997 resultados para level conversion
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BACKGROUND: The role of video-assisted thoracoscopic surgery in the treatment of pleural empyema was assessed in a consecutive series of 328 patients between 1992 and 2002. An analysis of the predicting factors for conversion thoracotomy in presumed stage II empyema was performed. METHODS: Empyema stage III with pleural thickening and signs of restriction on computer tomography imaging was treated by open decortication, whereas a thoracoscopic debridement was attempted in presumed stage II disease. Conversion thoracotomy was liberally used during thoracoscopy if stage III disease was found at surgery. Predictive factors for conversion thoracotomy were calculated in a multivariate analysis among several variables such as age, sex, time interval between onset of symptoms and surgery, involved microorganisms, and underlying cause of empyema. RESULTS: Of the 328 patients surgically treated for stage II and III empyema, 150 underwent primary open decortication for presumed stage III disease. One hundred seventy-eight patients with presumed stage II empyema underwent a video-assisted thoracoscopic approach. Of these 178 patients, thoracoscopic debridement was successful in 99 of 178 patients (56%), and conversion thoracotomy and open decortication was judged necessary in 79 of 178 patients (44%). The conversion thoracotomy rate was higher in parapneumonic empyema (55%) as compared with posttraumatic (32%) or postoperative (29%) empyema; however, delayed referral (p < 0.0001) and gram-negative microorganisms (p < 0.01) were the only significant predictors for conversion thoracotomy in a multivariate analysis. CONCLUSIONS: Video-assisted thoracoscopic debridement offers an elegant, minimally invasive approach in a number of patients with presumed stage II empyema. However, to achieve a high success rate with the video-assisted thoracoscopic approach, early referral of the patients to surgery is required. Conversion thoracotomy should be liberally used in case of chronicity, especially after delayed referral (> 2 weeks) and in the presence of gram-negative organisms.
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We propose an edge detector based on the selection of wellcontrasted pieces of level lines, following the proposal ofDesolneux-Moisan-Morel (DMM) [1]. The DMM edge detectorhas the problem of over-representation, that is, everyedge is detected several times in slightly different positions.In this paper we propose two modifications of the originalDMM edge detector in order to solve this problem. The firstmodification is a post-processing of the output using a generalmethod to select the best representative of a bundle of curves.The second modification is the use of Canny’s edge detectorinstead of the norm of the gradient to build the statistics. Thetwo modifications are independent and can be applied separately.Elementary reasoning and some experiments showthat the best results are obtained when both modifications areapplied together.
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This paper presents a detailed report of the representative farm analysis (summarized in FAPRI Policy Working Paper #01-00). At the request of several members of the Committee on Agriculture, Nutrition, and Forestry of the U.S. Senate, we have continued to analyze the impacts of the Farmers’ Risk Management Act of 1999 (S. 1666) and the Risk Management for the 21st Century Act (S. 1580). Earlier analysis reported in FAPRI Policy Working Paper #04-99 concentrated on the aggregate net farm income and government outlay impacts. The representative farm analysis is conducted for several types of farms, including both irrigated and non-irrigated cotton farms in Tom Green County, Texas; dryland wheat farms in Morton County, North Dakota and Sumner County, Kansas; and a corn farm in Webster County, Iowa. We consider additional factors that may shed light on the differential impacts of the two plans. 1. Farm-level income impacts under alternative weather scenarios. 2. Additional indirect impacts, such as a change in ability to obtain financing. 3. Implications of within-year price shocks. Our results indicate that farmers who buy crop insurance will increase their coverage levels under S. 1580. Farmers with high yield risk find that the 65 percent coverage level maximizes expected returns, but some who feel that they obtain other benefits from higher coverage will find that the S. 1580 subsidy schedule significantly lowers the cost of obtaining the additional coverage. Farmers with lower yield risk find that the increased indemnities from additional coverage will more than offset the increase in producer premium. In addition, because S. 1580 extends its increased premium subsidy percentages to revenue insurance products, farmers will have an increased incentive to buy revenue insurance. Differences in the ancillary benefits from crop insurance under the baseline and S. 1580 would be driven by the increase in insurance participation and buy-up. Given the same levels of insurance participation and buy-up, the ancillary benefits under the two scenarios would be the same.
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BACKGROUND & AIMS: In the last decade, pegylated interferon-α (PegIFN-α) plus ribavirin (RBV) was the standard treatment of chronic hepatitis C for genotype 1, and it remains the standard for genotypes 2 and 3. Recent studies reported associations between RBV-induced anemia and genetic polymorphisms of concentrative nucleoside transporters such as CNT3 (encoded by SLC28A3) and inosine triphosphatase (encoded by ITPA). We aimed at studying genetic determinants of RBV kinetics, efficacy and treatment-associated anemia. METHODS: We included 216 patients from two Swiss study cohorts (61% HCV genotype 1, 39% genotypes 2 or 3). Patients were analyzed for SLC28A2 single nucleotide polymorphism (SNP) rs11854484, SLC28A3 rs56350726, and SLC28A3 rs10868138 as well as ITPA SNPs rs1127354 and rs7270101, and followed for treatment-associated hemoglobin changes and sustained virological response (SVR). In 67 patients, RBV serum levels were additionally measured during treatment. RESULTS: Patients with SLC28A2 rs11854484 genotype TT had higher dosage- and body weight-adjusted RBV levels than those with genotypes TC or CC (p=0.02 and p=0.06 at weeks 4 and 8, respectively). ITPA SNP rs1127354 was associated with hemoglobin drop ≥3 g/dl during treatment, in genotype (relative risk (RR)=2.1, 95% CI 1.3-3.5) as well as allelic analyses (RR=2.0, 95%CI 1.2-3.4). SLC28A3 rs56350726 was associated with SVR in genotype (RR=2.2; 95% CI 1.1-4.3) as well as allelic analyses (RR=2.0, 95% CI 1.1-3.4). CONCLUSIONS: The newly identified association between RBV serum levels and SLC28A2 rs11854484 genotype, as well as the replicated association of ITPA and SLC28A3 genetic polymorphisms with RBV-induced anemia and treatment response, may support individualized treatment of chronic hepatitis C and warrant further investigation in larger studies.
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Imatinib is the standard of care for patients with advanced metastatic gastrointestinal stromal tumors (GIST), and is also approved for adjuvant treatment in patients at substantial risk of relapse. Studies have shown that maximizing benefit from imatinib depends on long-term administration at recommended doses. Pharmacokinetic (PK) and pharmacodynamic factors, adherence, and drug-drug interactions can affect exposure to imatinib and impact clinical outcomes. This article reviews the relevance of these factors to imatinib's clinical activity and response in the context of what has been demonstrated in chronic myelogenous leukemia (CML), and in light of new data correlating imatinib exposure to response in patients with GIST. Because of the wide inter-patient variability in drug exposure with imatinib in both CML and GIST, blood level testing (BLT) may play a role in investigating instances of suboptimal response, unusually severe toxicities, drug-drug interactions, and suspected non-adherence. Published clinical data in CML and in GIST were considered, including data from a PK substudy of the B2222 trial correlating imatinib blood levels with clinical responses in patients with GIST. Imatinib trough plasma levels <1100ng/mL were associated with lower rates of objective response and faster development of progressive disease in patients with GIST. These findings have been supported by other analyses correlating free imatinib (unbound) levels with response. These results suggest a future application for imatinib BLT in predicting and optimizing therapeutic response. Nevertheless, early estimates of threshold imatinib blood levels must be confirmed prospectively in future studies and elaborated for different patient subgroups.
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BACKGROUND: Early diagnosis of postoperative orthopaedic infections is important in order to rapidly initiate adequate antimicrobial therapy. There are currently no reliable diagnostic markers to differentiate infectious from noninfectious causes of postoperative fever. We investigated the value of the serum procalcitonin level in febrile patients after orthopaedic surgery. METHODS: We prospectively evaluated 103 consecutive patients with new onset of fever within ten days after orthopaedic surgery. Fever episodes were classified by two independent investigators who were blinded to procalcitonin results as infectious or noninfectious origin. White blood-cell count, C-reactive protein level, and procalcitonin level were assessed on days 0, 1, and 3 of the postoperative fever. RESULTS: Infection was diagnosed in forty-five (44%) of 103 patients and involved the respiratory tract (eighteen patients), urinary tract (eighteen), joints (four), surgical site (two), bloodstream (two), and soft tissues (one). Unlike C-reactive protein levels and white blood-cell counts, procalcitonin values were significantly higher in patients with infection compared with patients without infection on the day of fever onset (p = 0.04), day 1 (p = 0.07), and day 3 (p = 0.003). Receiver-operating characteristics demonstrated that procalcitonin had the highest diagnostic accuracy, with a value of 0.62, 0.62, and 0.71 on days 0, 1, and 3, respectively. In a multivariate logistic regression analysis, procalcitonin was a significant predictor for postoperative infection on days 0, 1, and 3 of fever with an odds ratio of 2.3 (95% confidence interval, 1.1 to 4.4), 2.3 (95% confidence interval, 1.1 to 5.2), and 3.3 (95% confidence interval, 1.2 to 9.0), respectively. CONCLUSIONS: Serum procalcitonin is a helpful diagnostic marker supporting clinical and microbiological findings for more reliable differentiation of infectious from noninfectious causes of fever after orthopaedic surgery.
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BACKGROUND: Cardiovascular diseases (CVD) cause 1.8 million premature (<75 years) death annually in Europe. The majority of these deaths are preventable with the most efficient and cost-effective approach being on the population level. The aim of this position paper is to assist authorities in selecting the most adequate management strategies to prevent CVD. DESIGN AND METHODS: Experts reviewed and summarized the published evidence on the major modifiable CVD risk factors: food, physical inactivity, smoking, and alcohol. Population-based preventive strategies focus on fiscal measures (e.g. taxation), national and regional policies (e.g. smoke-free legislation), and environmental changes (e.g. availability of alcohol). RESULTS: Food is a complex area, but several strategies can be effective in increasing fruit and vegetables and lowering intake of salt, saturated fat, trans-fats, and free sugars. Tobacco and alcohol can be regulated mainly by fiscal measures and national policies, but local availability also plays a role. Changes in national policies and the built environment will integrate physical activity into daily life. CONCLUSION: Societal changes and commercial influences have led to the present unhealthy environment, in which default option in life style increases CVD risk. A challenge for both central and local authorities is, therefore, to ensure healthier defaults. This position paper summarizes the evidence and recommends a number of structural strategies at international, national, and regional levels that in combination can substantially reduce CVD.
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Meta-analysis of genome-wide association studies (GWASs) has led to the discoveries of many common variants associated with complex human diseases. There is a growing recognition that identifying "causal" rare variants also requires large-scale meta-analysis. The fact that association tests with rare variants are performed at the gene level rather than at the variant level poses unprecedented challenges in the meta-analysis. First, different studies may adopt different gene-level tests, so the results are not compatible. Second, gene-level tests require multivariate statistics (i.e., components of the test statistic and their covariance matrix), which are difficult to obtain. To overcome these challenges, we propose to perform gene-level tests for rare variants by combining the results of single-variant analysis (i.e., p values of association tests and effect estimates) from participating studies. This simple strategy is possible because of an insight that multivariate statistics can be recovered from single-variant statistics, together with the correlation matrix of the single-variant test statistics, which can be estimated from one of the participating studies or from a publicly available database. We show both theoretically and numerically that the proposed meta-analysis approach provides accurate control of the type I error and is as powerful as joint analysis of individual participant data. This approach accommodates any disease phenotype and any study design and produces all commonly used gene-level tests. An application to the GWAS summary results of the Genetic Investigation of ANthropometric Traits (GIANT) consortium reveals rare and low-frequency variants associated with human height. The relevant software is freely available.
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Objective To analyze innovative contents on Early Child Development Promotion. Method This action-research involves nine faculties from four Higher Education Institutions at inner-state of São Paulo, Brazil.Data were collected by syllabi analyses (2009-2011), interviews and focus group. We have adopted an ECDP underpinning from international consensus, thus evaluating KT Results We have found relevant incorporation between teaching and extension in Nursing (87,5%) and Psychology (75%) undergraduate courses, while Pedagogy was restricted to teaching. Conclusion This KT evaluation has evinced innovative potential of extension, regardless teaching and research, for a better Early Childhood.
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Mountain ranges are biodiversity hotspots worldwide and provide refuge to many organisms under contemporary climate change. Gathering field information on mountain biodiversity over time is of primary importance to understand the response of biotic communities to climate changes. For plants, several long-term observation sites and networks of mountain biodiversity are emerging worldwide to gather field data and monitor altitudinal range shifts and community composition changes under contemporary climate change. Most of these monitoring sites, however, focus on alpine ecosystems and mountain summits, such as the global observation research initiative in alpine environments (GLORIA). Here we describe the Alps Vegetation Database, a comprehensive community level archive (GIVD ID EU-00-014) which aims at compiling all available geo-referenced vegetation plots from lowland forests to alpine grasslands across the greatest mountain range in Europe: the Alps. This research initiative was funded between 2008 and 2011 by the Danish Council for Independent Research and was part of a larger project to compare cross-scale plant community structure between the Alps and the Scandes. The Alps Vegetation Database currently harbours 35,731 geo-referenced vegetation plots and 5,023 valid taxa across Mediterranean, temperate and alpine environments. The data are mainly used by the main contributors of the Alps Vegetation Database in an ecoinformatics approach to test hypotheses related to plant macroecology and biogeography, but external proposals for joint collaborations are welcome.
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In cooperative multiagent systems, agents interac to solve tasks. Global dynamics of multiagent teams result from local agent interactions, and are complex and difficult to predict. Evolutionary computation has proven a promising approach to the design of such teams. The majority of current studies use teams composed of agents with identical control rules ("geneti- cally homogeneous teams") and select behavior at the team level ("team-level selection"). Here we extend current approaches to include four combinations of genetic team composition and level of selection. We compare the performance of genetically homo- geneous teams evolved with individual-level selection, genetically homogeneous teams evolved with team-level selection, genetically heterogeneous teams evolved with individual-level selection, and genetically heterogeneous teams evolved with team-level selection. We use a simulated foraging task to show that the optimal combination depends on the amount of cooperation required by the task. Accordingly, we distinguish between three types of cooperative tasks and suggest guidelines for the optimal choice of genetic team composition and level of selection