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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 |
Sumario: | 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. |
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