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Development Of A Therapeutic Algorithm To Guide Clinicians Considering Palliative Sedation Therapy In Pediatric Patients At The End Of Life | 38512
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Background: Despite advances in palliative care a subset of patients experience suffering at the end-of-life refractory to traditional
therapy. Palliative sedation therapy (PST) with medications achieving continuous deep sedation (CDS) is well documented in
the adult literature as an ethically permissible treatment for intractable suffering. Guidelines for CDS in children are less clear.
Objective: Clarify the ethical permissibility of CDS in children at the end of life and develop an algorithm for use in clinical practice.
Design/Methods: Identification of patients who received propofol PST within 20 days of inpatient death (2003-2010) and
review of the medical record for indicators of pain, suffering, and sedation from 48 hours before PST to the time of death. Based
upon this case series we conducted a literature review and developed a clinical algorithm for initiation of PST in children.
Results: Three of 192 (1.6%) of children received propofol PST. Use of opioids and supportive medications decreased in 2 cases
and in the third case, CDS was effective in relieving other distressing symptoms. Clinical notes suggested improved comfort and
rest in all patients. CDS is justified to relieve end-of-life suffering only if the distressing symptoms are refractory to standard
palliative management. The indications for PST at the end of life include two core components: the presence of severe suffering
refractory to standard palliative management and the primary aim of relief of distress. No ethical contraindication to the use
of PST exists in children and numerous case series, including our own, demonstrate its’ efficacy. We provide an algorithm for
clinicians considering PST in a pediatric patient at the end of life.
Conclusions: Children with intolerable suffering at the end-of-life should not be allowed to continue with refractory symptoms
due to clinician inexperience with this infrequent intervention “of last resort.” Our algorithm provides a guideline for clinicians
and institutions to use in clinical practice.
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