Clinical characteristics and prediction model of re-positive nucleic acid tests among Omicron infections by machine learning: a real-world study of 35,488 cases.

ABSTRACT:

Background

During the Omicron BA.2 variant outbreak in Shanghai, China, from April to May 2022, PCR nucleic acid test re-positivity (TR) occurred frequently, yet the risk factors and predictive models for TR remain unclear. This study aims to identify the factors influencing Omicron TR and to develop machine learning models to predict TR risk. Accurately predicting re-positive patients is crucial for identifying high-risk individuals, optimizing resource allocation, and developing personalized treatment and management plans, thereby effectively controlling the spread of the epidemic, reducing community burden, and ensuring public health.

Methods

A retrospective study was conducted among individuals infected with Omicron BA.2 variant from April 12 to May 25, 2022, in the larg

SUBMITTER: Cao Y 

PROVIDER: S-EPMC11654198 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature