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
Methods
The aim of this study was to conduct the largest low contact stress (LCS) retrieval study to elucidate the failure mechanisms of the Porocoat and Duofix femoral component. The latter design was voluntarily recalled by the manufacturer. Uncemented LCS explants were divided into three groups: Duofix, Porocoat, and mixed. Demographics, polyethylene wear, tissue ingrowth, and metallurgical analyses were performed.Aims
Materials and Methods
