Anterior cruciate ligament (ACL) injuries are common in sports and often require surgical intervention, e.g., ACL reconstruction (ACLR), aimed at restoring knee stability and enabling a return to pre-injury activity levels. The choice of graft is crucial, impacting biomechanical properties, clinical outcomes, and complication rates, and is especially important in revision surgeries after graft failure. Over the past 30 years, trends in graft selection have evolved towards more individualized approaches, considering factors such as patient activity level, prior injuries, and tissue availability. In Europe, autografts like hamstring tendon (HT), bone-patellar tendon-bone (BTB), and quadriceps tendon (QT) are preferred, with the increasing use of QT grafts. This review synthesizes the current literature on graft selection and its influence on ACLR outcomes.

Purpose: The aim of this study was to conduct a systematic review and meta‐analysis on the reliability and applicability of artificial intelligence (AI)‐based analysis of leg axis parameters. We hypothesized that AI‐based leg axis measurements would be less time‐consuming and as accurate as those performed by human raters.Methods: The study protocol was registered with the International Prospective Register of Systematic Reviews (PROSPERO). PubMed, Epistemonikos, and Web of Science were searched up to 24 February 2024, using a BOOLEAN search strategy. Titles and abstracts of identified records were screened through a stepwise process. Data extraction and quality assessment of the included papers were followed by a frequentist meta‐analysis employing a common effect/random effects model with inverse variance and the Sidik–Jonkman heterogeneity estimator.Results: A total of 13 studies encompassing 3192 patients were included in this meta‐analysis. All studies compared AI‐based leg axis measurements on long‐leg radiographs (LLR) with those performed by human raters. The parameters hip knee ankle angle (HKA), mechanical lateral distal femoral angle (mLDFA), mechanical medial proximal tibial angle (mMPTA), and joint‐line convergence angle (JLCA) showed excellent agreement between AI and human raters. The AI system was approximately 3 min faster in reading standing long‐leg anteroposterior radiographs (LLRs) compared with human raters.Conclusion: AI‐based assessment of leg axis parameters is an efficient, accurate, and time‐saving procedure. The quality of AI‐based assessment of the investigated parameters does not appear to be affected by the presence of implants or pathological conditions.Level of Evidence: Level I.

Background and Objectives: Artificial intelligence-driven large language models such as ChatGPT increasingly influence patient education in surgical fields. This study evaluates the quality and accuracy of ChatGPT-3.5-generated responses to patient questions regarding femoroacetabular impingement syndrome (FAIS) and hip arthroscopy (HAS). Materials and Methods: In this descriptive observational study, ChatGPT-3.5 generated and answered 20 representative patient questions about FAIS and HAS (n = 20 question–answer pairs). No patient-derived questions or data were used. Each response was independently evaluated by two fellowship-trained orthopedic surgeons across four domains: relevance, accuracy, clarity, and completeness, using a five-point Likert scale. Inter-rater reliability was calculated using the intraclass correlation coefficient (ICC), and descriptive inter-rater agreement percentages were reported. Additional qualitative impressions from the reviewers were recorded to contextualize areas in which responses were rated slightly lower, particularly regarding explanatory depth and postoperative variability. Results: Mean ratings across all domains ranged from 4.85 ± 0.24 (95% CI: 4.74–4.96) to 5.00 ± 0.00. Relevance achieved a perfect mean score of 5.00, while accuracy and clarity each obtained 4.98 ± 0.11 (95% CI: 4.91–5.00). Completeness demonstrated the lowest scores (4.85 ± 0.24). Due to pronounced ceiling effects, ICC values were non-informative; however, descriptive agreement between raters was high, with 100% concordance for relevance and 90% agreement for accuracy and clarity. No factually incorrect or unsafe information was identified. Overall, responses were concise, structured, and clinically appropriate, though occasionally lacking in granularity concerning individual recovery trajectories and procedure-specific nuances. Conclusions: ChatGPT-3.5 demonstrates significant potential as a supplementary patient education tool in hip preservation surgery. While its responses were consistently accurate and easy to understand, their occasional lack of detail, particularly concerning postoperative expectations and variability in outcomes, indicates that the findings apply primarily to synthetic, standardized questions in a controlled setting. Further validation is required before generalizing these results to real-world patient interactions. Future studies should incorporate authentic patient questions, diverse evaluator groups, and longitudinal assessment across different LLM versions to better define clinical applicability and safety.

Background: The aim of the study was to compare the short-term outcome of SuperPATH, direct anterior (DAA) and conventional approach (CA) hemiarthroplasty (HA) in patients with femoral neck fractures using a network meta-analysis. Methods: PubMed, China National Knowledge Infrastructure, Epistemonikos, and Embase were searched until May 31, 2024. In a network meta-analysis, mean differences with 95% confidence intervals were calculated using the Hartung–Knapp–Sidik–Jonkman method and a fixed/random effects model for continuous outcomes, and odds ratios with 95% confidence intervals were calculated using the Mantel–Haenszel method and a fixed/random effects model for dichotomous outcomes. Results: The literature search identified a total of 9 randomized controlled trials on SuperPATH with 762 patients and 8 randomized controlled trials on DAA with 641 patients. In the overall ranking, SuperPATH was placed first, DAA second and CA third. SuperPATH HA was best in 7, second best in 2 and third best in 1 of the 10 outcome parameters. DAA HA was best in 2 and second best in 8 of the 10 outcome parameters. CA HA was best in 1 and third best in 9 of the 10 outcome parameters. In the indirect comparison between SuperPATH HA and DAA HA, SuperPATH HA had a 1.36 point lower visual analog scale at 2 to 7 days postoperatively and a 0.17 lower overall complication rate compared to DAA. Conclusion: For the treatment of patients with femoral neck fractures, SuperPATH HA ranked first, DAA HA ranked second and CA HA ranked third. Based on the results, we recommend that trauma surgeons increase their use of minimally invasive hip HA techniques. It should be noted that SuperPATH HA had a significantly lower overall complication rate compared to DAA HA when the minimally invasive technique was chosen.

Purpose: The hip‐knee‐ankle angle is a crucial parameter in orthopaedic surgery for lower limb assessment. However, traditional methods for measuring the hip‐knee‐ankle angle on standing long‐leg anteroposterior radiographs are time‐consuming, require significant expertise and lack reproducibility. Given the emergence of artificial intelligence as a promising tool to automate these measurements, this study aimed to assess the accuracy of Gleamer BoneMetrics for hip‐knee‐ankle angle measurement and its correlation with assessments by experienced orthopaedic surgeons. Methods: A total of 75 patients who underwent knee arthroplasty between October 2023 and June 2024 were included. Preoperative and postoperative long‐leg anteroposterior radiographs were analysed both by two experienced orthopaedic surgeons who manually measured the hip‐knee‐ankle angle and by the Gleamer BoneMetrics software; the analyses were tested for both inter‐ and intra‐rater reliability. Statistical analysis was performed using intraclass correlation coefficients and Bland‐Altman plots to assess the correlation between the Gleamer BoneMetrics and the human raters. Results: The Gleamer BoneMetrics demonstrated excellent inter‐ and intra‐rater reliability, with intraclass correlation coefficient values ranging from 0.995 to 0.998, which were comparable to the surgeons' measurements of 0.997–0.998. The Gleamer BoneMetrics's intra‐rater reliability was also excellent, with intraclass correlation coefficient values of 1.0 preoperatively and 0.996 postoperatively. Bland–Altman analysis showed minimal measurement discrepancies between Gleamer BoneMetrics and the human raters. However, in 2% of the cases ( n = 3), Gleamer BoneMetrics was not able to provide measurements. Conclusion: The artificial intelligence‐based BoneMetrics software offers an efficient and accurate method for hip‐knee‐ankle angle measurement, with performance comparable to experienced orthopaedic surgeons. While promising, further development is necessary to address cases in which image quality or positioning issues prevent automated measurement and to reduce reliance on human quality control. Level of Evidence: Level III.

Aims: The transepicondylar axis is a well-established reference for the determination of femoral component rotation in total knee arthroplasty (TKA). However, when severe bone loss is present in the femoral condyles, rotational alignment can be more complicated. There is a lack of validated landmarks in the supracondylar region of the distal femur. Therefore, the aim of this study was to analyze the correlation between the surgical transepicondylar axis (sTEA) and the suggested dorsal cortex line (DCL) in the coronal plane and the inter- and intraobserver reliability of its CT scan measurement.Methods: A total of 75 randomly selected CT scans were measured by three experienced surgeons independently. The DCL was defined in the coronal plane as a tangent to the dorsal femoral cortex located 75 mm above the joint line in the frontal plane. The difference between sTEA and DCL was calculated. Descriptive statistics and angulation correlations were generated for the sTEA and DCL, as well as for the distribution of measurement error for intra- and inter-rater reliability.Results: The external rotation of the DCL to the sTEA was a mean of 9.47° (SD 3.06°), and a median of 9.2° (IQR 7.45° to 11.60°), with a minimum value of 1.7° and maximum of 16.3°. The measurements of the DCL demonstrated very good to excellent test-retest and inter-rater reliability coefficients (intraclass correlation coefficient 0.80 to 0.99).Conclusion: This study reveals a correlation between the sTEA and the DCL. Overall, 10° of external rotation of the dorsal femoral cortical bone to the sTEA may serve as a reliable landmark for initial position of the femoral component. Surgeons should be aware that there are outliers in this study in up to 17% of the measurements, which potentially could result in deviations of femoral component rotation.Cite this article: Bone Jt Open 2024;5(12):1067–1071.