Does Type of Pain Predict Pain Severity Changes in Individuals With Multiple Sclerosis? A Longitudinal Analysis Using Generalized Estimating Equations

Authors

  • Nancy Mayo Dept. of Clinical Epidemiology, McGill University Health Center, Royal Victoria Hospital, Montreal, Canada
  • Pierre Duquete Notre-Dame Hospital (CHUM), University of Montreal, Montreal, Canada
  • Shahnaz Shahrbanian Dept. of Physical & Occupational Therapy, Faculty of Medicine, McGill University, Montreal, Canada
Abstract:

 Background & Objective:  Pain is a common symptom among people with MS. In the majority of MS patients, pain is chronic in nature, but it can change over time. The objective of this study was to determine if pain type can predict pain severity changes in individuals with MS over time.  Materials & Methods:  The research method was a longitudinal design that evaluated pain type and severity at baseline and after 3 years of follow up among people with MS. At the beginning of the study a random sample comprising of 188 individuals with MS were recruited. From those, 78 individuals experienced pain included the study. The McGill pain questionnaire and ID-Pain questionnaire were used to assess type of pain. Numeric Rating Scale was used to measure pain severity. McNemar, Cohen’s un-weighted Kappa Coefficient, Paired Student t-tests and Generalized Estimating Equations were used to analyze the data. Results:  Findings indicated that all pain severity ratings raised on average, though this difference was statistically significant only for lowest pain (P=0.0006). Type of pain did not change in the major part of study sample (P=0.44). Results further indicated that over the follow-up period the lowest pain severity scores were significantly predicted by type of pain (P<0.05), while the pain ratings in worst pain severity was not predicted by the type of pain. Conclusion:  Results of the current study help for better understanding of the pain type and severity changes over time among patients with MS.

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Journal title

volume 27  issue None

pages  9- 15

publication date 2019-05

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