Predictive model for the development of critical coronavirus disease 2019 and its risk factors among patients in Japan
| Autor: | Kohei Takada, Munehiro Hayashi, Takehiro Izumo, Nobuyasu Awano, Kazushi Fujimoto, Akihiro Ueda, Naoyuki Kuse, Minoru Inomata, Mari Tone, Yutaka Muto |
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| Rok vydání: | 2021 |
| Předmět: |
Male
Pulmonary and Respiratory Medicine medicine.medical_specialty Critical Illness medicine.medical_treatment Disease Logistic regression Extracorporeal Membrane Oxygenation Japan Predictive Value of Tests Renal Dialysis Risk Factors Internal medicine Diabetes mellitus Positive predicative value Humans Medicine Aged Retrospective Studies Aged 80 and over Coronavirus disease 2019 Receiver operating characteristic SARS-CoV-2 business.industry Univariate COVID-19 Prognosis medicine.disease Confidence interval C-Reactive Protein Predictive model Japanese Female Original Article Hemodialysis business |
| Zdroj: | Respiratory Investigation |
| ISSN: | 2212-5345 |
| DOI: | 10.1016/j.resinv.2021.08.001 |
| Popis: | 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 O2 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 O2 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. |
| Databáze: | OpenAIRE |
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