Novel criteria to classify ARDS severity using a machine learning approach.

ABSTRACT:

Background

Usually, arterial oxygenation in patients with the acute respiratory distress syndrome (ARDS) improves substantially by increasing the level of positive end-expiratory pressure (PEEP). Herein, we are proposing a novel variable [PaO₂/(FiO₂xPEEP) or P/FP_E] for PEEP ≥ 5 to address Berlin's definition gap for ARDS severity by using machine learning (ML) approaches.

Methods

We examined P/FP_E values delimiting the boundaries of mild, moderate, and severe ARDS. We applied ML to predict ARDS severity after onset over time by comparing current Berlin PaO₂/FiO₂ criteria with P/FP_E under three different scenarios. We extracted clinical data from the first 3 ICU days after ARDS onset (N = 2738, 1519,

SUBMITTER: Sayed M 

PROVIDER: S-EPMC8056190 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature