five

Patient characteristics.

收藏
NIAID Data Ecosystem2026-05-10 收录
下载链接:
https://figshare.com/articles/dataset/Patient_characteristics_/30107085
下载链接
链接失效反馈
官方服务:
资源简介:
Although the symptoms of Coronavirus Disease 2019 (COVID-19) omicron strains are generally mild, some individuals with initially mild symptoms later required supplemental oxygen or hospitalization, while others died, highlighting the importance of rapid diagnosis and early treatment for such patients. Therefore, this study evaluated the benefit of a combined approach to identify individuals at risk of severe illness due to COVID-19 using urinary L-type fatty acid-binding protein (L-FABP) levels and the Sequential Organ Failure Assessment (SOFA) scores calculated from blood tests for pre-admission screening of patients with COVID-19. L-FABP, a non-invasive urine biomarker, and the SOFA score, an established method for assessing organ failure severity, were evaluated in conjunction with patient data collected from 842 individuals admitted to a hospital in Tokyo, Japan. The combined approach demonstrated a higher accuracy in identifying patients at risk of severe illness compared to the L-FABP levels or SOFA scores alone. Thus, the results suggest that a two-tiered screening process, utilizing measurement of L-FABP levels as an initial rapid test, followed by SOFA score assessment for high-risk patients, results in efficient pre-admission screening and improved patient management. In conclusion, this study underscores the potential of combining L-FABP levels and SOFA scores for optimizing patient care during the ongoing COVID-19 pandemic, emphasizing the need for further validation and refinement of the predictive models.
创建时间:
2025-09-11
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作