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Pain Predicts Function One Year Later: A Comparison across Pain Measures in a Rheumatoid Arthritis Sample.

Vivian SantiagoKaren RaphaelBetty Chewning
Published in: Pain research and treatment (2016)
Background. Guidance is limited on best measures and time periods to reference when measuring pain in order to predict future function. Objective. To examine how different measures of pain predict functional limitations a year later in a sample of rheumatoid arthritis patients. Methods. Logistic regression analyses were conducted using baseline and one-year data (n = 262). Pain intensity in the last 24 hours was measured on a 0-10 numerical rating scale and in the last month using an item from the Arthritis Impact Measurement Scale 2 (AIMS2). AIMS2 also provided frequency of severe pain, pain composite scores, and patient-reported limitations. Physician-rated function was also examined. Results. Composite AIMS2 pain scale performed best, predicting every functional outcome with the greatest magnitude, a one-point increase in pain score predicting 21% increased odds of limitations (combined patient and physician report). However, its constituent item-frequency of severe pain in the last month-performed nearly as well (19% increased odds). Pain intensity measures in last month and last 24 hours yielded inconsistent findings. Conclusion. Although all measures of pain predicted some functional limitations, predictive consistency varied by measure. Frequency of severe pain in the last month provided a good balance of brevity and predictive power.
Keyphrases
  • chronic pain
  • pain management
  • neuropathic pain
  • rheumatoid arthritis
  • primary care
  • spinal cord injury
  • systemic sclerosis
  • interstitial lung disease
  • artificial intelligence