229 research outputs found

    PCN58 IS CYP2D6 GENETIC TEST IN COMBINATION WITH HORMONE THERAPY FOR ER+ HORMONE SENSITIVE WOMEN WITH EARLY BREAST CANCER COST-EFFECTIVE?

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    PCN162 The Cost-Effectiveness of Second-Line Crizotinib in Eml4-Alk Rearranged Advanced Non-Small Cell Lung Cancer

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    Background: Snoring / sleep apnea are potentially life threatening breathing occurs during sleep. Little attention is being giving to this clinical condition. Objective: To determine the prevalence of snoring and risk factors associated with obstructive sleep apnea (OSA) among adults workers in two local governments of state, Nigeria Methodology: A cross - sectional survey of 121 young adult and adults working in two local governments of Ekiti state, south western Nigeria was carried out. A self administered questionnaire that was incorporated with Epworth Sleepiness Scale and Berlin Score was used to collect data on socio-demographic characteristics, information related to snoring, sleep related problems and their anthropometric. The Body Mass Index (BMI) and blood pressure of each participant were also measured. Results: Snoring was reported in forty nine (40.5%) of the participants. Their age ranges from 23 to 65 years, mean of 43.89 ± 8.53 SD. The proportion of males and Berlin score (high risk) were significantly (p < 0.001) higher among snores than non regression found sex (OR=7.791, 95% CI =2.971- 20.429), Berlin Score (high risk) (OR= 8.642, 95% CI= 3.159 - 23.639) as significant (P< 0.001) independent risk factors for OSA. Excessive day time sleepiness as determined by ESS score of the participants. Conclusion: The overall prevalence of snoring in this study was 40.5%. Snoring was found to increase with age, body mass index, male sex and those with high risk for Berlin score with high risk of developing Obstructive sleep apne

    Suplemento de acido fólico: ¿Prevención de anemia en prematuros?

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    Study protocol: NITric oxide during cardiopulmonary bypass to improve Recovery in Infants with Congenital heart defects (NITRIC trial): a randomised controlled trial

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    Introduction Congenital heart disease (CHD) is a major cause of infant mortality. Many infants with CHD require corrective surgery with most operations requiring cardiopulmonary bypass (CPB). CPB triggers a systemic inflammatory response which is associated with low cardiac output syndrome (LCOS), postoperative morbidity and mortality. Delivery of nitric oxide (NO) into CPB circuits can provide myocardial protection and reduce bypass-induced inflammation, leading to less LCOS and improved recovery. We hypothesised that using NO during CPB increases ventilator-free days (VFD) (the number of days patients spend alive and free from invasive mechanical ventilation up until day 28) compared with standard care. Here, we describe the NITRIC trial protocol. Methods and analysis The NITRIC trial is a randomised, double-blind, controlled, parallel-group, two-sided superiority trial to be conducted in six paediatric cardiac surgical centres. One thousand three-hundred and twenty infants <2 years of age undergoing cardiac surgery with CPB will be randomly assigned to NO at 20 ppm administered into the CPB oxygenator for the duration of CPB or standard care (no NO) in a 1:1 ratio with stratification by age (<6 and ≥6 weeks), single ventricle physiology (Y/N) and study centre. The primary outcome will be VFD to day 28. Secondary outcomes include a composite of LCOS, need for extracorporeal membrane oxygenation or death within 28 days of surgery; length of stay in intensive care and in hospital; and, healthcare costs. Analyses will be conducted on an intention-to-treat basis. Preplanned secondary analyses will investigate the impact of NO on host inflammatory profiles postsurgery. Ethics and dissemination The study has ethical approval (HREC/17/QRCH/43, dated 26 April 2017), is registered in the Australian New Zealand Clinical Trials Registry (ACTRN12617000821392) and commenced recruitment in July 2017. The primary manuscript will be submitted for publication in a peer-reviewed journal. Trial registration number ACTRN12617000821392.</p

    Ecmo-assisted carinal resection and reconstruction after left pneumonectomy

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    Extracorporeal Membrane Oxygenation (ECMO) has become an increasingly important technique for patients with respiratory or cardiac failure for a variety of causes. In addition, there are many reports about the use of ECMO in surgical operation on neonates and children patients with tracheal obstruction. In this report we present a case about an adult patient who underwent a carinal resection and reconstruction after left pneumonectomy with ECMO assistance successfully. To our knowledge, this case is the first of its kind to use ECMO in adult carinal resection and reconstruction after pneumonectomy. In this report, we try to illustrate that ECMO is effective in operations of this kind

    Large scale structure and the generalised Chaplygin gas as dark energy

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    The growth of large scale structure is studied in a universe containing both cold dark matter (CDM) and generalized Chaplygin gas (GCg). GCg is assumed to contribute only to the background evolution of the universe while the CDM component collapses and forms structures. We present some new analytical as well as numerical results for linear and non-linear growth in such model. The model passes the standard cosmological distance test without the need of a cosmological constant (LCDM). But we find that the scenario is severely constrained by current observations of large scale structure. Any small deviations of the GCg parameters away from the standard Lambda dominated cosmology (LCDM) produces substantial suppression for the growth of structures.Comment: 6 pages, matches version accepted for publication in Phys.Rev.D (in press

    Revisiting Generalized Chaplygin Gas as a Unified Dark Matter and Dark Energy Model

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    In this paper, we revisit generalized Chaplygin gas (GCG) model as a unified dark matter and dark energy model. The energy density of GCG model is given as ρGCG/ρGCG0=[Bs+(1Bs)a3(1+α)]1/(1+α)\rho_{GCG}/\rho_{GCG0}=[B_{s}+(1-B_{s})a^{-3(1+\alpha)}]^{1/(1+\alpha)}, where α\alpha and BsB_s are two model parameters which will be constrained by type Ia supernova as standard candles, baryon acoustic oscillation as standard rulers and the seventh year full WMAP data points. In this paper, we will not separate GCG into dark matter and dark energy parts any more as adopted in the literatures. By using Markov Chain Monte Carlo method, we find the result: α=0.001260.001260.00126+0.000970+0.00268\alpha=0.00126_{- 0.00126- 0.00126}^{+ 0.000970+ 0.00268} and Bs=0.7750.01610.0338+0.0161+0.0307B_s= 0.775_{- 0.0161- 0.0338}^{+ 0.0161+ 0.0307}.Comment: 6 pages, 4 figure

    Atlantic mammal traits: a dataset of morphological traits of mammals in the atlantic forest of south America

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    Measures of traits are the basis of functional biological diversity. Numerous works consider mean species-level measures of traits while ignoring individual variance within species. However, there is a large amount of variation within species and it is increasingly apparent that it is important to consider trait variation not only between species, but also within species. Mammals are an interesting group for investigating trait-based approaches because they play diverse and important ecological functions (e.g., pollination, seed dispersal, predation, grazing) that are correlated with functional traits. Here we compile a data set comprising morphological and life history information of 279 mammal species from 39,850 individuals of 388 populations ranging from −5.83 to −29.75 decimal degrees of latitude and −34.82 to −56.73 decimal degrees of longitude in the Atlantic forest of South America. We present trait information from 16,840 individuals of 181 species of non-volant mammals (Rodentia, Didelphimorphia, Carnivora, Primates, Cingulata, Artiodactyla, Pilosa, Lagomorpha, Perissodactyla) and from 23,010 individuals of 98 species of volant mammals (Chiroptera). The traits reported include body mass, age, sex, reproductive stage, as well as the geographic coordinates of sampling for all taxa. Moreover, we gathered information on forearm length for bats and body length and tail length for rodents and marsupials. No copyright restrictions are associated with the use of this data set. Please cite this data paper when the data are used in publications. We also request that researchers and teachers inform us of how they are using the data.Fil: Gonçalves, Fernando. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Bovendorp, Ricardo S.. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Beca, Gabrielle. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Bello, Carolina. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Costa Pereira, Raul. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Muylaert, Renata L.. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Rodarte, Raisa R.. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Villar, Nacho. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Souza, Rafael. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Graipel, Maurício E.. Universidade Federal de Santa Catarina; BrasilFil: Cherem, Jorge J.. Caipora Cooperativa, Florianopolis; BrasilFil: Faria, Deborah. Universidade Estadual de Santa Cruz; BrasilFil: Baumgarten, Julio. Universidade Estadual de Santa Cruz; BrasilFil: Alvarez, Martín R.. Universidade Estadual de Santa Cruz; BrasilFil: Vieira, Emerson M.. Universidade do Brasília; BrasilFil: Cáceres, Nilton. Universidade Federal de Santa María. Santa María; BrasilFil: Pardini, Renata. Universidade de Sao Paulo; BrasilFil: Leite, Yuri L. R.. Universidade Federal do Espírito Santo; BrasilFil: Costa, Leonora Pires. Universidade Federal do Espírito Santo; BrasilFil: Mello, Marco Aurelio Ribeiro. Universidade Federal de Minas Gerais; BrasilFil: Fischer, Erich. Universidade Federal do Mato Grosso do Sul; BrasilFil: Passos, Fernando C.. Universidade Federal do Paraná; BrasilFil: Varzinczak, Luiz H.. Universidade Federal do Paraná; BrasilFil: Prevedello, Jayme A.. Universidade do Estado de Rio do Janeiro; BrasilFil: Cruz-Neto, Ariovaldo P.. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Carvalho, Fernando. Universidade do Extremo Sul Catarinense; BrasilFil: Reis Percequillo, Alexandre. Universidade de Sao Paulo; BrasilFil: Paviolo, Agustin Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú; ArgentinaFil: Duarte, José M. B.. Universidade Estadual Paulista Julio de Mesquita Filho; Brasil. Fundación Oswaldo Cruz; BrasilFil: Bernard, Enrico. Universidade Federal de Pernambuco; BrasilFil: Agostini, Ilaria. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú; ArgentinaFil: Lamattina, Daniela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste; Argentina. Ministerio de Salud de la Nación; ArgentinaFil: Vanderhoeven, Ezequiel Andres. Ministerio de Salud de la Nación; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste; Argentin
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