N1 (swine) flu risks

Feelings of invulnerability, seen in judgments of 0% risk, can reflect misunderstandings of risk and risk behaviors, suggesting increased need for risk communication. However, judgments of 0% risk may be given by individuals who feel invulnerable, and by individuals who are rounding from small non-zero probabilities. We examined the effect of allowing participants to give more precise responses in the 0-1% range on the validity of reported probability judgments. Participants assessed probabilities for getting H1N1 influenza and dying from it conditional on infection, using a 0-100% visual linear scale. Those responding in the 0-1% range received a follow-up question with more options in that range. This two-step procedure reduced the use of 0% and increased the resolution of responses in the 0-1% range. Moreover, revised probability responses improved predictions of attitudes and self-reported behaviors. Hence, our two-step procedure allows for more precise and more valid measurement of perceived invulnerability. [Authors]

A multicentre, retrospective case-control study assessing the role of trabecular bone score (TBS) in menopausal Caucasian women with low areal bone mineral density (BMDa): Analysing the odds of vertebral fracture.

INTRODUCTION: The trabecular bone score (TBS) is a new parameter that is determined from grey level analysis of DXA images. It relies on the mean thickness and volume fraction of trabecular bone microarchitecture. This was a preliminary case-control study to evaluate the potential diagnostic value of TBS, both alone and combined with bone mineral density (BMDa), in the assessment of vertebral fracture. METHODS: Out of a subject pool of 441 Caucasian, postmenopausal women between the ages of 50 and 80 years, we identified 42 women with osteoporosis-related vertebral fractures, and compared them with 126 age-matched women without any fractures (1 case: 3 controls). Primary outcomes were BMDa and TBS. Inter-group comparisons were undertaken using Student's t-tests and Wilcoxon signed ranks tests for parametric and non-parametric data, respectively. Odds ratios for vertebral fracture were calculated for each incremental one standard deviation decrease in BMDa and TBS, and areas under the receiver operating curve (AUC) calculated and sensitivity analysis were conducted to compare BMDa alone, TBS alone, and the combination of BMDa and TBS. Subgroup analyses were performed specifically for women with osteopenia, and for women with T-score-defined osteoporosis. RESULTS: Across all subjects (n=42, 126) weight and body mass index were greater and BMDa and TBS both less in women with fractures. The odds of vertebral fracture were 3.20 (95% CI, 2.01-5.08) for each incremental decrease in TBS, 1.95 (1.34-2.84) for BMDa, and 3.62 (2.32-5.65) for BMDa + TBS combined. The AUC was greater for TBS than for BMDa (0.746 vs. 0.662, p=0.011). At iso-specificity (61.9%) or iso-sensitivity (61.9%) for both BMDa and TBS, TBS + BMDa sensitivity or specificity was 19.1% or 16.7% greater than for either BMDa or TBS alone. Among subjects with osteoporosis (n=11, 40) both BMDa (p=0.0008) and TBS (p=0.0001) were lower in subjects with fractures, and both OR and AUC (p=0.013) for BMDa + TBS were greater than for BMDa alone (OR=4.04 [2.35-6.92] vs. 2.43 [1.49-3.95]; AUC=0.835 [0.755-0.897] vs. 0.718 [0.627-0.797], p=0.013). Among subjects with osteopenia, TBS was lower in women with fractures (p=0.0296), but BMDa was not (p=0.75). Similarly, the OR for TBS was statistically greater than 1.00 (2.82, 1.27-6.26), but not for BMDa (1.12, 0.56-2.22), as was the AUC (p=0.035), but there was no statistical difference in specificity (p=0.357) or sensitivity (p=0.678). CONCLUSIONS: The trabecular bone score warrants further study as to whether it has any clinical application in osteoporosis detection and the evaluation of fracture risk.

Residence time, expansion toward the equator in the invaded range and native range size matter to climatic niche shifts in non-native species

Aim Identifying climatic niche shifts and their drivers is important to accurately predict the risk of biological invasions. The niches of non-native plants and birds have recently been assessed in large-scale multi-species studies, but such large-scale tests are lacking for non-native reptiles and amphibians (herpetofauna). Furthermore, little is known about the factors contributing to niche shifts when they occur. Based on the occurrence of 71 reptile and amphibian species, we compared native and non-native realized niches in 101 invaded ranges at a worldwide scale and identified the factors that affect niche shifts. Location The world except the Antarctic. Methods We assessed climatic niche dynamics in a gridded environmental space allowing the quantification of niche overlap and expansion into climatic conditions not colonized by the species in their native range. We analyzed the factors affecting niche shifts using a model averaging approach based on generalized linear mixed-effects models. Results Approximately 57% of the invaded ranges (51% for amphibians and 61% for reptiles) showed niche shifts (≥10% expansion in the realized climatic niche). Island endemics, species introduced to Oceania and invaded ranges outside the native biogeographic realm showed a higher proportion of niche shifts. Niche shifts were more likely for species that had smaller native range sizes, were introduced earlier into a new range or invaded areas located at lower latitudes than the native range. Main conclusions The proportion of niche shifts for non-native herpetofauna was higher than those for Holarctic non-native plants and European non-native birds. The 'climate matching hypothesis' should be used with caution for species shifting their niche because it could underestimate the risk of their establishment.

Data-driven topo-climatic mapping with machine learning methods

Automatic environmental monitoring networks enforced by wireless communication technologies provide large and ever increasing volumes of data nowadays. The use of this information in natural hazard research is an important issue. Particularly useful for risk assessment and decision making are the spatial maps of hazard-related parameters produced from point observations and available auxiliary information. The purpose of this article is to present and explore the appropriate tools to process large amounts of available data and produce predictions at fine spatial scales. These are the algorithms of machine learning, which are aimed at non-parametric robust modelling of non-linear dependencies from empirical data. The computational efficiency of the data-driven methods allows producing the prediction maps in real time which makes them superior to physical models for the operational use in risk assessment and mitigation. Particularly, this situation encounters in spatial prediction of climatic variables (topo-climatic mapping). In complex topographies of the mountainous regions, the meteorological processes are highly influenced by the relief. The article shows how these relations, possibly regionalized and non-linear, can be modelled from data using the information from digital elevation models. The particular illustration of the developed methodology concerns the mapping of temperatures (including the situations of Föhn and temperature inversion) given the measurements taken from the Swiss meteorological monitoring network. The range of the methods used in the study includes data-driven feature selection, support vector algorithms and artificial neural networks.

Risk analysis of climate change on coffee nematodes and leaf miner in Brazil

The objective of this work was to assess the potential impact of climate change on the spatial distribution of coffee nematodes (races of Meloidogyne incognita) and leaf miner (Leucoptera coffeella), using a Geographic Information System. Assessment of the impacts of climate change on pest infestations and disease epidemics in crops is needed as a basis for revising management practices to minimize crop losses as climatic conditions shift. Future scenarios focused on the decades of the 2020's, 2050's, and 2080's (scenarios A2 and B2) were obtained from five General Circulation Models available on Data Distribution Centre from Intergovernmental Panel on Climate Change. Geographic distribution maps were prepared using models to predict the number of generations of the nematodes and leaf miner. Maps obtained in scenario A2 allowed prediction of an increased infestation of the nematode and of the pest, due to greater number of generations per month, than occurred under the climatological normal from 1961-1990. The number of generations also increased in the B2 scenario, but was lower than in the A2 scenario for both organisms.

Intergenerational differences in cardiovascular risk factor levels in Switzerland

Background: There is little information regarding cardiovascular risk factor (CV RF) trends in Switzerland. We aimed at assessing generation differences in CV RFs by comparing CV RFs levels within selected age groups separated by a 20 year time lag. Design: Two population-based surveys. Methods: Data from the Monica (1984-1986) and Colaus (2004-2006) surveys were used. Analyses were stratified by sex and age groups (35-44, 45-54, 55-64 and 65-75 years). Results: No changes were found for BMI levels and status between surveys: in men, 26}3, 26}3, 27}4 and 27}4 kg/m2 for age groups 35-44, 45-54, 55-64 and 65-74, respectively, in MONICA, vs. 26}4, 26}4, 27}4 and 28}4 kg/m2 in COLAUS, p=NS, in women: 24}4, 26}4, 26}4 and 26}5 kg/m2 in MONICA, vs. 24}5, 25}5, 26}5 and 26}5 kg/m2 in COLAUS, p=NS. Similar results were found after adjusting for education. Smoking prevalence increased in men: 28, 30, 22 and 15% for age groups 35-44, 45-54, 55-64 and 65-74, respectively, in MONICA, vs. 35, 29, 28 and 21% in COLAUS. In women, changes differed according to age: 39, 26, 16 and 18%, in MONICA vs. 28, 30, 22 and 15% in COLAUS. Blood pressure decreased in the younger age groups and remained constant in the older ones: in men, systolic blood pressure was 129}15, 133}16, 138}18 and 143}21 mm Hg in MONICA, vs. 125}12, 129}15, 137}16 and 144}19 mm Hg in COLAUS, p<0.01. Similar findings were obtained after adjusting for education. Prevalence of hypertension increased, due to an increase in the prevalence of treated subjects, in men : 4, 8, 16 and 19% for age groups 35-44, 45-54, 55-64 and 65-74, respectively, in MONICA, vs. 5, 14, 31 and 46% in COLAUS, p<0.05; in women: 2, 10, 16, and 24% in MONICA, vs. 4, 12, 24, and 34% in COLAUS, p<0.05. This increase was stronger in men: 14, 17, 23 and 31% for age groups 35-44, 45-54, 55-64 and 65-74, respectively, in MONICA vs. 10, 21, 41 and 55% in COLAUS, p<0.01 and smaller in women: 6, 15, 24 and 44% in MONICA vs. 6, 16, 30 and 42% in COLAUS, p=NS. Similar findings were obtained after adjusting for education. Conclusion: With the exception of BMI, the newer Swiss generations appear to have a worse CV profile than the older generations. This is especially true regarding smoking and hypertension.

Regional differences in self-reported screening, prevalence and management of cardiovascular risk factors in Switzerland.

BACKGROUND: In Switzerland, health policies are decided at the local level, but little is known regarding their impact on the screening and management of cardiovascular risk factors (CVRFs). We thus aimed at assessing geographical levels of CVRFs in Switzerland.¦METHODS: Swiss Health Survey for 2007 (N = 17,879). Seven administrative regions were defined: West (Leman), West-Central (Mittelland), Zurich, South (Ticino), North-West, East and Central Switzerland. Obesity, smoking, hypertension, dyslipidemia and diabetes prevalence, treatment and screening within the last 12 months were assessed by interview.¦RESULTS: After multivariate adjustment for age, gender, educational level, marital status and Swiss citizenship, no significant differences were found between regions regarding prevalence of obesity or current smoking. Similarly, no differences were found regarding hypertension screening and prevalence. Two thirds of subjects who had been told they had high blood pressure were treated, the lowest treatment rates being found in East Switzerland: odds-ratio and [95% confidence interval] 0.65 [0.50-0.85]. Screening for hypercholesterolemia was more frequently reported in French (Leman) and Italian (Ticino) speaking regions. Four out of ten participants who had been told they had high cholesterol levels were treated and the lowest treatment rates were found in German-speaking regions. Screening for diabetes was higher in Ticino (1.24 [1.09 - 1.42]). Six out of ten participants who had been told they had diabetes were treated, the lowest treatment rates were found for German-speaking regions.¦CONCLUSIONS: In Switzerland, cardiovascular risk factor screening and management differ between regions and these differences cannot be accounted for by differences in populations' characteristics. Management of most cardiovascular risk factors could be improved.