146 research outputs found

    Do Fruit Nutrients Affect Subgrouping Patterns in Wild Spider Monkeys (Ateles geoffroyi)?

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    One of the main costs of group living is feeding competition. Fission–fusion dynamics are thought to be a strategy to avoid overt competition for food resources. We tested whether food abundance and quality affected such dynamics in a species characterized by a high degree of fission–fusion dynamics. We collected data on 22 adult and subadult spider monkeys (Ateles geoffroyi) living in a large community in the protected area of Otoch Ma’ax Yetel Kooh, Yucatan, Mexico. We recorded subgroup size and fission events as well as fruit abundance during 12 mo and conducted nutritional analyses on the fruit species that the study subjects consumed most. We found no effect of fruit abundance or nutritional quality of recently visited food patches on individual fission decisions, but the amount of protein in the food patches visited over the course of the day was a good predictor of subgroup size. While the absence of support for a relationship between fruit characteristics and fission decisions may be due to the short temporal scale of the analysis, our findings relating subgroup size to the amount of protein in the visited food patches over the course of the day may be explained by individual spider monkeys attempting to obtain sufficient protein intake from their fruit-based diet. © 2016 Springer Science+Business Media New Yor

    Neotropical xenarthrans: a data set of occurrence of xenarthran species in the neotropics

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    Xenarthrans -anteaters, sloths, and armadillos- have essential functions for ecosystem maintenance, such as insect control and nutrient cycling, playing key roles as ecosystem engineers. Because of habitat loss and fragmentation, hunting pressure, and conflicts with domestic dogs, these species have been threatened locally, regionally, or even across their full distribution ranges. The Neotropics harbor 21 species of armadillos, 10 anteaters, and 6 sloths. Our data set includes the families Chlamyphoridae (13), Dasypodidae (7), Myrmecophagidae (3), Bradypodidae (4), and Megalonychidae (2). We have no occurrence data on Dasypus pilosus (Dasypodidae). Regarding Cyclopedidae, until recently, only one species was recognized, but new genetic studies have revealed that the group is represented by seven species. In this data paper, we compiled a total of 42,528 records of 31 species, represented by occurrence and quantitative data, totaling 24,847 unique georeferenced records. The geographic range is from the southern United States, Mexico, and Caribbean countries at the northern portion of the Neotropics, to the austral distribution in Argentina, Paraguay, Chile, and Uruguay. Regarding anteaters, Myrmecophaga tridactyla has the most records (n = 5,941), and Cyclopes sp. Have the fewest (n = 240). The armadillo species with the most data is Dasypus novemcinctus (n = 11,588), and the fewest data are recorded for Calyptophractus retusus (n = 33). With regard to sloth species, Bradypus variegatus has the most records (n = 962), and Bradypus pygmaeus has the fewest (n = 12). Our main objective with Neotropical Xenarthrans is to make occurrence and quantitative data available to facilitate more ecological research, particularly if we integrate the xenarthran data with other data sets of Neotropical Series that will become.Fil: Marques Santos, Paloma. Universidade Federal de Minas Gerais. Instituto de CiĂȘncias BiolĂłgicas; BrasilFil: Bocchiglieri, Adriana. Universidade Federal de Sergipe; BrasilFil: Garcia Chiarello, Adriano. Universidade de Sao Paulo; BrasilFil: Pereira Paglia, Adriano. Universidade Federal de Minas Gerais. Instituto de CiĂȘncias BiolĂłgicas; BrasilFil: Moreira, Adryelle. Amplo Engenharia e GestĂŁo de Projetos ; BrasilFil: Abba, Agustin Manuel. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - La Plata. Centro de Estudios ParasitolĂłgicos y de Vectores. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. Centro de Estudios ParasitolĂłgicos y de Vectores; ArgentinaFil: Paviolo, Agustin Javier. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - Nordeste. Instituto de BiologĂ­a Subtropical. Universidad Nacional de Misiones. Instituto de BiologĂ­a Subtropical; ArgentinaFil: Gatica, Ailin. Universidad Nacional de San Luis; Argentina. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - San Luis. Instituto Multidisciplinario de Investigaciones BiolĂłgicas de San Luis. Universidad Nacional de San Luis. Facultad de Ciencias FĂ­sico MatemĂĄticas y Naturales. Instituto Multidisciplinario de Investigaciones BiolĂłgicas de San Luis; ArgentinaFil: Ochoa, Ana Cecilia. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - San Luis. Instituto Multidisciplinario de Investigaciones BiolĂłgicas de San Luis. Universidad Nacional de San Luis. Facultad de Ciencias FĂ­sico MatemĂĄticas y Naturales. Instituto Multidisciplinario de Investigaciones BiolĂłgicas de San Luis; ArgentinaFil: de Angelo, Carlos Daniel. Universidad Nacional de Rio Cuarto. Facultad de Cs.exactas Fisicoquimicas y Naturales. Instituto de Ciencias de la Tierra, Biodiversidad y Ambiente. - Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - Cordoba. Instituto de Ciencias de la Tierra, Biodiversidad y Ambiente.; ArgentinaFil: Tellaeche, Cintia Gisele. Universidad Nacional de Jujuy. Facultad de Ciencias Agrarias. Centro de Estudios Ambientales Territoriales y Sociales; Argentina. Universidad Nacional de Jujuy. Instituto de Ecorregiones Andinas. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - Salta. Instituto de Ecorregiones Andinas; ArgentinaFil: Varela, Diego Martin. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - Nordeste. Instituto de BiologĂ­a Subtropical. Instituto de BiologĂ­a Subtropical - Nodo Puerto IguazĂș | Universidad Nacional de Misiones. Instituto de BiologĂ­a Subtropical. Instituto de BiologĂ­a Subtropical - Nodo Puerto IguazĂș; ArgentinaFil: Vanderhoeven, Ezequiel Andres. Ministerio de Salud. Instituto Nacional de Medicina Tropical; Argentina. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas; ArgentinaFil: Caruso, MarĂ­a Flavia. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas; Argentina. AdministraciĂłn de Parques Nacionales. DelegaciĂłn Regional del Noroeste; ArgentinaFil: Arrabal, Juan Pablo. Secretaria de Gobierno de Salud. Instituto Nacional de Medicina Tropical - Sede Puerto IguazĂș Misiones; Argentina. Centro de Investigaciones del Bosque AtlĂĄntico; ArgentinaFil: Iezzi, MarĂ­a Eugenia. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - Nordeste. Instituto de BiologĂ­a Subtropical. Instituto de BiologĂ­a Subtropical - Nodo Puerto IguazĂș | Universidad Nacional de Misiones. Instituto de BiologĂ­a Subtropical. Instituto de BiologĂ­a Subtropical - Nodo Puerto IguazĂș; ArgentinaFil: Di Bitetti, Mario Santiago. Centro de Investigaciones del Bosque AtlĂĄntico; Argentina. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - Nordeste. Instituto de BiologĂ­a Subtropical. Instituto de BiologĂ­a Subtropical - Nodo Puerto IguazĂș | Universidad Nacional de Misiones. Instituto de BiologĂ­a Subtropical. Instituto de BiologĂ­a Subtropical - Nodo Puerto IguazĂș; ArgentinaFil: Cruz, Paula Andrea. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - Nordeste. Instituto de BiologĂ­a Subtropical. Instituto de BiologĂ­a Subtropical - Nodo Puerto IguazĂș | Universidad Nacional de Misiones. Instituto de BiologĂ­a Subtropical. Instituto de BiologĂ­a Subtropical - Nodo Puerto IguazĂș; Argentina. Centro de Investigaciones del Bosque AtlĂĄntico; ArgentinaFil: Reppucci, Juan Ignacio. AdministraciĂłn de Parques Nacionales. DelegaciĂłn Regional del Noroeste; Argentina. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas; ArgentinaFil: Benito Santamaria, Silvia. Centro de Investigaciones del Bosque AtlĂĄntico; Argentina. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - Nordeste. Instituto de BiologĂ­a Subtropical. Instituto de BiologĂ­a Subtropical - Nodo Puerto IguazĂș | Universidad Nacional de Misiones. Instituto de BiologĂ­a Subtropical. Instituto de BiologĂ­a Subtropical - Nodo Puerto IguazĂș; ArgentinaFil: Quiroga, VerĂłnica Andrea. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - CĂłrdoba. Instituto de Diversidad y EcologĂ­a Animal. Universidad Nacional de CĂłrdoba. Facultad de Ciencias Exactas FĂ­sicas y Naturales. Instituto de Diversidad y EcologĂ­a Animal; ArgentinaFil: Di Blanco, Yamil Edgardo. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - Nordeste. Instituto de BiologĂ­a Subtropical. Instituto de BiologĂ­a Subtropical - Nodo Puerto IguazĂș | Universidad Nacional de Misiones. Instituto de BiologĂ­a Subtropical. Instituto de BiologĂ­a Subtropical - Nodo Puerto IguazĂș; ArgentinaFil: MarĂĄs, Gustavo Arnaldo. AdministraciĂłn de Parques Nacionales. DelegaciĂłn Regional del Noroeste; Argentina. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas; ArgentinaFil: Camino, Micaela. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - Nordeste. Centro de EcologĂ­a Aplicada del Litoral. Universidad Nacional del Nordeste. Centro de EcologĂ­a Aplicada del Litoral; ArgentinaFil: Perovic, Pablo GastĂłn. AdministraciĂłn de Parques Nacionales. DelegaciĂłn Regional del Noroeste; Argentina. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas; ArgentinaFil: MartĂ­nez Pardo, Julia. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - Nordeste. Instituto de BiologĂ­a Subtropical. Instituto de BiologĂ­a Subtropical - Nodo Puerto IguazĂș | Universidad Nacional de Misiones. Instituto de BiologĂ­a Subtropical. Instituto de BiologĂ­a Subtropical - Nodo Puerto IguazĂș; ArgentinaFil: Costa, SebastiĂĄn AndrĂ©s. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - Nordeste. Instituto de BiologĂ­a Subtropical. Instituto de BiologĂ­a Subtropical - Nodo Puerto IguazĂș | Universidad Nacional de Misiones. Instituto de BiologĂ­a Subtropical. Instituto de BiologĂ­a Subtropical - Nodo Puerto IguazĂș; ArgentinaFil: Pinheiro, Fabiana. Universidade Federal do Rio Grande do Sul; BrasilFil: Volkmer de Castilho, Pedro. Universidade Federal de Santa Catarina; BrasilFil: BercĂȘ, William. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Camara Assis, Julia. Universidade Estadual Paulista Julio de Mesquita Filho. Faculdade de Engenharia.; BrasilFil: Rodrigues Tonetti, Vinicius. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Alves Eigenheer, Milene. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Chinem, Simonne. Universidade de Sao Paulo; BrasilFil: Honda, Laura K.. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Bergallo, Helena de Godoy. Universidade do Estado de Rio do Janeiro; BrasilFil: Alberici, Vinicius. Universidade de Sao Paulo; BrasilFil: Wallace, Robert. Wildlife Conservation Society; Estados UnidosFil: Ribeiro, Milton Cezar. Universidade de Sao Paulo; BrasilFil: Galetti, Mauro. Universidade Estadual Paulista Julio de Mesquita Filho; Brasi

    Procalcitonin Is Not a Reliable Biomarker of Bacterial Coinfection in People With Coronavirus Disease 2019 Undergoing Microbiological Investigation at the Time of Hospital Admission

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    Abstract Admission procalcitonin measurements and microbiology results were available for 1040 hospitalized adults with coronavirus disease 2019 (from 48 902 included in the International Severe Acute Respiratory and Emerging Infections Consortium World Health Organization Clinical Characterisation Protocol UK study). Although procalcitonin was higher in bacterial coinfection, this was neither clinically significant (median [IQR], 0.33 [0.11–1.70] ng/mL vs 0.24 [0.10–0.90] ng/mL) nor diagnostically useful (area under the receiver operating characteristic curve, 0.56 [95% confidence interval, .51–.60]).</jats:p

    Implementation of corticosteroids in treating COVID-19 in the ISARIC WHO Clinical Characterisation Protocol UK:prospective observational cohort study

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    BACKGROUND: Dexamethasone was the first intervention proven to reduce mortality in patients with COVID-19 being treated in hospital. We aimed to evaluate the adoption of corticosteroids in the treatment of COVID-19 in the UK after the RECOVERY trial publication on June 16, 2020, and to identify discrepancies in care. METHODS: We did an audit of clinical implementation of corticosteroids in a prospective, observational, cohort study in 237 UK acute care hospitals between March 16, 2020, and April 14, 2021, restricted to patients aged 18 years or older with proven or high likelihood of COVID-19, who received supplementary oxygen. The primary outcome was administration of dexamethasone, prednisolone, hydrocortisone, or methylprednisolone. This study is registered with ISRCTN, ISRCTN66726260. FINDINGS: Between June 17, 2020, and April 14, 2021, 47 795 (75·2%) of 63 525 of patients on supplementary oxygen received corticosteroids, higher among patients requiring critical care than in those who received ward care (11 185 [86·6%] of 12 909 vs 36 415 [72·4%] of 50 278). Patients 50 years or older were significantly less likely to receive corticosteroids than those younger than 50 years (adjusted odds ratio 0·79 [95% CI 0·70–0·89], p=0·0001, for 70–79 years; 0·52 [0·46–0·58], p80 years), independent of patient demographics and illness severity. 84 (54·2%) of 155 pregnant women received corticosteroids. Rates of corticosteroid administration increased from 27·5% in the week before June 16, 2020, to 75–80% in January, 2021. INTERPRETATION: Implementation of corticosteroids into clinical practice in the UK for patients with COVID-19 has been successful, but not universal. Patients older than 70 years, independent of illness severity, chronic neurological disease, and dementia, were less likely to receive corticosteroids than those who were younger, as were pregnant women. This could reflect appropriate clinical decision making, but the possibility of inequitable access to life-saving care should be considered. FUNDING: UK National Institute for Health Research and UK Medical Research Council

    Incident type 2 diabetes attributable to suboptimal diet in 184 countries

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    The global burden of diet-attributable type 2 diabetes (T2D) is not well established. This risk assessment model estimated T2D incidence among adults attributable to direct and body weight-mediated effects of 11 dietary factors in 184 countries in 1990 and 2018. In 2018, suboptimal intake of these dietary factors was estimated to be attributable to 14.1 million (95% uncertainty interval (UI), 13.8–14.4 million) incident T2D cases, representing 70.3% (68.8–71.8%) of new cases globally. Largest T2D burdens were attributable to insufficient whole-grain intake (26.1% (25.0–27.1%)), excess refined rice and wheat intake (24.6% (22.3–27.2%)) and excess processed meat intake (20.3% (18.3–23.5%)). Across regions, highest proportional burdens were in central and eastern Europe and central Asia (85.6% (83.4–87.7%)) and Latin America and the Caribbean (81.8% (80.1–83.4%)); and lowest proportional burdens were in South Asia (55.4% (52.1–60.7%)). Proportions of diet-attributable T2D were generally larger in men than in women and were inversely correlated with age. Diet-attributable T2D was generally larger among urban versus rural residents and higher versus lower educated individuals, except in high-income countries, central and eastern Europe and central Asia, where burdens were larger in rural residents and in lower educated individuals. Compared with 1990, global diet-attributable T2D increased by 2.6 absolute percentage points (8.6 million more cases) in 2018, with variation in these trends by world region and dietary factor. These findings inform nutritional priorities and clinical and public health planning to improve dietary quality and reduce T2D globally.publishedVersio

    TRY plant trait database – enhanced coverage and open access

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    Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

    Proceedings of the 3rd Biennial Conference of the Society for Implementation Research Collaboration (SIRC) 2015: advancing efficient methodologies through community partnerships and team science

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    It is well documented that the majority of adults, children and families in need of evidence-based behavioral health interventionsi do not receive them [1, 2] and that few robust empirically supported methods for implementing evidence-based practices (EBPs) exist. The Society for Implementation Research Collaboration (SIRC) represents a burgeoning effort to advance the innovation and rigor of implementation research and is uniquely focused on bringing together researchers and stakeholders committed to evaluating the implementation of complex evidence-based behavioral health interventions. Through its diverse activities and membership, SIRC aims to foster the promise of implementation research to better serve the behavioral health needs of the population by identifying rigorous, relevant, and efficient strategies that successfully transfer scientific evidence to clinical knowledge for use in real world settings [3]. SIRC began as a National Institute of Mental Health (NIMH)-funded conference series in 2010 (previously titled the “Seattle Implementation Research Conference”; $150,000 USD for 3 conferences in 2011, 2013, and 2015) with the recognition that there were multiple researchers and stakeholdersi working in parallel on innovative implementation science projects in behavioral health, but that formal channels for communicating and collaborating with one another were relatively unavailable. There was a significant need for a forum within which implementation researchers and stakeholders could learn from one another, refine approaches to science and practice, and develop an implementation research agenda using common measures, methods, and research principles to improve both the frequency and quality with which behavioral health treatment implementation is evaluated. SIRC’s membership growth is a testament to this identified need with more than 1000 members from 2011 to the present.ii SIRC’s primary objectives are to: (1) foster communication and collaboration across diverse groups, including implementation researchers, intermediariesi, as well as community stakeholders (SIRC uses the term “EBP champions” for these groups) – and to do so across multiple career levels (e.g., students, early career faculty, established investigators); and (2) enhance and disseminate rigorous measures and methodologies for implementing EBPs and evaluating EBP implementation efforts. These objectives are well aligned with Glasgow and colleagues’ [4] five core tenets deemed critical for advancing implementation science: collaboration, efficiency and speed, rigor and relevance, improved capacity, and cumulative knowledge. SIRC advances these objectives and tenets through in-person conferences, which bring together multidisciplinary implementation researchers and those implementing evidence-based behavioral health interventions in the community to share their work and create professional connections and collaborations

    Co-infections, secondary infections, and antimicrobial use in patients hospitalised with COVID-19 during the first pandemic wave from the ISARIC WHO CCP-UK study: a multicentre, prospective cohort study

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    Background: Microbiological characterisation of co-infections and secondary infections in patients with COVID-19 is lacking, and antimicrobial use is high. We aimed to describe microbiologically confirmed co-infections and secondary infections, and antimicrobial use, in patients admitted to hospital with COVID-19. Methods: The International Severe Acute Respiratory and Emerging Infections Consortium (ISARIC) WHO Clinical Characterisation Protocol UK (CCP-UK) study is an ongoing, prospective cohort study recruiting inpatients from 260 hospitals in England, Scotland, and Wales, conducted by the ISARIC Coronavirus Clinical Characterisation Consortium. Patients with a confirmed or clinician-defined high likelihood of SARS-CoV-2 infection were eligible for inclusion in the ISARIC WHO CCP-UK study. For this specific study, we excluded patients with a recorded negative SARS-CoV-2 test result and those without a recorded outcome at 28 days after admission. Demographic, clinical, laboratory, therapeutic, and outcome data were collected using a prespecified case report form. Organisms considered clinically insignificant were excluded. Findings: We analysed data from 48 902 patients admitted to hospital between Feb 6 and June 8, 2020. The median patient age was 74 years (IQR 59–84) and 20 786 (42·6%) of 48 765 patients were female. Microbiological investigations were recorded for 8649 (17·7%) of 48 902 patients, with clinically significant COVID-19-related respiratory or bloodstream culture results recorded for 1107 patients. 762 (70·6%) of 1080 infections were secondary, occurring more than 2 days after hospital admission. Staphylococcus aureus and Haemophilus influenzae were the most common pathogens causing respiratory co-infections (diagnosed ≀2 days after admission), with Enterobacteriaceae and S aureus most common in secondary respiratory infections. Bloodstream infections were most frequently caused by Escherichia coli and S aureus. Among patients with available data, 13 390 (37·0%) of 36 145 had received antimicrobials in the community for this illness episode before hospital admission and 39 258 (85·2%) of 46 061 patients with inpatient antimicrobial data received one or more antimicrobials at some point during their admission (highest for patients in critical care). We identified frequent use of broad-spectrum agents and use of carbapenems rather than carbapenem-sparing alternatives. Interpretation: In patients admitted to hospital with COVID-19, microbiologically confirmed bacterial infections are rare, and more likely to be secondary infections. Gram-negative organisms and S aureus are the predominant pathogens. The frequency and nature of antimicrobial use are concerning, but tractable targets for stewardship interventions exist. Funding: National Institute for Health Research (NIHR), UK Medical Research Council, Wellcome Trust, UK Department for International Development, Bill &amp; Melinda Gates Foundation, EU Platform for European Preparedness Against (Re-)emerging Epidemics, NIHR Health Protection Research Unit (HPRU) in Emerging and Zoonotic Infections at University of Liverpool, and NIHR HPRU in Respiratory Infections at Imperial College London
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