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.
Results: The present study uses a computational neuroscience-based method to conduct such trajectory research, motivated by the use of hypothalamic-pituitary-adrenal (HPA) axis activity-history over a time-period as a way to mimic pain trajectories. A numerical simulation study is presented as a "proof of concept" for this modeling approach.
Conclusions: This model and its simulation results have highlighted the feasibility and the potential of developing such a broader model for patient evaluations.
Keywords: Chronic and acute pains; Computer simulation; HPA axis; Low back pain; Ordinary differential equation system; Pain trajectories.