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Dataset Information

Predicting invasive mechanical ventilation in COVID 19 patients: A validation study.


ABSTRACT:

Introduction

The decision to intubate and ventilate a patient is mainly clinical. Both delaying intubation (when needed) and unnecessarily invasively ventilating (when it can be avoided) are harmful. We recently developed an algorithm predicting respiratory failure and invasive mechanical ventilation in COVID-19 patients. This is an internal validation study of this model, which also suggests a categorized "time-weighted" model.

Methods

We used a dataset of COVID-19 patients who were admitted to Rabin Medical Center after the algorithm was developed. We evaluated model performance in predicting ventilation, regarding the actual endpoint of each patient. We further categorized each patient into one of four categories, based on the strength of the prediction of ventilation ove

SUBMITTER: Statlender L 

PROVIDER: S-EPMC10760863 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature