Corpus overview


MeSH Disease

HGNC Genes

SARS-CoV-2 proteins

There are no SARS-CoV-2 protein terms in the subcorpus


SARS-CoV-2 Proteins
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    COVID-19 MESHD surveillance - a descriptive study on data quality issues

    Authors: Cristina Costa-Santos; Ana Luisa Neves; Ricardo Correia; Paulo Santos; Matilde Monteiro-Soares; Alberto Freitas; Ines Ribeiro-Vaz; Teresa Henriques; Pedro Pereira Rodrigues; Altamiro Costa-Pereira; Ana Margarida Pereira; Joao Fonseca

    doi:10.1101/2020.11.03.20225565 Date: 2020-11-05 Source: medRxiv

    Background: High-quality data is crucial for guiding decision making and practicing evidence-based healthcare, especially if previous knowledge is lacking. Nevertheless, data quality frailties have been exposed worldwide during the current COVID-19 pandemic MESHD COVID-19 pandemic MESHD. Focusing on a major Portuguese surveillance dataset, our study aims to assess data quality issues and suggest possible solutions. Methods: On April 27th 2020, the Portuguese Directorate-General of Health ( DGS MESHD) made available a dataset (DGSApril) for researchers, upon request. On August 4th, an updated dataset (DGSAugust) was also obtained. The quality of data was assessed through analysis of data completeness and consistency between both datasets. Results: DGSAugust has not followed the data format and variables as DGSApril and a significant number of missing data and inconsistencies were found (e.g. 4,075 cases from the DGSApril were apparently not included in DGSAugust). Several variables also showed a low degree of completeness and/or changed their values from one dataset to another (e.g. the variable underlying conditions had more than half of cases showing different information between datasets). There were also significant inconsistencies between the number of cases and deaths MESHD due to COVID-19 MESHD shown in DGSAugust and by the DGS MESHD reports publicly provided daily. Conclusions: The low quality of COVID-19 MESHD surveillance datasets limits its usability to inform good decisions and perform useful research. Major improvements in surveillance datasets are therefore urgently needed - e.g. simplification of data entry processes, constant monitoring of data, and increased training and awareness of health care providers - as low data quality may lead to a deficient pandemic control.

    COVID-19 MESHD :Determinants of Hospitalization, ICU and Death among 20,293 reported cases in Portugal

    Authors: Vasco Ricoca Peixoto; Andre Vieira; Pedro Aguiar; Paulo Sousa; Carlos Carvalho; Daniel Rhys Thomas; Alexandre Abrantes; Carla Nunes

    doi:10.1101/2020.05.29.20115824 Date: 2020-05-30 Source: medRxiv

    Introduction Determinants of hospitalization, intensive care unit (ICU) admission and death MESHD are still unclear for Covid-19 MESHD and only a few studies have adjusted for confounding for different clinical outcomes including all reported cases in a country in the analysis. We used routine surveillance data from Portugal to identify risk factors for COVID-19 MESHD outcomes, in order to support risk stratification, clinical and public health interventions, and to improve scenarios to plan health care resources. Methods We conducted a retrospective cohort study including 20,293 laboratory confirmed cases of COVID-19 MESHD in Portugal to 28 April 2020, electronically through the National Epidemic Surveillance System of the Directorate-General of Health( DGS MESHD). We calculated absolute risks, relative risks (RR) and adjusted relative risks (aRR) to identify demographic and clinical factors associated with hospitalization, admission to ICU and death MESHD using Poisson regressions. Results Increasing age after 60 years was the greatest determinant for all outcomes. Assuming 0-50 years as reference, being aged 80-89 years was the strongest determinant of hospital admission (aRR-5.7), 70-79 years for ICU(aRR-10.4) and >90 years for death MESHD(aRR-226.8) with an aRR of 112.7 in those 70-79 . Among comorbidites, Immunodeficiency MESHD, cardiac disease MESHD, kidney disease MESHD, and neurologic disease MESHD were independent risk factors for hospitalization ( aRR 1 HGNC.83, 1.79, 1.56, 1.82), for ICU these were cardiac, Immunodeficiency, kidney and lung disease MESHD (aRR 4.33, 2.76, 2.43, 2.04), and for death MESHD they were kidney, cardiac and chronic neurological disease MESHD (aRR: 2.9, 2.6, 2.0) Male gender was a risk factor for all outcomes. There were statistically significant differences for the 3 outcomes between regions. Discussion and Conclusions Older age stands out as the strongest risk factor for all outcomes specially for death MESHD as absolute is risk was small for those younger than 50. These findings have implications in terms of risk stratified public health measures that should prioritize protecting older people. Epidemiologic scenarios and clinical guidelines may consider the estimated risks, even though under-ascertainment of mild and asymptomatic cases should be considered in different age groups.

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MeSH Disease
HGNC Genes
SARS-CoV-2 Proteins

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