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

被引：3

作者：

Chang, Sheng-Nan ^{[1
,2
]}

Hu, Nian-Ze ^{[3
]}

Wu, Jo-Hsuan ^{[4
]}

Cheng, Hsun-Mao ^{[5
]}

Caffrey, James L. ^{[6
]}

Yu, Hsi-Yu ^{[7
,8
]}

Chen, Yih-Sharng ^{[7
,8
]}

Hsu, Jiun ^{[1
,5
,9
]}

Lin, Jou-Wei ^{[1
,2
]}

机构：

[1] Natl Taiwan Univ Hosp, Cardiovasc Ctr, Yunlin Branch, Douliu City, Yunlin, Taiwan

[2] Natl Taiwan Univ, Coll Med, Dept Med, Taipei, Taiwan

[3] Natl Formosa Univ, Dept Informat Management, Huwei, Yunlin, Taiwan

[4] Univ Calif San Diego, Shiley Eye Inst, La Jolla, CA USA

[5] Natl Taiwan Univ Hosp, Yunlin Branch, Off Med Informat, Douliu City, Yunlin, Taiwan

[6] Univ North Texas Hlth Sci Ctr, Physiol & Cardiovasc Res Inst, Ft Worth, TX USA

[7] Natl Taiwan Univ Hosp, Dept Surg, Taipei, Taiwan

[8] Natl Taiwan Univ, Coll Med, Dept Surg, Taipei, Taiwan

[9] Natl Taiwan Univ Hosp, Dept Surg, Yunlin Branch, Douliu City, Yunlin, Taiwan

来源：

EUROPEAN JOURNAL OF MEDICAL RESEARCH | 2023年 / 28卷 / 01期

关键词：

Extracorporeal membrane oxygenation; Machine learning algorithm; Random forest; Oliguria; CARDIOPULMONARY-RESUSCITATION; CARDIAC-ARREST; SURVIVAL; MORTALITY; ADULTS; LIFE;

D O I：

10.1186/s40001-023-01294-1

中图分类号：

R-3 [医学研究方法]; R3 [基础医学];

学科分类号：

1001 ;

摘要：

BackgroundIt 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.MethodsA 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.ResultsUrine 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).ConclusionsOliguria within the first 24 h was deemed especially significant in differentiating in-hospital death and 1 year mortality.

引用

页数：11

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