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The Challenges in Predicting ECMO Survival, and a Path Forward
Extracorporeal membrane oxygenation (ECMO) support is a life-saving but complex technique for patients suffering from severe cardiac or pulmonary dysfunction. Increasingly greater utilization in the last 15 years means that a suite of mortality risk analytics is both feasible for researchers and req...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5671797/ https://www.ncbi.nlm.nih.gov/pubmed/28338480 http://dx.doi.org/10.1097/MAT.0000000000000572 |
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author | Huesch, Marco Brehm, Christopher |
author_facet | Huesch, Marco Brehm, Christopher |
author_sort | Huesch, Marco |
collection | PubMed |
description | Extracorporeal membrane oxygenation (ECMO) support is a life-saving but complex technique for patients suffering from severe cardiac or pulmonary dysfunction. Increasingly greater utilization in the last 15 years means that a suite of mortality risk analytics is both feasible for researchers and required by clinicians, patients, administrators, and insurers. We argue that to date, research into such risk analytics has been insufficient and does not adequately reflect the various indications and configurations of extracorporeal life support (ECLS). We propose a path to address these challenges and ensure that clinicians and researchers obtain robust, specific, risk analytics. |
format | Online Article Text |
id | pubmed-5671797 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Lippincott Williams & Wilkins |
record_format | MEDLINE/PubMed |
spelling | pubmed-56717972017-11-22 The Challenges in Predicting ECMO Survival, and a Path Forward Huesch, Marco Brehm, Christopher ASAIO J Brief Communication Extracorporeal membrane oxygenation (ECMO) support is a life-saving but complex technique for patients suffering from severe cardiac or pulmonary dysfunction. Increasingly greater utilization in the last 15 years means that a suite of mortality risk analytics is both feasible for researchers and required by clinicians, patients, administrators, and insurers. We argue that to date, research into such risk analytics has been insufficient and does not adequately reflect the various indications and configurations of extracorporeal life support (ECLS). We propose a path to address these challenges and ensure that clinicians and researchers obtain robust, specific, risk analytics. Lippincott Williams & Wilkins 2017-11 2017-10-31 /pmc/articles/PMC5671797/ /pubmed/28338480 http://dx.doi.org/10.1097/MAT.0000000000000572 Text en Copyright © 2017 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the ASAIO. This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND) (http://creativecommons.org/licenses/by-nc-nd/4.0/) , where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. |
spellingShingle | Brief Communication Huesch, Marco Brehm, Christopher The Challenges in Predicting ECMO Survival, and a Path Forward |
title | The Challenges in Predicting ECMO Survival, and a Path Forward |
title_full | The Challenges in Predicting ECMO Survival, and a Path Forward |
title_fullStr | The Challenges in Predicting ECMO Survival, and a Path Forward |
title_full_unstemmed | The Challenges in Predicting ECMO Survival, and a Path Forward |
title_short | The Challenges in Predicting ECMO Survival, and a Path Forward |
title_sort | challenges in predicting ecmo survival, and a path forward |
topic | Brief Communication |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5671797/ https://www.ncbi.nlm.nih.gov/pubmed/28338480 http://dx.doi.org/10.1097/MAT.0000000000000572 |
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