30 research outputs found

    COVID-19 symptoms at hospital admission vary with age and sex: results from the ISARIC prospective multinational observational study

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    Background: The ISARIC prospective multinational observational study is the largest cohort of hospitalized patients with COVID-19. We present relationships of age, sex, and nationality to presenting symptoms. Methods: International, prospective observational study of 60 109 hospitalized symptomatic patients with laboratory-confirmed COVID-19 recruited from 43 countries between 30 January and 3 August 2020. Logistic regression was performed to evaluate relationships of age and sex to published COVID-19 case definitions and the most commonly reported symptoms. Results: ‘Typical’ symptoms of fever (69%), cough (68%) and shortness of breath (66%) were the most commonly reported. 92% of patients experienced at least one of these. Prevalence of typical symptoms was greatest in 30- to 60-year-olds (respectively 80, 79, 69%; at least one 95%). They were reported less frequently in children (≀ 18 years: 69, 48, 23; 85%), older adults (≄ 70 years: 61, 62, 65; 90%), and women (66, 66, 64; 90%; vs. men 71, 70, 67; 93%, each P < 0.001). The most common atypical presentations under 60 years of age were nausea and vomiting and abdominal pain, and over 60 years was confusion. Regression models showed significant differences in symptoms with sex, age and country. Interpretation: This international collaboration has allowed us to report reliable symptom data from the largest cohort of patients admitted to hospital with COVID-19. Adults over 60 and children admitted to hospital with COVID-19 are less likely to present with typical symptoms. Nausea and vomiting are common atypical presentations under 30 years. Confusion is a frequent atypical presentation of COVID-19 in adults over 60 years. Women are less likely to experience typical symptoms than men

    Déformation des cartes vectorielles polygonales pour améliorer la lisibilité des cartes de flux un-à-plusieurs

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    The data and codes that allowed us to obtain the results presented in this paper are available in figshare at the permanent link https://doi.org/10.6084/m9.figshare.21501999.International audienceCartographers have long been interested in the representation of various movements such as migration, commercial exchanges and transportation. There are several techniques for visualizing this information; this paper focuses on flow mapping. A flow map is a type of map that shows a set of movements through line symbols connecting an origin to a destination. Each link is associated with a value that corresponds to the volume of the movement. However, once a certain volume of data is reached, the maps quickly become cluttered and can be difficult to read and understand. Moreover, the values of the movements must be correctly represented so as not to induce biased interpretations. The objective of this paper is to create flow maps in which the flows have highly variable thicknesses so that the associated value is correctly represented. The technique used to create the flow paths does not create crossings between flows. In order to remove any visual clutter, such as overlaps between flows and geographic features, some areas of the map are distorted. In other words, our method of map distortion adapts the polygon vector base map to the flows, the central information of the visualization, and not the other way around
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