External Validation and Comparison of Statistical and Machine Learning-Based Models in Predicting Outcomes Following Out-of-Hospital Cardiac Arrest: A Multicenter Retrospective Analysis.

ABSTRACT:

Background

The aim of this study was to validate and compare the performance of statistical (Utstein-Based Return of Spontaneous Circulation and Shockable Rhythm-Witness-Age-pH) and machine learning-based (Prehospital Return of Spontaneous Circulation and Swedish Cardiac Arrest Risk Score) models in predicting the outcomes following out-of-hospital cardiac arrest and to assess the impact of the COVID-19 pandemic on the models' performance.

Methods and results

This retrospective analysis included adult patients with out-of-hospital cardiac arrest treated at 3 academic hospitals between 2015 and 2023. The primary outcome was neurological outcomes at hospital discharge. Patients were divided into pre- (2015-2019) and post-2020 (2020-2023) subgroups to examine the effect of the

SUBMITTER: Wang CH 

PROVIDER: S-EPMC11935587 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature