190 research outputs found

    Utilizing Virtual Learning to Deliver Evidence-based Practice

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    Using ordinal logistic regression to evaluate the performance of laser-Doppler predictions of burn-healing time

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    Background Laser-Doppler imaging (LDI) of cutaneous blood flow is beginning to be used by burn surgeons to predict the healing time of burn wounds; predicted healing time is used to determine wound treatment as either dressings or surgery. In this paper, we do a statistical analysis of the performance of the technique. Methods We used data from a study carried out by five burn centers: LDI was done once between days 2 to 5 post burn, and healing was assessed at both 14 days and 21 days post burn. Random-effects ordinal logistic regression and other models such as the continuation ratio model were used to model healing-time as a function of the LDI data, and of demographic and wound history variables. Statistical methods were also used to study the false-color palette, which enables the laser-Doppler imager to be used by clinicians as a decision-support tool. Results Overall performance is that diagnoses are over 90% correct. Related questions addressed were what was the best blood flow summary statistic and whether, given the blood flow measurements, demographic and observational variables had any additional predictive power (age, sex, race, % total body surface area burned (%TBSA), site and cause of burn, day of LDI scan, burn center). It was found that mean laser-Doppler flux over a wound area was the best statistic, and that, given the same mean flux, women recover slightly more slowly than men. Further, the likely degradation in predictive performance on moving to a patient group with larger %TBSA than those in the data sample was studied, and shown to be small. Conclusion Modeling healing time is a complex statistical problem, with random effects due to multiple burn areas per individual, and censoring caused by patients missing hospital visits and undergoing surgery. This analysis applies state-of-the art statistical methods such as the bootstrap and permutation tests to a medical problem of topical interest. New medical findings are that age and %TBSA are not important predictors of healing time when the LDI results are known, whereas gender does influence recovery time, even when blood flow is controlled for. The conclusion regarding the palette is that an optimum three-color palette can be chosen 'automatically', but the optimum choice of a 5-color palette cannot be made solely by optimizing the percentage of correct diagnoses

    A false-discovery-rate-based loss framework for selection of interactions

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    Interaction effects have been consistently found important in explaining the variation in outcomes in many scientific research fields. Yet, in practice, variable selection including interactions is complicated due to the limited sample size, conflicting philosophies regarding model interpretability, and accompanying amplified multiple-testing problems. The lack of statistically sound algorithms for automatic variable selection with interactions has discouraged activities in exploring important interaction effects. In this article, we investigated issues of selecting interactions from three aspects: (1) What is the model space to be searched? (2) How is the hypothesis-testing performed? (3) How to address the multiple-testing issue? We propose loss functions and corresponding decision rules that control FDR in a Bayesian context. Properties of the decision rules are discussed and their performance in terms of power and FDR is compared through simulations. Methods are illustrated on data from a colorectal cancer study assessing the chemotherapy treatments and data from a diffuse large-B-cell lymphoma study assessing the prognostic effect of gene expressions. Copyright © 2007 John Wiley & Sons, Ltd.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/58564/1/3118_ftp.pd

    Educational outreach to general practitioners reduces children's asthma symptoms: a cluster randomised controlled trial

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    <p>Abstract</p> <p>Background</p> <p>Childhood asthma is common in Cape Town, a province of South Africa, but is underdiagnosed by general practitioners. Medications are often prescribed inappropriately, and care is episodic. The objective of this study is to assess the impact of educational outreach to general practitioners on asthma symptoms of children in their practice.</p> <p>Methods</p> <p>This is a cluster randomised trial with general practices as the unit of intervention, randomisation, and analysis. The setting is Mitchells Plain (population 300,000), a dormitory town near Cape Town. Solo general practitioners, without nurse support, operate from storefront practices. Caregiver-reported symptom data were collected for 318 eligible children (2 to 17 years) with moderate to severe asthma, who were attending general practitioners in Mitchells Plain. One year post-intervention follow-up data were collected for 271 (85%) of these children in all 43 practices.</p> <p>Practices randomised to intervention (21) received two 30-minute educational outreach visits by a trained pharmacist who left materials describing key interventions to improve asthma care. Intervention and control practices received the national childhood asthma guideline. Asthma severity was measured in a parent-completed survey administered through schools using a symptom frequency and severity scale. We compared intervention and control group children on the change in score from pre-to one-year post-intervention.</p> <p>Results</p> <p>Symptom scores declined an additional 0.84 points in the intervention vs. control group (on a nine-point scale. p = 0.03). For every 12 children with asthma exposed to a doctor allocated to the intervention, one extra child will have substantially reduced symptoms.</p> <p>Conclusion</p> <p>Educational outreach was accepted by general practitioners and was effective. It could be applied to other health care quality problems in this setting.</p

    Phase equilibria and glass transition in colloidal systems with short-ranged attractive interactions. Application to protein crystallization

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    We have studied a model of a complex fluid consisting of particles interacting through a hard core and a short range attractive potential of both Yukawa and square-well form. Using a hybrid method, including a self-consistent and quite accurate approximation for the liquid integral equation in the case of the Yukawa fluid, perturbation theory to evaluate the crystal free energies, and mode-coupling theory of the glass transition, we determine both the equilibrium phase diagram of the system and the lines of equilibrium between the supercooled fluid and the glass phases. For these potentials, we study the phase diagrams for different values of the potential range, the ratio of the range of the interaction to the diameter of the repulsive core being the main control parameter. Our arguments are relevant to a variety of systems, from dense colloidal systems with depletion forces, through particle gels, nano-particle aggregation, and globular protein crystallization.Comment: 20 pages, 10 figure

    Monitoring international migration flows in Europe. Towards a statistical data base combining data from different sources

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    The paper reviews techniques developed in demography, geography and statistics that are useful for bridging the gap between available data on international migration flows and the information required for policy making and research. The basic idea of the paper is as follows: to establish a coherent and consistent data base that contains sufficiently detailed, up-to-date and accurate information, data from several sources should be combined. That raises issues of definition and measurement, and of how to combine data from different origins properly. The issues may be tackled more easily if the statistics that are being compiled are viewed as different outcomes or manifestations of underlying stochastic processes governing migration. The link between the processes and their outcomes is described by models, the parameters of which must be estimated from the available data. That may be done within the context of socio-demographic accounting. The paper discusses the experience of the U.S. Bureau of the Census in combining migration data from several sources. It also summarizes the many efforts in Europe to establish a coherent and consistent data base on international migration. The paper was written at IIASA. It is part of the Migration Estimation Study, which is a collaborative IIASA-University of Groningen project, funded by the Netherlands Organization for Scientific Research (NWO). The project aims at developing techniques to obtain improved estimates of international migration flows by country of origin and country of destination
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