An Algorithmic Approach to Ventilator Withdrawal at the End of Life

Information

  • Research Project
  • 10004721
  • ApplicationId
    10004721
  • Core Project Number
    R01NR015768
  • Full Project Number
    5R01NR015768-05
  • Serial Number
    015768
  • FOA Number
    PAR-13-289
  • Sub Project Id
  • Project Start Date
    9/27/2016 - 8 years ago
  • Project End Date
    7/31/2022 - 2 years ago
  • Program Officer Name
    KEHL, KAREN
  • Budget Start Date
    8/19/2021 - 3 years ago
  • Budget End Date
    7/31/2022 - 2 years ago
  • Fiscal Year
    2021
  • Support Year
    05
  • Suffix
  • Award Notice Date
    8/19/2021 - 3 years ago
Organizations

An Algorithmic Approach to Ventilator Withdrawal at the End of Life

DESCRIPTION (provided by applicant): 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. We 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. We 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.

IC Name
NATIONAL INSTITUTE OF NURSING RESEARCH
  • Activity
    R01
  • Administering IC
    NR
  • Application Type
    5
  • Direct Cost Amount
    345928
  • Indirect Cost Amount
    124684
  • Total Cost
    226908
  • Sub Project Total Cost
  • ARRA Funded
    False
  • CFDA Code
    361
  • Ed Inst. Type
    SCHOOLS OF NURSING
  • Funding ICs
    NINR:226908\
  • Funding Mechanism
    Non-SBIR/STTR RPGs
  • Study Section
    ZNR1
  • Study Section Name
    Special Emphasis Panel
  • Organization Name
    WAYNE STATE UNIVERSITY
  • Organization Department
    NONE
  • Organization DUNS
    001962224
  • Organization City
    DETROIT
  • Organization State
    MI
  • Organization Country
    UNITED STATES
  • Organization Zip Code
    482024050
  • Organization District
    UNITED STATES