Aims. Periprosthetic hip and knee infection remains one of the most severe complications following arthroplasty, with an incidence between 0.5% to 1%. This study compares the outcomes of revision surgery for periprosthetic joint infection (PJI) following hip and knee arthroplasty prior to and after implementation of a specialist PJI multidisciplinary team (MDT). Methods. Data was retrospectively analyzed from a single centre. In all, 29 consecutive joints prior to the implementation of an infection MDT in November 2016 were compared with 29 consecutive joints subsequent to the MDT conception. All individuals who underwent a debridement antibiotics and implant retention (DAIR) procedure, a one-stage revision, or a two-stage revision for an acute or chronic PJI in this time period were included. The definition of successfully treated PJI was based on the Delphi international multidisciplinary consensus. Results. There were no statistically significant differences in patient demographics or comorbidities between the groups. There was also no significant difference in length of overall hospital stay (p = 0.530). The time taken for formal microbiology advice was significantly shorter in the post MDT group (p = 0.0001). There was a significant difference in failure rates between the two groups (p = 0.001), with 12 individuals (41.38%) pre-MDT requiring further revision surgery compared with one individual (6.67%) post-MDT inception. Conclusion. Our standardized multidisciplinary approach for periprosthetic knee and
While internet search engines have been the primary information source for patients’ questions, artificial intelligence large language models like ChatGPT are trending towards becoming the new primary source. The purpose of this study was to determine if ChatGPT can answer patient questions about total hip (THA) and knee arthroplasty (TKA) with consistent accuracy, comprehensiveness, and easy readability. We posed the 20 most Google-searched questions about THA and TKA, plus ten additional postoperative questions, to ChatGPT. Each question was asked twice to evaluate for consistency in quality. Following each response, we responded with, “Please explain so it is easier to understand,” to evaluate ChatGPT’s ability to reduce response reading grade level, measured as Flesch-Kincaid Grade Level (FKGL). Five resident physicians rated the 120 responses on 1 to 5 accuracy and comprehensiveness scales. Additionally, they answered a “yes” or “no” question regarding acceptability. Mean scores were calculated for each question, and responses were deemed acceptable if ≥ four raters answered “yes.”Aims
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Restarting elective services presents a challenge to restore and improve many of the planned patient care pathways which have been suspended during the response to the COVID-19 pandemic. A significant backlog of planned elective work has built up representing a considerable volume of patient need. We aimed to investigate the health status, quality of life, and the impact of delay for patients whose referrals and treatment for symptomatic joint arthritis had been delayed as a result of the response to COVID-19. We interviewed 111 patients referred to our elective outpatient service and whose first appointments had been cancelled as a result of the response to the COVID-19 pandemic.Aim
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