832 resultados para meta-programming
Resumo:
INTRODUCTION: Poststroke hyperglycemia has been associated with unfavorable outcome. Several trials investigated the use of intravenous insulin to control hyperglycemia in acute stroke. This meta-analysis summarizes all available evidence from randomized controlled trials in order to assess its efficacy and safety. METHODS: We searched PubMed until 15/02/2013 for randomized clinical trials using the following search items: 'intravenous insulin' or 'hyperglycemia', and 'stroke'. Eligible studies had to be randomized controlled trials of intravenous insulin in hyperglycemic patients with acute stroke. Analysis was performed on intention-to-treat basis using the Peto fixed-effects method. The efficacy outcomes were mortality and favorable functional outcome. The safety outcomes were mortality, any hypoglycemia (symptomatic or asymptomatic), and symptomatic hypoglycemia. RESULTS: Among 462 potentially eligible articles, nine studies with 1491 patients were included in the meta-analysis. There was no statistically significant difference in mortality between patients who were treated with intravenous insulin and controls (odds ratio: 1.16, 95% confidence interval: 0.89-1.49). Similarly, the rate of favorable functional outcome was not statistically different (odds ratio: 1.01, 95% confidence interval: 0.81-1.26). The rates of any hypoglycemia (odds ratio: 8.19, 95% confidence interval: 5.60-11.98) and of symptomatic hypoglycemia (odds ratio: 6.15, 95% confidence interval: 1.88-20.15) were higher in patients treated with intravenous insulin. There was no heterogeneity across the included trials in any of the outcomes studied. CONCLUSIONS: This meta-analysis of randomized controlled trials does not support the use of intravenous insulin in hyperglycemic stroke patients to improve mortality or functional outcome. The risk of hypoglycemia is increased, however.
Resumo:
ABSTRACT Despite the lack of randomized trials, lung metastasectomy is currently proposed for colorectal cancer patients under certain conditions. Many retrospective studies have reported different prognostic factors of poorer survival, but eligibility for pulmonary metastasectomy remains determined by the complete resection of all pulmonary metastases. The aim of this review is to clarify which pre-operative risk factors reported in systematic reviews or meta-analysis are determinant for survival in colorectal metastatic patients. Different criteria have been now identified to select which patient will really benefit from lung metastasectomy.
Resumo:
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.
Resumo:
BACKGROUND: Disease-management programs may enhance the quality of care provided to patients with chronic diseases, such as chronic obstructive pulmonary disease (COPD). The aim of this systematic review was to assess the effectiveness of COPD disease-management programs. METHODS: We conducted a computerized search of MEDLINE, EMBASE, CINAHL, PsychINFO, and the Cochrane Library (CENTRAL) for studies evaluating interventions meeting our operational definition of disease management: patient education, 2 or more different intervention components, 2 or more health care professionals actively involved in patients' care, and intervention lasting 12 months or more. Programs conducted in hospital only and those targeting patients receiving palliative care were excluded. Two reviewers evaluated 12,749 titles and fully reviewed 139 articles; among these, data from 13 studies were included and extracted. Clinical outcomes considered were all-cause mortality, lung function, exercise capacity (walking distance), health-related quality of life, symptoms, COPD exacerbations, and health care use. A meta-analysis of exercise capacity and all-cause mortality was performed using random-effects models. RESULTS: The studies included were 9 randomized controlled trials, 1 controlled trial, and 3 uncontrolled before-after trials. Results indicate that the disease-management programs studied significantly improved exercise capacity (32.2 m, 95% confidence interval [CI], 4.1-60.3), decreased risk of hospitalization, and moderately improved health-related quality of life. All-cause mortality did not differ between groups (pooled odds ratio 0.84, 95% CI, 0.54-1.40). CONCLUSION: COPD disease-management programs modestly improved exercise capacity, health-related quality of life, and hospital admissions, but not all-cause mortality. Future studies should explore the specific elements or characteristics of these programs that bring the greatest benefit.
Resumo:
PURPOSE: The aim of this study was to conduct a systematic review and perform a meta-analysis on the diagnostic performances of (18)F-fluorodeoxyglucose positron emission tomography (FDG PET) for giant cell arteritis (GCA), with or without polymyalgia rheumatica (PMR). METHODS: MEDLINE, Embase and the Cochrane Library were searched for articles in English that evaluated FDG PET in GCA or PMR. All complete studies were reviewed and qualitatively analysed. Studies that fulfilled the three following criteria were included in a meta-analysis: (1) FDG PET used as a diagnostic tool for GCA and PMR; (2) American College of Rheumatology and Healey criteria used as the reference standard for the diagnosis of GCA and PMR, respectively; and (3) the use of a control group. RESULTS: We found 14 complete articles. A smooth linear or long segmental pattern of FDG uptake in the aorta and its main branches seems to be a characteristic pattern of GCA. Vessel uptake that was superior to liver uptake was considered an efficient marker for vasculitis. The meta-analysis of six selected studies (101 vasculitis and 182 controls) provided the following results: sensitivity 0.80 [95% confidence interval (CI) 0.63-0.91], specificity 0.89 (95% CI 0.78-0.94), positive predictive value 0.85 (95% CI 0.62-0.95), negative predictive value 0.88 (95% CI 0.72-0.95), positive likelihood ratio 6.73 (95% CI 3.55-12.77), negative likelihood ratio 0.25 (95% CI 0.13-0.46) and accuracy 0.84 (95% CI 0.76-0.90). CONCLUSION: We found overall valuable diagnostic performances for FDG PET against reference criteria. Standardized FDG uptake criteria are needed to optimize these diagnostic performances.
Resumo:
OBJECTIVE To verify if the type of donor is a risk factor for infection in kidney transplant recipients. METHODS Systematic Review of Literature with Meta-analysis with searches conducted in the databases MEDLINE, LILACS, Embase, Cochrane, Web of Science, SciELO and CINAHL. RESULTS We selected 198 studies and included four observational studies describing infections among patients distinguishing the type of donor. Through meta-analysis, it was shown that in patients undergoing deceased donor transplant, the outcome infection was 2.65 higher, than those who received an organ from a living donor. CONCLUSION The study showed that deceased kidney donor recipients are at an increased risk for developing infections and so the need for establishing and enforcing protocols from proper management of ischemic time to the prevention and control of infection in this population emerges.
Resumo:
Abstract OBJECTIVE Evaluating the evidence of hypertension prevalence among indigenous populations in Brazil through a systematic review and meta-analysis. METHODS A search was performed by two reviewers, with no restriction of date or language in the databases of PubMed, LILACS, SciELO, Virtual Health Library and Capes Journal Portal. Also, a meta-regression model was designed in which the last collection year of each study was used as a moderating variable. RESULTS 23 articles were included in the review. No hypertension was found in indigenous populations in 10 studies, and its prevalence was increasing and varied, reaching levels of up to 29.7%. Combined hypertension prevalence in Indigenous from the period of 1970 to 2014 was 6.2% (95% CI, 3.1% - 10.3%). In the regression, the value of the odds ratio was 1.12 (95% CI, 1.07 - 1.18; p <0.0001), indicating a 12% increase every year in the probability of an indigenous person presenting hypertension. CONCLUSION There has been a constant increase in prevalence despite the absence of hypertension in about half of the studies, probably due to changes in cultural, economic and lifestyle habits, resulting from indigenous interaction with non-indigenous society.
Resumo:
The mathematical representation of Brunswik s lens model has been usedextensively to study human judgment and provides a unique opportunity to conduct ameta-analysis of studies that covers roughly five decades. Specifically, we analyzestatistics of the lens model equation (Tucker, 1964) associated with 259 different taskenvironments obtained from 78 papers. In short, we find on average fairly high levelsof judgmental achievement and note that people can achieve similar levels of cognitiveperformance in both noisy and predictable environments. Although overall performancevaries little between laboratory and field studies, both differ in terms of components ofperformance and types of environments (numbers of cues and redundancy). An analysisof learning studies reveals that the most effective form of feedback is information aboutthe task. We also analyze empirically when bootstrapping is more likely to occur. Weconclude by indicating shortcomings of the kinds of studies conducted to date, limitationsin the lens model methodology, and possibilities for future research.
Resumo:
Models incorporating more realistic models of customer behavior, as customers choosing froman offer set, have recently become popular in assortment optimization and revenue management.The dynamic program for these models is intractable and approximated by a deterministiclinear program called the CDLP which has an exponential number of columns. However, whenthe segment consideration sets overlap, the CDLP is difficult to solve. Column generationhas been proposed but finding an entering column has been shown to be NP-hard. In thispaper we propose a new approach called SDCP to solving CDLP based on segments and theirconsideration sets. SDCP is a relaxation of CDLP and hence forms a looser upper bound onthe dynamic program but coincides with CDLP for the case of non-overlapping segments. Ifthe number of elements in a consideration set for a segment is not very large (SDCP) can beapplied to any discrete-choice model of consumer behavior. We tighten the SDCP bound by(i) simulations, called the randomized concave programming (RCP) method, and (ii) by addingcuts to a recent compact formulation of the problem for a latent multinomial-choice model ofdemand (SBLP+). This latter approach turns out to be very effective, essentially obtainingCDLP value, and excellent revenue performance in simulations, even for overlapping segments.By formulating the problem as a separation problem, we give insight into why CDLP is easyfor the MNL with non-overlapping considerations sets and why generalizations of MNL posedifficulties. We perform numerical simulations to determine the revenue performance of all themethods on reference data sets in the literature.
Resumo:
The choice network revenue management model incorporates customer purchase behavioras a function of the offered products, and is the appropriate model for airline and hotel networkrevenue management, dynamic sales of bundles, and dynamic assortment optimization.The optimization problem is a stochastic dynamic program and is intractable. A certainty-equivalencerelaxation of the dynamic program, called the choice deterministic linear program(CDLP) is usually used to generate dyamic controls. Recently, a compact linear programmingformulation of this linear program was given for the multi-segment multinomial-logit (MNL)model of customer choice with non-overlapping consideration sets. Our objective is to obtaina tighter bound than this formulation while retaining the appealing properties of a compactlinear programming representation. To this end, it is natural to consider the affine relaxationof the dynamic program. We first show that the affine relaxation is NP-complete even for asingle-segment MNL model. Nevertheless, by analyzing the affine relaxation we derive a newcompact linear program that approximates the dynamic programming value function betterthan CDLP, provably between the CDLP value and the affine relaxation, and often comingclose to the latter in our numerical experiments. When the segment consideration sets overlap,we show that some strong equalities called product cuts developed for the CDLP remain validfor our new formulation. Finally we perform extensive numerical comparisons on the variousbounds to evaluate their performance.
Resumo:
We present a new unifying framework for investigating throughput-WIP(Work-in-Process) optimal control problems in queueing systems,based on reformulating them as linear programming (LP) problems withspecial structure: We show that if a throughput-WIP performance pairin a stochastic system satisfies the Threshold Property we introducein this paper, then we can reformulate the problem of optimizing alinear objective of throughput-WIP performance as a (semi-infinite)LP problem over a polygon with special structure (a thresholdpolygon). The strong structural properties of such polygones explainthe optimality of threshold policies for optimizing linearperformance objectives: their vertices correspond to the performancepairs of threshold policies. We analyze in this framework theversatile input-output queueing intensity control model introduced byChen and Yao (1990), obtaining a variety of new results, including (a)an exact reformulation of the control problem as an LP problem over athreshold polygon; (b) an analytical characterization of the Min WIPfunction (giving the minimum WIP level required to attain a targetthroughput level); (c) an LP Value Decomposition Theorem that relatesthe objective value under an arbitrary policy with that of a giventhreshold policy (thus revealing the LP interpretation of Chen andYao's optimality conditions); (d) diminishing returns and invarianceproperties of throughput-WIP performance, which underlie thresholdoptimality; (e) a unified treatment of the time-discounted andtime-average cases.
Resumo:
This paper introduces the approach of using Total Unduplicated Reach and Frequency analysis (TURF) to design a product line through a binary linear programming model. This improves the efficiency of the search for the solution to the problem compared to the algorithms that have been used to date. The results obtained through our exact algorithm are presented, and this method shows to be extremely efficient both in obtaining optimal solutions and in computing time for very large instances of the problem at hand. Furthermore, the proposed technique enables the model to be improved in order to overcome the main drawbacks presented by TURF analysis in practice.