Citations

Abstract Purpose The purpose of this systematic review was to compare the inter‐ and intra‐observer reliability of Kellgren–Lawrence (KL) grading versus minimum joint space width (mJSW) measurement on knee radiographs, and to examine the influence of rater type, radiographic view and atlas‐based training. Methods A systematic search of PubMed/MEDLINE, Embase, Scopus and Web of Science was conducted through July 2025 following Preferred Reporting Items for Systematic reviews and Meta‐Analyses (PRISMA) guidelines. Studies reporting inter‐ and/or intra‐observer reliability for KL or mJSW on standard knee radiographs were included. Extracted data included kappa ( κ ) and intraclass correlation coefficient (ICC) values, rater expertise, radiographic view and atlas usage. Raters were categorized as expert, trainee/non‐expert or artificial intelligence (AI)‐assisted/automated. Results Twenty‐four studies (10,394 radiographs) met the inclusion criteria. Inter‐observer reliability was generally higher for mJSW (mean ICC = 0.82 ± 0.17) compared with KL (mean k = 0.72 ± 0.17), with similar trends observed for intra‐observer reliability. Experts and AI‐assisted systems outperformed trainees/non‐experts for both metrics. Reliability improved with semiflexed posteroanterior/Rosenberg views and atlas‐guided training. Conclusion This systematic review demonstrates that mJSW measurement generally shows higher reproducibility than KL grading. Reliability improved with expertise, standardized imaging and structured training, and AI‐assisted approaches performed comparably to expert raters. Quantitative mJSW should complement KL grading, particularly when combined with alignment measures, to enhance consistency and clinical relevance of radiographic assessment. Level of Evidence Level III.

Background: We aimed to develop automated data extraction pipelines with large language models (LLMs) to extract registry data from total hip arthroplasty (THA) operative notes and compare the performance with that of existing natural language processing (NLP) algorithms. Methods: We randomly sampled 1,000 primary THA cases from our institutional registry. Two human annotators manually reviewed each operative note for 3 data points: surgical approach, bearing surface, and fixation technique. All labeled THA notes were split into the development set (n = 239) and the testing set (n = 719). We developed a custom data extraction pipeline for each data point by combining an iteratively customized prompt with an LLM. The performance was compared with that of existing rules-based NLP algorithms. Results: The accuracy of LLMs was superior to that of NLP algorithms for all data points: surgical approach (96% compared with 94%), bearing surface (89% compared with 74%), and fixation technique (96% compared with 95%). Furthermore, the LLM accurately inferred the bearing surface for 80% of the notes that were ambiguous about the bearing surface. Conclusions: We developed LLM pipelines for extracting 3 registry-relevant data points from THA operative notes, demonstrating superior performance to existing NLP algorithms. Clinical Relevance: LLMs have the potential to impact clinical care, including the evaluation of electronic medical record free-text data. As registries serve as a cornerstone of orthopaedic evidence, this work demonstrates promise for LLMs to simplify, improve, and democratize the construction of registry databases from operative notes.

Introduction: Manual measurement of leg length (LL) and offset can be tedious. This study developed an automated algorithm for measuring LL and offset from pre- and postoperative AP pelvis radiographs in a large cohort of THA patients. Methods: Using a deep learning model trained on 1100 total AP pelvis radiographs, an algorithm was developed to calculate LL and offset. Algorithm measurements were compared with manual measurements by 4 raters on a sample of 100 pre- and postoperative image pairs. Inter- and intra-rater consistency was calculated using the intraclass correlation coefficient (ICC). The algorithm was applied to calculate the pre- and postoperative LL and offset discrepancies and the change in LL and offset bilaterally in a cohort of 15,951 image pairs. Results: ICC values between the algorithm and human raters ranged from 0.83 to 0.88 for offset measurements and 0.92 to 0.97 for LL measurements. Human raters demonstrated good-to-excellent inter-rater ICC and uniformly excellent intra-rater ICC. Entire database measurements demonstrated shorter LLs for arthritic joints versus the contralateral leg preoperatively and reduced LL discrepancy post-arthroplasty. Conclusions: We present a deep learning algorithm for calculating LL and offset using AP pelvis radiographs. This tool can support population-level studies and may assist operative management.

Artificial intelligence (AI) is increasingly shaping pediatric spine care, leveraging its rapid advancements in healthcare to improve efficiency, accuracy, and disease understanding. Moreover, machine learning and deep learning excel at detecting complex patterns. This holds promise in processing spinal deformity data, with the potential to surpass traditional statistical methods in predictive accuracy. Challenges persist, however, including unclear clinical implementation guidelines, limited model transparency, and ethical concerns surrounding data privacy and bias. Small sample sizes and the need for larger, diverse datasets further complicate integration. In order to realize AI’s transformative potential in pediatric spine care, these critical obstacles must be addressed for effective and ethical clinical adoption. This review examines the role of AI through applications such as image sorting, surgical outcome prediction, forecasting of spinal curve progression, and vertebral volumetric analysis using deep reasoning. It also explores possible intraoperative contributions from AI, including robotics and optimized screw trajectory planning, and the potential of large language models in clinical practice.

ABSTRACT Femoroacetabular impingement (FAI) of the hip results from altered morphology of the proximal femur and/or acetabulum, creating abnormal contact between these structures during normal hip range of motion. The etiology of this structural phenotype is unknown. This study aimed to identify common single‐nucleotide variants (SNVs) among two families with seemingly heritable FAI. Additionally, this study examined biologic networks among proteins encoded by identified SNVs and surveyed the literature regarding the role of these proteins in musculoskeletal development. Methodologically, blood samples were collected from affected and unaffected members of two separate families with a pattern of heritable FAI. Exome sequencing identified SNVs, and a protein–protein interaction network assessment, in addition to a literature review, was performed to better understand the role of variant‐associated genes in musculoskeletal development. Results showed 33 and 43 variant‐associated genes affected in Family 1 and Family 2, respectively. Although no overlap in variant‐associated genes was found between families, network analysis showed that variant‐associated genes are functionally interconnected and are known to interact with each other. Furthermore, the variant‐associated genes are broadly associated with musculoskeletal development. Ultimately, genetic analysis of two families of multiple generations of FAI revealed variations in genes regulating musculoskeletal development, with several being critical local regulators of bone morphogenesis.

Background: Orthopaedic surgeons routinely delay surgical management of femoral neck fractures in patients taking direct oral anticoagulants (DOACs) to decrease perioperative bleeding and associated complications. However, this practice contradicts the principles of hip fracture management, as early surgery is associated with morbidity and mortality benefits. The purpose of this study was to quantify the association of DOAC use and perioperative outcomes in patients who underwent hemiarthroplasty (HA) or total hip arthroplasty (THA) for femoral neck fractures. We hypothesized that early surgical intervention on a patient taking a DOAC medication would not lead to worse perioperative outcomes. Methods: A retrospective cohort study was conducted on 2,833 patients who underwent primary THA or HA for femoral neck fractures between December 31, 2017, and January 29, 2024, across our hospital system. The patients taking a DOAC were divided into 3 groups based on the time since the last DOAC intake: 1 day, 2 days, and ≥3 days. Propensity matching was performed 1:1, accounting for age, sex, Elixhauser Comorbidity Index, preoperative chronic kidney disease stage, preoperative hemoglobin, body mass index, and hospital type. Subanalyses utilizing linear and conditional logistic regression models were performed to assess differences in outcomes between the groups that had a DOAC withheld and the control groups. Results: The mean age of all patients was 81 ± 10 years, 1,805 patients (64%) were women, and 207 patients (7%) were taking a DOAC prior to surgery. Despite comparable preoperative and postoperative hemoglobin levels between the groups that had a DOAC withheld and the control groups (all p > 0.05), the patients who had a DOAC withheld for 1 day were more likely to receive a postoperative blood transfusion (23.1% compared with 0%; p = 0.002). This difference in transfusion rate was not observed in other cohorts. There were no differences in medical complications, reoperation, discharge disposition, or mortality between the groups that had a DOAC withheld and the matched controls at any time point. Conclusions: Delaying surgical management due to DOAC medications may be unnecessary in patients undergoing arthroplasty for femoral neck fractures. Consideration should be given to adjusting transfusion triggers to reduce unwarranted blood transfusions in patients taking a DOAC. Level of Evidence: Therapeutic Level III . See Instructions for Authors for a complete description of levels of evidence.

Aims The use of jumbo femoral heads, defined as those with a diameter of ≥ 40 mm, in primary total hip arthroplasty (THA) has gained popularity, to mitigate dislocation. The aim of this study was to determine the risk of dislocation, implant survival, and clinical outcomes of a large cohort of primary THAs with jumbo femoral heads. Methods We conducted a retrospective analysis of 1,828 primary THAs with jumbo femoral heads, which were undertaken for osteoarthritis, in 1,578 patients between January 2000 and December 2022, at a single academic medical centre. The femoral head diameter was 40 mm in 1,584 THAs (87%) and 44 mm in 244 THAs (13%). The outer diameter of the acetabular component ranged from 52 mm to 72 mm in those with 40 mm heads, and from 54 mm to 78 mm in those with 44 mm heads. The types of bearing included ceramic-on-highly cross-linked polyethylene (1,229 THAs; 67%) and metal-on-polyethylene (599 THAs; 33%). Elevated liners were used in 472 THAs (26%) and 1,083 (59%) were lateralized. The most common operative approach was posterior (1,388 THAs; 76%). Outcomes of interest included the rate of dislocation, revision for dislocation, any revision, any reoperation, and the Harris Hip Score (HHS). The mean age of the patients at the time of THA was 64 years (8 to 94); 1,477 (81%) were male, and their mean BMI was 28 kg/m² (5 to 55). The mean follow-up was six years (2 to 14). Results The ten-year survival free of dislocation was 97% (95% CI 96 to 98; 97% for 40 mm heads (95% CI 95 to 98) and 99% for 44 mm heads (95% CI 97 to 100) (hazard ratio 3 (95% CI 1 to 14); p = 0.106)). The ten-year survival free of revision for dislocation was 99.6% (95% CI 99 to 100) (99.5% for 40 mm heads (95% CI 98 to 100) and 100% for 44 mm heads (p = 0.546)). The ten-year survival free of any revision and any reoperation was 95% (95% CI 94 to 97) and 93% (95% CI 91 to 95), respectively. There were no significant differences in survival free of any revision (p = 0.746) or any reoperation (p = 0.762) between the two groups. Conclusion In this large single-centre study of the use of jumbo femoral heads in primary THAs, the ten-year survival free of dislocation was 97%, with extremely few revisions for dislocation. These results highlight the potential for jumbo femoral heads to reduce the risk of dislocation and enhance implant longevity without compromising other clinical outcomes. Cite this article: Bone Joint J 2025;107-B(7):698–706.

As artificial intelligence (AI) advances in healthcare, encompassing robust applications for the diagnosis and prognostication of musculoskeletal diseases, clinicians must increasingly understand the implications of machine learning and deep learning in their practice. This review article explores computer vision algorithms and patient-specific, multimodal prediction models; provides a simple framework to guide discussion on the limitations of AI model development; and introduces the field of generative AI.