TY - JOUR
T1 - Transitioning from acute to chronic pain
T2 - A simulation study of trajectories of low back pain
AU - Su, Jianzhong
AU - Du, Ying
AU - Bevers, Kelley
AU - Xiao, Pengcheng
AU - Licciardone, John
AU - Brotto, Marco
AU - Gatchel, Robert J.
N1 - Funding Information:
Ying Du is supported by the National Natural Science Foundation of China (No.11672107).
Publisher Copyright:
© 2019 The Author(s).
PY - 2019/9/6
Y1 - 2019/9/6
N2 - 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.
AB - 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.
KW - Chronic and acute pains
KW - Computer simulation
KW - HPA axis
KW - Low back pain
KW - Ordinary differential equation system
KW - Pain trajectories
UR - http://www.scopus.com/inward/record.url?scp=85071977013&partnerID=8YFLogxK
U2 - 10.1186/s12967-019-2030-0
DO - 10.1186/s12967-019-2030-0
M3 - Article
C2 - 31492167
AN - SCOPUS:85071977013
SN - 1479-5876
VL - 17
JO - Journal of Translational Medicine
JF - Journal of Translational Medicine
IS - 1
M1 - 306
ER -