• J Palliat Med · Sep 2015

    Observational Study

    A Two-Group Trial of a Terminal Ventilator Withdrawal Algorithm: Pilot Testing.

    • Margaret L Campbell, Hossein N Yarandi, and Michael Mendez.
    • 1 College of Nursing, Wayne State University , Detroit, Michigan.
    • J Palliat Med. 2015 Sep 1; 18 (9): 781-5.

    BackgroundTerminal ventilator withdrawal entails cessation of mechanical ventilation to allow a natural death. There is little empirical evidence to guide the conduct of this procedure. If the process is not well conducted, patients undergoing terminal ventilator withdrawal are at high risk for experiencing significant respiratory distress.ObjectivesOur aim was to (1) establish the feasibility of a nurse-led algorithmic approach; (2) determine differences in patient comfort between groups; and (3) determine differences in the use of opioids and benzodiazepines.MethodsA prospective, two-group, repeated measures, observation design was used with nurses from one medical intensive care unit (MICU) conducting the algorithm and nurses from a second MICU providing unstandardized usual care. Patient respiratory comfort/distress was measured with the Respiratory Distress Observation Scale (RDOS).ResultsNurses and respiratory therapists were trained to follow the algorithm in one-hour educational sessions; fidelity to the algorithm was subsequently confirmed. Fourteen patients evenly distributed by ethnicity and gender were enrolled, eight in the control MICU and six in the intervention unit. No significant differences in age, consciousness, illness severity, or baseline RDOS were found. All control patients underwent a one-step terminal extubation process. There were no incidences of post-extubation stridor in the intervention group, whereas three (38%) control patients experienced stridor. Patients in the intervention group had greater respiratory comfort compared with control patients (p<0.05). Differences in medication use were found with lorazepam favored in the control unit; morphine is recommended in the algorithm.ConclusionsFeasibility and proof of concept for the nurse-led algorithm were established.

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