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Predictive model for the development of critical coronavirus disease 2019 and its risk factors among patients in Japan
BACKGROUND: This study aimed to examine risk factors associated with critical coronavirus disease 19 (COVID-19) and to establish a risk predictive model for Japanese patients. METHODS: We retrospectively assessed adult Japanese patients diagnosed with COVID-19 at the Japanese Red Cross Medical Cente...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Japanese Respiratory Society. Published by Elsevier B.V.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8433043/ https://www.ncbi.nlm.nih.gov/pubmed/34538593 http://dx.doi.org/10.1016/j.resinv.2021.08.001 |
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author | Muto, Yutaka Awano, Nobuyasu Inomata, Minoru Kuse, Naoyuki Tone, Mari Takada, Kohei Fujimoto, Kazushi Ueda, Akihiro Hayashi, Munehiro Izumo, Takehiro |
author_facet | Muto, Yutaka Awano, Nobuyasu Inomata, Minoru Kuse, Naoyuki Tone, Mari Takada, Kohei Fujimoto, Kazushi Ueda, Akihiro Hayashi, Munehiro Izumo, Takehiro |
author_sort | Muto, Yutaka |
collection | PubMed |
description | BACKGROUND: This study aimed to examine risk factors associated with critical coronavirus disease 19 (COVID-19) and to establish a risk predictive model for Japanese patients. METHODS: We retrospectively assessed adult Japanese patients diagnosed with COVID-19 at the Japanese Red Cross Medical Center, Tokyo, Japan between February 1, 2020 and March 10, 2021. The patients were divided into critical and non-critical groups based on their condition during the clinical courses. Univariate and multivariate logistic regression analyses were performed to investigate the relationship between clinical characteristics and critical illness. Based on the results, we established a predictive model for the development of critical COVID-19. RESULTS: In total, 300 patients were enrolled in this study. Among them, 86 were included in the critical group. Analyses revealed that age ≥65 y, hemodialysis, need for O(2) supplementation upon diagnosis, and an initial serum C-reactive protein level of ≥6.5 mg/dL were independently associated with the development of critical COVID-19. Next, a predictive model for the development of critical COVID-19 was created, and this included the following variables: age ≥65 y, male sex, diabetes, hemodialysis, need for O(2) supplementation upon diagnosis, and an initial serum C-reactive protein level of ≥6.5 mg/dL. The area under the receiver operating characteristic curve of the model was 0.86 (95% confidence interval, 0.81–0.90). Using a cutoff score of 12, the positive and negative predictive values of 74.0% and 80.4% were obtained, respectively. CONCLUSIONS: Upon diagnosis, the predictive model can be used to identify adult Japanese patients with COVID-19 who will require intensive treatment. |
format | Online Article Text |
id | pubmed-8433043 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | The Japanese Respiratory Society. Published by Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-84330432021-09-13 Predictive model for the development of critical coronavirus disease 2019 and its risk factors among patients in Japan Muto, Yutaka Awano, Nobuyasu Inomata, Minoru Kuse, Naoyuki Tone, Mari Takada, Kohei Fujimoto, Kazushi Ueda, Akihiro Hayashi, Munehiro Izumo, Takehiro Respir Investig Original Article BACKGROUND: This study aimed to examine risk factors associated with critical coronavirus disease 19 (COVID-19) and to establish a risk predictive model for Japanese patients. METHODS: We retrospectively assessed adult Japanese patients diagnosed with COVID-19 at the Japanese Red Cross Medical Center, Tokyo, Japan between February 1, 2020 and March 10, 2021. The patients were divided into critical and non-critical groups based on their condition during the clinical courses. Univariate and multivariate logistic regression analyses were performed to investigate the relationship between clinical characteristics and critical illness. Based on the results, we established a predictive model for the development of critical COVID-19. RESULTS: In total, 300 patients were enrolled in this study. Among them, 86 were included in the critical group. Analyses revealed that age ≥65 y, hemodialysis, need for O(2) supplementation upon diagnosis, and an initial serum C-reactive protein level of ≥6.5 mg/dL were independently associated with the development of critical COVID-19. Next, a predictive model for the development of critical COVID-19 was created, and this included the following variables: age ≥65 y, male sex, diabetes, hemodialysis, need for O(2) supplementation upon diagnosis, and an initial serum C-reactive protein level of ≥6.5 mg/dL. The area under the receiver operating characteristic curve of the model was 0.86 (95% confidence interval, 0.81–0.90). Using a cutoff score of 12, the positive and negative predictive values of 74.0% and 80.4% were obtained, respectively. CONCLUSIONS: Upon diagnosis, the predictive model can be used to identify adult Japanese patients with COVID-19 who will require intensive treatment. The Japanese Respiratory Society. Published by Elsevier B.V. 2021-11 2021-09-11 /pmc/articles/PMC8433043/ /pubmed/34538593 http://dx.doi.org/10.1016/j.resinv.2021.08.001 Text en © 2021 The Japanese Respiratory Society. Published by Elsevier B.V. All rights reserved. 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 Muto, Yutaka Awano, Nobuyasu Inomata, Minoru Kuse, Naoyuki Tone, Mari Takada, Kohei Fujimoto, Kazushi Ueda, Akihiro Hayashi, Munehiro Izumo, Takehiro Predictive model for the development of critical coronavirus disease 2019 and its risk factors among patients in Japan |
title | Predictive model for the development of critical coronavirus disease 2019 and its risk factors among patients in Japan |
title_full | Predictive model for the development of critical coronavirus disease 2019 and its risk factors among patients in Japan |
title_fullStr | Predictive model for the development of critical coronavirus disease 2019 and its risk factors among patients in Japan |
title_full_unstemmed | Predictive model for the development of critical coronavirus disease 2019 and its risk factors among patients in Japan |
title_short | Predictive model for the development of critical coronavirus disease 2019 and its risk factors among patients in Japan |
title_sort | predictive model for the development of critical coronavirus disease 2019 and its risk factors among patients in japan |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8433043/ https://www.ncbi.nlm.nih.gov/pubmed/34538593 http://dx.doi.org/10.1016/j.resinv.2021.08.001 |
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