Accuracy of prehospital triage of trauma patients by emergency physicians: a retrospective study in western Switzerland.

OBJECTIVE: Accurate identification of major trauma patients in the prehospital setting positively affects survival and resource utilization. Triage algorithms using predictive criteria of injury severity have been identified in paramedic-based prehospital systems. Our rescue system is based on prehospital paramedics and emergency physicians. The aim of this study was to evaluate the accuracy of the prehospital triage performed by physicians and to identify the predictive factors leading to errors of triage.METHODS: Retrospective study of trauma patients triaged by physicians. Prehospital triage was analyzed using criteria defining major trauma victims (MTVs, Injury Severity Score >15, admission to ICU, need for immediate surgery and death within 48 h). Adequate triage was defined as MTVs oriented to the trauma centre or non-MTV (NMTV) oriented to regional hospitals.RESULTS: One thousand six hundred and eighti-five patients (blunt trauma 96%) were included (558 MTV and 1127 NMTV). Triage was adequate in 1455 patients (86.4%). Overtriage occurred in 171 cases (10.1%) and undertriage in 59 cases (3.5%). Sensitivity and specificity was 90 and 85%, respectively, whereas positive predictive value and negative predictive value were 75 and 94%, respectively. Using logistic regression analysis, significant (P<0.05) predictors of undertriage were head or thorax injuries (odds ratio >2.5). Predictors of overtriage were paediatric age group, pedestrian or 2 wheel-vehicle road traffic accidents (odds ratio >2.0).CONCLUSION: Physicians using clinical judgement provide effective prehospital triage of trauma patients. Only a few factors predicting errors in triage process were identified in this study.

Coronary artery disease screening in diabetic patients: how good is guideline adherence?

INTRODUCTION: Diabetic patients are at high risk for coronary artery disease (CAD), which is the leading cause of death in this population. The Swiss Society of Endocrinology-Diabetology (SSED) recommends CAD screening for diabetic patients with > or = 2 additional cardiovascular risk factors (CVRF), by stress echocardiography (SE) or myocardial perfusion imaging (MPI). The aim of this study was to assess the application of these guidelines and the treatment of CVRF in the diabetes outpatient clinics of the five Swiss University Hospitals. METHODS: The study was initiated in Lausanne and the study questionnaires were circulated to the endocrinologists of the five Swiss University Hospitals. Practitioners were asked to include consecutive patients attending the diabetes outpatient clinics over one month. Prevalence of CAD, screening methods for CAD, prevalence of CVRF, biological analyses over the last 6 months and medical therapy were recorded. RESULTS: A total of 302 subjects were included. The mean age was 53 +/- 14 years, 68% had type 2 diabetes, 27% type 1 and 5% other types. Among T2DM with > or = 2 CVRF, 45% were screened for CAD according to SSED guidelines. In T2DM 25% had blood pressure < or = 130/80 mm Hg, 15% a lipid profile within target, 23% HbA1c < or = 7.0%. Overall, 2% achieved all 3 targets. CONCLUSIONS: Only 45% of T2DM with > or = 2 CVRF were screened for CAD according to SSED guidelines and 2% of T2DM had proper control over all CVRF. Efforts are still necessary to improve CAD prevention and screening of diabetic patients in Swiss University Hospitals.

Development of a two-step screening ESI-TOF-MS method for rapid determination of significant stress-induced metabolome modifications in plant leaf extracts: the wound response in Arabidopsis thaliana as a case study.

To study the stress-induced effects caused by wounding under a new perspective, a metabolomic strategy based on HPLC-MS has been devised for the model plant Arabidopsis thaliana. To detect induced metabolites and precisely localise these compounds among the numerous constitutive metabolites, HPLC-MS analyses were performed in a two-step strategy. In a first step, rapid direct TOF-MS measurements of the crude leaf extract were performed with a ballistic gradient on a short LC-column. The HPLC-MS data were investigated by multivariate analysis as total mass spectra (TMS). Principal components analysis (PCA) and hierarchical cluster analysis (HCA) on principal coordinates were combined for data treatment. PCA and HCA demonstrated a clear clustering of plant specimens selecting the highest discriminating ions given by the complete data analysis, leading to the specific detection of discrete-induced ions (m/z values). Furthermore, pool constitution with plants of homogeneous behaviour was achieved for confirmatory analysis. In this second step, long high-resolution LC profilings on an UPLC-TOF-MS system were used on pooled samples. This allowed to precisely localise the putative biological marker induced by wounding and by specific extraction of accurate m/z values detected in the screening procedure with the TMS spectra.

Screening interventions in smokers by primary care physicians

Texte intégral: http://www.springerlink.com/content/3q68180337551r47/fulltext.pdf

Screening for occupational asthma by using a self-administered questionnaire in a clinical setting

OBJECTIVE: Because of its high prevalence, early screening for occupational asthma (OA) is crucial. We aimed to evaluate the screening performance of the Occupational Asthma Screening Questionnaire-11 items (OASQ-11) in a clinical setting. METHODS: Between January 2009 and December 2011, 169 workers referred for potential OA to our hospital completed the OASQ-11 and underwent workups to determine the final diagnosis. The discriminative abilities of the OASQ-11 as a whole and in relation to demographic and exposure parameters were determined by the area under the receiving operator characteristic curve (AUC). RESULTS: Model 1, consisting of the OASQ's items, showed fair discrimination (AUC, 0.69; 95% confidence interval, 0.58 to 0.80). Addition of age and exposure duration to model 1 improved discrimination (AUC, 0.80; confidence interval, 0.72 to 0.88). CONCLUSION: A simple model consisting of the OASQ-11's items, age, and exposure duration could well discriminate subjects with OA in a clinical setting.

Improving the Accuracy and Usability of Iowa Falling Weight Deflectometer Data, May 2013

This study aims to improve the accuracy and usability of Iowa Falling Weight Deflectometer (FWD) data by incorporating significant enhancements into the fully-automated software system for rapid processing of the FWD data. These enhancements include: (1) refined prediction of backcalculated pavement layer modulus through deflection basin matching/optimization, (2) temperature correction of backcalculated Hot-Mix Asphalt (HMA) layer modulus, (3) computation of 1993 AASHTO design guide related effective SN (SNeff) and effective k-value (keff ), (4) computation of Iowa DOT asphalt concrete (AC) overlay design related Structural Rating (SR) and kvalue (k), and (5) enhancement of user-friendliness of input and output from the software tool. A high-quality, easy-to-use backcalculation software package, referred to as, I-BACK: the Iowa Pavement Backcalculation Software, was developed to achieve the project goals and requirements. This report presents theoretical background behind the incorporated enhancements as well as guidance on the use of I-BACK developed in this study. The developed tool, I-BACK, provides more fine-tuned ANN pavement backcalculation results by implementation of deflection basin matching optimizer for conventional flexible, full-depth, rigid, and composite pavements. Implementation of this tool within Iowa DOT will facilitate accurate pavement structural evaluation and rehabilitation designs for pavement/asset management purposes. This research has also set the framework for the development of a simplified FWD deflection based HMA overlay design procedure which is one of the recommended areas for future research.

Improving the Accuracy and Usability of Iowa Falling Weight Deflectometer Data: Tech Transfer Summary, May 2013

This study aims to improve the accuracy and usability of Iowa Falling Weight Deflectometer (FWD) data by incorporating significant enhancements into the fully-automated software system for rapid processing of the FWD data. These enhancements include: (1) refined prediction of backcalculated pavement layer modulus through deflection basin matching/optimization, (2) temperature correction of backcalculated Hot-Mix Asphalt (HMA) layer modulus, (3) computation of 1993 AASHTO design guide related effective SN (SNeff) and effective k-value (keff ), (4) computation of Iowa DOT asphalt concrete (AC) overlay design related Structural Rating (SR) and kvalue (k), and (5) enhancement of user-friendliness of input and output from the software tool. A high-quality, easy-to-use backcalculation software package, referred to as, I-BACK: the Iowa Pavement Backcalculation Software, was developed to achieve the project goals and requirements. This report presents theoretical background behind the incorporated enhancements as well as guidance on the use of I-BACK developed in this study. The developed tool, I-BACK, provides more fine-tuned ANN pavement backcalculation results by implementation of deflection basin matching optimizer for conventional flexible, full-depth, rigid, and composite pavements. Implementation of this tool within Iowa DOT will facilitate accurate pavement structural evaluation and rehabilitation designs for pavement/asset management purposes. This research has also set the framework for the development of a simplified FWD deflection based HMA overlay design procedure which is one of the recommended areas for future research.

Accuracy of plant assemblage predictions from species distribution models varies along environmental gradients

Aim: Climatic niche modelling of species and community distributions implicitly assumes strong and constant climatic determinism across geographic space. This assumption had however never been tested so far. We tested it by assessing how stacked-species distribution models (S-SDMs) perform for predicting plant species assemblages along elevation. Location: Western Swiss Alps. Methods: Using robust presence-absence data, we first assessed the ability of topo-climatic S-SDMs to predict plant assemblages in a study area encompassing a 2800 m wide elevation gradient. We then assessed the relationships among several evaluation metrics and trait-based tests of community assembly rules. Results: The standard errors of individual SDMs decreased significantly towards higher elevations. Overall, the S-SDM overpredicted far more than they underpredicted richness and could not reproduce the humpback curve along elevation. Overprediction was greater at low and mid-range elevations in absolute values but greater at high elevations when standardised by the actual richness. Looking at species composition, the evaluation metrics accounting for both the presence and absence of species (overall prediction success and kappa) or focusing on correctly predicted absences (specificity) increased with increasing elevation, while the metrics focusing on correctly predicted presences (Jaccard index and sensitivity) decreased. The best overall evaluation - as driven by specificity - occurred at high elevation where species assemblages were shown to be under significant environmental filtering of small plants. In contrast, the decreased overall accuracy in the lowlands was associated with functional patterns representing any type of assembly rule (environmental filtering, limiting similarity or null assembly). Main Conclusions: Our study reveals interesting patterns of change in S-SDM errors with changes in assembly rules along elevation. Yet, significant levels of assemblage prediction errors occurred throughout the gradient, calling for further improvement of SDMs, e.g., by adding key environmental filters that act at fine scales and developing approaches to account for variations in the influence of predictors along environmental gradients.

Axial sub-nanometer accuracy in digital holographic microscopy

We present state-of-the-art dual-wavelength digital holographic microscopy (DHM) measurement on a calibrated 8.9 nm high chromium thin step sample and demonstrate sub-nanometer axial accuracy. By using a modified DHM reference calibrated hologram (RCH) reconstruction method, a temporal averaging procedure and a specific dual-wavelength DHM arrangement, it is shown that specimen topography can be measured with an accuracy, defined as the axial standard deviation, reduced to at least 0.9 nm. Indeed for the first time to the best of our knowledge, it is reported that averaging each of the two wavefronts recorded with real-time dual-wavelength DHM can provide up to 30% spatial noise reduction for the given configuration. Moreover, the presented experimental configuration achieves a temporal stability below 0.8 nm, thus paving the way to Angström range for dual-wavelength DHM.

EADock: docking of small molecules into protein active sites with a multiobjective evolutionary optimization.

In recent years, protein-ligand docking has become a powerful tool for drug development. Although several approaches suitable for high throughput screening are available, there is a need for methods able to identify binding modes with high accuracy. This accuracy is essential to reliably compute the binding free energy of the ligand. Such methods are needed when the binding mode of lead compounds is not determined experimentally but is needed for structure-based lead optimization. We present here a new docking software, called EADock, that aims at this goal. It uses an hybrid evolutionary algorithm with two fitness functions, in combination with a sophisticated management of the diversity. EADock is interfaced with the CHARMM package for energy calculations and coordinate handling. A validation was carried out on 37 crystallized protein-ligand complexes featuring 11 different proteins. The search space was defined as a sphere of 15 A around the center of mass of the ligand position in the crystal structure, and on the contrary to other benchmarks, our algorithm was fed with optimized ligand positions up to 10 A root mean square deviation (RMSD) from the crystal structure, excluding the latter. This validation illustrates the efficiency of our sampling strategy, as correct binding modes, defined by a RMSD to the crystal structure lower than 2 A, were identified and ranked first for 68% of the complexes. The success rate increases to 78% when considering the five best ranked clusters, and 92% when all clusters present in the last generation are taken into account. Most failures could be explained by the presence of crystal contacts in the experimental structure. Finally, the ability of EADock to accurately predict binding modes on a real application was illustrated by the successful docking of the RGD cyclic pentapeptide on the alphaVbeta3 integrin, starting far away from the binding pocket.