Skip to main content
 

Main menu

  • Home
  • Content
    • Current Issue
    • Editor's Commentary
    • Coming Next Month
    • Archives
    • Top 10 Papers in 2020
  • Authors
    • Author Guidelines
    • Submit a Manuscript
  • Reviewers
    • Reviewer Information
    • Create Reviewer Account
    • Appreciation of Reviewers
  • CRCE
    • Through the Journal
    • JournalCasts
    • AARC University
    • PowerPoint Template
  • Open Forum
    • Call for Abstracts 2021
    • 2020 Abstracts
    • Previous Open Forums
  • Podcast
    • English
    • Español
    • Portugûes
    • 国语

User menu

  • Subscribe
  • My alerts
  • Log in

Search

  • Advanced search
American Association for Respiratory Care
  • Subscribe
  • My alerts
  • Log in
American Association for Respiratory Care

Advanced Search

  • Home
  • Content
    • Current Issue
    • Editor's Commentary
    • Coming Next Month
    • Archives
    • Top 10 Papers in 2020
  • Authors
    • Author Guidelines
    • Submit a Manuscript
  • Reviewers
    • Reviewer Information
    • Create Reviewer Account
    • Appreciation of Reviewers
  • CRCE
    • Through the Journal
    • JournalCasts
    • AARC University
    • PowerPoint Template
  • Open Forum
    • Call for Abstracts 2021
    • 2020 Abstracts
    • Previous Open Forums
  • Podcast
    • English
    • Español
    • Portugûes
    • 国语
  • Follow aarc on Twitter
  • Visit aarc on Facebook
Research ArticleOriginal Research

Identifying Subjects at Risk for Diaphragm Atrophy During Mechanical Ventilation Using Routinely Available Clinical Data

Martin Urner, Nicholas Mitsakakis, Stefannie Vorona, Lu Chen, Michael C Sklar, Martin Dres, Gordon D Rubenfeld, Laurent J Brochard, Niall D Ferguson, Eddy Fan and Ewan C Goligher
Respiratory Care April 2021, 66 (4) 551-558; DOI: https://doi.org/10.4187/respcare.08223
Martin Urner
Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, Canada.
Institute for Health Policy, Management, and Evaluation, University of Toronto, Toronto, Canada.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Nicholas Mitsakakis
Institute for Health Policy, Management, and Evaluation, University of Toronto, Toronto, Canada.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Stefannie Vorona
Department of Medicine, Division of Respirology, University Health Network, Toronto, Canada.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Lu Chen
Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, Canada.
Keenan Centre for Biomedical Research, Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto, Canada.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Michael C Sklar
Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, Canada.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Martin Dres
Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, Canada.
Keenan Centre for Biomedical Research, Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto, Canada.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Gordon D Rubenfeld
Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, Canada.
Institute for Health Policy, Management, and Evaluation, University of Toronto, Toronto, Canada.
Program in Trauma, Emergency, and Critical Care Organization, Sunnybrook Health Sciences Center, Toronto, Ontario, Canada.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Laurent J Brochard
Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, Canada.
Keenan Centre for Biomedical Research, Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto, Canada.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Niall D Ferguson
Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, Canada.
Institute for Health Policy, Management, and Evaluation, University of Toronto, Toronto, Canada.
Department of Medicine, Division of Respirology, University Health Network, Toronto, Canada.
Departments of Medicine and Physiology, University of Toronto, Toronto, Canada.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Eddy Fan
Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, Canada.
Institute for Health Policy, Management, and Evaluation, University of Toronto, Toronto, Canada.
Department of Medicine, Division of Respirology, University Health Network, Toronto, Canada.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Ewan C Goligher
Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, Canada.
Institute for Health Policy, Management, and Evaluation, University of Toronto, Toronto, Canada.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: [email protected]
  • Article
  • Figures & Data
  • References
  • Info & Metrics
  • PDF
Loading

This article requires a subscription to view the full text. If you have a subscription you may use the login form below to view the article. Access to this article can also be purchased.

Abstract

BACKGROUND: Diaphragmatic respiratory effort during mechanical ventilation is an important determinant of patient outcome, but direct measurement of diaphragmatic contractility requires specialized instrumentation and technical expertise. We sought to determine whether routinely collected clinical variables can predict diaphragmatic contractility and stratify the risk of diaphragm atrophy.

METHODS: We conducted a secondary analysis of a prospective cohort study on diaphragm ultrasound in mechanically ventilated subjects. Clinical variables, such as breathing frequency, ventilator settings, and blood gases, were recorded longitudinally. Machine learning techniques were used to identify variables predicting diaphragm contractility and stratifying the risk of diaphragm atrophy (> 10% decrease in thickness from baseline). Performance of the variables was evaluated in mixed-effects logistic regression and random-effects tree models using the area under the receiver operating characteristic curve.

RESULTS: Measurements were available for 761 study days in 191 subjects, of whom 73 (38%) developed diaphragm atrophy. No routinely collected clinical variable, alone or in combination, could accurately predict either diaphragm contractility or the development of diaphragm atrophy (model area under the receiver operating characteristic curve 0.63–0.75). The risk of diaphragm atrophy was not significantly different according to the presence or absence of patient-triggered breaths (38.3% vs 38.6%; odds ratio 1.01, 95% CI 0.05–2.03). Diaphragm thickening fraction < 15% during either of the first 2 d of the study was associated with a higher risk of atrophy (44.6% vs 26.1%; odds ratio 2.28, 95% CI 1.05–4.95).

CONCLUSIONS: Diaphragmatic contractility and the risk of diaphragm atrophy could not be reliably determined from routinely collected clinical variables and ventilator settings. A single measurement of diaphragm thickening fraction measured within 48 h of initiating mechanical ventilation can be used to stratify the risk of diaphragm atrophy during mechanical ventilation.

  • diaphragm thickening
  • diaphragm thickening fraction
  • machine learning
  • random forest
  • spontaneous breathing
  • diaphragm atrophy

Footnotes

  • Correspondence: Ewan C Goligher MD PhD, Toronto General Hospital, 585 University Ave, Peter Munk Building 11-192, Toronto, Ontario, Canada, M5G 2N2. E-mail: ewan.goligher{at}mail.utoronto.ca
  • See the Related Editorial on Page 701

  • Supplementary material related to this paper is available at http://www.rcjournal.com.

  • Dr Urner is supported by a Vanier Canada Graduate Scholarship. Drs Fan and Goligher are supported in part by the CIHR. The authors have disclosed no conflicts of interest.

  • Copyright © 2021 by Daedalus Enterprises
View Full Text

Pay Per Article - You may access this article (from the computer you are currently using) for 1 day for US$30.00

Regain Access - You can regain access to a recent Pay per Article purchase if your access period has not yet expired.

Log in using your username and password

Forgot your user name or password?
PreviousNext
Back to top

In this issue

Respiratory Care: 66 (4)
Respiratory Care
Vol. 66, Issue 4
1 Apr 2021
  • Table of Contents
  • Table of Contents (PDF)
  • Cover (PDF)
  • Index by author
Print
Download PDF
Article Alerts
Sign In to Email Alerts with your Email Address
Email Article

Thank you for your interest in spreading the word on American Association for Respiratory Care.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
Identifying Subjects at Risk for Diaphragm Atrophy During Mechanical Ventilation Using Routinely Available Clinical Data
(Your Name) has sent you a message from American Association for Respiratory Care
(Your Name) thought you would like to see the American Association for Respiratory Care web site.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Citation Tools
Identifying Subjects at Risk for Diaphragm Atrophy During Mechanical Ventilation Using Routinely Available Clinical Data
Martin Urner, Nicholas Mitsakakis, Stefannie Vorona, Lu Chen, Michael C Sklar, Martin Dres, Gordon D Rubenfeld, Laurent J Brochard, Niall D Ferguson, Eddy Fan, Ewan C Goligher
Respiratory Care Apr 2021, 66 (4) 551-558; DOI: 10.4187/respcare.08223

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero

Share
Identifying Subjects at Risk for Diaphragm Atrophy During Mechanical Ventilation Using Routinely Available Clinical Data
Martin Urner, Nicholas Mitsakakis, Stefannie Vorona, Lu Chen, Michael C Sklar, Martin Dres, Gordon D Rubenfeld, Laurent J Brochard, Niall D Ferguson, Eddy Fan, Ewan C Goligher
Respiratory Care Apr 2021, 66 (4) 551-558; DOI: 10.4187/respcare.08223
del.icio.us logo Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Jump to section

  • Article
    • Abstract
    • Introduction
    • Methods
    • Results
    • Discussion
    • Conclusions
    • Footnotes
    • REFERENCES
  • Figures & Data
  • Info & Metrics
  • References
  • PDF

Related Articles

Cited By...

Keywords

  • diaphragm thickening
  • diaphragm thickening fraction
  • machine learning
  • random forest
  • spontaneous breathing
  • diaphragm atrophy

Info For

  • Subscribers
  • Institutions
  • Advertisers

About Us

  • About Us
  • Editorial Board
  • Reprints/Permissions

AARC

  • Membership
  • Meetings
  • Clinical Practice Guidelines

More

  • Contact Us
  • RSS
American Association for Respiratory Care

Print ISSN: 0020-1324        Online ISSN: 1943-3654

© Daedalus Enterprises, Inc.

Powered by HighWire