86 resultados para implementing evidence in practice


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Rationale. The Brisbane Cardiac Consortium, a quality improvement collaboration of clinicians from three hospitals and five divisions of general practice, developed and reported clinical indicators as measures of the quality of care received by patients with acute coronary syndromes or congestive heart failure. Development of indicators. An expert panel derived indicators that measured gaps between evidence and practice. Data collected from hospital records and general practice heart-check forms were used to calculate process and outcome indicators for each condition. Our indicators were reliable (kappa scores 0.7-1.0) and widely accepted by clinicians as having face validity. Independent review of indicator-failed, in-hospital cases revealed that, for 27 of 28 process indicators, clinically legitimate reasons for withholding specific interventions were found in

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To promote the range of interventions for building family/general practice (family medicine) research capacity, we describe successful international examples. Such examples of interventions that build research capacity focus on diseases and illness research, as well as process research; monitor the output of research in family/general practice (family medicine); increase the number of family medicine research journals; encourage and enable research skills acquisition (including making it part of professional training); strengthen the academic base; and promote research networks and collaborations. The responsibility for these interventions lies with the government, colleges and academies, and universities. There are exciting and varied methods of building research capacity in family medicine.

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Rationale and aims 'OTseeker' is an online database of randomized controlled trials (RCTs) and systematic reviews relevant to occupational therapy. RCTs are critically appraised and rated for quality using the 'PEDro' scale. We aimed to investigate the inter-rater reliability of the PEDro scale before and after revising rating guidelines. Methods In study 1, five raters scored 100 RCTs using the original PEDro scale guidelines. In study 2, two raters scored 40 different RCTs using revised guidelines. All RCTs were randomly selected from the OTseeker database. Reliability was calculated using Kappa and intraclass correlation coefficients [ICC (model 2,1)]. Results Inter-rater reliability was 'good to excellent' in the first study (Kappas >= 0.53; ICCs >= 0.71). After revising the rating guidelines, the reliability levels were equivalent or higher to those previously obtained (Kappas >= 0.53; ICCs >= 0.89), except for the item, 'groups similar at baseline', which still had moderate reliability (Kappa = 0.53). In study 2, two PEDro scale items, which had their definitions revised, 'less than 15% dropout' and 'point measures and variability', showed higher reliability. In both studies, the PEDro items with the lowest reliability were 'groups similar at baseline' (Kappas = 0.53), 'less than 15% dropout' (Kappas

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Aim. This paper reports a study to test the hypothesis that day surgery patients who listen to music during their preoperative wait will have statistically significantly lower levels of anxiety than patients who receive routine care. Background. Although previous day surgery research suggests that music effectively reduces preoperative anxiety, methodological issues limit the generalizability of results. Methods. In early 2004, a randomized controlled trial design was conducted to assess anxiety before and after listening to patient preferred music. Participants were allocated to an intervention (n = 60), placebo (n = 60) or control group (n = 60). Pre- and post-test measures of anxiety were carried out using the State-Trait Anxiety Inventory. Results. Music statistically significantly reduced the state anxiety level of the music (intervention) group. No relationships were found between socio-demographic or clinical variables such as gender or type of surgery. Conclusion. The findings support the use of music as an independent nursing intervention for preoperative anxiety in patients having day surgery.

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We report the clinical characteristics of a schizophrenia sample of 409 pedigrees-263 of European ancestry ( EA) and 146 of African American ancestry ( AA)-together with the results of a genome scan ( with a simple tandem repeat polymorphism interval of 9 cM) and follow-up fine mapping. A family was required to have a proband with schizophrenia ( SZ) and one or more siblings of the proband with SZ or schizoaffective disorder. Linkage analyses included 403 independent full-sibling affected sibling pairs ( ASPs) ( 279 EA and 124 AA) and 100 all-possible half-sibling ASPs ( 15 EA and 85 AA). Nonparametric multipoint linkage analysis of all families detected two regions with suggestive evidence of linkage at 8p23.3-q12 and 11p11.2-q22.3 ( empirical Z likelihood-ratio score [ Z(lr)] threshold >= 2.65) and, in exploratory analyses, two other regions at 4p16.1-p15.32 in AA families and at 5p14.3-q11.2 in EA families. The most significant linkage peak was in chromosome 8p; its signal was mainly driven by the EA families. Z(lr) scores >= 2.0 in 8p were observed from 30.7 cM to 61.7 cM ( Center for Inherited Disease Research map locations). The maximum evidence in the full sample was a multipoint Z(lr) of 3.25 ( equivalent Kong-Cox LOD of 2.30) near D8S1771 ( at 52 cM); there appeared to be two peaks, both telomeric to neuregulin 1 ( NRG1). There is a paracentric inversion common in EA individuals within this region, the effect of which on the linkage evidence remains unknown in this and in other previously analyzed samples. Fine mapping of 8p did not significantly alter the significance or length of the peak. We also performed fine mapping of 4p16.3-p15.2, 5p15.2-q13.3, 10p15.3-p14, 10q25.3-q26.3, and 11p13-q23.3. The highest increase in Z(lr) scores was observed for 5p14.1-q12.1, where the maximum Z(lr) increased from 2.77 initially to 3.80 after fine mapping in the EA families.

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In the context of cancer diagnosis and treatment, we consider the problem of constructing an accurate prediction rule on the basis of a relatively small number of tumor tissue samples of known type containing the expression data on very many (possibly thousands) genes. Recently, results have been presented in the literature suggesting that it is possible to construct a prediction rule from only a few genes such that it has a negligible prediction error rate. However, in these results the test error or the leave-one-out cross-validated error is calculated without allowance for the selection bias. There is no allowance because the rule is either tested on tissue samples that were used in the first instance to select the genes being used in the rule or because the cross-validation of the rule is not external to the selection process; that is, gene selection is not performed in training the rule at each stage of the cross-validation process. We describe how in practice the selection bias can be assessed and corrected for by either performing a cross-validation or applying the bootstrap external to the selection process. We recommend using 10-fold rather than leave-one-out cross-validation, and concerning the bootstrap, we suggest using the so-called. 632+ bootstrap error estimate designed to handle overfitted prediction rules. Using two published data sets, we demonstrate that when correction is made for the selection bias, the cross-validated error is no longer zero for a subset of only a few genes.

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There are many factors which affect the L2 learner’s performance at the levels of phonology, morphology and syntax. Consequently when L2 learners attempt to communicate in the target language, their language production will show systematic variability across the above mentioned linguistic domains. This variation can be attributed to some factors such as interlocutors, topic familiarity, prior knowledge, task condition, planning time and tasks types. This paper reports the results of an on going research investigating the issue of variability attributed to the task type. It is hypothesized that the particular type of task learners are required to perform will result in variation in their performance. Results of the statistical analyses of this study investigating the issue of variation in the performance of twenty L2 learners at the English department of Tabriz University provided evidence in support of the hypothesis that performance of L2 learners show systematic variability attributed to task.

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Data mining is the process to identify valid, implicit, previously unknown, potentially useful and understandable information from large databases. It is an important step in the process of knowledge discovery in databases, (Olaru & Wehenkel, 1999). In a data mining process, input data can be structured, seme-structured, or unstructured. Data can be in text, categorical or numerical values. One of the important characteristics of data mining is its ability to deal data with large volume, distributed, time variant, noisy, and high dimensionality. A large number of data mining algorithms have been developed for different applications. For example, association rules mining can be useful for market basket problems, clustering algorithms can be used to discover trends in unsupervised learning problems, classification algorithms can be applied in decision-making problems, and sequential and time series mining algorithms can be used in predicting events, fault detection, and other supervised learning problems (Vapnik, 1999). Classification is among the most important tasks in the data mining, particularly for data mining applications into engineering fields. Together with regression, classification is mainly for predictive modelling. So far, there have been a number of classification algorithms in practice. According to (Sebastiani, 2002), the main classification algorithms can be categorized as: decision tree and rule based approach such as C4.5 (Quinlan, 1996); probability methods such as Bayesian classifier (Lewis, 1998); on-line methods such as Winnow (Littlestone, 1988) and CVFDT (Hulten 2001), neural networks methods (Rumelhart, Hinton & Wiliams, 1986); example-based methods such as k-nearest neighbors (Duda & Hart, 1973), and SVM (Cortes & Vapnik, 1995). Other important techniques for classification tasks include Associative Classification (Liu et al, 1998) and Ensemble Classification (Tumer, 1996).

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Background & Aims: An elevated transferrin saturation is the earliest phenotypic abnormality in hereditary hemochromatosis. Determination of transferrin saturation remains the most useful noninvasive screening test for affected individuals, but there is debate as to the appropriate screening level. The aims of this study were to estimate the mean transferrin saturation in hemochromatosis heterozygotes and normal individuals and to evaluate potential transferrin saturation screening levels. Methods: Statistical mixture modeling was applied to data from a survey of asymptomatic Australians to estimate the mean transferrin saturation in hemochromatosis heterozygotes and normal individuals. To evaluate potential transferrin saturation screening levels, modeling results were compared with data from identified hemochromatosis heterozygotes and homozygotes. Results: After removal of hemochromatosis homozygotes, two populations of transferrin saturation were identified in asymptomatic Australians (P < 0.01). In men, 88.2% of the truncated sample had a lower mean transferrin saturation of 24.1%, whereas 11.8% had an increased mean transferrin saturation of 37.3%. Similar results were found in women, A transferrin saturation threshold of 45% identified 98% of homozygotes without misidentifying any normal individuals. Conclusions: The results confirm that hemochromatosis heterozygotes form a distinct transferrin saturation subpopulation and support the use of transferrin saturation as an inexpensive screening test for hemochromatosis. In practice, a fasting transferrin saturation of greater than or equal to 45% identifies virtually all affected homozygous subjects without necessitating further investigation of unaffected normal individuals.

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Numerous factors affect the distribution of mangrove plants. Most mangrove species are typically dispersed by water-buoyant propagules, allowing them to lake advantage of estuarine, coastal and ocean currents both to replenish existing stands and to establish new ones. The direction they travel depends on sea currents and land barriers, but the dispersal distance depends on the time that propagules remain buoyant and viable. This is expected to differ for each species. Similarly, each species will also differ in establishment success and growth development rate, and each has tolerance limits and growth responses which are apparently unique. Such attributes are presumably responsible for the characteristic distributional ranges of each species, as each responds to the environmental, physical and biotic settings they might occupy. In practice, species are often ordered by the interplay of different factors along environmental gradients, and these may conveniently be considered at four geographic scales-global, regional, estuarine and intertidal. We believe these influencing factors act similarly around the world, and to demonstrate this point, we present examples of distributional gradients from the two global biogeographic regions, the Atlantic East Pacific and the Indo-West Pacific.

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We present the results of a spectroscopic survey of 675 bright (16.5 < b(J) < 18) galaxies in a 6 degrees field centred on the Fornax cluster with the FLAIR-II spectrograph on the UK Schmidt Telescope. Three galaxy samples were observed: compact galaxies to search for new blue compact dwarfs, candidate M 32-like compact dwarf ellipticals, and a subset of the brightest known cluster members in order to study the cluster dynamics. We measured redshifts for 516 galaxies, of which 108 were members of the Fornax Cluster. Defining dwarf galaxies to be those with b(J) greater than or equal to 15 (M-B greater than or equal to - 16.5), there are a total of 62 dwarf cluster galaxies in our sample. Nine of these are new cluster members previously misidentified as background galaxies. The cluster dynamics show that the dwarf galaxies are still falling into the cluster whereas the giants are virialized. We classified the observed galaxies as late-type if we detected H alpha emission at an equivalent width greater than 1 Angstrom. The spectra were obtained through fixed apertures, so they reflect activity in the galaxy cores, but this does not significantly bias the classifications of the compact dwarfs in our sample. The new classifications reveal a higher rate of star formation among the dwarf galaxies than suggested by morphological classification: 35 per cent have significant H alpha emission indicative of star formations but only 19 per cent were morphologically classified as late-types. The star-forming dwarf galaxies span the full range of physical sizes and we find no evidence in our data for a distinct class of star-forming blue compact dwarf (BCD) galaxy. The distribution of scale sizes is consistent with evolutionary processes which transform late-type dwarfs to early-type dwarfs. The fraction of dwarfs with active star formation drops rapidly towards the cluster centre: this is the usual density-morphology relation confirmed here for dwarf galaxies. The star-forming dwarfs are concentrated in the outer regions of the cluster, the most extreme in an infalling subcluster. We estimate gas depletion time-scales for five dwarfs with detected Hi emission: these are long (of order 10(10) yr), indicating that an active gas removal process must be involved if they are transformed into gas-poor dwarfs as they fall further into the cluster. Finally, in agreement with our previous results, we find no compact dwarf elliptical (M 32-like) galaxies in the Fornax Cluster.

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It is well known that the optimal auction-one that maximizes the seller's expected revenue-can be implemented using a standard auction format with a suitably chosen reserve price. This reserve price is above the seller's value of retaining the object and the mechanism requires a commitment not to sell the object below the reserve. This commitment is what makes the reserve valuable to the seller. However, in practice, a reserve price commits the seller to sell the object if the reserve is reached, but does not commit her to withhold the object from sale if bidding falls short of the reserve. In this note we investigate whether reserve prices remain valuable for the seller when she may negotiate with the highest bidder if the reserve is not met. We show that the value of the reserve price may be completely undermined if the seller is a sufficiently weak bargainer. (c) 2004 Elsevier B.V. All rights reserved.

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Prophylactic vaccines for genital human papillomavirus (HPV) infection have been shown to be feasible in animal models, and suitable vaccine material based on virus-like particles can be produced in bulk at reasonable cost. Initiation of phase III clinical trials will follow definition of trial outcome measures through further epidemiological studies, and development-of assays of host protective immunity. Vaccines could in principle eliminate HPV-related disease, as the human race is the only natural host for the relevant papillomaviruses (PVs). Therapeutic vaccines for genital HPV infection are also possible, but have not yet been demonstrated as feasible in practice because the choice of vaccine antigens is difficult, the method of their optimal delivery is uncertain, and the nature of the relevant antiviral immunity is unknown. PV species specificity will require trials to be conducted in man, which will slow definition of an ideal vaccine.

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The role of physiological understanding in improving the efficiency of breeding programs is examined largely from the perspective of conventional breeding programs. Impact of physiological research to date on breeding programs, and the nature of that research, was assessed from (i) responses to a questionnaire distributed to plant breeders and physiologists, and (ii) a survey of literature abstracts. Ways to better utilise physiological understanding for improving breeding programs are suggested, together with possible constraints to delivering beneficial outcomes. Responses from the questionnaire indicated a general view that the contribution by crop physiology to date has been modest. However, most of those surveyed expected the contribution to be larger in the next 20 years. Some constraints to progress perceived by breeders and physiologists were highlighted. The survey of literature abstracts indicated that from a plant breeding perspective, much physiological research is not progressing further than making suggestions about possible approaches to selection. There was limited evidence in the literature of objective comparison of such suggestions with existing methodology, or of development and application of these within active breeding programs. It is argued in this paper that the development of outputs from physiological research for breeding requires a good understanding of the breeding program(s) being serviced and factors affecting its performance. Simple quantitative genetic models, or at least the ideas they represent, should be considered in conducting physiological research and in envisaging and evaluating outputs. The key steps of a generalised breeding program are outlined, and the potential pathways for physiological understanding to impact on these steps are discussed. Impact on breeding programs may arise through (i) better choice of environments in which to conduct selection trials, (ii) identification of selection criteria and traits for focused introgression programs, and (iii) identifying traits for indirect selection criteria as an adjunct to criteria already used. While many breeders and physiologists apparently recognise that physiological understanding may have a major role in the first area, there appears to be relatively Little research activity targeting this issue, and a corresponding bias, arguably unjustified, toward examining traits for indirect selection. Furthermore, research on traits aimed at crop improvement is often deficient because key genetic parameters, such as genetic variation in relevant breeding populations and genetic (as opposed to phenotypic) correlations with yield or other characters of economic importance, are not properly considered in the research. Some areas requiring special attention for successfully interfacing physiology research with breeding are discussed. These include (i) the need to work with relevant genetic populations, (ii) close integration of the physiological research with an active breeding program, and (iii) the dangers of a pre-defined or narrow focus in the physiological research.