As xoias de Regodreigón.

66 (1-2) Jan.-Jun. 1956, p. 90-96

Epidemiology, patterns of care, and mortality for patients with acute respiratory distress syndrome in intensive care units in 50 countries

IMPORTANCE: Limited information exists about the epidemiology, recognition, management, and outcomes of patients with the acute respiratory distress syndrome (ARDS). OBJECTIVES: To evaluate intensive care unit (ICU) incidence and outcome of ARDS and to assess clinician recognition, ventilation management, and use of adjuncts-for example prone positioning-in routine clinical practice for patients fulfilling the ARDS Berlin Definition. DESIGN, SETTING, AND PARTICIPANTS:The Large Observational Study to Understand the Global Impact of Severe Acute Respiratory Failure (LUNG SAFE) was an international, multicenter, prospective cohort study of patients undergoing invasive or noninvasive ventilation, conducted during 4 consecutive weeks in the winter of 2014 in a convenience sample of 459 ICUs from 50 countries across 5 continents. EXPOSURES:Acute respiratory distress syndrome. MAIN OUTCOMES AND MEASURES: The primary outcome was ICU incidence of ARDS. Secondary outcomes included assessment of clinician recognition of ARDS, the application of ventilatory management, the use of adjunctive interventions in routine clinical practice, and clinical outcomes from ARDS. RESULTS: Of 29,144 patients admitted to participating ICUs, 3022 (10.4%) fulfilled ARDS criteria. Of these, 2377 patients developed ARDS in the first 48 hours and whose respiratory failure was managed with invasive mechanical ventilation. The period prevalence of mild ARDS was 30.0% (95% CI, 28.2%-31.9%); of moderate ARDS, 46.6% (95% CI, 44.5%-48.6%); and of severe ARDS, 23.4% (95% CI, 21.7%-25.2%). ARDS represented 0.42 cases per ICU bed over 4 weeks and represented 10.4% (95% CI, 10.0%-10.7%) of ICU admissions and 23.4% of patients requiring mechanical ventilation. Clinical recognition of ARDS ranged from 51.3% (95% CI, 47.5%-55.0%) in mild to 78.5% (95% CI, 74.8%-81.8%) in severe ARDS. Less than two-thirds of patients with ARDS received a tidal volume 8 of mL/kg or less of predicted body weight. Plateau pressure was measured in 40.1% (95% CI, 38.2-42.1), whereas 82.6% (95% CI, 81.0%-84.1%) received a positive end-expository pressure (PEEP) of less than 12 cm H2O. Prone positioning was used in 16.3% (95% CI, 13.7%-19.2%) of patients with severe ARDS. Clinician recognition of ARDS was associated with higher PEEP, greater use of neuromuscular blockade, and prone positioning. Hospital mortality was 34.9% (95% CI, 31.4%-38.5%) for those with mild, 40.3% (95% CI, 37.4%-43.3%) for those with moderate, and 46.1% (95% CI, 41.9%-50.4%) for those with severe ARDS. CONCLUSIONS AND RELEVANCE: Among ICUs in 50 countries, the period prevalence of ARDS was 10.4% of ICU admissions. This syndrome appeared to be underrecognized and undertreated and associated with a high mortality rate. These findings indicate the potential for improvement in the management of patients with ARDS

Assessment on the efficacy of methods 2 to 5 and method 7 set out in Commission Regulation (EU) No 142/2011 to inactivate relevant pathogens when producing processed animal protein of porcine origin intended to feed poultry and aquaculture animals

An assessment was conducted on the level of inactivation of relevant pathogens that could be present in processed animal protein of porcine origin intended to feed poultry and aquaculture animals when methods 2 to 5 and method 7, as detailed in Regulation (EU) No 142/2011, are applied. Five approved scenarios were selected for method 7. Salmonella Senftenberg, Enterococcus faecalis, spores of Clostridium perfringens and parvoviruses were shortlisted as target indicators. Inactivation parameters for these indicators were extracted from extensive literature search and a recent EFSA scientific opinion. An adapted Bigelow model was fitted to retrieved data to estimate the probability that methods 2 to 5, in coincidental and consecutive modes, and the five scenarios of method 7 are able to achieve a 5 log10 and a 3 log10 reduction of bacterial indicators and parvoviruses, respectively. Spores of C. perfringens were the indicator with the lowest probability of achieving the target reduction by methods 2 to 5, in coincidental and consecutive mode, and by the five considered scenarios of method 7. An expert knowledge elicitation was conducted to estimate the certainty of achieving a 5 log10 reduction of spores of C. perfringens considering the results of the model and additional evidence. A 5 log10 reduction of C. perfringens spores was judged: 99–100% certain for methods 2 and 3 in coincidental mode; 98–100% certain for method 7 scenario 3; 80–99% certain for method 5 in coincidental mode; 66–100% certain for method 4 in coincidental mode and for method 7 scenarios 4 and 5; 25–75% certain for method 7 scenario 2; and 0–5% certain for method 7 scenario 1. Higher certainty is expected for methods 2 to 5 in consecutive mode compared to coincidental mode.info:eu-repo/semantics/publishedVersio

Informe técnico de experiencias en el cultivo de trigo. Campaña 2020 La Pampa

En una transecta norte sur de la provincia de La Pampa, desde Bernardo Larroude, Eduardo Castex, Anguil y Guatraché se sembraron distintas variedades de trigo disponibles en el mercado y se aplicaron dos niveles de tecnología de fertilización. Tanto en B. Larroudé como en E. Castex la aplicación de fungicida se realizó en función de la presencia de enfermedades, para la localidad de Guatraché se cuenta con información de rendimiento sin aplicación, con una y dos aplicaciones de fungicida. Por su parte en Anguil se realizaron 3 niveles de fertilización y control de enfermedades con una aplicación de fungicida. Con la finalidad de poder mostrar resultados obtenidos durante el 2020, se realizó el siguiente informe, correspondiente a una Investigación Acción Participativa entre el INTA (EEA Anguil, AER Guatraché y Gral. Pico), empresa privada (Bunge Argentina S.A), técnicos (Ings. Juan Martín Apollonio y Javier Seewald) y productores (Sr. Leandro Isidro y Gastón Galleto).EEA AnguilFil: Alvarez, Cristian. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Anguil. Agencia de Extensión Rural General Pico; ArgentinaFil: Fernández, Romina. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Anguil; ArgentinaFil: Paredes, Susana. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Anguil. Agencia de Extensión Rural Guatraché; ArgentinaFil: Figueruelo, Andrea. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Anguil; ArgentinaFil: Funaro, Daniel. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Anguil; ArgentinaFil: Apolonio, Juan. Actividad privada; ArgentinaFil: Saks, Matias. Bunge Argentina S.A.; ArgentinaFil: Galetto; Gaston. Actividad privada; ArgentinaFil: Isidro, Leando. Actividad privada; ArgentinaFil: Wiggenhauser, Walter. Actividad privada, ArgentinaFil: Peinetti, Nestor. Actividad privada; ArgentinaFil: Dillchneider, Alexandra. Universidad Nacional de La Pampa. Facultad de Agronomía; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Porta Siota, Fernando. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Anguil; ArgentinaFil: Fossaceca, Donato. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Anguil; ArgentinaFil: Sannen, Alan. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Anguil; ArgentinaFil: Seewald, Javier. Actividad privada; Argentin

Soil organic carbon stocks in native forest of Argentina: a useful surrogate for mitigation and conservation planning under climate variability

Background The nationally determined contribution (NDC) presented by Argentina within the framework of the Paris Agreement is aligned with the decisions made in the context of the United Nations Framework Convention on Climate Change (UNFCCC) on the reduction of emissions derived from deforestation and forest degradation, as well as forest carbon conservation (REDD+). In addition, climate change constitutes one of the greatest threats to forest biodiversity and ecosystem services. However, the soil organic carbon (SOC) stocks of native forests have not been incorporated into the Forest Reference Emission Levels calculations and for conservation planning under climate variability due to a lack of information. The objectives of this study were: (i) to model SOC stocks to 30 cm of native forests at a national scale using climatic, topographic and vegetation as predictor variables, and (ii) to relate SOC stocks with spatial–temporal remotely sensed indices to determine biodiversity conservation concerns due to threats from high inter‑annual climate variability. Methods We used 1040 forest soil samples (0–30 cm) to generate spatially explicit estimates of SOC native forests in Argentina at a spatial resolution of approximately 200 m. We selected 52 potential predictive environmental covariates, which represent key factors for the spatial distribution of SOC. All covariate maps were uploaded to the Google Earth Engine cloud‑based computing platform for subsequent modelling. To determine the biodiversity threats from high inter‑annual climate variability, we employed the spatial–temporal satellite‑derived indices based on Enhanced Vegetation Index (EVI) and land surface temperature (LST) images from Landsat imagery. Results SOC model (0–30 cm depth) prediction accounted for 69% of the variation of this soil property across the whole native forest coverage in Argentina. Total mean SOC stock reached 2.81 Pg C (2.71–2.84 Pg C with a probability of 90%) for a total area of 460,790 km2, where Chaco forests represented 58.4% of total SOC stored, followed by Andean Patagonian forests (16.7%) and Espinal forests (10.0%). SOC stock model was fitted as a function of regional climate, which greatly influenced forest ecosystems, including precipitation (annual mean precipitation and precipitation of warmest quarter) and temperature (day land surface temperature, seasonality, maximum temperature of warmest month, month of maximum temperature, night land surface temperature, and monthly minimum temperature). Biodiversity was influenced by the SOC levels and the forest regions. Conclusions In the framework of the Kyoto Protocol and REDD+, information derived in the present work from the estimate of SOC in native forests can be incorporated into the annual National Inventory Report of Argentina to assist forest management proposals. It also gives insight into how native forests can be more resilient to reduce the impact of biodiversity loss.EEA Santa CruzFil: Peri, Pablo Luis. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santa Cruz; Argentina.Fil: Peri, Pablo Luis. Universidad Nacional de la Patagonia Austral; Argentina.Fil: Peri, Pablo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Gaitan, Juan José. Universidad Nacional de Luján. Buenos Aires; Argentina.Fil: Gaitan, Juan José. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Mastrangelo, Matias Enrique. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias. Grupo de Estudio de Agroecosistemas y Paisajes Rurales; Argentina.Fil: Mastrangelo, Matias Enrique. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Nosetto, Marcelo Daniel. Universidad Nacional de San Luis. Instituto de Matemática Aplicada San Luis. Grupo de Estudios Ambientales; Argentina.Fil: Nosetto, Marcelo Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Villagra, Pablo Eugenio. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales (IANIGLA); Argentina.Fil: Villagra, Pablo Eugenio. Universidad Nacional de Cuyo. Facultad de Ciencias Agrarias; Argentina.Fil: Balducci, Ezequiel. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Yuto; Argentina.Fil: Pinazo, Martín Alcides. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Montecarlo; Argentina.Fil: Eclesia, Roxana Paola. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Paraná; Argentina.Fil: Von Wallis, Alejandra. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Montecarlo; Argentina.Fil: Villarino, Sebastián. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias. Grupo de Estudio de Agroecosistemas y Paisajes Rurales; Argentina.Fil: Villarino, Sebastián. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Alaggia, Francisco Guillermo. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Manfredi. Campo Anexo Villa Dolores; Argentina.Fil: Alaggia, Francisco Guillermo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Gonzalez-Polo, Marina. Universidad Nacional del Comahue; Argentina.Fil: Gonzalez-Polo, Marina. Consejo Nacional de Investigaciones Científicas y Técnicas. INIBIOMA; Argentina.Fil: Manrique, Silvana M. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Energía No Convencional. CCT Salta‑Jujuy; Argentina.Fil: Meglioli, Pablo A. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales (IANIGLA); Argentina.Fil: Meglioli, Pablo A. Universidad Nacional de Cuyo. Facultad de Ciencias Agrarias; Argentina.Fil: Rodríguez‑Souilla, Julián. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas (CADIC); Argentina.Fil: Mónaco, Martín H. Ministerio de Ambiente y Desarrollo Sostenible. Dirección Nacional de Bosques; Argentina.Fil: Chaves, Jimena Elizabeth. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas (CADIC); Argentina.Fil: Medina, Ariel. Ministerio de Ambiente y Desarrollo Sostenible. Dirección Nacional de Bosques; Argentina.Fil: Gasparri, Ignacio. Universidad Nacional de Tucumán. Instituto de Ecología Regional; Argentina.Fil: Gasparri, Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Alvarez Arnesi, Eugenio. Universidad Nacional de Rosario. Instituto de Investigaciones en Ciencias Agrarias de Rosario; Argentina.Fil: Alvarez Arnesi, Eugenio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe; Argentina.Fil: Barral, María Paula. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias. Grupo de Estudio de Agroecosistemas y Paisajes Rurales; Argentina.Fil: Barral, María Paula. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Von Müller, Axel. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Esquel Argentina.Fil: Pahr, Norberto Manuel. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Montecarlo; Argentina.Fil: Uribe Echevarría, Josefina. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Quimilí; Argentina.Fil: Fernandez, Pedro Sebastian. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Famaillá; Argentina.Fil: Fernandez, Pedro Sebastian. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Ecología Regional; Argentina.Fil: Morsucci, Marina. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales (IANIGLA); Argentina.Fil: Morsucci, Marina. Universidad Nacional de Cuyo. Facultad de Ciencias Agrarias; Argentina.Fil: Lopez, Dardo Ruben. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Manfredi. Campo Anexo Villa Dolores; Argentina.Fil: Lopez, Dardo Ruben. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Cellini, Juan Manuel. Universidad Nacional de la Plata (UNLP). Facultad de Ciencias Naturales y Museo. Laboratorio de Investigaciones en Maderas; Argentina.Fil: Alvarez, Leandro M. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales (IANIGLA); Argentina.Fil: Alvarez, Leandro M. Universidad Nacional de Cuyo. Facultad de Ciencias Agrarias; Argentina.Fil: Barberis, Ignacio Martín. Universidad Nacional de Rosario. Instituto de Investigaciones en Ciencias Agrarias de Rosario; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe; Argentina.Fil: Barberis, Ignacio Martín. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe; Argentina.Fil: Colomb, Hernán Pablo. Ministerio de Ambiente y Desarrollo Sostenible. Dirección Nacional de Bosques; Argentina.Fil: Colomb, Hernán. Administración de Parques Nacionales (APN). Parque Nacional Los Alerces; Argentina.Fil: La Manna, Ludmila. Universidad Nacional de la Patagonia San Juan Bosco. Centro de Estudios Ambientales Integrados (CEAI); Argentina.Fil: La Manna, Ludmila. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Barbaro, Sebastian Ernesto. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Cerro Azul; Argentina.Fil: Blundo, Cecilia. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Ecología Regional; Argentina.Fil: Blundo, Cecilia. Universidad Nacional de Tucumán. Tucumán; Argentina.Fil: Sirimarco, Marina Ximena. Universidad Nacional de Mar del Plata. Grupo de Estudio de Agroecosistemas y Paisajes Rurales (GEAP); Argentina.Fil: Sirimarco, Marina Ximena. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Cavallero, Laura. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Manfredi. Campo Anexo Villa Dolores; Argentina.Fil: Zalazar, Gualberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales (IANIGLA); Argentina.Fil: Zalazar, Gualberto. Universidad Nacional de Cuyo. Facultad de Ciencias Agrarias; Argentina.Fil: Martínez Pastur, Guillermo José. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Austral de Investigaciones Científicas (CADIC); Argentina

Safety and efficacy of ribociclib plus letrozole in patients with HR+, HER2– advanced breast cancer: Results from the Spanish sub-population of the phase 3b CompLEEment-1 trial

Background: Breast cancer is the most common malignancy and the second leading cause of cancer-related mortality in Spanish women. Ribociclib in combination with endocrine therapy (ET) has shown superiority in prolonging survival in patients with hormone receptor-positive (HR+), human epidermal growth factor receptor 2-negative (HER2-) advanced breast cancer (ABC) vs. ET alone.Methods: CompLEEment-1 is a single-arm, open-label phase 3b trial evaluating ribociclib plus letrozole in a broad population of patients with HR+, HER2- ABC. The primary endpoints were safety and tolerability. Here we report data for Spanish patients enrolled in CompLEEment-1.Results: A total of 526 patients were evaluated (median follow-up: 26.97 months). Baseline characteristics showed a diverse population with a median age of 54 years. At study entry, 56.5% of patients had visceral metastases and 8.7% had received prior chemotherapy for advanced disease. Rates of all-grade and Grade >= 3 adverse events (AEs) were 99.0% and 76.2%, respectively; 21.3% of patients experienced a serious AE, and 15.8% of AEs led to treatment discontinuation. AEs of special interest of neutropenia, increased alanine aminotransferase, increased aspartate aminotransferase and QTcF prolongation occurred in 77.8%, 14.8%, 11.4% and 4.0% of patients, respectively. Patients aged >70 years experienced increased rates of all-grade and Grade >= 3 neutropenia and anemia. Efficacy results were consistent with the global study.Conclusions: Results from Spanish patients enrolled in CompLEEment-1 are consistent with global data showing efficacy and a manageable safety profile for ribociclib plus letrozole treatment in patients with HR+, HER2-ABC, including populations of interest (NCT02941926).Trial registration: ClinicalTrials.gov NCT0294192

Obstetric outcomes of sars-cov-2 infection in asymptomatic pregnant women

Altres ajuts: Fondo Europeo de Desarrollo Regional (FEDER)Around two percent of asymptomatic women in labor test positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Spain. Families and care providers face childbirth with uncertainty. We determined if SARS-CoV-2 infection at delivery among asymptomatic mothers had different obstetric outcomes compared to negative patients. This was a multicenter prospective study based on universal antenatal screening for SARS-CoV-2 infection. A total of 42 hospitals tested women admitted for delivery using polymerase chain reaction, from March to May 2020. We included positive mothers and a sample of negative mothers asymptomatic throughout the antenatal period, with 6-week postpartum follow-up. Association between SARS-CoV-2 and obstetric outcomes was evaluated by multivariate logistic regression analyses. In total, 174 asymptomatic SARS-CoV-2 positive pregnancies were compared with 430 asymptomatic negative pregnancies. No differences were observed between both groups in key maternal and neonatal outcomes at delivery and follow-up, with the exception of prelabor rupture of membranes at term (adjusted odds ratio 1.88, 95% confidence interval 1.13-3.11; p = 0.015). Asymptomatic SARS-CoV-2 positive mothers have higher odds of prelabor rupture of membranes at term, without an increase in perinatal complications, compared to negative mothers. Pregnant women testing positive for SARS-CoV-2 at admission for delivery should be reassured by their healthcare workers in the absence of symptoms

Measurement of the cosmic ray spectrum above 4×10184{\times}10^{18} eV using inclined events detected with the Pierre Auger Observatory

A measurement of the cosmic-ray spectrum for energies exceeding $4{\times}10^{18}$ eV is presented, which is based on the analysis of showers with zenith angles greater than $60^{\circ}$ detected with the Pierre Auger Observatory between 1 January 2004 and 31 December 2013. The measured spectrum confirms a flux suppression at the highest energies. Above $5.3{\times}10^{18}$ eV, the "ankle", the flux can be described by a power law $E^{-\gamma}$ with index $\gamma=2.70 \pm 0.02 \,\text{(stat)} \pm 0.1\,\text{(sys)}$ followed by a smooth suppression region. For the energy ($E_\text{s}$) at which the spectral flux has fallen to one-half of its extrapolated value in the absence of suppression, we find $E_\text{s}=(5.12\pm0.25\,\text{(stat)}^{+1.0}_{-1.2}\,\text{(sys)}){\times}10^{19}$ eV.Comment: Replaced with published version. Added journal reference and DO