External validation of a machine learning model to predict hemodynamic instability in intensive care unit.

ABSTRACT:

Background

Early prediction model of hemodynamic instability has the potential to improve the critical care, whereas limited external validation on the generalizability. We aimed to independently validate the Hemodynamic Stability Index (HSI), a multi-parameter machine learning model, in predicting hemodynamic instability in Asian patients.

Method

Hemodynamic instability was marked by using inotropic, vasopressor, significant fluid therapy, and/or blood transfusions. This retrospective study included among 15,967 ICU patients who aged 20 years or older (not included 20 years) and stayed in ICU for more than 6 h admitted to Taipei Veteran General Hospital (TPEVGH) between January 1, 2010, and March 31, 2020, of whom hemodynamic instability occurred in 3053 patients (prevalenc

SUBMITTER: Dung-Hung C 

PROVIDER: S-EPMC9281065 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature