9 research outputs found

    ¿Es necesario disponer de ECMO para reparar cardiopatías congénitas de complejidad elevada? Nuestra experiencia en los últimos 6 años

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    Introducción y objetivos: La ECMO puede contribuir a optimizar los resultados quirúrgicos de la reparación de cardiopatías congénitas complejas. El objetivo es analizar la morbilidad asociada al procedimiento y los factores de riesgo de mortalidad en pacientes que se les implanta una ECMO poscardiotomía. Métodos: Revisión retrospectiva de pacientes que requirieron ECMO tras reparación quirúrgica de cardiopatías congénitas entre marzo del 2010 y marzo del 2016. Resultados: Treinta pacientes precisaron ECMO tras cirugía reparadora. Los diagnósticos más frecuentes fueron: transposición de grandes arterias, Fallot y postrasplante. La mediana de edad fue 5 meses (7 días-20 años) y la de peso 5 kg (2-92 kg). En 22 (73%) pacientes se implantó ECMO en quirófano por imposibilidad de retirar circulación extracorpórea. En 8 (26%) se implantó en la unidad de intensivos, 6 de ellos por bajo gasto cardiaco y 2 por pésima oxigenación. En pacientes con fisiología de origen biventricular la supervivencia fue del 60% y con fisiología univentricular, del 40%. En 20 (67%) se pudo retirar la ECMO, de los cuales 16 sobrevivieron. Supervivencia global: 53%. Factores de riesgo de mortalidad: fallo renal, ECMO más de 5 días, láctico > 5 (previo ECMO), pH < 7,35 (previo ECMO) y sepsis. La reintervención por sangrado no se relacionó con mortalidad. Tiempo medio de seguimiento: 23 meses, sin fallecimiento durante este periodo. Conclusiones: Creemos que actualmente es necesario disponer de la ECMO en el postoperatorio de los pacientes intervenidos de cardiopatías congénitas, dado que parece asociarse a un beneficio en términos de supervivencia

    Freeze-out radii extracted from three-pion cumulants in pp, p–Pb and Pb–Pb collisions at the LHC

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    In high-energy collisions, the spatio-temporal size of the particle production region can be measured using the Bose-Einstein correlations of identical bosons at low relative momentum. The source radii are typically extracted using two-pion correlations, and characterize the system at the last stage of interaction, called kinetic freeze-out. In low-multiplicity collisions, unlike in high-multiplicity collisions, two-pion correlations are substantially altered by background correlations, e.g. mini-jets. Such correlations can be suppressed using three-pion cumulant correlations. We present the first measurements of the size of the system at freeze-out extracted from three-pion cumulant correlations in pp, p-Pb and Pb-Pb collisions at the LHC with ALICE. At similar multiplicity, the invariant radii extracted in p-Pb collisions are found to be 5-15% larger than those in pp, while those in Pb-Pb are 35-55% larger than those in p-Pb. Our measurements disfavor models which incorporate substantially stronger collective expansion in p-Pb as compared to pp collisions at similar multiplicity

    Multiplicity dependence of jet-like two-particle correlation structures in p–Pb collisions at √sNN=5.02 TeV

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    Two-particle angular correlations between unidentified charged trigger and associated particles are measured by the ALICE detector in p–Pb collisions at a nucleon–nucleon centre-of-mass energy of 5.02 TeV. The transverse-momentum range 0.7 < pT,assoc < pT,trig < 5.0 GeV/c is examined, to include correlations induced by jets originating from low momentum-transfer scatterings (minijets). The correlations expressed as associated yield per trigger particle are obtained in the pseudorapidity range |η| < 0.9. The near-side long-range pseudorapidity correlations observed in high-multiplicity p–Pb collisions are subtracted from both near-side short-range and away-side correlations in order to remove the non-jet-like components. The yields in the jet-like peaks are found to be invariant with event multiplicity with the exception of events with low multiplicity. This invariance is consistent with the particles being produced via the incoherent fragmentation of multiple parton–parton scatterings, while the yield related to the previously observed ridge structures is not jet-related. The number of uncorrelated sources of particle production is found to increase linearly with multiplicity, suggesting no saturation of the number of multi-parton interactions even in the highest multiplicity p–Pb collisions. Further, the number scales only in the intermediate multiplicity region with the number of binary nucleon–nucleon collisions estimated with a Glauber Monte-Carlo simulation

    Beauty production in pp collisions at √s=2.76 TeV measured via semi-electronic decays

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    The ALICE Collaboration at the LHC reports measurement of the inclusive production cross section of electrons from semi-leptonic decays of beauty hadrons with rapidity |y| < 0.8 and transverse momentum 1 < pT < 10 GeV/c, in pp collisions at √s = 2.76 TeV. Electrons not originating from semi-electronic decay of beauty hadrons are suppressed using the impact parameter of the corresponding tracks. The production cross section of beauty decay electrons is compared to the result obtained with an alternative method which uses the distribution of the azimuthal angle between heavy-flavour decay electrons and charged hadrons. Perturbative QCD predictions agree with the measured cross section within the experimental and theoretical uncertainties. The integrated visible cross section, σb→e = 3.47 ± 0.40(stat) +1.12 −1.33(sys) ± 0.07(norm) μb, was extrapolated to full phase space using Fixed Order plus Next-to-Leading Log (FONLL) calculations to obtain the total bb production ¯ cross section, σbb¯ = 130 ± 15.1(stat) +42.1 −49.8(sys) +3.4 −3.1(extr) ± 2.5(norm) ± 4.4(BR) μb

    Production of charged pions, kaons and protons at large transverse momenta in pp and Pb–Pb collisions at √sNN = 2.76 TeV

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    Transverse momentum spectra of π±, K± and p(p¯) up to pT = 20 GeV/c at mid-rapidity in pp, peripheral (60–80%) and central (0–5%) Pb–Pb collisions at √sNN = 2.76 TeV have been measured using the ALICE detector at the Large Hadron Collider. The proton-to-pion and the kaon-to-pion ratios both show a distinct peak at pT ≈ 3 GeV/c in central Pb–Pb collisions. Below the peak, pT 10 GeV/c particle ratios in pp and Pb–Pb collisions are in agreement and the nuclear modification factors for π±, K± and p(p¯) indicate that, within the systematic and statistical uncertainties, the suppression is the same. This suggests that the chemical composition of leading particles from jets in the medium is similar to that of vacuum jets

    Freeze-out radii extracted from three-pion cumulants in pp, p–Pb and Pb–Pb collisions at the LHC

    No full text
    In high-energy collisions, the spatio-temporal size of the particle production region can be measured using the Bose–Einstein correlations of identical bosons at low relative momentum. The source radii are typically extracted using two-pion correlations, and characterize the system at the last stage of interaction, called kinetic freeze-out. In low-multiplicity collisions, unlike in high-multiplicity collisions, two-pion correlations are substantially altered by background correlations, e.g. mini-jets. Such correlations can be suppressed using three-pion cumulant correlations. We present the first measurements of the size of the system at freeze-out extracted from three-pion cumulant correlations in pp, p–Pb and Pb–Pb collisions at the LHC with ALICE. At similar multiplicity, the invariant radii extracted in p–Pb collisions are found to be 5–15% larger than those in pp, while those in Pb–Pb are 35–55% larger than those in p–Pb. Our measurements disfavor models which incorporate substantially stronger collective expansion in p–Pb as compared to pp collisions at similar multiplicity

    Measurement of charged jet suppression in Pb-Pb collisions at √sNN = 2.76 TeV

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    A measurement of the transverse momentum spectra of jets in Pb-Pb collisions at sNN−−−√=2.76 TeV is reported. Jets are reconstructed from charged particles using the anti-kT jet algorithm with jet resolution parameters R of 0.2 and 0.3 in pseudo-rapidity |η|<0.5. The transverse momentum pT of charged particles is measured down to 0.15 GeV/c which gives access to the low pT fragments of the jet. Jets found in heavy-ion collisions are corrected event-by-event for average background density and on an inclusive basis (via unfolding) for residual background fluctuations and detector effects. A strong suppression of jet production in central events with respect to peripheral events is observed. The suppression is found to be similar to the suppression of charged hadrons, which suggests that substantial energy is radiated at angles larger than the jet resolution parameter R=0.3 considered in the analysis. The fragmentation bias introduced by selecting jets with a high pT leading particle, which rejects jets with a soft fragmentation pattern, has a similar effect on the jet yield for central and peripheral events. The ratio of jet spectra with R=0.2 and R=0.3 is found to be similar in Pb-Pb and simulated PYTHIA pp events, indicating no strong broadening of the radial jet structure in the reconstructed jets with R<0.3.

    The value of open-source clinical science in pandemic response: lessons from ISARIC

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    ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19

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    The International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) COVID-19 dataset is one of the largest international databases of prospectively collected clinical data on people hospitalized with COVID-19. This dataset was compiled during the COVID-19 pandemic by a network of hospitals that collect data using the ISARIC-World Health Organization Clinical Characterization Protocol and data tools. The database includes data from more than 705,000 patients, collected in more than 60 countries and 1,500 centres worldwide. Patient data are available from acute hospital admissions with COVID-19 and outpatient follow-ups. The data include signs and symptoms, pre-existing comorbidities, vital signs, chronic and acute treatments, complications, dates of hospitalization and discharge, mortality, viral strains, vaccination status, and other data. Here, we present the dataset characteristics, explain its architecture and how to gain access, and provide tools to facilitate its use
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