Machine learning-based scoring system to predict in-hospital outcomes in patients hospitalized with COVID-19.

ABSTRACT:

Background

The evolution of patients hospitalized with coronavirus disease 2019 (COVID-19) is still hard to predict, even after several months of dealing with the pandemic.

Aims

To develop and validate a score to predict outcomes in patients hospitalized with COVID-19.

Methods

All consecutive adults hospitalized for COVID-19 from February to April 2020 were included in a nationwide observational study. Primary composite outcome was transfer to an intensive care unit from an emergency department or conventional ward, or in-hospital death. A score that estimates the risk of experiencing the primary outcome was constructed from a derivation cohort using stacked LASSO (Least Absolute Shrinkage and Selection Operator), and was tested in a validation cohort.

Results

SUBMITTER: Weizman O 

PROVIDER: S-EPMC9595484 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature