Osteoarthritis (OA) is a chronic disease characterised by the progressive destruction of the articular cartilage matrix affecting many parts of the joint, including bone, synovium, ligaments and articular cartilage and remains a major public health concern. The decision for surgery, joint replacement, shared between clinician and patient when conservative treatment fails, is mostly driven by severe patient reported pain. Persistent post-surgical pain (PPSP) has been defined by the International Association of the Study of Pain as pain that develops after surgery for at least 3 months. Although knee or hip OA surgery is usually associated with positive outcomes, a significant proportion of patients receiving knee replacement (KR) or hip replacement(HR), report PPSP in the first two years after surgery. Predicting PPSP following KA and HR in OA patients, that can help identify at-risk patients and the development of targeted preventive strategies, remains difficult, and current prognostic models have limited accuracy.
My research aims to identify possible predictors of PPSP following joint replacement by integrating multimodal (biological and clinical) data from participants with osteoarthritis OA (the main underlying conditions needing KA and HA) present in the UK Biobank.
