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Bone & Joint Open
Vol. 5, Issue 2 | Pages 139 - 146
15 Feb 2024
Wright BM Bodnar MS Moore AD Maseda MC Kucharik MP Diaz CC Schmidt CM Mir HR

Aims

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.

Methods

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.”


Bone & Joint Research
Vol. 5, Issue 3 | Pages 73 - 79
1 Mar 2016
Anwander H Cron GO Rakhra K Beaule PE

Objectives

Hips with metal-on-metal total hip arthroplasty (MoM THA) have a high rate of adverse local tissue reactions (ALTR), often associated with hypersensitivity reactions. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) measures tissue perfusion with the parameter Ktrans (volume transfer constant of contrast agent). Our purpose was 1) to evaluate the feasibility of DCE-MRI in patients with THA and 2) to compare DCE-MRI in patients with MoM bearings with metal-on-polyethylene (MoP) bearings, hypothesising that the perfusion index Ktrans in hips with MoM THA is higher than in hips with MoP THA.

Methods

In this pilot study, 16 patients with primary THA were recruited (eight MoM, eight MoP). DCE-MRI of the hip was performed at 1.5 Tesla (T). For each patient, Ktrans was computed voxel-by-voxel in all tissue lateral to the bladder. The mean Ktrans for all voxels was then calculated. These values were compared with respect to implant type and gender, and further correlated with clinical parameters.