Virtual reality for pain management in advanced heart failure: A randomized controlled study

Background: Hospitalized patients with advanced heart failure often experience acute and/or chronic pain. While virtual reality has been extensively studied across a wide range of clinical settings, no studies have yet evaluated potential impact on pain management on this patient population. Aim: To investigate the impact of a virtual reality experience on self-reported pain, quality-of-life, general distress, and satisfaction compared to a two-dimensional guided imagery active control. Design: Single-center prospective randomized controlled study. The primary outcome was the difference in pre- versus post-intervention self-reported pain scores on a numerical rating scale from 0 to 10. Secondary outcomes included changes in quality-of-life scores, general distress, and satisfaction with the intervention. Setting/participants: Between October 2018 and March 2020, 88 participants hospitalized with advanced heart failure were recruited from an urban tertiary academic medical center. Results: Participants experienced significant improvement in pain score after either 10 minutes of virtual reality (change from pre- to post −2.9 ± 2.6, p < 0.0001) or 10 minutes of guided imagery (change from pre- to post −1.3 ± 1.8, p = 0.0001); the virtual reality arm experienced a 1.5 unit comparatively greater reduction in pain score compared to guided imagery ( p = 0.0011). Total quality-of-life and general distress scores did not significantly change for either arm. Seventy-eight participants (89%) responded that they would be willing to use the assigned intervention again. Conclusion: Virtual reality may be an effective nonpharmacologic adjuvant pain management intervention in hospitalized patients with heart failure. Trial Registration: ClinicalTrials.gov database (NCT04572425).

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Implementing Guidelines for Cancer Pain Management: Results of a Randomized Controlled Clinical Trial

Journal of Clinical Oncology ◽

10.1200/jco.1999.17.1.361 ◽

1999 ◽

Vol 17 (1) ◽

pp. 361-361 ◽

Cited By ~ 188

Author(s):

Stuart L. Du Pen ◽

Anna R. Du Pen ◽

Nayak Polissar ◽

Jennifer Hansberry ◽

Beth Miller Kraybill ◽

...

Keyword(s):

Quality Of Life ◽

Decision Making ◽

Pain Management ◽

Cancer Pain ◽

Symptom Management ◽

Controlled Study ◽

Cancer Pain Management ◽

Randomized Controlled ◽

Prospective Longitudinal

PURPOSE: Pain and symptom management is an integral part of the clinical practice of oncology. A number of guidelines have been developed to assist the clinician in optimizing comfort care. We implemented clinical guidelines for cancer pain management in the community setting and evaluated whether these guidelines improved care. PATIENTS AND METHODS: Eighty-one cancer patients, aged 37 to 76 years, were enrolled onto a prospective, longitudinal, randomized controlled study from the outpatient clinic settings of 26 western Washington–area medical oncologists. A multilevel treatment algorithm based on the Agency for Health Care Policy and Research Guidelines for Cancer Pain Management was compared with standard-practice (control) pain and symptom management therapies used by community oncologists. The primary outcome of interest was pain (Brief Pain Inventory); secondary outcomes of interest were all other symptoms (Memorial Symptom Assessment Scale) and quality of life (Functional Assessment of Cancer Therapy Scale). RESULTS: Patients randomized to the pain algorithm group achieved a statistically significant reduction in usual pain intensity, measured as slope scores, when compared with standard community practice (P < .02). Concurrent chemotherapy and patient adherence to treatment were significant mediators of worst pain. There were no significant differences in other symptoms or quality of life between the two treatment groups. CONCLUSION: This guideline implementation study supports the use of algorithmic decision making in the management of cancer pain. These findings suggest that comprehensive pain assessment and evidence-based analgesic decision-making processes do enhance usual pain outcomes.

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