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
To evaluate how abnormal proximal femoral anatomy affects different femoral version measurements in young patients with hip pain. First, femoral version was measured in 50 hips of symptomatic consecutively selected patients with hip pain (mean age 20 years (SD 6), 60% (n = 25) females) on preoperative CT scans using different measurement methods: Lee et al, Reikerås et al, Tomczak et al, and Murphy et al. Neck-shaft angle (NSA) and α angle were measured on coronal and radial CT images. Second, CT scans from three patients with femoral retroversion, normal femoral version, and anteversion were used to create 3D femur models, which were manipulated to generate models with different NSAs and different cam lesions, resulting in eight models per patient. Femoral version measurements were repeated on manipulated femora.Aims
Methods
The Patient-Reported Outcomes Measurement Information System (PROMIS) has demonstrated faster administration, lower burden of data capture and reduced floor and ceiling effects compared to traditional Patient Reported Outcomes Measurements (PROMs). We investigated the suitability of PROMIS Mobility score in assessing physical function in the sequelae of childhood hip disease. In all, 266 adolscents (aged ≥ 12 years) and adults were identified with a prior diagnosis of childhood hip disease (either Perthes’ disease (n = 232 (87.2%)) or Slipped Capital Femoral Epiphysis (n = 34 (12.8%)) with a mean age of 27.73 years (SD 12.24). Participants completed the PROMIS Mobility Computer Adaptive Test, the Non-Arthritic Hip Score (NAHS), EuroQol five-dimension five-level questionnaire, and the Numeric Pain Rating Scale. We investigated the correlation between the PROMIS Mobility and other tools to assess use in this population and any clustering of outcome scores.Aims
Methods
