Transitioning from acute to chronic pain: a simulation study of trajectories of low back pain

• Main Authors: Jianzhong Su, Ying Du, Kelley Bevers, Pengcheng Xiao, John Licciardone, Marco Brotto, Robert J. Gatchel
• Format: Article
• Language: English
• Published: BMC 2019-09-01
• Series: Journal of Translational Medicine
• Subjects: Low back pain; Chronic and acute pains; Pain trajectories; HPA axis; Ordinary differential equation system; Computer simulation
• Online Access: http://link.springer.com/article/10.1186/s12967-019-2030-0

Abstract 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.