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Predicting severe or critical symptoms in hospitalized patients with COVID-19 from Yichang, China

Objectives: We aimed to identify potential risk factors for severe or critical coronavirus disease 2019 (COVID-19) and establish a prediction model based on significant factors. Methods: A total of 370 patients with COVID-19 were consecutively enrolled at The Third People’s Hospital of Yichang from...

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Autores principales: Chen, Xin, Peng, Feng, Zhou, Xiaoni, Zhu, Jiang, Gong, Yingying, Shupeng, Wang, Niu, Wenquan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7880337/
https://www.ncbi.nlm.nih.gov/pubmed/33318316
http://dx.doi.org/10.18632/aging.202261
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author Chen, Xin
Peng, Feng
Zhou, Xiaoni
Zhu, Jiang
Chen, Xin
Gong, Yingying
Shupeng, Wang
Niu, Wenquan
author_facet Chen, Xin
Peng, Feng
Zhou, Xiaoni
Zhu, Jiang
Chen, Xin
Gong, Yingying
Shupeng, Wang
Niu, Wenquan
author_sort Chen, Xin
collection PubMed
description Objectives: We aimed to identify potential risk factors for severe or critical coronavirus disease 2019 (COVID-19) and establish a prediction model based on significant factors. Methods: A total of 370 patients with COVID-19 were consecutively enrolled at The Third People’s Hospital of Yichang from January to March 2020. COVID-19 was diagnosed according to the COVID-19 diagnosis and treatment plan released by the National Health and Health Committee of China. Effect-size estimates are summarized as odds ratio (OR) and 95% confidence interval (CI). Results: 326 patients were diagnosed with mild or ordinary COVID-19, and 44 with severe or critical COVID-19. After propensity score matching and statistical adjustment, eight factors were significantly associated with severe or critical COVID-19 (p <0.05) relative to mild or ordinary COVID-19. Due to strong pairwise correlations, only five factors, including diagnostic delay (OR, 95% CI, p: 1.08, 1.02 to 1.17, 0.048), albumin (0.82, 0.75 to 0.91, <0.001), lactate dehydrogenase (1.56, 1.14 to 2.13, 0.011), white blood cell (1.27, 1.08 to 1.50, 0.004), and neutrophil (1.40, 1.16 to 1.70, <0.001), were retained for model construction and performance assessment. The nomogram model based on the five factors had good prediction capability and accuracy (C-index: 90.6%). Conclusions: Our findings provide evidence for the significant contribution of five independent factors to the risk of severe or critical COVID-19, and their prediction was reinforced in a nomogram model.
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spelling pubmed-78803372021-02-22 Predicting severe or critical symptoms in hospitalized patients with COVID-19 from Yichang, China Chen, Xin Peng, Feng Zhou, Xiaoni Zhu, Jiang Chen, Xin Gong, Yingying Shupeng, Wang Niu, Wenquan Aging (Albany NY) Research Paper Objectives: We aimed to identify potential risk factors for severe or critical coronavirus disease 2019 (COVID-19) and establish a prediction model based on significant factors. Methods: A total of 370 patients with COVID-19 were consecutively enrolled at The Third People’s Hospital of Yichang from January to March 2020. COVID-19 was diagnosed according to the COVID-19 diagnosis and treatment plan released by the National Health and Health Committee of China. Effect-size estimates are summarized as odds ratio (OR) and 95% confidence interval (CI). Results: 326 patients were diagnosed with mild or ordinary COVID-19, and 44 with severe or critical COVID-19. After propensity score matching and statistical adjustment, eight factors were significantly associated with severe or critical COVID-19 (p <0.05) relative to mild or ordinary COVID-19. Due to strong pairwise correlations, only five factors, including diagnostic delay (OR, 95% CI, p: 1.08, 1.02 to 1.17, 0.048), albumin (0.82, 0.75 to 0.91, <0.001), lactate dehydrogenase (1.56, 1.14 to 2.13, 0.011), white blood cell (1.27, 1.08 to 1.50, 0.004), and neutrophil (1.40, 1.16 to 1.70, <0.001), were retained for model construction and performance assessment. The nomogram model based on the five factors had good prediction capability and accuracy (C-index: 90.6%). Conclusions: Our findings provide evidence for the significant contribution of five independent factors to the risk of severe or critical COVID-19, and their prediction was reinforced in a nomogram model. Impact Journals 2020-12-09 /pmc/articles/PMC7880337/ /pubmed/33318316 http://dx.doi.org/10.18632/aging.202261 Text en Copyright: © 2021 Chen et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/3.0/) (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Paper
Chen, Xin
Peng, Feng
Zhou, Xiaoni
Zhu, Jiang
Chen, Xin
Gong, Yingying
Shupeng, Wang
Niu, Wenquan
Predicting severe or critical symptoms in hospitalized patients with COVID-19 from Yichang, China
title Predicting severe or critical symptoms in hospitalized patients with COVID-19 from Yichang, China
title_full Predicting severe or critical symptoms in hospitalized patients with COVID-19 from Yichang, China
title_fullStr Predicting severe or critical symptoms in hospitalized patients with COVID-19 from Yichang, China
title_full_unstemmed Predicting severe or critical symptoms in hospitalized patients with COVID-19 from Yichang, China
title_short Predicting severe or critical symptoms in hospitalized patients with COVID-19 from Yichang, China
title_sort predicting severe or critical symptoms in hospitalized patients with covid-19 from yichang, china
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7880337/
https://www.ncbi.nlm.nih.gov/pubmed/33318316
http://dx.doi.org/10.18632/aging.202261
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