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Sociodemographic predictors of confirmed COVID-19 mortality and hospitalization among patients in Saudi Arabia: Analyzing a national COVID-19 database

BACKGROUND: Even with the widespread availability of vaccines for the COVID-19 disease, there is no sign of decline in the rate of spread of the disease. Based on findings of different studies across the globe, the disease is characterized by poor outcomes in specific sociodemographic categories suc...

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Autores principales: Alothaid, Hani, Alshehri, Mohammed Ali, Yusuf, Azeez Oriyomi, Alzahrani, Mohammad Eid, McDaniel, Justin, Alamri, Saeed, Aldughaim, Mohammed S., Alswaidi, Fahad M., Al-Qahtani, Ahmed A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Author(s). Published by Elsevier Ltd on behalf of King Saud Bin Abdulaziz University for Health Sciences. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9065652/
https://www.ncbi.nlm.nih.gov/pubmed/35550940
http://dx.doi.org/10.1016/j.jiph.2022.04.015
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author Alothaid, Hani
Alshehri, Mohammed Ali
Yusuf, Azeez Oriyomi
Alzahrani, Mohammad Eid
McDaniel, Justin
Alamri, Saeed
Aldughaim, Mohammed S.
Alswaidi, Fahad M.
Al-Qahtani, Ahmed A.
author_facet Alothaid, Hani
Alshehri, Mohammed Ali
Yusuf, Azeez Oriyomi
Alzahrani, Mohammad Eid
McDaniel, Justin
Alamri, Saeed
Aldughaim, Mohammed S.
Alswaidi, Fahad M.
Al-Qahtani, Ahmed A.
author_sort Alothaid, Hani
collection PubMed
description BACKGROUND: Even with the widespread availability of vaccines for the COVID-19 disease, there is no sign of decline in the rate of spread of the disease. Based on findings of different studies across the globe, the disease is characterized by poor outcomes in specific sociodemographic categories such as age, gender and presence of symptoms. METHODS: In this study, we carried out a multivariable logistic regression analysis on a national database (HESN+) of confirmed COVID-19 cases in Saudi Arabia to determine predictors of hospitalization and mortality for these patients. RESULTS: Data was extracted for 328,301 confirmed COVID- 19 patients (mean age (SD) = 37.79 (1.68)) with 34.92% females and 65.08% males. Of these, 59.87% were Saudi Arabian citizens and 40.13% were non-Saudi. 68.91% of cases were discovered in Riyadh (n = 67,384), Makkah (n = 72,590) and the Eastern Province (n = 79,666). 72.2% of all cases were diagnosed and treated by the Ministry of Health (MOH). Of all confirmed cases, 95.28% showed one or more symptoms associated with COVID-19. 5.48% of these were hospitalized and 1.11% died. Predictors of mortality and hospitalization, respectively, included age (OR; 1.088 and 1.03), being male (OR; 1.443 and 1.138), nationality (OR; 2.11 and 1.993), presence of symptoms (OR; 1.816 and 4.386), and the health care sector in which patients received treatment (MOH OR; 1.352 and 4.731). CONCLUSION: We found that COVID-19-related hospitalization or mortality was higher among males, older adults, and patients showing one or more symptoms, and mortality likelihood was more than fourfold for patients treated by the MOH. Immigrants were also more likely to be hospitalized or die from COVID-19 infection compared to Saudi nationals.
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spelling pubmed-90656522022-05-04 Sociodemographic predictors of confirmed COVID-19 mortality and hospitalization among patients in Saudi Arabia: Analyzing a national COVID-19 database Alothaid, Hani Alshehri, Mohammed Ali Yusuf, Azeez Oriyomi Alzahrani, Mohammad Eid McDaniel, Justin Alamri, Saeed Aldughaim, Mohammed S. Alswaidi, Fahad M. Al-Qahtani, Ahmed A. J Infect Public Health Original Article BACKGROUND: Even with the widespread availability of vaccines for the COVID-19 disease, there is no sign of decline in the rate of spread of the disease. Based on findings of different studies across the globe, the disease is characterized by poor outcomes in specific sociodemographic categories such as age, gender and presence of symptoms. METHODS: In this study, we carried out a multivariable logistic regression analysis on a national database (HESN+) of confirmed COVID-19 cases in Saudi Arabia to determine predictors of hospitalization and mortality for these patients. RESULTS: Data was extracted for 328,301 confirmed COVID- 19 patients (mean age (SD) = 37.79 (1.68)) with 34.92% females and 65.08% males. Of these, 59.87% were Saudi Arabian citizens and 40.13% were non-Saudi. 68.91% of cases were discovered in Riyadh (n = 67,384), Makkah (n = 72,590) and the Eastern Province (n = 79,666). 72.2% of all cases were diagnosed and treated by the Ministry of Health (MOH). Of all confirmed cases, 95.28% showed one or more symptoms associated with COVID-19. 5.48% of these were hospitalized and 1.11% died. Predictors of mortality and hospitalization, respectively, included age (OR; 1.088 and 1.03), being male (OR; 1.443 and 1.138), nationality (OR; 2.11 and 1.993), presence of symptoms (OR; 1.816 and 4.386), and the health care sector in which patients received treatment (MOH OR; 1.352 and 4.731). CONCLUSION: We found that COVID-19-related hospitalization or mortality was higher among males, older adults, and patients showing one or more symptoms, and mortality likelihood was more than fourfold for patients treated by the MOH. Immigrants were also more likely to be hospitalized or die from COVID-19 infection compared to Saudi nationals. The Author(s). Published by Elsevier Ltd on behalf of King Saud Bin Abdulaziz University for Health Sciences. 2022-06 2022-05-04 /pmc/articles/PMC9065652/ /pubmed/35550940 http://dx.doi.org/10.1016/j.jiph.2022.04.015 Text en © 2022 The Author(s) Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Original Article
Alothaid, Hani
Alshehri, Mohammed Ali
Yusuf, Azeez Oriyomi
Alzahrani, Mohammad Eid
McDaniel, Justin
Alamri, Saeed
Aldughaim, Mohammed S.
Alswaidi, Fahad M.
Al-Qahtani, Ahmed A.
Sociodemographic predictors of confirmed COVID-19 mortality and hospitalization among patients in Saudi Arabia: Analyzing a national COVID-19 database
title Sociodemographic predictors of confirmed COVID-19 mortality and hospitalization among patients in Saudi Arabia: Analyzing a national COVID-19 database
title_full Sociodemographic predictors of confirmed COVID-19 mortality and hospitalization among patients in Saudi Arabia: Analyzing a national COVID-19 database
title_fullStr Sociodemographic predictors of confirmed COVID-19 mortality and hospitalization among patients in Saudi Arabia: Analyzing a national COVID-19 database
title_full_unstemmed Sociodemographic predictors of confirmed COVID-19 mortality and hospitalization among patients in Saudi Arabia: Analyzing a national COVID-19 database
title_short Sociodemographic predictors of confirmed COVID-19 mortality and hospitalization among patients in Saudi Arabia: Analyzing a national COVID-19 database
title_sort sociodemographic predictors of confirmed covid-19 mortality and hospitalization among patients in saudi arabia: analyzing a national covid-19 database
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9065652/
https://www.ncbi.nlm.nih.gov/pubmed/35550940
http://dx.doi.org/10.1016/j.jiph.2022.04.015
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