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National early warning score (NEWS) 2 predicts hospital mortality from COVID-19 patients
BACKGROUND: COVID-19 has a high risk of mortality, especially in patients with comorbid diseases such as cardiac disease, type 2 diabetes mellitus, chronic kidney disease, and hypertension. The National Early Warning Score (NEWS) is a tool that helps in identifying changes in patient conditions that...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8902861/ https://www.ncbi.nlm.nih.gov/pubmed/35284070 http://dx.doi.org/10.1016/j.amsu.2022.103462 |
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author | Wibisono, Eric Hadi, Usman Bramantono Arfijanto, Muhammad Vitanata Rusli, Musofa Rahman, Brian Eka Asmarawati, Tri Pudy Choirunnisa, Miftahani Leo Rahayu, Dwi Retno Puji |
author_facet | Wibisono, Eric Hadi, Usman Bramantono Arfijanto, Muhammad Vitanata Rusli, Musofa Rahman, Brian Eka Asmarawati, Tri Pudy Choirunnisa, Miftahani Leo Rahayu, Dwi Retno Puji |
author_sort | Wibisono, Eric |
collection | PubMed |
description | BACKGROUND: COVID-19 has a high risk of mortality, especially in patients with comorbid diseases such as cardiac disease, type 2 diabetes mellitus, chronic kidney disease, and hypertension. The National Early Warning Score (NEWS) is a tool that helps in identifying changes in patient conditions that require intensive treatment. OBJECTIVE: Analyzing NEWS-2 to identify the risk of death in COVID-19 patients. METHODS: This research was conducted from June to July 2020 by using quota sampling. The number of participants in this study was 112 participants (case group = 56 participants and control group = 56 participants). Participants were assessed for NEWS-2 and evaluated for their treatment outcomes. The analysis used in this study was the Chi-squared test and logistic regression with p < 0.05. RESULTS: 45 participants died of having NEWS-2 score >5, and as many as 50 participants showed an improvement in their condition by having NEWS-2 score 5 (OR = 34.091; p < 0.001). The accuracy of NEWS-2's assessment of mortality of COVID-19 patients had a sensitivity of 80.4% and a specificity of 89.3%. There were several comorbid diseases that had a significant relationship on mortality of COVID-19 patients such as cardiac disease (β = 5.907; 1.107–31.527 95% CI; p = 0.038), T2DM (β = 3.143; 1.269–7.783 95% CI; p = 0.013), CKD (β = 3.851; 1.195–12.416 95% CI; p = 0.024), and hypertension (β = 2.820; 1.075–7.399 95% CI; p = 0.035). CONCLUSION: The NEWS-2 can be used to identify the risk of death of COVID-19 patients. |
format | Online Article Text |
id | pubmed-8902861 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-89028612022-03-09 National early warning score (NEWS) 2 predicts hospital mortality from COVID-19 patients Wibisono, Eric Hadi, Usman Bramantono Arfijanto, Muhammad Vitanata Rusli, Musofa Rahman, Brian Eka Asmarawati, Tri Pudy Choirunnisa, Miftahani Leo Rahayu, Dwi Retno Puji Ann Med Surg (Lond) Cross-sectional Study BACKGROUND: COVID-19 has a high risk of mortality, especially in patients with comorbid diseases such as cardiac disease, type 2 diabetes mellitus, chronic kidney disease, and hypertension. The National Early Warning Score (NEWS) is a tool that helps in identifying changes in patient conditions that require intensive treatment. OBJECTIVE: Analyzing NEWS-2 to identify the risk of death in COVID-19 patients. METHODS: This research was conducted from June to July 2020 by using quota sampling. The number of participants in this study was 112 participants (case group = 56 participants and control group = 56 participants). Participants were assessed for NEWS-2 and evaluated for their treatment outcomes. The analysis used in this study was the Chi-squared test and logistic regression with p < 0.05. RESULTS: 45 participants died of having NEWS-2 score >5, and as many as 50 participants showed an improvement in their condition by having NEWS-2 score 5 (OR = 34.091; p < 0.001). The accuracy of NEWS-2's assessment of mortality of COVID-19 patients had a sensitivity of 80.4% and a specificity of 89.3%. There were several comorbid diseases that had a significant relationship on mortality of COVID-19 patients such as cardiac disease (β = 5.907; 1.107–31.527 95% CI; p = 0.038), T2DM (β = 3.143; 1.269–7.783 95% CI; p = 0.013), CKD (β = 3.851; 1.195–12.416 95% CI; p = 0.024), and hypertension (β = 2.820; 1.075–7.399 95% CI; p = 0.035). CONCLUSION: The NEWS-2 can be used to identify the risk of death of COVID-19 patients. Elsevier 2022-03-08 /pmc/articles/PMC8902861/ /pubmed/35284070 http://dx.doi.org/10.1016/j.amsu.2022.103462 Text en © 2022 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Cross-sectional Study Wibisono, Eric Hadi, Usman Bramantono Arfijanto, Muhammad Vitanata Rusli, Musofa Rahman, Brian Eka Asmarawati, Tri Pudy Choirunnisa, Miftahani Leo Rahayu, Dwi Retno Puji National early warning score (NEWS) 2 predicts hospital mortality from COVID-19 patients |
title | National early warning score (NEWS) 2 predicts hospital mortality from COVID-19 patients |
title_full | National early warning score (NEWS) 2 predicts hospital mortality from COVID-19 patients |
title_fullStr | National early warning score (NEWS) 2 predicts hospital mortality from COVID-19 patients |
title_full_unstemmed | National early warning score (NEWS) 2 predicts hospital mortality from COVID-19 patients |
title_short | National early warning score (NEWS) 2 predicts hospital mortality from COVID-19 patients |
title_sort | national early warning score (news) 2 predicts hospital mortality from covid-19 patients |
topic | Cross-sectional Study |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8902861/ https://www.ncbi.nlm.nih.gov/pubmed/35284070 http://dx.doi.org/10.1016/j.amsu.2022.103462 |
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