Machine Learning Prediction Models for Mechanically Ventilated Patients: Analyses of the MIMIC-III Database.

ABSTRACT: Background: Mechanically ventilated patients in the intensive care unit (ICU) have high mortality rates. There are multiple prediction scores, such as the Simplified Acute Physiology Score II (SAPS II), Oxford Acute Severity of Illness Score (OASIS), and Sequential Organ Failure Assessment (SOFA), widely used in the general ICU population. We aimed to establish prediction scores on mechanically ventilated patients with the combination of these disease severity scores and other features available on the first day of admission. Methods: A retrospective administrative database study from the Medical Information Mart for Intensive Care (MIMIC-III) database was conducted. The exposures of interest consisted of the demographics, pre-ICU comorbidity, ICU diagnosis, disease severity

SUBMITTER: Zhu Y 

PROVIDER: S-EPMC8280779 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature