An Algorithmic Approach to Ventilator Withdrawal at the End of Life

The proposed study is an important, under-investigated area of ICU care for terminally ill patients undergoing terminal ventilator withdrawal. The proposed research has relevance to public health because an algorithmic approach to the ventilator withdrawal process will enhance clinicians' ability to conduct the process while assuring patient comfort, using opioids and/or benzodiazepines effectively.

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Key information

Conditions

Critical Care Palliative Care

Age range

18 year and older

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Detroit Receiving Hospital, Detroit, Michigan, United States

About this study

Terminal ventilator withdrawal is a process that entails the cessation of mechanical ventilatory support with patients who are unable to sustain spontaneous breathing and is commonly performed in the ICU. Ventilator withdrawal is undertaken to allow a natural death. Opioids and/or benzodiazepines are administered before, during, and after as an integral component of the ventilator withdrawal process to prevent or relieve respiratory distress, but there are few guidelines to determine how much to administer or when. Insufficient opioid and/or benzodiazepine administration places the patient at risk for unrelieved respiratory distress and preventable suffering. Conversely, excessive medication administration may hasten death, an unintended consequence, and one that concerns clinicians. The effective doses of medications given during ventilator withdrawal are unknown. The investigators hypothesize that an algorithmic approach to ventilator withdrawal, relying on a biobehavioral instrument to measure and trend distress, will ensure patient comfort, and guide effective opioid and/or benzodiazepine administration. The investigators plan to use a stepped wedge cluster randomized controlled trial with all clusters providing unstructured usual care until each cluster is randomized to implement the algorithmic approach (intervention). The proposed study is innovative because there is no standardized, evidence-based approach guided by an objective measure of respiratory distress to this common ICU procedure. The study has broad clinical significance to provide knowledge that can potentially reduce patient suffering.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

Patients undergoing ventilator withdrawal

Exclusion criteria

Patients who are conscious and cognitively intact
Patients who will undergo organ donation after ventilator withdrawal
Patients who are brain dead
Patients with bulbar amyotrophic lateral sclerosis
Patients with C-1 to C-4 quadriplegia
Patients with locked-in syndrome

Treatment and study plan

Ventilator withdrawal algorithm

Procedure

Steps and decision trees in the algorithm include in descending order:

Ascertain patient consciousness, perform cuff-leak test, evaluate for indications for pre-medication, select a withdrawal method, assess for respiratory distress with Respiratory Distress Observation Scale, medicate for respiratory distress with morphine, make an extubation decision, ascertain need for continuous morphine, ascertain need for supplemental oxygen, assess for post-extubation stridor, treat post-extubation stridor

Primary outcomes

Patient respiratory comfort

Time frame: Change from baseline through repeated measures up to 8 hours

Respiratory comfort will be measured with the Respiratory Distress Observation Scale at baseline, at every ventilator change, after the ventilator is turned off, every 15-minutes for 2 hours after the ventilator is turned off.

Sponsors and collaborators

Lead sponsor

Wayne State University

Other

Collaborators

National Institute of Nursing Research (NINR)

Registry information

Important dates

Study start: 2017
Primary completion: 2022
Study completion: 2022
First posted: Apr 20, 2017
Registry last updated: Nov 29, 2022

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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Completed