An Algorithmic Approach to Ventilator Withdrawal at the End of Life
| Status: | Enrolling by invitation |
|---|---|
| Conditions: | Hospital |
| Therapuetic Areas: | Other |
| Healthy: | No |
| Age Range: | 18 - Any |
| Updated: | 1/27/2019 |
| Start Date: | April 20, 2017 |
| End Date: | July 2021 |
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.
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.
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.
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.
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
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