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Pain Body Map Can Predict Chronic Pain Outcomes – a New Study Suggests

The very first question a doctor asks you when you go with the complaint of pain is, “where does it hurt?” It is a natural and obvious starting point for a diagnosis. But this seemingly simple question has much more weight to it than meets the eyes. A paper, published in PLOS ONE suggests that the pain distribution reported by a patient is enough on its own to predict a host of other information, like its intensity, impact, and consequences ( after 3 months) of treatment.

 A lead researcher, Benedict J. Alter from the Department of Anesthesiology and Perioperative Medicine, University of Pittsburgh reported that

The distribution of pain in the body is a vital component of pain assessment. Using a hierarchical clustering approach with only a patient’s reported pain areas on a digital body map, we found multiple distinct subgroups of patients … [with] significantly different pain intensity, quality, and impact.

For the study, the team used a body map consisted of 2 drawings, one of the fronts & one of the back views of the body, all split into 74 regions in total. 22,000 patients of chronic pain from over 7 pain management clinics were asked to indicate which regions were causing pain, and then they were compared for health, pain, and three-month outcomes against the pain body map right when the treatment begins.

The team said in a statement, “Using an algorithmic approach, we found that how a patient reports the bodily distribution of their chronic pain affects nearly all aspects of the pain experience, including what happens three months later,”

The team found that all the patients with chronic pain fit into 9 groups, based on pain intensity, impact on the patient’s life, pain quality, demographic and medical characteristics. Another interesting finding was that the more widespread a patient’s pain is, the more persistent it is. That, they realized, might imply something important about how pain affects the brain. They also found that group G or group with neck, shoulder, and lower back pain had the worst three-month outcome. They used an algorithmic approach to disclose that such patients have far more pain characteristics than the two widespread pain groups.

 “[The] definitive relationship of body map cluster assignment and pain pathophysiology remains to be seen,” the paper cautions, “[and] even within accepted diagnoses lies significant [differences] in patient characteristics.” However, they say, “given its speed and ease of use for patients, we predict that body map cluster assignment will be a useful component of chronic pain biosignature development.”

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