Standardizing the diagnosis of inhalation injury using a descriptive score based on mucosal injury criteria.

INTRODUCTION: Inhalation injury is an important determinant of outcome in patients with major burns. However the diagnostic criteria remain imprecise, preventing objective comparisons of published data. The aims were to evaluate the utility of an inhalation score based on mucosal injury, while assessing separately the oro-pharyngeal sphere (ENT) and tracheobronchial tree (TB) in patients admitted to the ICU with a suspicion of inhalation injury. METHODS: Prospective observational study in 100 patients admitted with suspicion of inhalation injury among 168 consecutive burn admissions to the ICU of a university hospital. Inclusion criteria, endoscopic airway assessment during the first hours. ENT/TB lesion grading was 1: oedema, hyperemia, hypersecretion, 2: bullous mucosal detachment, erosion, exudates, 3: profound ulcers, necrosis. RESULTS: Of the 100 patients (age 42±17 years, burns 23±19%BSA), 79 presented an ENT inhalation injury ≥ENT1 (soot present in 24%): 36 had a tracheobronchial extension, 33 having a grade ≥TB1. Burned vibrissae: 10 patients "without" suffered ENT injury, while 6 patients "with" had no further lesions. Length of mechanical ventilation was strongly associated with the first 24 hrs' fluid resuscitation volume (p<0.0001) and the presence of inhalation injury (p=0.03), while the ICU length of stay was correlated with the %BSA. Soot was associated with prolonged mechanical ventilation (p=0.0115). There was no extubation failure. CONCLUSIONS: The developed inhalation score was simple to use, providing a unified language, and drawing attention to upper airway involvement. Burned vibrissae and suspected history proved to be insufficient diagnostic criteria. Further studies are required to validate the score in a larger population.

Modelling hydrodynamics in the Rio Parana, Argentina : an evaluation and inter-comparison of reduced-complexity and physics based models applied to a large sand-bed river

Depth-averaged velocities and unit discharges within a 30 km reach of one of the world's largest rivers, the Rio Parana, Argentina, were simulated using three hydrodynamic models with different process representations: a reduced complexity (RC) model that neglects most of the physics governing fluid flow, a two-dimensional model based on the shallow water equations, and a three-dimensional model based on the Reynolds-averaged Navier-Stokes equations. Row characteristics simulated using all three models were compared with data obtained by acoustic Doppler current profiler surveys at four cross sections within the study reach. This analysis demonstrates that, surprisingly, the performance of the RC model is generally equal to, and in some instances better than, that of the physics based models in terms of the statistical agreement between simulated and measured flow properties. In addition, in contrast to previous applications of RC models, the present study demonstrates that the RC model can successfully predict measured flow velocities. The strong performance of the RC model reflects, in part, the simplicity of the depth-averaged mean flow patterns within the study reach and the dominant role of channel-scale topographic features in controlling the flow dynamics. Moreover, the very low water surface slopes that typify large sand-bed rivers enable flow depths to be estimated reliably in the RC model using a simple fixed-lid planar water surface approximation. This approach overcomes a major problem encountered in the application of RC models in environments characterised by shallow flows and steep bed gradients. The RC model is four orders of magnitude faster than the physics based models when performing steady-state hydrodynamic calculations. However, the iterative nature of the RC model calculations implies a reduction in computational efficiency relative to some other RC models. A further implication of this is that, if used to simulate channel morphodynamics, the present RC model may offer only a marginal advantage in terms of computational efficiency over approaches based on the shallow water equations. These observations illustrate the trade off between model realism and efficiency that is a key consideration in RC modelling. Moreover, this outcome highlights a need to rethink the use of RC morphodynamic models in fluvial geomorphology and to move away from existing grid-based approaches, such as the popular cellular automata (CA) models, that remain essentially reductionist in nature. In the case of the world's largest sand-bed rivers, this might be achieved by implementing the RC model outlined here as one element within a hierarchical modelling framework that would enable computationally efficient simulation of the morphodynamics of large rivers over millennial time scales. (C) 2012 Elsevier B.V. All rights reserved.

Impact of relative size and language on the attitudes between nations and linguistic groups : The case of Switzerland

This study explores the impact of relative size on the intra- and intergroup attitudes of groups who either share a language or have a different language. For that purpose, we examined international attitudes, comparing a small nation, Switzerland, and two larger nations, Germany and France. We found support for the assumption that large neighbouring nations pose a threat to the smaller nation's identity, especially when they are linguistically similar. Consequently, in line with Tajfel's Social Identity Theory (1978), the smaller nation's inhabitants evaluate those of the larger nation less positively, liking them less and perceiving them to be more arrogant than vice versa. By investigating the special case of the French-speaking and the German-speaking Swiss as linguistic groups within their own nation we were able to demonstrate that these groups seek support with the larger-linguistically-similar nation to defend themselves against the more direct in-country threat to their identity. They acknowledge the similarity with the larger nation, yet keep defending their social identity by expressing a dislike for this perceived similarity.

The role of epilepsy in early language development in a child with a congenital lesion in the right hemisphere

Early epilepsy is known to worsen the developmental prognosis of young children with a congenital focal brain lesion, but its direct role is often very difficult to delineate from the other variables. This requires prolonged periods of follow-up with simultaneous serial electrophysiological and developmental assessments which are rarely obtained. We studied a male infant with a right prenatal infarct in the territory of the right middle cerebral artery resulting in a left spastic hemiparesis, and an epileptic disorder (infantile spasms with transient right hemihypsarrhythmia and focal seizures) from the age of 7 months until the age of 4 years. Pregnancy and delivery were normal. A dissociated delay of early language acquisition affecting mainly comprehension without any autistic features was documented. This delay was much more severe than usually expected in children with early focal lesions, and its evolution, with catch-up to normal, was correlated with the active phase of the epilepsy. We postulate that the epilepsy specifically amplified a pattern of delayed language emergence, mainly affecting lexical comprehension, reported in children with early right hemisphere damage.

Ensemble methods for environmental data modelling with support vector regression

This paper investigates the use of ensemble of predictors in order to improve the performance of spatial prediction methods. Support vector regression (SVR), a popular method from the field of statistical machine learning, is used. Several instances of SVR are combined using different data sampling schemes (bagging and boosting). Bagging shows good performance, and proves to be more computationally efficient than training a single SVR model while reducing error. Boosting, however, does not improve results on this specific problem.

Isolated disturbance of written language-acquisition as an initial symptom of epileptic aphasia in a 7-year-old child - a 3-year follow-up-study

A 7-year-old right-handed girl developed partial complex seizures with a left-sided onset. A brief period of post-ictal aphasia of the conduction type was documented before seizure control and complete normalization of oral language were obtained. We also found that she had a history of previous unexplained difficulty with written language acquisition that had occurred prior to the clinically recognized epilepsy and a subsequent loss of this ability. This rapidly improved with control of the epilepsy. The evolution of written language were been followed for 3 years, and continued improvement has occurred with fluctuations related to her epilepsy. This observation adds support to the growing body of data indicating that specific cognitive disturbances can be due to epilepsy in young children. It shows the vulnerability of skills which are in a period of active development, and the possibility that oral/written language can be differentially involved by cerebral dysfunction in the young child.

Modelling Bone Mineral Density in Swiss Breast Cancer Patients Treated with Letrozole, Tamoxifen and Sequences of Letrozole and Tamoxifen in the BIG 1-98 Study (SAKK 21/07).

Background: Bone health is a concern when treating early stage breast cancer patients with adjuvant aromatase inhibitors. Early detection of patients (pts) at risk of osteoporosis and fractures may be helpful for starting preventive therapies and selecting the most appropriate endocrine therapy schedule. We present statistical models describing the evolution of lumbar and hip bone mineral density (BMD) in pts treated with tamoxifen (T), letrozole (L) and sequences of T and L. Methods: Available dual-energy x-ray absorptiometry exams (DXA) of pts treated in trial BIG 1-98 were retrospectively collected from Swiss centers. Treatment arms: A) T for 5 years, B) L for 5 years, C) 2 years of T followed by 3 years of L and, D) 2 years of L followed by 3 years of T. Pts without DXA were used as a control for detecting selection biases. Patients randomized to arm A were subsequently allowed an unplanned switch from T to L. Allowing for variations between DXA machines and centres, two repeated measures models, using a covariance structure that allow for different times between DXA, were used to estimate changes in hip and lumbar BMD (g/cm2) from trial randomization. Prospectively defined covariates, considered as fixed effects in the multivariable models in an intention to treat analysis, at the time of trial randomization were: age, height, weight, hysterectomy, race, known osteoporosis, tobacco use, prior bone fracture, prior hormone replacement therapy (HRT), bisphosphonate use and previous neo-/adjuvant chemotherapy (ChT). Similarly, the T-scores for lumbar and hip BMD measurements were modeled using a per-protocol approach (allowing for treatment switch in arm A), specifically studying the effect of each therapy upon T-score percentage. Results: A total of 247 out of 546 pts had between 1 and 5 DXA; a total of 576 DXA were collected. Number of DXA measurements per arm were; arm A 133, B 137, C 141 and D 135. The median follow-up time was 5.8 years. Significant factors positively correlated with lumbar and hip BMD in the multivariate analysis were weight, previous HRT use, neo-/adjuvant ChT, hysterectomy and height. Significant negatively correlated factors in the models were osteoporosis, treatment arm (B/C/D vs. A), time since endocrine therapy start, age and smoking (current vs. never).Modeling the T-score percentage, differences from T to L were -4.199% (p = 0.036) and -4.907% (p = 0.025) for the hip and lumbar measurements respectively, before any treatment switch occurred. Conclusions: Our statistical models describe the lumbar and hip BMD evolution for pts treated with L and/or T. The results of both localisations confirm that, contrary to expectation, the sequential schedules do not seem less detrimental for the BMD than L monotherapy. The estimated difference in BMD T-score percent is at least 4% from T to L.

Modelling ecological niches with support vector machines

1. The ecological niche is a fundamental biological concept. Modelling species' niches is central to numerous ecological applications, including predicting species invasions, identifying reservoirs for disease, nature reserve design and forecasting the effects of anthropogenic and natural climate change on species' ranges. 2. A computational analogue of Hutchinson's ecological niche concept (the multidimensional hyperspace of species' environmental requirements) is the support of the distribution of environments in which the species persist. Recently developed machine-learning algorithms can estimate the support of such high-dimensional distributions. We show how support vector machines can be used to map ecological niches using only observations of species presence to train distribution models for 106 species of woody plants and trees in a montane environment using up to nine environmental covariates. 3. We compared the accuracy of three methods that differ in their approaches to reducing model complexity. We tested models with independent observations of both species presence and species absence. We found that the simplest procedure, which uses all available variables and no pre-processing to reduce correlation, was best overall. Ecological niche models based on support vector machines are theoretically superior to models that rely on simulating pseudo-absence data and are comparable in empirical tests. 4. Synthesis and applications. Accurate species distribution models are crucial for effective environmental planning, management and conservation, and for unravelling the role of the environment in human health and welfare. Models based on distribution estimation rather than classification overcome theoretical and practical obstacles that pervade species distribution modelling. In particular, ecological niche models based on machine-learning algorithms for estimating the support of a statistical distribution provide a promising new approach to identifying species' potential distributions and to project changes in these distributions as a result of climate change, land use and landscape alteration.