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
Periprosthetic joint infections (PJIs) and fracture-related infections (FRIs) are associated with a significant risk of adverse events. However, there is a paucity of data on cardiac complications following revision surgery for PJI and FRI and how they impact overall mortality. Therefore, this study aimed to investigate the risk of perioperative myocardial injury (PMI) and mortality in this patient cohort. We prospectively included consecutive patients at high cardiovascular risk (defined as age ≥ 45 years with pre-existing coronary, peripheral, or cerebrovascular artery disease, or any patient aged ≥ 65 years, plus a postoperative hospital stay of > 24 hours) undergoing septic or aseptic major orthopaedic surgery between July 2014 and October 2016. All patients received a systematic screening to reliably detect PMI, using serial measurements of high-sensitivity cardiac troponin T. All-cause mortality was assessed at one year. Multivariable logistic regression models were applied to compare incidence of PMI and mortality between patients undergoing septic revision surgery for PJI or FRI, and patients receiving aseptic major bone and joint surgery.Aims
Methods
Wear debris released from bearing surfaces has been shown to
provoke negative immune responses in the recipient. Excessive wear
has been linked to early failure of prostheses. Analysis using coordinate
measuring machines (CMMs) can provide estimates of total volumetric
material loss of explanted prostheses and can help to understand
device failure. The accuracy of volumetric testing has been debated,
with some investigators stating that only protocols involving hundreds
of thousands of measurement points are sufficient. We looked to
examine this assumption and to apply the findings to the clinical
arena. We examined the effects on the calculated material loss from
a ceramic femoral head when different CMM scanning parameters were
used. Calculated wear volumes were compared with gold standard gravimetric
tests in a blinded study. Objectives
Methods
