Background: Identifying how pain transitions from acute to chronic is critical in designing effective prevention and management techniques for patients' well-being, physically, psychosocially, and financially. There is an increasingly pressing need for a quantitative and predictive method to evaluate how low back pain trajectories are classified and, subsequently, how we can more effectively intervene during these progression stages.
Methods: In order to better understand pain mechanisms, we investigated, using computational modeling, how best to describe pain trajectories by developing a platform by which we studied the transition of acute chronic pain.
A recent literature review concluded that the comorbidity of chronic pain and depression in adults is approximately 50%-65%. Physical and cognitive declines, concurrent multiple health conditions, and complex medication regimens add to the unique and complex challenges of effectively treating pain in particularly geriatric populations. Interdisciplinary medical intervention and monitoring for psychiatric sequelae, such as depression, cognitive change, and synergistic physical side effects are necessary.
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