Modelling the effect of minor orthopaedic day surgery on patient mood at the early post-operative period: a prospective population-based cohort study.

OBJECTIVE: The effect of minor orthopaedic day surgery (MiODS) on patient's mood. METHODS: A prospective population-based cohort study of 148 consecutive patients with age above 18 and less than 65, an American Society of Anaesthesiology (ASA) score of 1, and the requirement of general anaesthesia (GA) were included. The Medical Outcomes Study - Short Form 36 (SF-36), Beck Anxiety Inventory (BAI) and Beck Depression Inventory (BDI) were used pre- and post-operatively. RESULTS: The mean physical component score of SF-36 before surgery was 45.3 (SD=+/-10.1) and 8 weeks following surgery was 44.9 (SD=+/-11.04) [n=148, p=0.51, 95% CI=(-1.03 to 1.52)]. For the measurement of the changes in mood using BDI, BAI and SF-36, latent construct modelling was employed to increase validity. The covariance between mood pre- and post-operatively (cov=69.44) corresponded to a correlation coefficient, r=0.88 indicating that patients suffering a greater number of mood symptoms before surgery continue to have a greater number of symptoms following surgery. When the latent mood constructs were permitted to have different means the model fitted well with chi(2) (df=1)=0.86 for which p=0.77, thus the null hypothesis that MiODS has no effect on patient mood was rejected. CONCLUSIONS: MiODS affects patient mood which deteriorates at 8 weeks post-operatively regardless of the pre-operative patient mood state. More importantly patients suffering a greater number of mood symptoms before MiODS continue to have a greater number of symptoms following surgery.

Hepatitis C virus infections in the Swiss HIV Cohort Study: a rapidly evolving epidemic.

BACKGROUND: Hepatitis C virus (HCV) infection has a growing impact on morbidity and mortality in patients infected with human immunodeficiency virus (HIV). We assessed trends in HCV incidence in the different HIV transmission groups in the Swiss HIV Cohort Study (SHCS). METHODS: HCV infection incidence was assessed from 1998, when routine serial HCV screening was introduced in the SHCS, until 2011. All HCV-seronegative patients with at least 1 follow-up serology were included. Incidence rates (IRs) of HCV infections were compared between men who have sex with men (MSM), injection drug users (IDU), and heterosexuals (HET). RESULTS: HCV incidence was assessed in 3333 MSM, 123 IDU, and 3078 HET with a negative HCV serology at baseline. Over 23 707 person-years (py) for MSM, 733 py for IDU, and 20 752 py for HET, 101 (3%), 41 (33%), and 25 (1%) of patients seroconverted, respectively. The IR of HCV infections in MSM increased from 0.23 (95% credible interval [CrI], .08-.54) per 100 py in 1998 to 4.09 (95% CrI, 2.57-6.18) in 2011. The IR decreased in IDU and remained <1 per 100 py in HET. In MSM, history of inconsistent condom use (adjusted hazard ratio [HR], 2.09; 95% CI, 1.33-3.29) and past syphilis (adjusted HR, 2.11; 95% confidence interval [CI], 1.39-3.20) predicted HCV seroconversion. CONCLUSIONS: In the SHCS, HCV infection incidence decreased in IDU, remained stable in HET, and increased 18-fold in MSM in the last 13 years. These observations underscore the need for improved HCV surveillance and prevention among HIV-infected MSM.

How quickly should we titrate antihypertensive medication? Systematic review modelling blood pressure response from trial data.

Context There are no evidence syntheses available to guide clinicians on when to titrate antihypertensive medication after initiation. Objective To model the blood pressure (BP) response after initiating antihypertensive medication. Data sources electronic databases including Medline, Embase, Cochrane Register and reference lists up to December 2009. Study selection Trials that initiated antihypertensive medication as single therapy in hypertensive patients who were either drug naive or had a placebo washout from previous drugs. Data extraction Office BP measurements at a minimum of two weekly intervals for a minimum of 4 weeks. An asymptotic approach model of BP response was assumed and non-linear mixed effects modelling used to calculate model parameters. Results and conclusions Eighteen trials that recruited 4168 patients met inclusion criteria. The time to reach 50% of the maximum estimated BP lowering effect was 1 week (systolic 0.91 weeks, 95% CI 0.74 to 1.10; diastolic 0.95, 0.75 to 1.15). Models incorporating drug class as a source of variability did not improve fit of the data. Incorporating the presence of a titration schedule improved model fit for both systolic and diastolic pressure. Titration increased both the predicted maximum effect and the time taken to reach 50% of the maximum (systolic 1.2 vs 0.7 weeks; diastolic 1.4 vs 0.7 weeks). Conclusions Estimates of the maximum efficacy of antihypertensive agents can be made early after starting therapy. This knowledge will guide clinicians in deciding when a newly started antihypertensive agent is likely to be effective or not at controlling BP.

Which is the optimal sampling strategy for habitat suitability modelling

Designing an efficient sampling strategy is of crucial importance for habitat suitability modelling. This paper compares four such strategies, namely, 'random', 'regular', 'proportional-stratified' and 'equal -stratified'- to investigate (1) how they affect prediction accuracy and (2) how sensitive they are to sample size. In order to compare them, a virtual species approach (Ecol. Model. 145 (2001) 111) in a real landscape, based on reliable data, was chosen. The distribution of the virtual species was sampled 300 times using each of the four strategies in four sample sizes. The sampled data were then fed into a GLM to make two types of prediction: (1) habitat suitability and (2) presence/ absence. Comparing the predictions to the known distribution of the virtual species allows model accuracy to be assessed. Habitat suitability predictions were assessed by Pearson's correlation coefficient and presence/absence predictions by Cohen's K agreement coefficient. The results show the 'regular' and 'equal-stratified' sampling strategies to be the most accurate and most robust. We propose the following characteristics to improve sample design: (1) increase sample size, (2) prefer systematic to random sampling and (3) include environmental information in the design'

Comparative genomics of epidemic versus sporadic Staphylococcus aureus strains does not reveal molecular markers for epidemicity.

Staphylococcus aureus, especially when it is methicillin resistant, has been recognised as a major cause of nosocomial and community-acquired infections. It has also been shown that certain strains were able to cause clonal epidemics whereas others showed a more incidental occurrence. On the basis of this behavioural distinction, a genetic feature underlying this difference in epidemicity can be assumed. Understanding the difference will not only contribute to the development of markers for the identification of epidemic strains but will also shed light on the evolution of clones. Genomes of strains from two independent collections (n=18 and n=10 strains) were analysed. Both collections were composed of carefully selected, genetically diverse strains with clinically well-defined epidemic and sporadic behaviour. Comparative genome hybridisation (CGH) was performed using an Agilent array for one collection (up to 11 probes per open reading frame - ORF), and an Affymetrix array for the other (up to 30 probes per ORF). Presence and absence information of probe homologues and ORFs was taken for analysis of molecular variance (AMOVA) at the strain and behaviour levels. Not a single probe showed 100% concordant differences between epidemic and sporadic strains. Moreover, probe differences between groups were always smaller than those within groups. This was also true, when the analysis was focussed on presence versus absence of ORF's or when probe information was transformed into allelic profiles. These findings present strong evidence against the presence or absence of a single common specific genetic factor differentiating epidemic from sporadic S. aureus clones.

A fully adaptive numerical approximation for a two-dimensional epidemic model with nonlinear cross-diffusion

An epidemic model is formulated by a reactionâeuro"diffusion system where the spatial pattern formation is driven by cross-diffusion. The reaction terms describe the local dynamics of susceptible and infected species, whereas the diffusion terms account for the spatial distribution dynamics. For both self-diffusion and cross-diffusion, nonlinear constitutive assumptions are suggested. To simulate the pattern formation two finite volume formulations are proposed, which employ a conservative and a non-conservative discretization, respectively. An efficient simulation is obtained by a fully adaptive multiresolution strategy. Numerical examples illustrate the impact of the cross-diffusion on the pattern formation.

Is the obesity epidemic exaggerated? Clues from a developing country

Rapid response to: Patrick Basham and John Luik. Is the obesity epidemic exaggerated? Yes. BMJ 2008; 336: 244. doi: 10.1136/bmj.39458.495127.AD

Stochastic Population Projection for Germany - based on the Quadratic Spline approach to modelling age specific fertility rates

This contribution builds upon a former paper by the authors (Lipps and Betz 2004), in which a stochastic population projection for East- and West Germany is performed. Aim was to forecast relevant population parameters and their distribution in a consistent way. We now present some modifications, which have been modelled since. First, population parameters for the entire German population are modelled. In order to overcome the modelling problem of the structural break in the East during reunification, we show that the adaptation process of the relevant figures by the East can be considered to be completed by now. As a consequence, German parameters can be modelled just by using the West German historic patterns, with the start-off population of entire Germany. Second, a new model to simulate age specific fertility rates is presented, based on a quadratic spline approach. This offers a higher flexibility to model various age specific fertility curves. The simulation results are compared with the scenario based official forecasts for Germany in 2050. Exemplary for some population parameters (e.g. dependency ratio), it can be shown that the range spanned by the medium and extreme variants correspond to the s-intervals in the stochastic framework. It seems therefore more appropriate to treat this range as a s-interval covering about two thirds of the true distribution.

Analysis, modelling and classification of geospatial data using machine learning

The research considers the problem of spatial data classification using machine learning algorithms: probabilistic neural networks (PNN) and support vector machines (SVM). As a benchmark model simple k-nearest neighbor algorithm is considered. PNN is a neural network reformulation of well known nonparametric principles of probability density modeling using kernel density estimator and Bayesian optimal or maximum a posteriori decision rules. PNN is well suited to problems where not only predictions but also quantification of accuracy and integration of prior information are necessary. An important property of PNN is that they can be easily used in decision support systems dealing with problems of automatic classification. Support vector machine is an implementation of the principles of statistical learning theory for the classification tasks. Recently they were successfully applied for different environmental topics: classification of soil types and hydro-geological units, optimization of monitoring networks, susceptibility mapping of natural hazards. In the present paper both simulated and real data case studies (low and high dimensional) are considered. The main attention is paid to the detection and learning of spatial patterns by the algorithms applied.

SBML qualitative models: a model representation format and infrastructure to foster interactions between qualitative modelling formalisms and tools.

BACKGROUND: Qualitative frameworks, especially those based on the logical discrete formalism, are increasingly used to model regulatory and signalling networks. A major advantage of these frameworks is that they do not require precise quantitative data, and that they are well-suited for studies of large networks. While numerous groups have developed specific computational tools that provide original methods to analyse qualitative models, a standard format to exchange qualitative models has been missing. RESULTS: We present the Systems Biology Markup Language (SBML) Qualitative Models Package ("qual"), an extension of the SBML Level 3 standard designed for computer representation of qualitative models of biological networks. We demonstrate the interoperability of models via SBML qual through the analysis of a specific signalling network by three independent software tools. Furthermore, the collective effort to define the SBML qual format paved the way for the development of LogicalModel, an open-source model library, which will facilitate the adoption of the format as well as the collaborative development of algorithms to analyse qualitative models. CONCLUSIONS: SBML qual allows the exchange of qualitative models among a number of complementary software tools. SBML qual has the potential to promote collaborative work on the development of novel computational approaches, as well as on the specification and the analysis of comprehensive qualitative models of regulatory and signalling networks.

Public perceptions of collectives at the outbreak of the H1N1 epidemic: Heroes, villains and victims

Lay perceptions of collectives (e.g., groups, organizations, countries) implicated in the 2009 H1N1 outbreak were studied. Collectives serve symbolic functions to help laypersons make sense of the uncertainty involved in a disease outbreak. We argue that lay representations are dramatized, featuring characters like heroes, villains and victims. In interviews conducted soon after the outbreak, 47 Swiss respondents discussed the risk posed by H1N1, its origins and effects, and protective measures. Countries were the most frequent collectives mentioned. Poor, underdeveloped countries were depicted as victims, albeit ambivalently, as they were viewed as partly responsible for their own plight. Experts (physicians, researchers) and political and health authorities were depicted as heroes. Two villains emerged: the media (viewed as fear mongering or as a puppet serving powerful interests) and private corporations (e.g., the pharmaceutical industry). Laypersons' framing of disease threat diverges substantially from official perspectives.

There and back again? Combining habitat suitability modelling and connectivity analyses to assess a potential return of the otter to Switzerland

After a steady decline in the early 20th century, several terrestrial carnivore species have recently recovered in Western Europe, either through reintroductions or natural recolonization. Because of the large space requirements of these species and potential conflicts with human activities, ensuring their recovery requires the implementation of conservation and management measures that address the environmental, landscape and social dimensions of the problem. Few examples exist of such integrated management. Taking the case of the otter (Lutra lutra) in Switzerland, we propose a multi-step approach that allows to (1) identify areas with potentially suitable habitat, (2) evaluate their connectivity, (3) verify the potentiality of the species recolonization from populations in neighbouring countries. We showed that even though suitable habitat is available for the species and the level of structural connectivity within Switzerland is satisfactory, the level of connectivity with neighbouring populations is crucial to prioritize strategies that favour the species recovery in the field. This research is the first example integrating habitat suitability and connectivity assessment at different scales with other factors in a multi-step assessment for species recovery.