An Algorithmic Approach to Ventilator Withdrawal at the End of Life

Wayne State University

Status: Completed

Conditions: Critical Care; Palliative Care

Treatments: Procedure: Ventilator withdrawal algorithm

Study type: Interventional

Funder types: Other; NIH

Identifiers

NCT03121391

R01NR015768 (U.S. NIH Grant/Contract)

Details and patient eligibility

About

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.

Full description

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.

Enrollment: 165 patients

Sex: All

Ages: 18+ years old

Volunteers: No Healthy Volunteers

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

Trial design

Primary purpose: Supportive Care

Allocation: Randomized

Interventional model: Crossover Assignment

Masking: None (Open label)

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165 participants in 2 patient groups

Control

No Intervention group

Description:

The medical intensive care unit in four hospitals will comprise the clusters. All four clusters begin the study under the control condition. Ventilator withdrawal is conducted by the usual personnel in those units. Data is collected through observation of the process and the respiratory comfort of the enrolled patients. Each cluster is randomly selected to sequentially cross over to the intervention. The remaining clusters continue with usual care (control) until selected for crossover.

Intervention

Active Comparator group

Description:

Each cluster is randomly selected to sequentially crossover to the intervention. When crossed over to the intervention the assigned intensive care nurse conducts the ventilator withdrawal according to the algorithm. The algorithm is informed by an objective measure of patient respiratory comfort. Data is collected through observation of the process and the respiratory comfort of the enrolled patients.

Treatment:

Procedure: Ventilator withdrawal algorithm