Machine learning (ML), a branch of artificial intelligence that uses algorithms to learn from data and make predictions, offers a pathway towards more personalized and tailored surgical treatments. This approach is particularly relevant to prevalent joint diseases such as osteoarthritis (OA). In contrast to end-stage disease, where joint arthroplasty provides excellent results, early stages of OA currently lack effective therapies to halt or reverse progression. Accurate prediction of OA progression is crucial if timely interventions are to be developed, to enhance patient care and optimize the design of clinical trials. A systematic review was conducted in accordance with PRISMA guidelines. We searched MEDLINE and Embase on 5 May 2024 for studies utilizing ML to predict OA progression. Titles and abstracts were independently screened, followed by full-text reviews for studies that met the eligibility criteria. Key information was extracted and synthesized for analysis, including types of data (such as clinical, radiological, or biochemical), definitions of OA progression, ML algorithms, validation methods, and outcome measures.Aims
Methods
To explore key stakeholder views around feasibility and acceptability of trials seeking to prevent post-traumatic osteoarthritis (PTOA) following knee injury, and provide guidance for next steps in PTOA trial design. Healthcare professionals, clinicians, and/or researchers (HCP/Rs) were surveyed, and the data were presented at a congress workshop. A second and related survey was then developed for people with joint damage caused by knee injury and/or osteoarthritis (PJDs), who were approached by a UK Charity newsletter or Oxford involvement registry. Anonymized data were collected and analyzed in Qualtrics.Aims
Methods
Accumulated evidence indicates that local cell origins may ingrain differences in the phenotypic activity of human osteoblasts. We hypothesized that these differences may also exist in osteoblasts harvested from the same bone type at periarticular sites, including those adjacent to the fixation sites for total joint implant components. Human osteoblasts were obtained from the acetabulum and femoral neck of seven patients undergoing total hip arthroplasty (THA) and from the femoral and tibial cuts of six patients undergoing total knee arthroplasty (TKA). Osteoblasts were extracted from the usually discarded bone via enzyme digestion, characterized by flow cytometry, and cultured to passage three before measurement of metabolic activity, collagen production, alkaline phosphatase (ALP) expression, and mineralization.Aims
Methods
To investigate factors that contribute to patient decisions regarding attendance for arthroplasty during the COVID-19 pandemic. A postal questionnaire was distributed to patients on the waiting list for hip or knee arthroplasty in a single tertiary centre within the UK. Patient factors that may have influenced the decision to attend for arthroplasty, global quality of life (QoL) (EuroQol five-dimension three-level (EQ-5D-3L)), and joint-specific QoL (Oxford Hip or Knee Score) were assessed. Patients were asked at which ‘COVID-alert’ level they would be willing to attend an NHS and a “COVID-light” hospital for arthroplasty. Independent predictors were assessed using multivariate logistic regression.Aims
Methods
Charcot neuroarthropathy is a rare but serious complication of diabetes, causing progressive destruction of the bones and joints of the foot leading to deformity, altered biomechanics and an increased risk of ulceration. Management is complicated by a lack of consensus on diagnostic criteria and an incomplete understanding of the pathogenesis. In this review, we consider recent insights into the development of Charcot neuroarthropathy. It is likely to be dependent on several interrelated factors which may include a genetic pre-disposition in combination with diabetic neuropathy. This leads to decreased neuropeptides (nitric oxide and calcitonin gene-related peptide), which may affect the normal coupling of bone formation and resorption, and increased levels of Receptor activator of nuclear factor kappa-B ligand, potentiating osteoclastogenesis. Repetitive unrecognized trauma due to neuropathy increases levels of pro-inflammatory cytokines (interleukin-1β, interleukin-6, tumour necrosis factor α) which could also contribute to increased bone resorption, in combination with a pre-inflammatory state, with increased autoimmune reactivity and a profile of monocytes primed to transform into osteoclasts - cluster of differentiation 14 (CD14). Increased blood glucose and loss of circulating Receptor for Advanced Glycation End-Products (AGLEPs), leading to increased non-enzymatic glycation of collagen and accumulation of AGLEPs in the tissues of the foot, may also contribute to the pathological process. An understanding of the relative contributions of each of these mechanisms and a final common pathway for the development of Charcot neuroarthropathy are still lacking.
