Development of a machine learning algorithm to predict intubation among hospitalized patients with COVID-19.

ABSTRACT:

Purpose

The purpose of this study is to develop a machine learning algorithm to predict future intubation among patients diagnosed or suspected with COVID-19.

Materials and methods

This is a retrospective cohort study of patients diagnosed or under investigation for COVID-19. A machine learning algorithm was trained to predict future presence of intubation based on prior vitals, laboratory, and demographic data. Model performance was compared to ROX index, a validated prognostic tool for prediction of mechanical ventilation.

Results

4087 patients admitted to five hospitals between February 2020 and April 2020 were included. 11.03% of patients were intubated. The machine learning model outperformed the ROX-index, demonstrating an area under the receiver characteristic

SUBMITTER: Arvind V 

PROVIDER: S-EPMC7669246 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature