Physical health, previous joint pain, and the presence of diabetes can strongly predict whether a patient with arthritis will experience pain, say researchers presenting their findings at the annual meeting of the American Academy of Orthopaedic Surgeons in Las Vegas.
Man Hung, Ph.D., of the department of orthopaedic surgery operations at the University of Utah in Salt Lake City and her colleagues created several algorithms for predicting arthritis pain based on data from a sample of 5,721 U.S. adults with arthritis with an average age of 60 years.
They discovered that specific combinations of physical health, mental health, and general health status, as well as diabetes, previous joint pain, and a patient’s education level, predicted pain in people with arthritis.
Physical health status the greatest predictor of pain that limited work, whereas a body mass index greater than 30 kg/m2 was not linked to pain, the researchers found.
One of the algorithms that the researchers developed was able to predict pain at an accuracy rate of 98.6%, they said.
The algorithms offer new insights of pain, allowing the development of cost-effective care management programs for those experiencing arthritis, they concluded.