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The Hidden Factor—Low Quality of Data is a Major Peril in the Identification of Risk Factors for COVID-19 Deaths: A Comment on Nogueira, P.J., et al. “The Role of Health Preconditions on COVID-19 Deaths in Portugal: Evidence from Surveillance Data of the First 20293 Infection Cases”. J. Clin. Med. 2020, 9, 2368

Detalles Bibliográficos
Autores principales: Costa-Santos, Cristina, Ribeiro-Vaz, Inês, Monteiro-Soares, Matilde
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7693923/
https://www.ncbi.nlm.nih.gov/pubmed/33120868
http://dx.doi.org/10.3390/jcm9113442
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author Costa-Santos, Cristina
Ribeiro-Vaz, Inês
Monteiro-Soares, Matilde
author_facet Costa-Santos, Cristina
Ribeiro-Vaz, Inês
Monteiro-Soares, Matilde
author_sort Costa-Santos, Cristina
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spelling pubmed-76939232020-11-28 The Hidden Factor—Low Quality of Data is a Major Peril in the Identification of Risk Factors for COVID-19 Deaths: A Comment on Nogueira, P.J., et al. “The Role of Health Preconditions on COVID-19 Deaths in Portugal: Evidence from Surveillance Data of the First 20293 Infection Cases”. J. Clin. Med. 2020, 9, 2368 Costa-Santos, Cristina Ribeiro-Vaz, Inês Monteiro-Soares, Matilde J Clin Med Comment MDPI 2020-10-27 /pmc/articles/PMC7693923/ /pubmed/33120868 http://dx.doi.org/10.3390/jcm9113442 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Comment
Costa-Santos, Cristina
Ribeiro-Vaz, Inês
Monteiro-Soares, Matilde
The Hidden Factor—Low Quality of Data is a Major Peril in the Identification of Risk Factors for COVID-19 Deaths: A Comment on Nogueira, P.J., et al. “The Role of Health Preconditions on COVID-19 Deaths in Portugal: Evidence from Surveillance Data of the First 20293 Infection Cases”. J. Clin. Med. 2020, 9, 2368
title The Hidden Factor—Low Quality of Data is a Major Peril in the Identification of Risk Factors for COVID-19 Deaths: A Comment on Nogueira, P.J., et al. “The Role of Health Preconditions on COVID-19 Deaths in Portugal: Evidence from Surveillance Data of the First 20293 Infection Cases”. J. Clin. Med. 2020, 9, 2368
title_full The Hidden Factor—Low Quality of Data is a Major Peril in the Identification of Risk Factors for COVID-19 Deaths: A Comment on Nogueira, P.J., et al. “The Role of Health Preconditions on COVID-19 Deaths in Portugal: Evidence from Surveillance Data of the First 20293 Infection Cases”. J. Clin. Med. 2020, 9, 2368
title_fullStr The Hidden Factor—Low Quality of Data is a Major Peril in the Identification of Risk Factors for COVID-19 Deaths: A Comment on Nogueira, P.J., et al. “The Role of Health Preconditions on COVID-19 Deaths in Portugal: Evidence from Surveillance Data of the First 20293 Infection Cases”. J. Clin. Med. 2020, 9, 2368
title_full_unstemmed The Hidden Factor—Low Quality of Data is a Major Peril in the Identification of Risk Factors for COVID-19 Deaths: A Comment on Nogueira, P.J., et al. “The Role of Health Preconditions on COVID-19 Deaths in Portugal: Evidence from Surveillance Data of the First 20293 Infection Cases”. J. Clin. Med. 2020, 9, 2368
title_short The Hidden Factor—Low Quality of Data is a Major Peril in the Identification of Risk Factors for COVID-19 Deaths: A Comment on Nogueira, P.J., et al. “The Role of Health Preconditions on COVID-19 Deaths in Portugal: Evidence from Surveillance Data of the First 20293 Infection Cases”. J. Clin. Med. 2020, 9, 2368
title_sort hidden factor—low quality of data is a major peril in the identification of risk factors for covid-19 deaths: a comment on nogueira, p.j., et al. “the role of health preconditions on covid-19 deaths in portugal: evidence from surveillance data of the first 20293 infection cases”. j. clin. med. 2020, 9, 2368
topic Comment
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7693923/
https://www.ncbi.nlm.nih.gov/pubmed/33120868
http://dx.doi.org/10.3390/jcm9113442
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