Despite new technologies for total knee arthroplasty (TKA), approximately 20% of patients are dissatisfied. A major reason for dissatisfaction and revision surgery after TKA is persistent pain. The radiological grade of osteoarthritis (OA) preoperatively has been investigated as a predictor of the outcome after TKA, with conflicting results. The aim of this study was to determine if there is a difference in the intensity of pain 12 months after TKA in relation to the preoperative radiological grade of OA alone, and the combination of the intensity of preoperative pain and radiological grade of OA. The preoperative data of 300 patients who underwent primary TKA were collected, including clinical information (age, sex, preoperative pain), psychological variables (depression, anxiety, pain catastrophizing, anticipated pain), and quantitative sensory testing (temporal summation, pressure pain thresholds, conditioned pain modulation). The preoperative radiological severity of OA was graded according to the Kellgren-Lawrence (KL) classification. Persistent pain in the knee was recorded 12 months postoperatively. Generalized linear models explored differences in postoperative pain according to the KL grade, and combined preoperative pain and KL grade. Relative risk models explored which preoperative variables were associated with the high preoperative pain/low KL grade group.Aims
Methods
The management of periprosthetic joint infection (PJI) after total knee arthroplasty (TKA) is challenging. The correct antibiotic management remains elusive due to differences in epidemiology and resistance between countries, and reports in the literature. Before the efficacy of surgical treatment is investigated, it is crucial to analyze the bacterial strains causing PJI, especially for patients in whom no organisms are grown. A review of all revision TKAs which were undertaken between 2006 and 2018 in a tertiary referral centre was performed, including all those meeting the consensus criteria for PJI, in which organisms were identified. Using a cluster analysis, three chronological time periods were created. We then evaluated the antibiotic resistance of the identified bacteria between these three clusters and the effectiveness of our antibiotic regime.Aims
Methods
