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https://hdl.handle.net/10216/149494| Author(s): | Perez Duque, M Saad, NJ Lucaccioni, H Costa, C McMahon, G Machado, F Balasegaram, S Sá Machado, R |
| Title: | Clinical and hospitalisation predictors of COVID-19 in the first month of the pandemic, Portugal |
| Publisher: | Public Library of Science |
| Issue Date: | 2021 |
| Abstract: | COVID-19 mainly presents as a respiratory disease with flu-like symptoms, however, recent findings suggest that non-respiratory symptoms can occur early in the infection and cluster together in different groups in different regions. We collected surveillance data among COVID-19 suspected cases tested in mainland Portugal during the first wave of the pandemic, March-April 2020. A multivariable logistic-regression analysis was performed to ascertain the effects of age, sex, prior medical condition and symptoms on the likelihood of testing positive and hospitalisation. Of 25,926 COVID-19 suspected cases included in this study, 5,298 (20%) tested positive. Symptoms were grouped into ten clusters, of which two main ones: one with cough and fever and another with the remainder. There was a higher odds of a positive test with increasing age, myalgia and headache. The odds of being hospitalised increased with age, presence of fever, dyspnoea, or having a prior medical condition although these results varied by region. Presence of cough and other respiratory symptoms did not predict COVID-19 compared to non-COVID respiratory disease patients in any region. Dyspnoea was a strong determinant of hospitalisation, as well as fever and the presence of a prior medical condition, whereas these results varied by region. |
| DOI: | 10.1371/journal.pone.0260249 |
| URI: | https://hdl.handle.net/10216/149494 |
| Source: | PLoS One. 2021 Nov 19;16(11):e0260249 |
| Document Type: | Artigo em Revista Científica Internacional |
| Rights: | openAccess |
| License: | https://creativecommons.org/licenses/by/4.0/ |
| Appears in Collections: | ISPUP - Artigo em Revista Científica Internacional |
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| perez-duque-po-2021.pdf | 850.76 kB | Adobe PDF | ![]() View/Open |
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