Functional linear modeling of activity data shows analgesic-mediated improved sleep in dogs with spontaneous osteoarthritis pain

M E Gruen,B D X Lascelles,D R Samson

doi:10.1038/s41598-019-50623-0

M E Gruen, B D X Lascelles + Show 1 more

Open Access

https://doi.org/10.1038/s41598-019-50623-0

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Abstract

In humans, pain due to osteoarthritis has been demonstrated to be associated with insomnia and sleep disturbances that affect perception of pain, productivity, and quality of life. Dogs, which develop spontaneous osteoarthritis and represent an increasingly used model for human osteoarthritis, would be expected to show similar sleep disturbances. Further, these sleep disturbances should be mitigated by analgesic therapy. Previous efforts to quantify sleep in osteoarthritic dogs using accelerometry have not demonstrated a beneficial effect of analgesic therapy; this is despite owner-reported improvements in dogs’ sleep quality. However, analytic techniques for time-series accelerometry data have advanced with the development of functional linear modeling. Our aim was to apply functional linear modeling to accelerometry data from osteoarthritic dogs participating in a cross-over non-steroidal anti-inflammatory (meloxicam) drug trial. Significant differences in activity patterns were seen dogs receiving drug (meloxicam) vs. placebo, suggestive of improved nighttime resting (sleep) and increased daytime activity. These results align with owner-reported outcome assessments of sleep quality and further support dogs as an important translational model with benefits for both veterinary and human health.

Highlights

In humans, clear evidence exists that chronic pain interferes with sleep[1]
Sleep quality is often measured objectively using actigraphy[7]; lower activity counts indicative of less movement are presumed to reflect higher quality sleep
Functional data analysis has been used to demonstrate subtle activity changes in cats with degenerative joint disease[15]. This latter study in cats highlights the potential applications for functional data analysis in studies of pain and activity, but to date, no studies in dogs or cats have used functional linear modeling (FLM) to assess the impact of pain relief on activity or sleep in a chronic pain state

Summary

Introduction

Clear evidence exists that chronic pain interferes with sleep[1]. Sleep disturbances decrease quality of life, are associated with higher anxiety and depression[2], and worsen chronic pain symptoms[3]. We concluded that while the SNoRE questionnaire demonstrated responsiveness validity, criterion validity of the instrument could not be inferred due to the lack of a change in activity as measured with accelerometry [10] This previous study has an important limitation; accelerometry data were collected every minute and averaged across multiple hours in the statistical analysis. Functional data analysis, functional linear modeling (FLM), has been developed to evaluate actigraphy time-series data This analytical approach has led to important discoveries about chronotype variation and sleep-wake regulation across human groups living in natural, non-industrial environments[11,12,13,14]. This latter study in cats highlights the potential applications for functional data analysis in studies of pain and activity, but to date, no studies in dogs or cats have used FLM to assess the impact of pain relief on activity or sleep in a chronic pain state

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