12 research outputs found

    All Roads Lead to Rome: Results of Non-Invasive Respiratory Therapies Applied in a Tertiary-Care Hospital Without an Intermediate Care Unit During the COVID-19 Pandemic

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    Introducción. Las terapias respiratorias no invasivas (TRNI) fueron ampliamente utilizadas en la primera ola de la pandemia de COVID-19, en escenarios distintos según los medios disponibles. El objetivo fue presentar la supervivencia a 90 días y los factores asociados a esta de los pacientes tratados con TRNI en un centro de tercer nivel sin Unidad de Cuidados Respiratorios Intermedios. Como objetivo secundario comparar los resultados obtenidos de las distintas terapias. Métodos. Estudio observacional de pacientes tratados con TRNI fuera de un ambiente de Cuidados Intensivos o Unidad de Cuidados Respiratorios Intermedios, diagnosticados de COVID-19 y con síndrome de distrés respiratorio agudo por criterios radiológicos y de ratio SpO2/FiO2. Se desarrolló un modelo multivariante de regresión logística para determinar las variables independientemente asociadas, y se compararon los resultados de la terapia de alto flujo con cánula nasal y la presión positiva continua en la vía aérea. Resultados. Se trataron 107 pacientes y sobrevivieron 85 (79,4%) a los 90 días. Antes de iniciar la TRNI el ratio medio de SpO2/FiO2 fue de 119,8±59,4. Un mayor score de SOFA se asoció significativamente a la mortalidad (OR 2,09; IC95% 1,34 – 3,27), mientras que la autopronación fue un factor protector (OR 0,23; IC95% 0,06 – 0,91). La terapia de alto flujo con cánula nasal fue utilizada en 63 sujetos (58,9%), y la presión positiva continua en la vía aérea en 41 (38,3%). No se encontraron diferencias entre ellas. Conclusión. Aproximadamente cuatro de cada cinco pacientes tratados con TRNI sobrevivieron a los 90 días, y no se encontraron diferencias significativas entre la terapia de alto flujo con cánula nasal y la presión positiva continua en la vía aérea.S

    Biomarkers for dementia in Latin American countries : gaps and opportunities

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    Limited knowledge on dementia biomarkers in Latin American and Caribbean (LAC) countries remains a serious barrier. Here, we report on the results from an online survey completed by dementia specialists from LAC. It aims to explore the ongoing work, needs, interests, potential barriers, and opportunities for future studies related to biomarkers. The survey was answered by 48 respondents from 10 LAC countries. The results show that neuroimaging is the most commonly used biomarker (73%), followed by genetic studies (40%), peripheral fluids biomarkers (31%) and cerebrospinal fluid biomarkers (29%). Regarding barriers in LAC, we identified that lack of funding appears to undermine the implementation of biomarkers in clinical or research settings, followed by insufficient infrastructure and training. The survey revealed that despite the above barriers, the region holds a great potential to advance dementia biomarkers research as the majority of respondents share an interest in the topic, would like to host studies, and confirmed access to unique populations. Considering the unique contributions that LAC could make to this growing field, we highlight the urgent need to introduce and expand biomarker research and suggest strategies to accelerate such developments. These insights allowed us to propose an action plan that addresses the recommendations towards a biomarker framework recently proposed by regional experts

    Biomarkers for dementia in Latin American countries: Gaps and opportunities

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    Limited knowledge on dementia biomarkers in Latin American and Caribbean (LAC) countries remains a serious barrier. Here, we reported a survey to explore the ongoing work, needs, interests, potential barriers, and opportunities for future studies related to biomarkers. The results show that neuroimaging is the most used biomarker (73%), followed by genetic studies (40%), peripheral fluids biomarkers (31%), and cerebrospinal fluid biomarkers (29%). Regarding barriers in LAC, lack of funding appears to undermine the implementation of biomarkers in clinical or research settings, followed by insufficient infrastructure and training. The survey revealed that despite the above barriers, the region holds a great potential to advance dementia biomarkers research. Considering the unique contributions that LAC could make to this growing field, we highlight the urgent need to expand biomarker research. These insights allowed us to propose an action plan that addresses the recommendations for a biomarker framework recently proposed by regional experts

    Effects of pre-operative isolation on postoperative pulmonary complications after elective surgery: an international prospective cohort study

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    Reconstruction of interactions in the ProtoDUNE-SP detector with Pandora

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    International audienceThe Pandora Software Development Kit and algorithm libraries provide pattern-recognition logic essential to the reconstruction of particle interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at ProtoDUNE-SP, a prototype for the Deep Underground Neutrino Experiment far detector. ProtoDUNE-SP, located at CERN, is exposed to a charged-particle test beam. This paper gives an overview of the Pandora reconstruction algorithms and how they have been tailored for use at ProtoDUNE-SP. In complex events with numerous cosmic-ray and beam background particles, the simulated reconstruction and identification efficiency for triggered test-beam particles is above 80% for the majority of particle type and beam momentum combinations. Specifically, simulated 1 GeV/cc charged pions and protons are correctly reconstructed and identified with efficiencies of 86.1±0.6\pm0.6% and 84.1±0.6\pm0.6%, respectively. The efficiencies measured for test-beam data are shown to be within 5% of those predicted by the simulation

    Reconstruction of interactions in the ProtoDUNE-SP detector with Pandora

    No full text
    International audienceThe Pandora Software Development Kit and algorithm libraries provide pattern-recognition logic essential to the reconstruction of particle interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at ProtoDUNE-SP, a prototype for the Deep Underground Neutrino Experiment far detector. ProtoDUNE-SP, located at CERN, is exposed to a charged-particle test beam. This paper gives an overview of the Pandora reconstruction algorithms and how they have been tailored for use at ProtoDUNE-SP. In complex events with numerous cosmic-ray and beam background particles, the simulated reconstruction and identification efficiency for triggered test-beam particles is above 80% for the majority of particle type and beam momentum combinations. Specifically, simulated 1 GeV/cc charged pions and protons are correctly reconstructed and identified with efficiencies of 86.1±0.6\pm0.6% and 84.1±0.6\pm0.6%, respectively. The efficiencies measured for test-beam data are shown to be within 5% of those predicted by the simulation

    Reconstruction of interactions in the ProtoDUNE-SP detector with Pandora

    No full text
    International audienceThe Pandora Software Development Kit and algorithm libraries provide pattern-recognition logic essential to the reconstruction of particle interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at ProtoDUNE-SP, a prototype for the Deep Underground Neutrino Experiment far detector. ProtoDUNE-SP, located at CERN, is exposed to a charged-particle test beam. This paper gives an overview of the Pandora reconstruction algorithms and how they have been tailored for use at ProtoDUNE-SP. In complex events with numerous cosmic-ray and beam background particles, the simulated reconstruction and identification efficiency for triggered test-beam particles is above 80% for the majority of particle type and beam momentum combinations. Specifically, simulated 1 GeV/cc charged pions and protons are correctly reconstructed and identified with efficiencies of 86.1±0.6\pm0.6% and 84.1±0.6\pm0.6%, respectively. The efficiencies measured for test-beam data are shown to be within 5% of those predicted by the simulation

    Reconstruction of interactions in the ProtoDUNE-SP detector with Pandora

    No full text
    International audienceThe Pandora Software Development Kit and algorithm libraries provide pattern-recognition logic essential to the reconstruction of particle interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at ProtoDUNE-SP, a prototype for the Deep Underground Neutrino Experiment far detector. ProtoDUNE-SP, located at CERN, is exposed to a charged-particle test beam. This paper gives an overview of the Pandora reconstruction algorithms and how they have been tailored for use at ProtoDUNE-SP. In complex events with numerous cosmic-ray and beam background particles, the simulated reconstruction and identification efficiency for triggered test-beam particles is above 80% for the majority of particle type and beam momentum combinations. Specifically, simulated 1 GeV/cc charged pions and protons are correctly reconstructed and identified with efficiencies of 86.1±0.6\pm0.6% and 84.1±0.6\pm0.6%, respectively. The efficiencies measured for test-beam data are shown to be within 5% of those predicted by the simulation
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