Trauma team activation varies across Dutch emergency departments: a national survey

Background Tiered trauma team response may contribute to efficient in-hospital trauma triage by reducing the amount of resources required and by improving health outcomes. This study evaluates current practice of trauma team activation (TTA) in Dutch emergency departments (EDs). Methods A survey was conducted among managers of all 102 EDs in the Netherlands, using a semi-structured online questionnaire. Results Seventy-two questionnaires were analysed. Most EDs use a one-team system (68 %). EDs with a tiered-response receive more multi trauma patients (p < 0.01) and have more trauma team alerts per year (p < 0.05) than one-team EDs. The number of trauma team members varies from three to 16 professionals. The ED nurse usually receives the pre-notification (97 %), whereas the decision to activate a team is made by an ED nurse (46 %), ED physician (30 %), by multiple professionals (20 %) or other (4 %). Information in the pre-notification mostly used for trauma team activation are Airway-Breathing-Circulation (87 %), Glasgow Coma Score (90 %), and Revised Trauma Score (85 %) or Paediatric Trauma Score (86 %). However, this information is only available for 75 % of the patients or less. Only 56 % of the respondents were satisfied with their current in-hospital trauma triage system. Conclusions Trauma team activation varies across Dutch EDs and there is room for improvement in the trauma triage system used, size of the teams and the professionals involved. More direct communication and more uniform criteria could be used to efficiently and safely activate a specific trauma team. Therefore, the implementation of a revised national consensus guideline is recommende

Structural characterization of the thermostable <i>Bradyrhizobium japonicum</i> D-sorbitol dehydrogenase

Bradyrhizobium japonicum sorbitol dehydrogenase is NADH-dependent and is active at elevated temperatures. The best substrate is d-glucitol (a synonym for d-sorbitol), although l-glucitol is also accepted, giving it particular potential in industrial applications. Crystallization led to a hexagonal crystal form, with crystals diffracting to 2.9 Å resolution. In attempts to phase the data, a molecular-replacement solution based upon PDB entry 4nbu (33% identical in sequence to the target) was found. The solution contained one molecule in the asymmetric unit, but a tetramer similar to that found in other short-chain dehydrogenases, including the search model, could be reconstructed by applying crystallographic symmetry operations. The active site contains electron density consistent with d-glucitol and phosphate, but there was not clear evidence for the binding of NADH. In a search for the features that determine the thermostability of the enzyme, the T (m) for the orthologue from Rhodobacter sphaeroides, for which the structure was already known, was also determined, and this enzyme proved to be considerably less thermostable. A continuous β-sheet is formed between two monomers in the tetramer of the B. japonicum enzyme, a feature not generally shared by short-chain dehydrogenases, and which may contribute to thermostability, as may an increased Pro/Gly ratio

A new insight into the zinc-dependent DNA-cleavage by the colicin E7 nuclease:a crystallographic and computational study

The crystal structure of a colicin E7 metallonuclease mutant complemented by QM/MM calculations suggests an alternative catalytic mechanism of Zn2+-containing HNH nucleases.</p

A new MR-SAD algorithm for the automatic building of protein models from low-resolution X-ray data and a poor starting model

Determining macromolecular structures from X-ray data with resolution worse than 3 Å remains a challenge. Even if a related starting model is available, its incompleteness or its bias together with a low observation-to-parameter ratio can render the process unsuccessful or very time-consuming. Yet, many biologically important macromolecules, especially large macromolecular assemblies, membrane proteins and receptors, tend to provide crystals that diffract to low resolution. A new algorithm to tackle this problem is presented that uses a multivariate function to simultaneously exploit information from both an initial partial model and low-resolution single-wavelength anomalous diffraction data. The new approach has been used for six challenging structure determinations, including the crystal structures of membrane proteins and macromolecular complexes that have evaded experts using other methods, and large structures from a 3.0 Å resolution F1-ATPase data set and a 4.5 Å resolution SecYEG–SecA complex data set. All of the models were automatically built by the method to Rfree values of between 28.9 and 39.9% and were free from the initial model bias

A new MR-SAD algorithm for the automatic building of protein models from low-resolution X-ray data and a poor starting model

Determining macromolecular structures from X-ray data with resolution worse than 3 Å remains a challenge. Even if a related starting model is available, its incompleteness or its bias together with a low observation-to-parameter ratio can render the process unsuccessful or very time-consuming. Yet, many biologically important macromolecules, especially large macromolecular assemblies, membrane proteins and receptors, tend to provide crystals that diffract to low resolution. A new algorithm to tackle this problem is presented that uses a multivariate function to simultaneously exploit information from both an initial partial model and low-resolution single-wavelength anomalous diffraction data. The new approach has been used for six challenging structure determinations, including the crystal structures of membrane proteins and macromolecular complexes that have evaded experts using other methods, and large structures from a 3.0 Å resolution F_1-ATPase data set and a 4.5 Å resolution SecYEG–SecA complex data set. All of the models were automatically built by the method to R_(free) values of between 28.9 and 39.9% and were free from the initial model bias

Is the impact of hospital performance data greater in patients who have compared hospitals?

<p>Abstract</p> <p>Background</p> <p>Public information on average has limited impact on patients' hospital choice. However, the impact may be greater in consumers who have compared hospitals prior to their hospital choice. We therefore assessed whether patients who have compared hospitals based their hospital choice mainly on public information, rather than e.g. advice of their general practitioner and consider other information important than patients who have not compared hospitals.</p> <p>Methods</p> <p>337 new surgical patients completed an internet-based questionnaire. They were asked whether they had compared hospitals prior to their hospital choice and which factors influenced their choice. They were also asked to select between four and ten items of hospital information (total: 41 items) relevant for their future hospital choice. These were subsequently used in a hospital choice experiment in which participants were asked to compare hospitals in an Adaptive Choice-Based Conjoint analysis to estimate which of the hospital characteristics had the highest Relative Importance (RI).</p> <p>Results</p> <p>Patients who have compared hospitals more often used public information for their hospital choice than patients who have not compared hospitals (12.7% vs. 1.5%, p < 0.001). However, they still mostly relied on their own (47.9%) and other people's experiences (31%) rather than to base their decision on public information. Both groups valued physician's expertise (RI 20.2 [16.6-24.8] in patients comparing hospitals vs. 16.5 [14.2-18.8] in patients not comparing hospitals) and waiting time (RI 15.1 [10.7-19.6] vs. 15.6 [13.2-17.9] respectively) as most important public information. Patients who have compared hospitals assigned greater importance to information on wound infections (p = 0.010) and respect for patients (p = 0.022), but lower importance to hospital distance (p = 0.041).</p> <p>Conclusion</p> <p>Public information has limited impact on patient's hospital choice, even in patients who have actually compared hospitals prior to hospital choice.</p