Background: Unknown is which response rate on patient-reported outcome measures (PROMs) is needed to both obtain an accurate outcome and ensure generalizability in evaluating total hip arthroplasty (THA) procedures. Without an evidence based minimum response rate (MRR) on THA PROMs, it is possible that hospitals report invalid patient-reported outcomes (PROs) due to a too low response rate. Alternatively, hospitals may invest too much in achieving an unnecessary high response rate. The aim of this study is to gain an insight into the MRR on PROMs needed to adequately evaluate THA procedures from a clinical perspective. Methods: Retrospective study on prospective collected data of primary, elective THA procedures was performed. MRR was investigated for each PROM (NRS pain at rest, NRS pain during activity, EQ-5D-3L, HOOS-PS, anchor function, OHS, anchor pain and NRS satisfaction) separately to calculate the primary outcome: MRR for the THA PROMs set. MRR on a PROM needed to have (condition 1.) similar PRO change score (3 month score minus preoperative score) including confidence interval, (condition 2.) maintaining the influence of each change score predictor and (condition 3.) equal distribution of each predictor, as those of a 100% PROM response rate group. Per PROM, a 100%-group was identified with all patients having the PRO change score. Randomly assessed groups of 90% till 10% response rate (in total 90 groups) were compared with the 100%-group. Linear mixed model analyses and linear regressions were executed. Results: The MRR for the THA PROMs set was 100% (range: 70–100% per PROM). The first condition resulted in a MRR of 60%, the second condition in a MRR of 100% and the third condition in a MRR of 10%. Conclusions: A 100% response rate on PROMs is needed in order to adequately evaluate THA procedures from a clinical perspective. All stakeholders using THA PROs should be aware that 100% of the THA patients should respond on both preoperative and 3 month postoperative PROMs. For now, taking the first step in improving evaluation of THA for quality control by achieving at least two of the three conditions of MRR, advised is to require a response rate on PROMs of 60% as the lower limit.

Patient Engagement Platforms, particularly chat functionalities, potentially improve communication but may also heighten workload, contributing to burnout among healthcare professionals. Natural Language Processing advancements, like ChatGPT and Med-PaLM, offer human-like responses to various questions, but concerns about their use in healthcare remain. This study evaluates whether Large Language Models can respond to patient questions as well as support staff in terms of quality and empathy. In this cross-sectional study, 111 patient questions on lower limb arthroplasty, answered by support staff via an app, were selected. These questions were put into ChatGPT 3.5 to generate responses, and were collected on July 2 and 3, 2024. Two blinded healthcare professionals, an orthopaedic surgeon and an anesthetist, evaluated both the responses generated by ChatGPT and support staff, on quality, empathy, and risk of potential adverse events, selecting their preferred responses and identifying what they thought was ChatGPT's response. A Patient Panel (n = 29) also assessed responses on empathy, preference, and source of the responses. Fifty questions were available for a comparative analysis between ChatGPT and support staff responses. No quality difference was found (p = 0.075) between ChatGPT and support staff, though ChatGPT was rated as more empathetic (p < 0.001). No difference was found between the two responses in the risk of incorrect treatment (p = 0.377). Physicians identified ChatGPT's responses in 84-90 % of cases. The Patient Panel found ChatGPT to be more empathetic (p < 0.001) but showed no preference for ChatGPT (p = 0.086). Patients accurately identified ChatGPT's responses in 34.5 % of cases (p = 0.005). Three ChatGPT responses showed high-risk errors. This study shows ChatGPT generated high quality and empathetic responses to patient questions about lower limb arthroplasty. Further investigation is needed to optimize clinical use, but high appreciation for ChatGPT responses highlights the potential for use in clinical practice in the near future.

The bridging nail is a retrograde intramedullary femoral nail designed to stabilize periprosthetic femoral fractures. It offers a minimal invasive surgical approach in combination with early mobilization. The goal of this study was to evaluate the osteosynthesis under full weight-bearing conditions. Three groups of five composite fibreglass femora were prepared with a cemented hip stem. Group 1 underwent cyclic axial loading with 1500 N during 150 000 cycles. After completion, linear loading to failure was conducted. Groups 2 and 3 were submitted to linear increased torsional loading with and without an axial load respectively. Failure was defined as rotational movement of the connection (slippage). In the axial cyclic loading configuration, one specimen failed after 122 000 cycles. Four specimens passed 150 000 cycles and failed after linearly increasing the axial loading of 1940–2600 N (mean, 2408 N ± 313 standard deviation (SD)). Slippage was first detected at a torque varying between 2.5 and 8.2 N m (mean, 5.1 N m ± 2.1 SD) in group 2 and between 10.0 and 15.4 N m (mean, 13.0 N m ± 2.3 SD) in group 3. In conclusion the bridging nail offers a stable connection with the stem of a hip arthroplasty which can resist high repetitive loads, representative of direct full axial weight bearing. The biomechanical results support the clinical experience of a stable osteosynthesis enabling early post-operative mobilization.