Prediction of respiratory decompensation in Covid-19 patients using machine learning: The READY trial.

ABSTRACT:

Background

Currently, physicians are limited in their ability to provide an accurate prognosis for COVID-19 positive patients. Existing scoring systems have been ineffective for identifying patient decompensation. Machine learning (ML) may offer an alternative strategy. A prospectively validated method to predict the need for ventilation in COVID-19 patients is essential to help triage patients, allocate resources, and prevent emergency intubations and their associated risks.

Methods

In a multicenter clinical trial, we evaluated the performance of a machine learning algorithm for prediction of invasive mechanical ventilation of COVID-19 patients within 24 h of an initial encounter. We enrolled patients with a COVID-19 diagnosis who were admitted to five United States health

SUBMITTER: Burdick H 

PROVIDER: S-EPMC7410013 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature