Author: Fukushima, Kazuaki; Yamada, Yuta; Fujiwara, Sho; Tanaka, Masaru; Kobayashi, Taiichiro; Yajima, Keishiro; Tanaka, Kozue; Sekiya, Noritaka; Imamura, Akifumi
Title: Development of a Risk Prediction Score to Identify High-Risk Groups for the Critical Coronavirus Disease 2019 (COVID-19) in Japan Cord-id: kb17aq44 Document date: 2021_1_1
ID: kb17aq44
Snippet: Coronavirus disease 2019 (COVID-19) emerged in mid-December 2019 and has rapidly spread worldwide. We conducted a retrospective analysis of data from patients with COVID-19 to construct a simple risk prediction score to be implemented in prehospital settings. Patients were classified into critical and non-critical groups based on disease severity during hospitalization. Multivariate analysis was performed to identify independent risk factors and develop a risk prediction score. A total of 234 pa
Document: Coronavirus disease 2019 (COVID-19) emerged in mid-December 2019 and has rapidly spread worldwide. We conducted a retrospective analysis of data from patients with COVID-19 to construct a simple risk prediction score to be implemented in prehospital settings. Patients were classified into critical and non-critical groups based on disease severity during hospitalization. Multivariate analysis was performed to identify independent risk factors and develop a risk prediction score. A total of 234 patients were included in the study. The median age of the critical group was significantly older than that of the non-critical group (68.0 and 44.0 years, respectively), and the percentage of males in the critical group was higher than that in the non-critical group (90.2% and 60.6%, respectively). Multivariate analysis revealed that factors such as age ≥ 45 years, male sex, comorbidities such as hypertension and cancer, and having fever and dyspnea on admission were independently associated with the critical COVID-19 infection. No critical events were noted in patients with a total risk factor score of ≤ 2. Contrastingly, patients with a total risk factor score ≥ 4 were more likely to have critical COVID-19 infection. This risk prediction score may be useful in identifying critical COVID-19 infections.
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