Impact of referral templates on the quality of referrals from primary to secondary care: a cluster randomised trial

Background: The referral letter is an important document facilitating the transfer of care from a general practitioner (GP) to secondary care. Hospital doctors have often criticised the quality and content of referral letters, and the effectiveness of improvement efforts remains uncertain. Methods: A cluster randomised trial was conducted using referral templates for patients in four diagnostic groups: dyspepsia, suspected colorectal cancer, chest pain and chronic obstructive pulmonary disease. The GP surgery was the unit of randomisation. Of the 14 surgeries served by the University Hospital of North Norway Harstad, seven were randomised to the intervention group. Intervention GPs used referral templates soliciting core clinical information when initiating a new referral in one of the four clinical areas. Intermittent surgery visits by study personnel were also carried out. A total of 500 patients were included, with 281 in the intervention and 219 in the control arm. Referral quality scoring was performed by three blinded raters. Data were analysed using multi-level regression modelling. All analyses were conducted on intention-to-treat basis. Results: In the final multilevel model, referrals in the intervention group scored 18 % higher (95 % CI (11 %, 25 %), p Conclusion: In this study, the dissemination of referral templates coupled with intermittent surgery visits produced higher quality referrals. Trial registration: This trial has been registered at ClinicalTrials.gov. The trial registration number is NCT01470963

Evaluation of the performance of self-healing concrete at small and large scale under laboratory conditions

HEALCON is an EU-FP7 project which aims to develop self-healing concrete to create durable and sustainable concrete structures. While during the first years of the project the self-healing materials (including the healing agents and suitable encapsulation methodologies) and monitoring techniques were designed and tested at lab-scale, large scale elements have been tested near the end of the project to verify the feasibility and efficiency of the self-healing concrete under conditions closer to reality. For this paper, two types of healing agents were investigated for use in mortar and concrete. The first type of healing agent studied was a coated superabsorbent polymer (C-SAP). It is known that the autogenous healing capacity is increased by incorporation of superabsorbent polymers (SAPs) in mortar/concrete. The agents present in the crack can absorb intruding water, swell and block the crack, leading to immediate sealing, but can also exude moisture to the surrounding concrete environment stimulating healing of the concrete by hydration of unreacted cement particles or by CaCO3 precipitation. The disadvantage of these SAPs in the fresh mortar/concrete mix is however that they absorb large quantities of mixing water, leading to unwanted effects (e.g. loss of workability and macro-pore formation). By coating of the SAPs, we want to eliminate this disadvantage. The fluid bed spraying of the different layers was applied by VTT. A second healing agent studied, is a biogenic healing agent, namely a Mixed Ureolytic Culture (MUC). This type of healing agent was developed by Avecom in order to reduce the cost associated with the production of pure bacterial strains. This mixed ureolytic culture is moreover self-protecting and does not need any further encapsulation. At first, the performance of the healing agents itself was evaluated. For the coated SAPs, the swelling performance and swelling rate were determined, showing that the coating can limit the uptake of water during the first 10-15 minutes. For the MUC, the ureolytic and CaCO3 precipitating capacity was determined, immediately after production of the MUC and after 3 months of storage. The results show the potential of these mixed cultures to be used as self-healing agent in mortar/concrete, but also show a decrease of their effectiveness with time. Subsequently, the healing agents were incorporated in mortar mixes at UGent. A dosage of 1 wt% relative to the cement content caused a large reduction of the mechanical properties of the mortar (up to ~ 50%), except for the coated SAP. The sealing efficiency was evaluated with the water flow test, as designed by one of the project partners in HEALCON. The performance of reference mixes was compared to that of self-healing mixes with SAP, coated SAP or MUC (+ urea). Results showed that for cracks with a width less than 0.150 mm, all mortars were sealed (almost) completely after storage for 28 days in wet-dry environment (12 h wet – 12 h dry) after crack creation. For cracks with a larger width, differences were noticed between the different specimens. Moreover, also the immediate sealing effect induced by the presence of SAPs could be noticed. It has to be noted however that the crack width plays an important role but is varying along the crack length (within a specimen) and between specimens, making the analysis more difficult. In order to extend the application to concrete, self-healing and reference reinforced concrete beams (2500 x 400 x 200 mm) were produced at the Danish Technological Institute. The self-healing concretes contained coated SAPs or MUC. Moreover, the beams were equipped with corrosion sensors that are connected to a wireless monitoring system, developed by the Technology-Transfer- Initiative at the University of Stuttgart. The multi reference electrodes (MuRE) were installed alongside the reinforcements and measure the corrosion potential at certain positions. Data is collected in sufficiently dense intervals by battery powered nodes that transmit the data wirelessly to a base station and further on to a database where it can be accessed through a web based application for data analysis over the internet. At the age of 28 days, three-point bending cracks up to 0.6 mm were created in the beams. Subsequently, the beams were regularly sprayed with water (four times one hour per day) for 6 weeks and afterwards, the beams were, once a week, exposed to 3 wt% NaCl solution for 24 h. Evaluation of the self-healing performance by microscopic analysis (crack microscopy and analysis of thin sections) showed that for the reference beam and beam with MUC no significant healing could be noticed (probably because of insufficient supply of nutrients for the bacteria). For the beams with coated SAPs, the smaller cracks (0.1 and 0.2 mm) were partly closed. Continuous corrosion monitoring showed corrosion in the reference and MUC beams already after the first exposure to NaCl solution. Onset of corrosion was delayed in the case the beams contained coated SAPs

Reference shape effects on Fourier transform holography

Soft-x-ray holography which utilizes an optics mask fabricated in direct contact with the sample, is a widely applied x-ray microscopy method, in particular, for investigating magnetic samples. The optics mask splits the x-ray beam into a reference wave and a wave to illuminate the sample. The reconstruction quality in such a Fourier-transform holography experiment depends primarily on the characteristics of the reference wave, typically emerging from a small, high-aspect-ratio pinhole in the mask. In this paper, we study two commonly used reference geometries and investigate how their 3D structure affects the reconstruction within an x-ray Fourier holography experiment. Insight into these effects is obtained by imaging the exit waves from reference pinholes via high-resolution coherent diffraction imaging combined with three-dimensional multislice simulations of the x-ray propagation through the reference pinhole. The results were used to simulate Fourier-transform holography experiments to determine the spatial resolution and precise location of the reconstruction plane for different reference geometries. Based on our findings, we discuss the properties of the reference pinholes with view on application in soft-x-ray holography experiments

Tuberculostearic Acid-Containing Phosphatidylinositols as Markers of Bacterial Burden in Tuberculosis

One-fourth of the global human population is estimated to be infected with strains of the Mycobacterium tuberculosis complex (MTBC), the causative agent of tuberculosis (TB). Using lipidomic approaches, we show that tuberculostearic acid (TSA)-containing phosphatidylinositols (PIs) are molecular markers for infection with clinically relevant MTBC strains and signify bacterial burden. For the most abundant lipid marker, detection limits of ∼10$^{2}$ colony forming units (CFUs) and ∼10$^{3}$ CFUs for bacterial and cell culture systems were determined, respectively. We developed a targeted lipid assay, which can be performed within a day including sample preparation─roughly 30-fold faster than in conventional methods based on bacterial culture. This indirect and culture-free detection approach allowed us to determine pathogen loads in infected murine macrophages, human neutrophils, and murine lung tissue. These marker lipids inferred from mycobacterial PIs were found in higher levels in peripheral blood mononuclear cells of TB patients compared to healthy individuals. Moreover, in a small cohort of drug-susceptible TB patients, elevated levels of these molecular markers were detected at the start of therapy and declined upon successful anti-TB treatment. Thus, the concentration of TSA-containing PIs can be used as a correlate for the mycobacterial burden in experimental models and in vitro systems and may prospectively also provide a clinically relevant tool to monitor TB severity

Meteorological and Back Trajectory Modeling for the Rocky Mountain Atmospheric Nitrogen and Sulfur Study II

The Rocky Mountain Atmospheric Nitrogen and Sulfur (RoMANS II) study with field operations during November 2008 through November 2009 was designed to evaluate the composition and sources of reactive nitrogen in Rocky Mountain National Park, Colorado, USA. As part of RoMANS II, a mesoscale meteorological model was utilized to provide input for back trajectory and chemical transport models. Evaluation of the model's ability to capture important transport patterns in this region of complex terrain is discussed. Previous source-receptor studies of nitrogen in this region are also reviewed. Finally, results of several back trajectory analyses for RoMANS II are presented. The trajectory mass balance (TrMB) model, a receptor-based linear regression technique, was used to estimate mean source attributions of airborne ammonia concentrations during RoMANS II. Though ammonia concentrations are usually higher when there is transport from the east, the TrMB model estimates that, on average, areas to the west contribute a larger mean fraction of the ammonia. Possible reasons for this are discussed and include the greater frequency of westerly versus easterly winds, the possibility that ammonia is transported long distances as ammonium nitrate, and the difficulty of correctly modeling the transport winds in this area

The differential effects of concurrent planning practice elements on reunification and adoption

Objective: The child welfare practice of concurrent planning attempts to shorten children\u27s stays in foster care. There is very little quantitative research on concurrent planning\u27s effects. This study examines the influence of concurrent planning practice elements (reunification prognosis, concurrent plan, full disclosure, and discussion of voluntary relinquishment) on reunification and adoption. Method: Using a sample of 885 children, an observational design, and statistical controls, children who received concurrent planning elements were compared to those who did not. Results: Findings show discussion of voluntary relinquishment to be positively associated with adoption and full disclosure to be negatively associated with reunification. Conclusions: Concurrent planning\u27s benefits may require more intensive services to be fully realized. Care should be taken to ensure activities achieve their intended effects

Traffic4cast at NeurIPS 2022 -- Predict Dynamics along Graph Edges from Sparse Node Data: Whole City Traffic and ETA from Stationary Vehicle Detectors

The global trends of urbanization and increased personal mobility force us to rethink the way we live and use urban space. The Traffic4cast competition series tackles this problem in a data-driven way, advancing the latest methods in machine learning for modeling complex spatial systems over time. In this edition, our dynamic road graph data combine information from road maps, $10^{12}$ probe data points, and stationary vehicle detectors in three cities over the span of two years. While stationary vehicle detectors are the most accurate way to capture traffic volume, they are only available in few locations. Traffic4cast 2022 explores models that have the ability to generalize loosely related temporal vertex data on just a few nodes to predict dynamic future traffic states on the edges of the entire road graph. In the core challenge, participants are invited to predict the likelihoods of three congestion classes derived from the speed levels in the GPS data for the entire road graph in three cities 15 min into the future. We only provide vehicle count data from spatially sparse stationary vehicle detectors in these three cities as model input for this task. The data are aggregated in 15 min time bins for one hour prior to the prediction time. For the extended challenge, participants are tasked to predict the average travel times on super-segments 15 min into the future - super-segments are longer sequences of road segments in the graph. The competition results provide an important advance in the prediction of complex city-wide traffic states just from publicly available sparse vehicle data and without the need for large amounts of real-time floating vehicle data.Comment: Pre-print under review, submitted to Proceedings of Machine Learning Researc

The Hidden Story of Heterogeneous B-raf V600E Mutation Quantitative Protein Expression in Metastatic Melanoma-Association with Clinical Outcome and Tumor Phenotypes

In comparison to other human cancer types, malignant melanoma exhibits the greatest amount of heterogeneity. After DNA-based detection of the BRAF V600E mutation in melanoma patients, targeted inhibitor treatment is the current recommendation. This approach, however, does not take the abundance of the therapeutic target, i.e., the B-raf V600E protein, into consideration. As shown by immunohistochemistry, the protein expression profiles of metastatic melanomas clearly reveal the existence of inter-and intra-tumor variability. Nevertheless, the technique is only semi-quantitative. To quantitate the mutant protein there is a fundamental need for more precise techniques that are aimed at defining the currently non-existent link between the levels of the target protein and subsequent drug efficacy. Using cutting-edge mass spectrometry combined with DNA and mRNA sequencing, the mutated B-raf protein within metastatic tumors was quantitated for the first time. B-raf V600E protein analysis revealed a subjacent layer of heterogeneity for mutation-positive metastatic melanomas. These were characterized into two distinct groups with different tumor morphologies, protein profiles and patient clinical outcomes. This study provides evidence that a higher level of expression in the mutated protein is associated with a more aggressive tumor progression. Our study design, comprised of surgical isolation of tumors, histopathological characterization, tissue biobanking, and protein analysis, may enable the eventual delineation of patient responders/non-responders and subsequent therapy for malignant melanoma

Maternal depressive symptoms during and after pregnancy and child developmental milestones

Abstract Background: Maternal depressive symptoms during and after pregnancy predict poorer child neurodevelopment. The effects of timing, symptom severity, and additive influences remain unclear. Methods: A total of 2,231 mothers of the Prediction and Prevention of Pre‐eclampsia and Intrauterine Growth Restriction (PREDO) study completed the Center for Epidemiological Studies Depression Scale biweekly up to 14 times during pregnancy and twice up to 12 months after pregnancy. At child’s age 1.9–5.7 years, the mothers completed the Beck Depression Inventory‐II on their concurrent depressive symptoms and Ages and Stages Questionnaire on child developmental milestones. Results: Higher mean maternal depressive symptoms, each biweekly score, and consistently clinically relevant symptomatology during pregnancy predicted lower total developmental milestones, fine and gross motor, communication, problem solving, and personal/social skills scores in children. Although maternal depressive symptoms up to 12 months after pregnancy and in early childhood also predicted lower developmental milestones scores, developmental milestones scores were the lowest in children whose mothers’ depressive symptoms were above the clinical cutoff either only during pregnancy, both during and up to 12 months after pregnancy, or at each three time‐points. Conclusion: Maternal depressive symptoms during pregnancy, in the first year postpartum and in early childhood are associated with poorer child neurodevelopment. Our findings further suggest that antenatal and postpregnancy depression have additive effects on neurodevelopment. Children of mothers with the most chronic and severe depressive symptoms during pregnancy had the most neurodevelopmental disadvantages. Our findings emphasize the adverse effects of maternal depression during and after pregnancy and in early childhood on child neurodevelopment