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Open Access 01-12-2023 | ECMO | Research

Urine output as one of the most important features in differentiating in-hospital death among patients receiving extracorporeal membrane oxygenation: a random forest approach

Authors: Sheng-Nan Chang, Nian-Ze Hu, Jo-Hsuan Wu, Hsun-Mao Cheng, James L. Caffrey, Hsi-Yu Yu, Yih-Sharng Chen, Jiun Hsu, Jou-Wei Lin

Published in: European Journal of Medical Research | Issue 1/2023

Abstract

Background

It is common to support cardiovascular function in critically ill patients with extracorporeal membrane oxygenation (ECMO). The purpose of this study was to identify patients receiving ECMO with a considerable risk of dying in hospital using machine learning algorithms.

Methods

A total of 1342 adult patients on ECMO support were randomly assigned to the training and test groups. The discriminatory power (DP) for predicting in-hospital mortality was tested using both random forest (RF) and logistic regression (LR) algorithms.

Results

Urine output on the first day of ECMO implantation was found to be one of the most predictive features that were related to in-hospital death in both RF and LR models. For those with oliguria, the hazard ratio for 1 year mortality was 1.445 (p < 0.001, 95% CI 1.265–1.650).

Conclusions

Oliguria within the first 24 h was deemed especially significant in differentiating in-hospital death and 1 year mortality.

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Title: Urine output as one of the most important features in differentiating in-hospital death among patients receiving extracorporeal membrane oxygenation: a random forest approach
Authors: Sheng-Nan Chang
Nian-Ze Hu
Jo-Hsuan Wu
Hsun-Mao Cheng
James L. Caffrey
Hsi-Yu Yu
Yih-Sharng Chen
Jiun Hsu
Jou-Wei Lin
Publication date: 01-12-2023
Publisher: BioMed Central
Keywords: ECMO
ECMO
Cardiopulmonary Resuscitation
Published in: European Journal of Medical Research / Issue 1/2023
Electronic ISSN: 2047-783X
DOI: https://doi.org/10.1186/s40001-023-01294-1

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Urine output as one of the most important features in differentiating in-hospital death among patients receiving extracorporeal membrane oxygenation: a random forest approach

Abstract

Background

Methods

Results

Conclusions

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Background

Methods

Results

Conclusions

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