This study evaluated the outcomes of double mobility trapeziometacarpal prostheses for treating osteoarthritis (OA) of the trapeziometacarpal (TMC) joint. A prospective observational analysis was conducted on 150 implants with a maximum follow-up of four years, including a clinical and radiographic assessment and an evaluation of complications. The results indicate a prosthesis survival rate of 97.9% after the first two years post-surgery, calculated using the Kaplan-Meier method. Significant improvements were observed in pain reduction (mean VAS at 3 months post-surgery 2,9 and 1.5 after 6 months), hand grip strength (25.93 kg at 6 months post-surgery), and range of motion (Kapandji score from 8.8 to 9.2, comparing the preoperative mean with the mean after the first postoperative month). The complication rate was low, with only two cases of cup migration and one case of trapezium resorption. Patient satisfaction was high due to the rapid functional recovery and reduced invasiveness compared to traditional techniques. Double-mobility prostheses offer a highly effective treatment for stage II and III TMC OA according to the Eaton-Littler classification, with minimal need for revision surgeries.

Introduction The purpose of the study was to evaluate the results of treatment of the nonunion of long bones using nonvascularized iliac crest grafts (ICGs) or vascularized bone grafts (VBGs), such as medial femoral condyle corticoperiosteal flaps (MFCFs) and fibula flaps (FFs). Although some studies have examined the results of these techniques, there are no reports that compare these treatments and perform a multifactorial analysis. Methods The study retrospectively examined 28 patients comprising 9 women and 19 men with an average age of 49.8 years (range: 16–72 years) who were treated for nonunion of long bones between April 2007 and November 2018. The patients were divided into two cohorts: group A had 17 patients treated with VBGs (9 patients treated with MFCF and 8 with FF), while group B had 11 patients treated with ICG. The following parameters were analyzed: radiographic patterns of nonunion, trauma energy, fracture exposure, associated fractures, previous surgeries, diabetes, smoking, age, and donor-site morbidity. Results VBGs improved the healing rate (HR) by 9.42 times more than the nonvascularized grafts. Treatment with VBGs showed a 25% decrease in healing time. Diabetes increased the infection rate by 4.25 times. Upper limbs showed 70% lower infection rate. Smoking among VBG patients was associated with a 75% decrease in the HR, and diabetes was associated with an 80% decrease. Conclusion This study reports the highest success rates in VBGs. The MFCFs seem to allow better clinical and radiological outcomes with less donor-site morbidity than FFs. M.G. and M.G. researched literature and conceived the study. M.G., M.G., C.C., R.M.L., B.S.K., I.S.B., M.R., S.L., M.C., and D.P. were involved in protocol development, data analysis, and correction of the manuscript. M.G. wrote the draft of the manuscript. All authors reviewed and edited the manuscript and approved the final version of the manuscript. Article published online: 27 August 2022 © 2022. Society of Indian Hand Surgery & Microsurgeons. All rights reserved. Thieme Medical and Scientific Publishers Pvt. Ltd. A-12, 2nd Floor, Sector 2, Noida-201301 UP, India

Background: Artificial intelligence (AI) is rapidly transforming healthcare, with increasing applications in sports medicine. Advances in machine learning, deep learning, and computer vision enable the analysis of large, heterogeneous datasets derived from imaging, wearable sensors, performance-monitoring systems, and electronic health records. While these technologies offer opportunities to enhance injury prevention, diagnostic accuracy, rehabilitation monitoring, and clinical decision-making, their integration into athlete care remains complex and context-dependent. Methods: A structured narrative review of the PubMed/MEDLINE database was conducted to identify clinically relevant AI applications in sports medicine. The search focused on key domains including injury risk prediction, musculoskeletal imaging, rehabilitation monitoring, return-to-play assessment, performance management, and clinical workflow support. Evidence from original studies, reviews, methodological reports, and regulatory documents was qualitatively synthesized to provide an overview of current applications, methodological limitations, and decision-level implications. Results: AI demonstrates growing utility across multiple domains of sports medicine. Machine learning models can identify complex, non-linear relationships among training load, physiological responses, and injury risk, though their predictive performance varies widely and is often limited by dataset heterogeneity and a lack of external validation. In musculoskeletal imaging, AI-based algorithms support automated detection and quantification of abnormalities, with performance in selected tasks approaching that of expert readers, yet remaining task-specific and context-dependent. Emerging applications include movement analysis and rehabilitation monitoring through wearable sensors and computer vision systems, as well as data-driven support for return-to-play decisions and clinical workflow optimization. However, current evidence highlights important limitations, including algorithmic bias, limited generalizability, poor interpretability, and the risk of misapplication in complex clinical decision-making contexts. Conclusions: AI is likely to become an important decision-support layer in sports medicine by enabling data integration and longitudinal monitoring. However, model performance does not necessarily translate into improved clinical outcomes, and AI-generated predictions remain probabilistic and context-sensitive. Consequently, clinical decisions—particularly high-stakes processes such as return-to-play—require structured integration of AI outputs within a broader clinical framework. The sports physician remains central as a human-in-the-loop integrator, responsible for contextualizing AI-derived information, mitigating potential errors, and ensuring safe, individualized athlete management.

Stress fractures (SFs) are a common overuse injury in athletes and represent the severe end of the bone stress injury (BSI) continuum. They result from repetitive mechanical loading exceeding the bone’s capacity for adaptation and are associated with impaired performance, prolonged time away from sport, and risk of recurrence if not appropriately managed. This narrative review provides a clinically oriented synthesis of current evidence on the epidemiology, pathophysiology, risk factors, diagnosis, management, and prevention of SFs in athletes. Particular emphasis is placed on modifiable contributors, including training load errors, neuromuscular fatigue, and low energy availability within the framework of Relative Energy Deficiency in Sport (RED-S). Diagnostic evaluation is discussed using a stepwise clinical approach integrating history, physical examination, targeted laboratory assessment, and imaging, with magnetic resonance imaging (MRI) as the reference standard for early detection and severity grading. Management is presented through a risk-based framework combining MRI severity and anatomical site classification to guide treatment decisions and return-to-sport pathways. While most low-risk SFs respond to conservative strategies, high-risk lesions require closer monitoring and, in selected cases, early surgical consideration. This review proposes a practical clinical framework to support decision-making in athletes with suspected or confirmed SFs, aiming to improve early diagnosis, optimize management, and reduce recurrence risk in sports medicine practice.

Background: Thumb carpometacarpal (CMC) arthritis affects up to 25% of women and 8% of men over 70 years of age, significantly compromising their activities of daily living. With the rapid growth of the elderly population globally and their specific clinical needs, understanding optimal surgical treatment for this age group is crucial. This systematic review compares trapeziectomy with ligament reconstruction and tendon interposition (LRTI) versus dual-mobility prosthesis for treating thumb CMC arthritis in elderly patients over 70 years old. Methods: A systematic search was conducted across PubMed, Scopus, Web of Science, and the Cochrane Library for studies published up to August 2025. Studies that directly compared both techniques were included, with subgroup analyses performed for elderly patients over 70 years of age when data were available. Primary outcomes included pain relief, functional improvement, grip and pinch strength, complications, and patient satisfaction. Results: Five studies met the inclusion criteria for direct comparison of both techniques, encompassing 313 patients (324 thumbs). While none exclusively focused on patients over 70, elderly patients represented 25–41% of study populations. Due to the absence of age-stratified data in the original studies, our analysis encompasses all age groups with specific considerations for elderly patients where identifiable. Dual-mobility prostheses demonstrated faster pain relief and earlier functional improvement, particularly within the first 3–6 months postoperatively. Prostheses consistently provided superior grip and pinch strength outcomes throughout follow-up periods. Both procedures effectively preserved thumb function, but prostheses better maintained thumb length and metacarpophalangeal stability. While complication rates were comparable, LRTI complications were typically minor and self-limiting, whereas prosthesis complications, though rare, could potentially require revision surgery. Longer-term follow-up data (>3 years) remain limited, particularly regarding implant degradation and adverse local tissue reactions. Conclusions: Both procedures effectively treat thumb CMC arthritis in elderly patients, with distinct advantages. Dual-mobility prostheses offer faster recovery, enhanced strength, and better thumb length preservation, making them potentially advantageous for elderly patients prioritizing rapid functional recovery. Trapeziectomy with LRTI provides reliable long-term pain relief with fewer serious complications, making it suitable for patients with poor bone quality or significant comorbidities. Treatment selection should be individualized based on patient characteristics, functional demands, and surgeon expertise. Future research specifically focusing on elderly populations with longer follow-up periods (>5 years) is critically needed to provide stronger evidence for this growing demographic and to better understand long-term implant performance.