Referral patterns and outcomes in noncritically ill patients with hospital-acquired acute kidney injury.

Background and objectives Despite modern treatment, the case fatality rate of hospital-acquired acute kidney injury (HA-AKI) is still high. We retrospectively described the prevalence and the outcome of HA-AKI without nephrology referral (nrHA-AKI) and late referred HA-AKI patients to nephrologists (lrHA-AKI) compared with early referral patients (erHA-AKI) with respect to renal function recovery, renal replacement therapy (RRT) requirement, and in-hospital mortality of HA-AKI. Design, setting, participants, & measurements Noncritically ill patients admitted to the tertiary care academic center of Lausanne, Switzerland, between 2004 and 2008 in the medical and surgical services were included. Acute kidney injury was defined using the Acute Kidney Injury Network (AKIN) classification. Results During 5 years, 4296 patients (4.12% of admissions) experienced 4727 episodes of HA-AKI during their hospital stay. The mean ± SD age of the patients was 61 ± 15 years with a 55% male predominance. There were 958 patients with nrHA-AKI (22.3%) and 2504 patients with lrHA-AKI (58.3%). RRT was required in 31% of the patients with lrHA-AKI compared with 24% of the patients with erHA-AKI. In the multiple risk factor analysis, compared with erHA-AKI, nrHA-AKI and lrHA-AKI were significantly associated with worse renal outcome and higher in-hospital mortality. Conclusions These data suggest that HA-AKI is frequent and the patients with nrHA-AKI or lrHA-AKI are at increased risk for in-hospital morbidity and mortality.

A framework for assessing the scale of influence of environmental factors on ecological patterns

The distribution of living organisms, habitats and ecosystems is primarily driven by abiotic environmental factors that are spatially structured. Assessing the spatial structure of environmental factors, e.g., through spatial autocorrelation analyses (SAC), can thus help us understand their scale of influence on the distribution of organisms, habitats, and ecosystems. Yet SAC analyses of environmental factors are still rarely performed in biogeographic studies. Here, we describe a novel framework that combines SAC and statistical clustering to identify scales of spatial patterning of environmental factors, which can then be interpreted as the scales at which those factors influence the geographic distribution of biological and ecological features. We illustrate this new framework with datasets at different spatial or thematic resolutions. This framework is conceptually and statistically robust, providing a valuable approach to tackle a wide range of issues in ecological and environmental research and particularly when building predictors for ecological models. The new framework can significantly promote fundamental research on all spatially-structured ecological patterns. It can also foster research and application in such fields as global change ecology, conservation planning, and landscape management.

Formulation and Implementation of Air Quality Control Pogrammes : Patterns of Interest Consideration

This article investigates some central aspects of the relationships between programme structure and implementation of sulphur dioxide air quality control policies. Previous implementation research, primarily adopting American approaches, has neglected the connections between the processes of programme formulation and implementation. 'Programme', as the key variable in implementation studies, has been defined too narrowly. On the basis of theoretical and conceptual reflections and provisional empirical results from studies in France, Italy, England, and the Federal Republic of Germany, the authors demonstrate that an integral process analysis using a more extended programme concept is necessary if patterns of interest recognition in policies are to be discovered. Otherwise, the still important question of critical social science cannot be answered, namely, what is the impact of special interests upon implementation processes.

Patterns of Subject Mix in Higher Education Institutions : A First Empirical Analysis Using the AQUAMETH Database

Teaching and research are organised differently between subject domains: attempts to construct typologies of higher education institutions, however, often do not include quantitative indicators concerning subject mix which would allow systematic comparisons of large numbers of higher education institutions among different countries, as the availability of data for such indicators is limited. In this paper, we present an exploratory approach for the construction of such indicators. The database constructed in the AQUAMETH project, which includes also data disaggregated at the disciplinary level, is explored with the aim of understanding patterns of subject mix. For six European countries, an exploratory and descriptive analysis of staff composition divided in four large domains (medical sciences, engineering and technology, natural sciences and social sciences and humanities) is performed, which leads to a classification distinguishing between specialist and generalist institutions. Among the latter, a further distinction is made based on the presence or absence of a medical department. Preliminary exploration of this classification and its comparison with other indicators show the influence of long term dynamics on the subject mix of individual higher education institutions, but also underline disciplinary differences, for example regarding student to staff ratios, as well as national patterns, for example regarding the number of PhD degrees per 100 undergraduate students. Despite its many limitations, this exploratory approach allows defining a classification of higher education institutions that accounts for a large share of differences between the analysed higher education institutions.

Predicting spatial patterns of plant species richness: a comparison of direct macroecological and species stacking approaches

Aim This study compares the direct, macroecological approach (MEM) for modelling species richness (SR) with the more recent approach of stacking predictions from individual species distributions (S-SDM). We implemented both approaches on the same dataset and discuss their respective theoretical assumptions, strengths and drawbacks. We also tested how both approaches performed in reproducing observed patterns of SR along an elevational gradient.Location Two study areas in the Alps of Switzerland.Methods We implemented MEM by relating the species counts to environmental predictors with statistical models, assuming a Poisson distribution. S-SDM was implemented by modelling each species distribution individually and then stacking the obtained prediction maps in three different ways - summing binary predictions, summing random draws of binomial trials and summing predicted probabilities - to obtain a final species count.Results The direct MEM approach yields nearly unbiased predictions centred around the observed mean values, but with a lower correlation between predictions and observations, than that achieved by the S-SDM approaches. This method also cannot provide any information on species identity and, thus, community composition. It does, however, accurately reproduce the hump-shaped pattern of SR observed along the elevational gradient. The S-SDM approach summing binary maps can predict individual species and thus communities, but tends to overpredict SR. The two other S-SDM approaches the summed binomial trials based on predicted probabilities and summed predicted probabilities - do not overpredict richness, but they predict many competing end points of assembly or they lose the individual species predictions, respectively. Furthermore, all S-SDM approaches fail to appropriately reproduce the observed hump-shaped patterns of SR along the elevational gradient.Main conclusions Macroecological approach and S-SDM have complementary strengths. We suggest that both could be used in combination to obtain better SR predictions by following the suggestion of constraining S-SDM by MEM predictions.

An assessment of donor-to-recipient transmission patterns of human cytomegalovirus by analysis of viral genomic variants.

BACKGROUND: We studied human cytomegalovirus (CMV) donor-to-recipient transmission patterns in organ transplantation by analyzing genomic variants on the basis of CMV glycoprotein B (gB) genotyping. METHODS: Organ transplant recipients were included in the study if they had CMV viremia, if they had received an organ from a CMV-seropositive donor, and if there was at least 1 other recipient of an organ from the same donor who developed CMV viremia. Genotypes (gB1-4) were determined by real-time polymerase chain reaction. RESULTS: Forty-seven recipients of organs from 21 donors developed CMV viremia. Twenty-three recipients had a pretransplant donor/recipient (D/R) CMV serostatus of D(+)/R(+), and 24 had a serostatus of D(+)/R(-). The prevalences of genotypes in recipients were as follows: for gB1, 51% (n = 24); for gB2, 19% (n = 9); for gB3, 9% (n = 4); for gB4, 0% (n = 0); and for mixed infection, 21% (n = 10). Recipients of an organ from a common donor had infection with CMV of the same gB genotype in 12 (57%) of 21 instances. Concordance between genotypes was higher among seronegative (i.e., D(+)/R(-)) recipients than among seropositive (D(+)/R(+)) recipients, although discordances resulting from the transmission of multiple strains were seen. In seropositive recipients, transmission of multiple strains from the donor could not be differentiated from reactivation of a recipient's own strains. CONCLUSION: Our analysis of strain concordance among recipients of organs from common donors showed that transmission of CMV has complex dynamic patterns. In seropositive recipients, transmission or reactivation of multiple CMV strains is possible.

Assessing the link between coping patterns and interpersonal behaviors in depressed women

Aim. Stressful life events are an important contributor to the onset and course of depression. Coping strategies and interpersonal patterns have been found to mediate the effects of stress [1]. Methods. This study examined the relationship between coping patterns and interpersonal interactions in early psychotherapy sessions of 25 female patients with major depression. Transcripts were rated for coping patterns using the Coping Patterns Rating Scale (CPRS; [2]). Interpersonal patterns were assessed using the Structural Analysis of Social Behavior (SASB; [3]). Results. Significant correlations were found between coping patterns and markers of interpersonal functioning in selected contexts. Discussion. The implications of these findings in understanding an important aspect of vulnerability to depression and enhancing treatment outcome are discussed.

Predicting spatial patterns of plant biodiversity : from species to communities

Understanding the distribution and composition of species assemblages and being able to predict them in space and time are highly important tasks io investigate the fate of biodiversity in the current global changes context. Species distribution models are tools that have proven useful to predict the potential distribution of species by relating their occurrences to environmental variables. Species assemblages can then be predicted by combining the prediction of individual species models. In the first part of my thesis, I tested the importance of new environmental predictors to improve species distribution prediction. I showed that edaphic variables, above all soil pH and nitrogen content could be important in species distribution models. In a second chapter, I tested the influence of different resolution of predictors on the predictive ability of species distribution models. I showed that fine resolution predictors could ameliorate the models for some species by giving a better estimation of the micro-topographic condition that species tolerate, but that fine resolution predictors for climatic factors still need to be ameliorated. The second goal of my thesis was to test the ability of empirical models to predict species assemblages' characteristics such as species richness or functional attributes. I showed that species richness could be modelled efficiently and that the resulting prediction gave a more realistic estimate of the number of species than when obtaining it by stacking outputs of single species distribution models. Regarding the prediction of functional characteristics (plant height, leaf surface, seed mass) of plant assemblages, mean and extreme values of functional traits were better predictable than indices reflecting the diversity of traits in the community. This approach proved interesting to understand which environmental conditions influence particular aspects of the vegetation functioning. It could also be useful to predict climate change impacts on the vegetation. In the last part of my thesis, I studied the capacity of stacked species distribution models to predict the plant assemblages. I showed that this method tended to over-predict the number of species and that the composition of the community was not predicted exactly either. Finally, I combined the results of macro- ecological models obtained in the preceding chapters with stacked species distribution models and showed that this approach reduced significantly the number of species predicted and that the prediction of the composition is also ameliorated in some cases. These results showed that this method is promising. It needs now to be tested on further data sets. - Comprendre la manière dont les plantes se répartissent dans l'environnement et s'organisent en communauté est une question primordiale dans le contexte actuel de changements globaux. Cette connaissance peut nous aider à sauvegarder la diversité des espèces et les écosystèmes. Des méthodes statistiques nous permettent de prédire la distribution des espèces de plantes dans l'espace géographique et dans le temps. Ces modèles de distribution d'espèces, relient les occurrences d'une espèce avec des variables environnementales pour décrire sa distribution potentielle. Cette méthode a fait ses preuves pour ce qui est de la prédiction d'espèces individuelles. Plus récemment plusieurs tentatives de cumul de modèles d'espèces individuelles ont été réalisées afin de prédire la composition des communautés végétales. Le premier objectif de mon travail est d'améliorer les modèles de distribution en testant l'importance de nouvelles variables prédictives. Parmi différentes variables édaphiques, le pH et la teneur en azote du sol se sont avérés des facteurs non négligeables pour prédire la distribution des plantes. Je démontre aussi dans un second chapitre que les prédicteurs environnementaux à fine résolution permettent de refléter les conditions micro-topographiques subies par les plantes mais qu'ils doivent encore être améliorés avant de pouvoir être employés de manière efficace dans les modèles. Le deuxième objectif de ce travail consistait à étudier le développement de modèles prédictifs pour des attributs des communautés végétales tels que, par exemple, la richesse en espèces rencontrée à chaque point. Je démontre qu'il est possible de prédire par ce biais des valeurs de richesse spécifiques plus réalistes qu'en sommant les prédictions obtenues précédemment pour des espèces individuelles. J'ai également prédit dans l'espace et dans le temps des caractéristiques de la végétation telles que sa hauteur moyenne, minimale et maximale. Cette approche peut être utile pour comprendre quels facteurs environnementaux promeuvent différents types de végétation ainsi que pour évaluer les changements à attendre au niveau de la végétation dans le futur sous différents régimes de changements climatiques. Dans une troisième partie de ma thèse, j'ai exploré la possibilité de prédire les assemblages de plantes premièrement en cumulant les prédictions obtenues à partir de modèles individuels pour chaque espèce. Cette méthode a le défaut de prédire trop d'espèces par rapport à ce qui est observé en réalité. J'ai finalement employé le modèle de richesse en espèce développé précédemment pour contraindre les résultats du modèle d'assemblage de plantes. Cela a permis l'amélioration des modèles en réduisant la sur-prédiction et en améliorant la prédiction de la composition en espèces. Cette méthode semble prometteuse mais de nouveaux tests sont nécessaires pour bien évaluer ses capacités.

Impact of vaccines given during pregnancy on the offspring of women consulting a travel clinic: a longitudinal study

BACKGROUND: Little is known on the impact of travel vaccinations during pregnancy on child outcomes, in particular on the long-term psychomotor development. The objectives of the study were (1) to estimate the rate of premature births, congenital abnormalities, and mental and physical development problems of children born from mothers who had been vaccinated during pregnancy and (2) to compare these rates with those of children whose mothers had not been vaccinated during pregnancy. METHODS: Longitudinal study including (1) retrospectively pregnant women having attended our travel clinic before (vaccinated) and (2) prospectively mothers attending our clinic (nonvaccinated). We performed phone interviews with mothers vaccinated during pregnancy, up to 10 years before, and face-to-face interviews with nonvaccinated age-matched mothers, ie, women attending the travel clinic who had one child of about the same age as the one of the case to compare child development between both groups. RESULTS: Fifty-three women vaccinated during pregnancy were interviewed as well as 53 nonvaccinated ones. Twenty-eight (53%) women received their vaccination during the first trimester. The most frequent vaccine administered was hepatitis A (55% of the cases), followed by di-Te (34%), IM poliomyelitis (23%), yellow fever (12%), A-C meningitis (8%), IM typhoid (4%), and oral poliomyelitis (4%). Children were followed for a range of 1 to 10 years. Rates of premature births were 5.7% in both groups; congenital abnormalities were 1.9% in the vaccinated cohort versus 5.7% in the nonvaccinated one; children took their first steps at a median age of 12 months in both cohorts; among schoolchildren, 5% of the vaccinated cohort versus 7.7% of the nonvaccinated attended a lower level or a specialized school. CONCLUSION: In this small sample size, there was no indication that usual travel vaccinations, including the yellow fever one, had deleterious effect on child outcome and development

Longitudinal analysis of patterns and predictors of changes in self-reported adherence to antiretroviral therapy: Swiss HIV Cohort Study.

BACKGROUND: Adherence to combination antiretroviral therapy (cART) is a dynamic process, however, changes in adherence behavior over time are insufficiently understood. METHODS: Data on self-reported missed doses of cART was collected every 6 months in Swiss HIV Cohort Study participants. We identified behavioral groups associated with specific cART adherence patterns using trajectory analyses. Repeated measures logistic regression identified predictors of changes in adherence between consecutive visits. RESULTS: Six thousand seven hundred nine individuals completed 49,071 adherence questionnaires [median 8 (interquartile range: 5-10)] during a median follow-up time of 4.5 years (interquartile range: 2.4-5.1). Individuals were clustered into 4 adherence groups: good (51.8%), worsening (17.4%), improving (17.6%), and poor adherence (13.2%). Independent predictors of worsening adherence were younger age, basic education, loss of a roommate, starting intravenous drug use, increasing alcohol intake, depression, longer time with HIV, onset of lipodystrophy, and changing care provider. Independent predictors of improvements in adherence were regimen simplification, changing class of cART, less time on cART, and starting comedications. CONCLUSIONS: Treatment, behavioral changes, and life events influence patterns of drug intake in HIV patients. Clinical care providers should routinely monitor factors related to worsening adherence and intervene early to reduce the risk of treatment failure and drug resistance.

Exploration of alpine orographic precipitation patterns with radar image processing and clustering techniques

A methodology of exploratory data analysis investigating the phenomenon of orographic precipitation enhancement is proposed. The precipitation observations obtained from three Swiss Doppler weather radars are analysed for the major precipitation event of August 2005 in the Alps. Image processing techniques are used to detect significant precipitation cells/pixels from radar images while filtering out spurious effects due to ground clutter. The contribution of topography to precipitation patterns is described by an extensive set of topographical descriptors computed from the digital elevation model at multiple spatial scales. Additionally, the motion vector field is derived from subsequent radar images and integrated into a set of topographic features to highlight the slopes exposed to main flows. Following the exploratory data analysis with a recent algorithm of spectral clustering, it is shown that orographic precipitation cells are generated under specific flow and topographic conditions. Repeatability of precipitation patterns in particular spatial locations is found to be linked to specific local terrain shapes, e.g. at the top of hills and on the upwind side of the mountains. This methodology and our empirical findings for the Alpine region provide a basis for building computational data-driven models of orographic enhancement and triggering of precipitation. Copyright (C) 2011 Royal Meteorological Society .

Measuring and Explaining the Increase of Travel Distance : A Multilevel Analysis Using Repeated Cross Sectional Travel Surveys

We want to shed some light on the development of person mobility by analysing the repeated cross-sectional data of the four National Travel Surveys (NTS) that were conducted in Germany since the mid seventies. The above mentioned driving forces operate on different levels of the system that generates the spatial behaviour we observe: Travel demand is derived from the needs and desires of individuals to participate in spatially separated activities. Individuals organise their lives in an interactive process within the context they live in, using given infrastructure. Essential determinants of their demand are the individual's socio-demographic characteristics, but also the opportunities and constraints defined by the household and the environment are relevant for the behaviour which ultimately can be realised. In order to fully capture the context which determines individual behaviour, the (nested) hierarchy of persons within households within spatial settings has to be considered. The data we will use for our analysis contains information on these three levels. With the analysis of this micro-data we attempt to improve our understanding of the afore subsumed macro developments. In addition we will investigate the prediction power of a few classic sociodemographic variables for the daily travel distance of individuals in the four NTS data sets, with a focus on the evolution of this predictive power. The additional task to correctly measure distances travelled by means of the NTS is threatened by the fact that although these surveys measure the same variables, different sampling designs and data collection procedures were used. So the aim of the analysis is also to detect variables whose control corrects for the known measurement error, as a prerequisite to apply appropriate models in order to better understand the development of individual travel behaviour in a multilevel context. This task is complicated by the fact that variables that inform on survey procedures and outcomes are only provided with the data set for 2002 (see Infas and DIW Berlin, 2003).

Effects of ploidy and sex-locus genotype on gene expression patterns in the fire ant Solenopsis invicta.

Males in many animal species differ greatly from females in morphology, physiology and behaviour. Ants, bees and wasps have a haplodiploid mechanism of sex determination whereby unfertilized eggs become males while fertilized eggs become females. However, many species also have a low frequency of diploid males, which are thought to develop from diploid eggs when individuals are homozygous at one or more sex determination loci. Diploid males are morphologically similar to haploids, though often larger and typically sterile. To determine how ploidy level and sex-locus genotype affect gene expression during development, we compared expression patterns between diploid males, haploid males and females (queens) at three developmental timepoints in Solenopsis invicta. In pupae, gene expression profiles of diploid males were very different from those of haploid males but nearly identical to those of queens. An unexpected shift in expression patterns emerged soon after adult eclosion, with diploid male patterns diverging from those of queens to resemble those of haploid males, a pattern retained in older adults. The finding that ploidy level effects on early gene expression override sex effects (including genes implicated in sperm production and pheromone production/perception) may explain diploid male sterility and lack of worker discrimination against them during development.