Pain chronification after total joint arthroplasty
“Pain chronification after total joint arthroplasty
Arthroplasties are surgical procedures aiming to control pain and recover functionality in osteoarthritis patients. However, they are associated with severe acute pain and the development of chronic post-surgical pain (CPSP). Psychological factors are well-established CPSP predictors, but few investigations have focused on positive psychological characteristics. Quantitative sensory testing are psychophysical measures with a potentially relevant value to predict pain outcomes. This project aims to investigate socio-demographic, clinical, psychological and psychophysical predictors of acute and chronic post-surgical pain after total joint arthroplasty (knee, hip, shoulder). Participants will be assessed longitudinally (pre-surgery, 48h, 3, 6 and 12 months post-surgery) on socio-demographic, clinical (e.g. pain, comorbidities, anesthetics/analgesics), psychological (anxiety, depression, pain catastrophizing, optimism, hope, satisfaction with life and self-efficacy) and psychophysical (Quantitative Sensory Testing) variables.
Uncovering patient characteristics that are associated with surgery outcomes is relevant to optimize pre and post-surgical pain management interventions, thus promoting patients’ well-being and avoiding excessive health-care costs. “
FCT (PhD grant)
Patrícia Ribeiro Pinto
Main Project Outcomes
S. Queirós, “Right ventricular segmentation in multi-view cardiac MRI using a unified U-net model”, in E. Puyol Antón et al. (eds) Statistical Atlases and Computational Models of the Heart. Multi-Disease, Multi-View, and Multi-Center Right Ventricular Segmentation in Cardiac MRI Challenge. STACOM 2021. Lecture Notes in Computer Science, vol 13131, pp. 287-295, Springer, Cham, 2022.
“Best Paper Award in the M&Ms-2 Challenge”, by M&Ms2 Challenge organizers and the Medical Image Computing and Computer Assisted Intervention (MICCAI) Society.