Postoperative infection of internal fixation of closed fractures the lower limbs in adults represents a devastating complication, characterized by diagnostic challenges, prolonged treatment duration and high disability rates. Current management of these infections faces multiple challenges, such as difficulties in early accurate diagnosis, and various controversies about the treatment plan, leading to poor overall diagnosis and treatment results. To address these issues, based on evidence-based medicine and principles with emphasis on scientific rigor, clinical applicability and innovation, the Trauma Branch of the Chinese Medical Association, Orthopedic Branch of the Chinese Medical Doctor Association, Orthopedics Branch of the Chinese Medical Association, and Trauma Orthopedics and Polytrauma Group of the Resuscitation and Emergency Committee of the Chinese Medical Doctor Association have collaboratively organized a panel of relevant experts to develop the Guideline for diagnosis and treatment of infection after internal fixation of closed lower limb fractures in adults ( version 2025). The guideline proposed 10 recommendations, aiming to provide a foundation for standardized diagnosis and treatment of postoperative infection in adults with closed lower limb fractures.

Spinal cord injury (SCI) is a neurological disorder that occurs after a direct or indirect violent injury to the spinal cord, often resulting in sensory and motor dysfunction below the injury level. Patients with SCI are often paralyzed in bed due to impaired nerve function and there has been no effective treatment for limb paralysis after SCI. As a cutting-edge technology with a multidisciplinary integration of neuroscience, computer science, biological engineering, electronic engineering and psychology, brain-computer interface (BCI) provides a new program for the rehabilitation of SCI patients by changing the traditional brain signal output pathways and realizing the direct connection between the brain and external devices. In order to further understand the application of BCI in SCI rehabilitation, the authors reviewed the classification, basic principles of BCI and the research progress of the application of BCI in SCI rehabilitation, which may provide references for the clinical transformation of BCI.

Postoperative infection of internal fixation of closed fractures the lower limbs in adults represents a devastating complication, characterized by diagnostic challenges, prolonged treatment duration and high disability rates. Current management of these infections faces multiple challenges, such as difficulties in early accurate diagnosis, and various controversies about the treatment plan, leading to poor overall diagnosis and treatment results. To address these issues, based on evidence-based medicine and principles with emphasis on scientific rigor, clinical applicability and innovation, the Trauma Branch of the Chinese Medical Association, Orthopedic Branch of the Chinese Medical Doctor Association, Orthopedics Branch of the Chinese Medical Association, and Trauma Orthopedics and Polytrauma Group of the Resuscitation and Emergency Committee of the Chinese Medical Doctor Association have collaboratively organized a panel of relevant experts to develop the Guideline for diagnosis and treatment of infection after internal fixation of closed lower limb fractures in adults ( version 2025). The guideline proposed 10 recommendations, aiming to provide a foundation for standardized diagnosis and treatment of postoperative infection in adults with closed lower limb fractures.

Spinal cord injury (SCI) is a neurological disorder that occurs after a direct or indirect violent injury to the spinal cord, often resulting in sensory and motor dysfunction below the injury level. Patients with SCI are often paralyzed in bed due to impaired nerve function and there has been no effective treatment for limb paralysis after SCI. As a cutting-edge technology with a multidisciplinary integration of neuroscience, computer science, biological engineering, electronic engineering and psychology, brain-computer interface (BCI) provides a new program for the rehabilitation of SCI patients by changing the traditional brain signal output pathways and realizing the direct connection between the brain and external devices. In order to further understand the application of BCI in SCI rehabilitation, the authors reviewed the classification, basic principles of BCI and the research progress of the application of BCI in SCI rehabilitation, which may provide references for the clinical transformation of BCI.

The medical metaverse is a combination of medicine and other cutting-edge technologies such as computer and information ones. In the medical metaverse, medical knowledge in the real world will be transformed into a digital form, so that activities concerning diagnosis, treatment, education and clinical practice can be carried out in a virtual environment. Based on the latest research advances at home and abroad, this review expounds on the medical metaverse from the aspects of supporting technologies, applications in clinic and medical education, current deficiencies and future development.

  Objective  To analyze the current status of the development of adaptation guidelines in China, as well as their methodological quality and the reporting quality, in order to provide reference for the development of adaptation guidelines.  Methods  We searched and collected adaptation guidelines led by Chinese researchers or institutions from 2015 to 2023 from four electronic databases, China National Knowledge Infrastructure, WanFang Data Knowledge Service Platform, SinoMed and PubMed, extracted the basic information of the adapted guidelines, and assessed their methodological quality and reporting quality using the Appraisal of Guidelines for REsearch and Evaluation (AGREE) Ⅱ and RIGHT-Ad@pt tools.  Results  A total of 14 adaptation guidelines were included, mainly focusing on nursing (42.9%, 6/14), with the most frequently used adaptation method of ADAPTE (71.4%, 10/14), and with reference to pre-existing guidelines mainly from the United States, the United Kingdom, and international organizations. Assessment by the AGREE Ⅱ tool showed that the average methodological quality score of the adapted guidelines was 36.6%. The scores were relatively high in the domains of clarity of expression and rigor of formulation (44.4% and 54.9%), and lowest in the domain of applicability (15.3%). The results of the RIGHT-Ad@pt tool showed that the reporting quality of the adaptation guidelines was relatively good, with the highest reporting rate of 91.2% and the lowest of 35.3%, and the reporting rates of seven articles were higher than 70%.  Conclusions  Adaptation guidelines in China are still in their infancy, with a relatively small number and mainly focusing on the nursing field. The most commonly used adaptation method is the ADAPTE method. The methodological quality and reporting quality of adaptation guidelines need to be further improved, and more research should be conducted on the specific conditions and timing of adaptation guidelines development.

The incidence of orthopedic trauma-related diseases keeps rising annually, which brings an urgent need to optimize the diagnostic and treatment processes to enhance treatment efficiency and improve patients′ prognosis. Traditional diagnostic methods in traumatic orthopedics primarily rely on manual film interpretation and classification, resulting in a substantial workload for physicians and consequently a low efficiency. Furthermore, during multidisciplinary consultations and cross-hospital referrals for patients with orthopedic trauma, accessing medical records and facilitating information exchange can be challenging, leading to delays in surgical intervention. The rapid advancement of artificial intelligence (AI) technology, characterized by feature engineering, artificial neural networks, and deep learning, has transformed the landscape of rapid diagnosis and precision treatment for orthopedic trauma. Nonetheless, centralized storage during task training poses risks of privacy disclosure and security concerns that impede the widespread application of AI models. In contrast, the decentralized nature of blockchain technology offers a secure operational environment for AI-driven diagnostics and treatments and the integration of blockchain and AI can deliver more accurate, efficient, and safe services for patients with orthopedic trauma. Currently, challenges remain in the inter-institutional sharing of data, constant phenomenon of data silos and absence of standardized protocols for developing collaborative models in clinical settings. To address these challenges, the authors reviewed the research advancements in integrated application of blockchain technology and artificial intelligence in diagnosing and treating orthopedic trauma, aiming to provide insights into the development of a digital diagnostic system tailored to this field in China.

The incidence of orthopedic trauma-related diseases keeps rising annually, which brings an urgent need to optimize the diagnostic and treatment processes to enhance treatment efficiency and improve patients′ prognosis. Traditional diagnostic methods in traumatic orthopedics primarily rely on manual film interpretation and classification, resulting in a substantial workload for physicians and consequently a low efficiency. Furthermore, during multidisciplinary consultations and cross-hospital referrals for patients with orthopedic trauma, accessing medical records and facilitating information exchange can be challenging, leading to delays in surgical intervention. The rapid advancement of artificial intelligence (AI) technology, characterized by feature engineering, artificial neural networks, and deep learning, has transformed the landscape of rapid diagnosis and precision treatment for orthopedic trauma. Nonetheless, centralized storage during task training poses risks of privacy disclosure and security concerns that impede the widespread application of AI models. In contrast, the decentralized nature of blockchain technology offers a secure operational environment for AI-driven diagnostics and treatments and the integration of blockchain and AI can deliver more accurate, efficient, and safe services for patients with orthopedic trauma. Currently, challenges remain in the inter-institutional sharing of data, constant phenomenon of data silos and absence of standardized protocols for developing collaborative models in clinical settings. To address these challenges, the authors reviewed the research advancements in integrated application of blockchain technology and artificial intelligence in diagnosing and treating orthopedic trauma, aiming to provide insights into the development of a digital diagnostic system tailored to this field in China.

In recent years, artificial intelligence-related technologies have been deeply combined with many medical fields, and the intersection of medicine and engineering has become a hot topic. There are problems with heavy data and difficulty making decisions in orthopedic disease diagnosis and treatment. Machine learning is an important method of artificial intelligence. Since it can automatically analyze and predict medical big data, it is widely used in the field of orthopedics. It also assists physicians in completing disease diagnosis and treatment efficiently. In this review paper, the application and progress of machine learning in preoperative, intraoperative, and postoperative diagnosis and treatment in orthopedics are reviewed, providing new ways for exploring more rational diagnosis and treatment strategies.

Orthopaedic surgery is complex and delicate. The Orthopaedic Navigation System is developed to provide an augmented reality three-dimensional (3D) visualization environment to improve treatment outcomes by analyzing preoperative, intraoperative and postoperative data. With the rapid development and clinical application of digital technology, artificial intelligence technology has been introduced into orthopaedic intraoperative navigation system. Artificial intelligence, combined with instrumentation devices and imaging technology, enhances the visualization capabilities of orthopaedic surgeons, allowing them to receive real-time feedback and guidance during surgery, which in turn provides optimal clinical decision-making. The application of artificial intelligence to intraoperative orthopaedic navigation also improves the repeatability of procedures and reduces the incidence of human error. This paper reviews the current status of the application of artificial intelligence in orthopaedic intraoperative navigation, and introduces the basic concepts of artificial and the development of image alignment, real-time tracking, and 3D visualization techniques based on artificial intelligence, as well as discusses the current limitations and shortcomings.