450 research outputs found

    The development and application of a new tool to assess the adequacy of the content and timing of antenatal care

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    Abstract Background: Current measures of antenatal care use are limited to initiation of care and number of visits. This study aimed to describe the development and application of a tool to assess the adequacy of the content and timing of antenatal care. Methods: The Content and Timing of care in Pregnancy (CTP) tool was developed based on clinical relevance for ongoing antenatal care and recommendations in national and international guidelines. The tool reflects minimal care recommended in every pregnancy, regardless of parity or risk status. CTP measures timing of initiation of care, content of care (number of blood pressure readings, blood tests and ultrasound scans) and whether the interventions were received at an appropriate time. Antenatal care trajectories for 333 pregnant women were then described using a standard tool (the APNCU index), that measures the quantity of care only, and the new CTP tool. Both tools categorise care into 4 categories, from ‘Inadequate’ (both tools) to ‘Adequate plus’ (APNCU) or ‘Appropriate’ (CTP). Participants recorded the timing and content of their antenatal care prospectively using diaries. Analysis included an examination of similarities and differences in categorisation of care episodes between the tools. Results: According to the CTP tool, the care trajectory of 10,2% of the women was classified as inadequate, 8,4% as intermediate, 36% as sufficient and 45,3% as appropriate. The assessment of quality of care differed significantly between the two tools. Seventeen care trajectories classified as ‘Adequate’ or ‘Adequate plus’ by the APNCU were deemed ‘Inadequate’ by the CTP. This suggests that, despite a high number of visits, these women did not receive the minimal recommended content and timing of care. Conclusions: The CTP tool provides a more detailed assessment of the adequacy of antenatal care than the current standard index. However, guidelines for the content of antenatal care vary, and the tool does not at the moment grade over-use of interventions as ‘Inappropriate’. Further work needs to be done to refine the content items prior to larger scale testing of the impact of the new measure

    Late entry to antenatal care in New South Wales, Australia

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    AIMS: This study aimed to assess the prevalence of women who entered antenatal care (ANC) late and to identify factors related to the late entry to ANC in New South Wales (NSW) in 2004. METHODS: The NSW Midwives Data Collection contained data of 85,034 women who gave birth in 2004. Data were downloaded using SAS and transferred to STATA 8.0. Entering ANC after 12 weeks of gestation was classified as late. The Andersen Health Seeking Behaviour Model was used for selection and analyses of related factors. Regression and hierarchical analyses were used to identify significant factors and their relative contributions to the variation of pregnancy duration at entry to ANC. RESULTS: 41% of women commenced ANC after 12 weeks of gestation. Inequality existed between groups of women with predisposing characteristics and enabling resources contributed more to the variation in pregnancy duration at entry to ANC than needs. The groups of women with highest risk were teenagers, migrants from developing countries, women living in Western Sydney, Aboriginal and Torres Strait Islanders, women with three or more previous pregnancies and heavy smokers. The high risk groups with largest number of women were migrants from developing countries and women living in Western Sydney. CONCLUSION: A large number of women in NSW entered ANC late in their pregnancies. Efforts to increase early entry to ANC should be targeted on identified high risk groups of women

    Performance of CMS muon reconstruction in pp collision events at sqrt(s) = 7 TeV

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    The performance of muon reconstruction, identification, and triggering in CMS has been studied using 40 inverse picobarns of data collected in pp collisions at sqrt(s) = 7 TeV at the LHC in 2010. A few benchmark sets of selection criteria covering a wide range of physics analysis needs have been examined. For all considered selections, the efficiency to reconstruct and identify a muon with a transverse momentum pT larger than a few GeV is above 95% over the whole region of pseudorapidity covered by the CMS muon system, abs(eta) < 2.4, while the probability to misidentify a hadron as a muon is well below 1%. The efficiency to trigger on single muons with pT above a few GeV is higher than 90% over the full eta range, and typically substantially better. The overall momentum scale is measured to a precision of 0.2% with muons from Z decays. The transverse momentum resolution varies from 1% to 6% depending on pseudorapidity for muons with pT below 100 GeV and, using cosmic rays, it is shown to be better than 10% in the central region up to pT = 1 TeV. Observed distributions of all quantities are well reproduced by the Monte Carlo simulation.Comment: Replaced with published version. Added journal reference and DO

    Performance of CMS muon reconstruction in pp collision events at sqrt(s) = 7 TeV

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    The performance of muon reconstruction, identification, and triggering in CMS has been studied using 40 inverse picobarns of data collected in pp collisions at sqrt(s) = 7 TeV at the LHC in 2010. A few benchmark sets of selection criteria covering a wide range of physics analysis needs have been examined. For all considered selections, the efficiency to reconstruct and identify a muon with a transverse momentum pT larger than a few GeV is above 95% over the whole region of pseudorapidity covered by the CMS muon system, abs(eta) < 2.4, while the probability to misidentify a hadron as a muon is well below 1%. The efficiency to trigger on single muons with pT above a few GeV is higher than 90% over the full eta range, and typically substantially better. The overall momentum scale is measured to a precision of 0.2% with muons from Z decays. The transverse momentum resolution varies from 1% to 6% depending on pseudorapidity for muons with pT below 100 GeV and, using cosmic rays, it is shown to be better than 10% in the central region up to pT = 1 TeV. Observed distributions of all quantities are well reproduced by the Monte Carlo simulation.Comment: Replaced with published version. Added journal reference and DO

    Predicting P-Glycoprotein-Mediated Drug Transport Based On Support Vector Machine and Three-Dimensional Crystal Structure of P-glycoprotein

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    Human P-glycoprotein (P-gp) is an ATP-binding cassette multidrug transporter that confers resistance to a wide range of chemotherapeutic agents in cancer cells by active efflux of the drugs from cells. P-gp also plays a key role in limiting oral absorption and brain penetration and in facilitating biliary and renal elimination of structurally diverse drugs. Thus, identification of drugs or new molecular entities to be P-gp substrates is of vital importance for predicting the pharmacokinetics, efficacy, safety, or tissue levels of drugs or drug candidates. At present, publicly available, reliable in silico models predicting P-gp substrates are scarce. In this study, a support vector machine (SVM) method was developed to predict P-gp substrates and P-gp-substrate interactions, based on a training data set of 197 known P-gp substrates and non-substrates collected from the literature. We showed that the SVM method had a prediction accuracy of approximately 80% on an independent external validation data set of 32 compounds. A homology model of human P-gp based on the X-ray structure of mouse P-gp as a template has been constructed. We showed that molecular docking to the P-gp structures successfully predicted the geometry of P-gp-ligand complexes. Our SVM prediction and the molecular docking methods have been integrated into a free web server (http://pgp.althotas.com), which allows the users to predict whether a given compound is a P-gp substrate and how it binds to and interacts with P-gp. Utilization of such a web server may prove valuable for both rational drug design and screening

    The Blood Pressure "Uncertainty Range" – a pragmatic approach to overcome current diagnostic uncertainties (II)

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    A tremendous amount of scientific evidence regarding the physiology and physiopathology of high blood pressure combined with a sophisticated therapeutic arsenal is at the disposal of the medical community to counteract the overall public health burden of hypertension. Ample evidence has also been gathered from a multitude of large-scale randomized trials indicating the beneficial effects of current treatment strategies in terms of reduced hypertension-related morbidity and mortality. In spite of these impressive advances and, deeply disappointingly from a public health perspective, the real picture of hypertension management is overshadowed by widespread diagnostic inaccuracies (underdiagnosis, overdiagnosis) as well as by treatment failures generated by undertreatment, overtreatment, and misuse of medications. The scientific, medical and patient communities as well as decision-makers worldwide are striving for greatest possible health gains from available resources. A seemingly well-crystallised reasoning is that comprehensive strategic approaches must not only target hypertension as a pathological entity, but rather, take into account the wider environment in which hypertension is a major risk factor for cardiovascular disease carrying a great deal of our inheritance, and its interplay in the constellation of other, well-known, modifiable risk factors, i.e., attention is to be switched from one's "blood pressure level" to one's absolute cardiovascular risk and its determinants. Likewise, a risk/benefit assessment in each individual case is required in order to achieve best possible results. Nevertheless, it is of paramount importance to insure generalizability of ABPM use in clinical practice with the aim of improving the accuracy of a first diagnosis for both individual treatment and clinical research purposes. Widespread adoption of the method requires quick adjustment of current guidelines, development of appropriate technology infrastructure and training of staff (i.e., education, decision support, and information systems for practitioners and patients). Progress can be achieved in a few years, or in the next 25 years

    Observation of the diphoton decay of the Higgs boson and measurement of its properties

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    Peer reviewe

    Performance of CMS muon reconstruction in pp collision events at √s = 7TeV

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    arXiv:1206.4071v2.-- Chatrchyan, S. et al.The performance of muon reconstruction, identification, and triggering in CMS has been studied using 40 pb -1 of data collected in pp collisions at s = 7 TeV at the LHC in 2010. A few benchmark sets of selection criteria covering a wide range of physics analysis needs have been examined. For all considered selections, the efficiency to reconstruct and identify a muon with a transverse momentum pT larger than a few GeV/c is above 95% over the whole region of pseudorapidity covered by the CMS muon system, < 2.4, while the probability to misidentify a hadron as a muon is well below 1%. The efficiency to trigger on single muons with pT above a few GeVc is higher than 90% over the full η range, and typically substantially better. The overall momentum scale is measured to a precision of 0.2% with muons from Z decays. The transverse momentum resolution varies from 1% to 6% depending on pseudorapidity for muons with pT below 100GeV/c and, using cosmic rays, it is shown to be better than 10% in the central region up to pT = 1 TeV/c. Observed distributions of all quantities are well reproduced by the Monte Carlo simulation.This work was supported by the Austrian Federal Ministry of Science and Research; the Belgium Fonds de la Recherche Scientifique, and Fonds voor Wetenschappelijk Onderzoek; the Brazilian Funding Agencies (CNPq, CAPES, FAPERJ, and FAPESP); the Bulgarian Ministry of Education and Science; CERN; the Chinese Academy of Sciences, Ministry of Science and Technology, and National Natural Science Foundation of China; the Colombian Funding Agency (COLCIENCIAS); the Croatian Ministry of Science, Education and Sport; the Research Promotion Foundation Cyprus; the Estonian Academy of Sciences and NICPB; the Academy of Finland, Finnish Ministry of Education and Culture, and Helsinki Institute of Physics; the Institut National de Physique Nucléaire et de Physique des Particules / CNRS, and Commissariat á l'Energie Atomique et aux Energies Alternatives/CEA, France; the Bundesministerium für Bildung und Forschung, Deutsche Forschungsgemeinschaft, and Helmholtz-Gemeinschaft Deutscher Forschungszentren, Germany; the General Secretariat for Research and Technology, Greece; the National Scientific Research Foundation, and National Office for Research and Technology, Hungary; the Department of Atomic Energy and the Department of Science and Technology, India; the Institute for Studies in Theoretical Physics and Mathematics, Iran; the Science Foundation, Ireland; the Istituto Nazionale di Fisica Nucleare, Italy; the Korean Ministry of Education, Science and Technology and the World Class University program of NRF, Korea; the Lithuanian Academy of Sciences; the Mexican Funding Agencies (CINVESTAV, CONACYT, SEP, and UASLP-FAI); the Ministry of Science and Innovation, New Zealand; the Pakistan Atomic Energy Commission; the State Commission for Sci- entific Research, Poland; the Fundaçao para a Ciência e a Tecnologia, Portugal; JINR (Armenia, Belarus, Georgia, Ukraine, Uzbekistan); the Ministry of Science and Technologies of the Russian Federation, the Russian Ministry of Atomic Energy and the Russian Foundation for Basic Research; the Ministry of Science and Technological Development of Serbia; the Ministerio de Ciencia e Innovación, and Programa Consolider-Ingenio 2010, Spain; the Swiss Funding Agencies (ETH Board, ETH Zurich, PSI, SNF, UniZH, Canton Zurich, and SER); the National Science Council, Taipei; the Scientific and Technical Research Council of Turkey, and Turkish Atomic Energy Authority; the Science and Technology Facilities Council, U.K.; the US Department of Energy, and the US National Science Foundation. Individuals have received support from the Marie-Curie programme and the European Research Council (European Union); the Leventis Foundation; the A. P. Sloan Foundation; the Alexander von Humboldt Foundation; the Belgian Federal Science Policy Office; the Fonds pour la Formation à la Recherche dans l'Industrie et dans l'Agriculture (FRIA-Belgium); the Agentschap voor Innovatie door Wetenschap en Technologie (IWT-Belgium); and the Council of Science and Industrial Research, India.Peer Reviewe
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