Improving patient comfort when withdrawing mechanical ventilation at the end of life.

There were many highlights at the EAPC 12th World Research Congress, including the excellent posters which were on display.  The overall poster winner was Margaret L. Campbell and colleagues from Wayne State University, United States of America.  For the next in our palliative care and intensive care series, Margaret L. Campbell tells us about her research which is the first intervention trial for the common palliative care process of withdrawing mechanical ventilation at the end of life in critical care.

Early in my career, I was a palliative care nurse practitioner in a level one trauma and emergency hospital. More than half of the patients referred for palliative care were from the medical intensive care unit, many of whom were at the end of their life and needed to have mechanical ventilation withdrawn. In those early days of United States (U.S.) palliative care, there were no clinical guidelines for this withdrawal. I saw that some patients came off the ventilator with no apparent distress, while others struggled to breathe, and I saw how upset they and their families were. Many years later, there is still global variability in how and if this decision is made, and how this procedure is undertaken. Yet, withdrawal of mechanical ventilation, if not performed correctly, leads to patient respiratory distress, which causes suffering to patients, and to their relatives who are witnessing it. There is also the concern that when medication regimens are not evidence-based or guided by an objective measure of patient distress, it may lead to a perception of hastening death, which is not an aim of this palliative process.

Withdrawal of invasive mechanical ventilation entails a reduction in mechanical ventilatory support until the patient is breathing spontaneously to help them to have a natural death. The most common approaches to this process are a gradual reduction in the support from the ventilator or a single step of ventilator being turned off and endotracheal tube removed. As there has previously been little rigorous clinical research to guide this process, clinicians rely on intuition, varying levels of experience, or local practice customs.

From 2017 until 2022, my colleagues and I undertook a randomised controlled research trial to test a nurse-led algorithmic approach to this withdrawal.  This approach means that there are various decision trees to guide the steps, for example ‘Can the patient experience distress?’. If the answer is yes, the algorithm suggests a gradual reduction, rather than a complete withdrawal in one step. We felt this was the best approach to take because of the varied patients undergoing ventilator withdrawal in ICU. For example, some people choosing ventilator withdrawal for themselves are awake and aware, and able to report breathlessness. However, most people are cognitively impaired or unconscious and unable to self-report breathlessness. It is possible that some patients who are deeply unconscious may not experience respiratory distress yet may be overtreated in anticipation of distress. Other patients will have the consciousness to experience respiratory distress but may not be able to let their clinical team know and be at risk for under-treatment since clinicians may underestimate the patient experience.

We knew that the ideal best practice process for conducting ventilator withdrawal across such different patients must account for the variance in their experience and so we developed a patient-centered algorithm guided by an objective measure of respiratory distress. The purpose of this study was threefold: i) to determine the effectiveness of a Principal Investigator-developed algorithm compared to usual care, ii) ascertain differences in medications given and iii) investigate the potential impact of select variables on duration of survival. The algorithm is nurse-led and respiratory therapist supported. Critical care nurses in the U.S. have the skills to assess and treat patients according to the algorithm with support from respiratory therapists who make the ventilator changes.

One hundred and forty-eight patients took part in this multi-site study. Our findings were that strong, significant effectiveness was shown when using the algorithm.  We found that the algorithm is scalable with critical care leadership buy-in and with nurse/respiratory therapist training to the algorithm. We successfully implemented the algorithm in all five of our study sites.  When clinicians make this care decision with a patient’s family, we make a promise that breathing will be comfortable to the end of life, and with implementation of this algorithmic approach, we keep that promise.

Links and resources

  • View Margaret’s EAPC award winning poster here.
  • To read more in the EAPC’s Palliative care and Intensive Care blog series, click here.
  • Read more about this research:

Campbell ML, Templin T, Walch J. A Respiratory Distress Observation Scale for patients unable to self-report dyspnea. Journal of Palliative Medicine. 2010;13(3):285-290.

Campbell ML, Yarandi HN. Effectiveness of an algorithmic approach to ventilator withdrawal. Journal of Pain and Symptom Management. 2022;63(6):1059.

About the author

Margaret L. Campbell is a Professor in the College of Nursing at Wayne State University, in the U.S. She studies breathlessness assessment and treatment for patients nearing the end of life. She developed the Respiratory Distress Observation Scale which is in wide use in North America and eleven other countries and has been translated into French, Italian, Dutch, Greek, Spanish, Japanese, and Chinese. Orcid: 0000-0003-4517-690X Twitter: campbell_meg.

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This entry was posted in EAPC 12th World Research Congresss, EAPC World Congresses, Palliative Care and Intensive Care, PATIENT & FAMILY CARE, RESEARCH. Bookmark the permalink.

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