Length of stay, pain and opioid consumption following manual versus robotic-assisted total hip arthroplasty.

Background: Robotic assistance in total hip arthroplasty (THA) has increased, but the influence on outcomes compared to manual THA remains uncertain. With the growing emphasis on reducing opioid consumption after arthroplasty, we studied whether robotic assistance was associated with length of stay (LOS), pain, and opioid use after THA.

Materials And Methods: We included 14,501 opioid-naïve patients who underwent THA at a single institution between 2019 and 2023 (8900 manual and 5601 robotic).

Development of a multimodal vision transformer model for predicting traumatic versus degenerative rotator cuff tears on magnetic resonance imaging: A single-centre retrospective study.

Purpose: The differentiation between traumatic and degenerative rotator cuff tears (RCTs remains a diagnostic challenge with significant implications for treatment planning. While magnetic resonance imaging (MRI) is standard practice, traditional radiological interpretation has shown limited reliability in distinguishing these etiologies. This study evaluates the potential of artificial intelligence (AI) models, specifically a multimodal vision transformer (ViT), to differentiate between traumatic and degenerative RCT.

Development of Explainable Machine Learning Models to Predict Outcomes After Platelet-Rich Plasma Injections for Knee Osteoarthritis.

Background: Platelet-rich plasma (PRP) has been increasingly used to treat knee osteoarthritis, but its efficacy remains unclear due to the variability of outcomes. Machine learning (ML) can improve the ability to predict responses to PRP treatment by identifying specific baseline characteristics of patients who may have greater clinical improvements.

Purpose: To develop and evaluate an ML model predicting clinical outcomes after PRP injection for knee osteoarthritis.

Developing and validating machine learning models to predict acetabular cup size in total hip arthroplasty.

Aims: Adequate implant inventory management can improve efficiency, storage space, and result in cost savings in arthroplasty. This study investigates if the prediction of cup size in elective primary total hip arthroplasty (THA) cound be improved with the use of advanced machine learning.

Methods: Using the arthroplasty registry of a single institution, we identified 30,583 patients who underwent primary THA between 2016 and 2024.

Pain and pain management following manual versus robotic assisted unicondylar knee arthroplasty.

Aims: The adoption of robotic assistance for unicondylar knee arthroplasty (UKA) is increasing, driven by reports of improved implant positioning. However, its impact on short-term patient outcomes remains debated. This study aimed to compare postoperative pain, opioid consumption, and length of hospital stay between manual (maUKA) and robotic-assisted (raUKA) procedures in a large, real-world cohort.

Obesity Class Does Not Associate With Incidence, Timing, or Invasiveness of Reoperations After Total Hip Arthroplasty.

Background: Body mass index (BMI) cut-off values have been proposed to determine eligibility for elective total hip arthroplasty (THA) in obese patients. However, the relationship between the severity of obesity and reoperations remains poorly understood. We evaluated whether the World Health Organization (WHO) obesity class is independently associated with the risk, invasiveness, or timing of reoperations after THA in obese patients.

Artificial intelligence-assisted analysis of musculoskeletal imaging-A narrative review of the current state of machine learning models.

The potential of Artificial intelligence (AI) is increasingly recognized in musculoskeletal radiology, offering solutions to challenges posed by increasing imaging volumes and fellowship trained radiologist shortages. The integration of AI is not intended to replace radiologists but to augment their capabilities, improving workflow efficiency and diagnostic accuracy. This narrative review examines the current landscape of AI applications in musculoskeletal imaging, focusing on both general-purpose multimodal models and specialized foundation models.

Artificial Intelligence and Musculoskeletal Surgical Applications.

Artificial intelligence (AI) has emerged as a transformative force in orthopedic surgery. Potentially encompassing pre-, intra-, and postoperative processes, it can process complex medical imaging, provide real-time surgical guidance, and analyze large datasets for outcome prediction and optimization. AI has shown improvements in surgical precision, efficiency, and patient outcomes across orthopedic subspecialties, and large language models and agentic AI systems are expanding AI utility beyond surgical applications into areas such as clinical documentation, patient education, and autonomous decision support.

Efficacy and safety of xenograft augmentation in rotator cuff repair: a systematic review and meta-analysis.

Rotator cuff tears are common disorders that can significantly impact patientś shoulder function and quality of life. Incomplete or failed healing is relatively common following repair of large tendon tears. Xenograft materials are increasingly used for augmentation of repairs, but their efficacy and safety remain under debate.

Correlation and Comparative Evaluation of MOCART and MOCART 2.0 for Assessing Cartilage Repair.

: Chondral and osteochondral lesions can lead to osteoarthritis if untreated, making accurate assessment of cartilage repair outcomes essential for optimizing treatment strategies. The objective of this study was to compare MOCART and MOCART 2.0 and to evaluate the clinical utility of both across different surgical cartilage repair techniques and various time points.

A practical guide to the implementation of AI in orthopaedic research-Part 7: Risks, limitations, safety and verification of medical AI systems.

Unlabelled: Artificial intelligence (AI) has been influencing healthcare and medical research for several years and will likely become indispensable in the near future. AI is intended to support healthcare professionals to make the healthcare system more efficient and ultimately improve patient outcomes. Despite the numerous benefits of AI systems, significant concerns remain.

A History of Bariatric Surgery Negatively Affects the Rate of 90-Day Complications of Elective Primary Total Joint Arthroplasty: A Comparative Analyses of 2,979 Patients.

Background: The potential benefits of preoperative weight loss with bariatric surgery in reducing short-term complications of total joint arthroplasty (TJA) have been questioned. We studied the odds of 90-day postoperative complications by comparing TJA patients who had a history of bariatric surgery to a control group.

Methods: There were 678 patients who had undergone bariatric surgery before TJA (199 total hip arthroplasty [THA], 479 total knee arthroplasty [TKA]) matched 1:4 for body mass index at the time of TJA, age, sex, replaced joint, and American Society of Anesthesiologists Class with a control group of 2,301 TJA (644 THA; 1,657 TKA) patients who did not have bariatric surgery.

Beyond traditional orthopaedic data analysis: AI, multimodal models and continuous monitoring.

Multimodal artificial intelligence (AI) has the potential to revolutionise healthcare by enabling the simultaneous processing and integration of various data types, including medical imaging, electronic health records, genomic information and real-time data. This review explores the current applications and future potential of multimodal AI across healthcare, with a particular focus on orthopaedic surgery. In presurgical planning, multimodal AI has demonstrated significant improvements in diagnostic accuracy and risk prediction, with studies reporting an Area under the receiving operator curve presenting good to excellent performance across various orthopaedic conditions.

Comparison of Outcomes Between Staged and Same-Day Circumferential Spinal Fusion for Adult Spinal Deformity: Systematic Review and Meta-Analysis.

Background: Adult spinal deformity (ASD) is a prevalent condition often treated with circumferential spinal fusion (CF), which can be performed as staged or same-day procedures. However, evidence guiding the choice between these approaches is lacking.

Objective: This study aims to compare patient outcomes following staged and same-day CF for ASD.

Mid-term Results Following Surgical Hip Dislocation for Residual Pediatric Deformities.

Background: Mid-term results following surgical hip dislocation (SHD) for healed slipped capital femoral epiphysis (SCFE) and Perthes-related deformities are limited. This study aimed to characterize patient-reported outcome measures [including rates of achieving the minimal clinically important difference (MCID) and patient-acceptable symptomatic state (PASS)], report survivorship free from conversion to arthroplasty, and identify risk factors associated with composite failure.

Methods: Twenty-seven patients (n=13 SCFE, n=14 Perthes) with minimum 2-year follow-up (mean 5.

The artificial intelligence advantage: Supercharging exploratory data analysis.

Explorative data analysis (EDA) is a critical step in scientific projects, aiming to uncover valuable insights and patterns within data. Traditionally, EDA involves manual inspection, visualization, and various statistical methods. The advent of artificial intelligence (AI) and machine learning (ML) has the potential to improve EDA, offering more sophisticated approaches that enhance its efficacy.

A practical guide to the implementation of AI in orthopaedic research, Part 6: How to evaluate the performance of AI research?

Unlabelled: Artificial intelligence's (AI) accelerating progress demands rigorous evaluation standards to ensure safe, effective integration into healthcare's high-stakes decisions. As AI increasingly enables prediction, analysis and judgement capabilities relevant to medicine, proper evaluation and interpretation are indispensable. Erroneous AI could endanger patients; thus, developing, validating and deploying medical AI demands adhering to strict, transparent standards centred on safety, ethics and responsible oversight.