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Dataset Information

Study on the mortality risk and predictive model for COVID-19 inpatients with pneumonia manifestations.


ABSTRACT:

Background

In 2020, COVID-19 posed a major threat to global public health in a remarkably short period. Although the WHO declared an end to the emergency phase in May 2023, a considerable proportion of recovered cases experience medium- and long-term effects, which pose ongoing health challenges to society. Therefore, it remains necessary to conduct relevant research in the post-epidemic era to explore the risk factors for death in COVID-19 inpatients.

Methods

We determined the mortality of COVID-19 inpatients with pneumonia manifestations through one-year follow-up, utilizing real-world data from three medical centers. Clinical characteristics associated with mortality risk were analyzed by logistic regression. Then, the dataset was randomly partitioned into three sets at a

SUBMITTER: Li Z 

PROVIDER: S-EPMC12903905 | biostudies-literature | 2026

REPOSITORIES: biostudies-literature