Hss Journal最新文献

Telemedicine has become an increasingly important component of musculoskeletal care, with recent advances in virtual physical examinations, enhanced patient education, and expanded access to treatment and telerehabilitation. Emerging applications of artificial intelligence, including virtual triaging and remote patient monitoring, promise to further augment telemedicine's effectiveness and scope. Despite limitations and a continued preference for in-person visits among some patients, telemedicine can be a valuable tool for musculoskeletal health practitioners, offering new ways to deliver high-quality, timely, and cost-effective care.

Artificial intelligence (AI) presents new opportunities to advance value-based healthcare in orthopedic surgery through 3 potential mechanisms: agency, automation, and augmentation. AI may enhance patient agency through improved health literacy and remote monitoring while reducing costs through triage and reduction in specialist visits. In automation, AI optimizes operating room scheduling and streamlines administrative tasks, with documented cost savings and improved efficiency. For augmentation, AI has been shown to be accurate in diagnostic imaging interpretation and surgical planning, while enabling more precise outcome predictions and personalized treatment approaches. However, implementation faces substantial challenges, including resistance from healthcare professionals, technical barriers to data quality and privacy, and significant financial investments required for infrastructure. Success in healthcare AI integration requires careful attention to regulatory frameworks, data privacy, and clinical validation.

Background:The proliferation of artificial intelligence has led to widespread patient use of large language models (LLMs). Purpose: We sought to characterize LLM responses to questions about piriformis syndrome (PS). Methods: On August 15, 2024, we asked 3 LLMs-ChatGPT-4, Copilot, and Gemini-to respond to the 25 most frequently asked questions about PS, as tracked by Google Trends. We evaluated the accuracy and completeness of the responses according to the Likert scale. We used the Ensuring Quality Information for Patients (EQIP) tool to assess the quality of the responses and assessed readability using Flesch-Kincaid Reading Ease (FKRE) and Flesch-Kincaid Grade Level (FKGL) scores. Results: The mean completeness scores of the responses obtained from ChatGPT, Copilot, and Gemini were 2.8 ± 0.3, 2.2 ± 0.6, and 2.6 ± 0.4, respectively. There was a significant difference in the mean completeness score among LLMs. In pairwise comparisons, ChatGPT and Gemini were superior to Copilot. There was no significant difference between the LLMs in terms of mean accuracy scores. In readability analyses, no significant difference was found in terms of FKRE scores. However, a significant difference was found in FKGL scores. A significant difference between LLMs was identified in the quality analysis performed according to EQIP scores. Conclusion: Although the use of LLMs in healthcare is promising, our findings suggest that these technologies need to be improved to perform better in terms of accuracy, completeness, quality, and readability on PS for a general audience.

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. The successful implementation of AI in orthopedic surgery requires careful attention to validation, regulatory compliance, and healthcare system integration. As these technologies continue to advance, maintaining the balance between innovation and patient safety remains crucial, with the ultimate goal of achieving more personalized, efficient, and equitable healthcare delivery while preserving the essential role of human clinical judgment. This review examines the current landscape and future trajectory of AI applications in orthopedic surgery, highlighting both technological advances and their clinical impact. Studies have suggested that AI-assisted procedures achieve higher accuracy and better functional outcomes compared to conventional methods, while reducing operative times and complications. However, these technologies are designed to augment rather than replace clinical expertise, serving as sophisticated tools to enhance surgeons' capabilities and improve patient care.

Background: Essential amino acid (EAA) supplementation, including conditionally essential amino acid (CEAA) and branched-chain amino acids (BCAA) supplementation, has been suggested as a mechanism to optimize patient outcomes by counteracting the atrophy associated with orthopedic procedures. Purpose: We sought to investigate the effect of EAA supplementation in the perioperative period on patients undergoing orthopedic and spine surgery, specifically whether it is associated with (1) reductions in postoperative muscle atrophy and (2) improved postoperative function including range of motion, strength, and mobility. Methods: We conducted a systematic review of the literature. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were used, and the protocol was registered in the Prospective Register of Systematic Reviews (PROSPERO) database (CRD42023447774). Studies of interest were prospective, placebo-controlled, randomized clinical trials (RCTs) published between 2002 and 2023 evaluating the impact of EAA supplementation on patients undergoing orthopedic and spine surgery. Results: Ten RCTs evaluating EAA supplementation in trauma, adult reconstruction, and spine surgery were identified; half of these focused on adult reconstruction. The EAA supplementation dose (3.4-20 g), frequency (daily to 3 times per day), and duration (14-49 days) varied widely across studies. Seven studies reported parameters relating to muscle size and/or composition, with 3 studies reporting superior muscle size/composition in patients receiving perioperative EAA supplementation, when compared with controls. Three studies reported favorable mobility outcomes for patients receiving EAA. Meta-analysis was prohibited by variation in measurement and outcome variables across the studies. Conclusions: Pooled data from level I studies supports the use of EAA, BCAA, and CEAA supplementations across several orthopedic subspecialties. However, significant heterogeneity exists in the quantity, duration, and content of EAA administered. Further prospective studies are needed to determine optimal/standardized parameters for supplementation.

Background: Compressive neuropathy of the common fibular nerve (CFN) is increasingly recognized as an etiology for foot drop and falls. Electrodiagnostic (EDX) studies are widely used to evaluate this condition, but such tests are invasive and costly. As with carpal and cubital tunnel syndromes, there may be patients with characteristic symptoms of CFN compressive neuropathy but normal EDX studies in which ultrasound may aid in decision-making.

Purpose: We sought to examine the association between ultrasound and nerve conduction studies (NCS) and electromyography (EMG) in the diagnosis of compressive neuropathy of the CFN.

Methods: We performed a retrospective review identifying 104 patients who underwent CFN decompression from January 1, 2015, to June 30, 2023. Patients were included if they had both ultrasound and NCS/EMG prior to CFN decompression for compressive neuropathy and if they were older than 18 years at time of surgery. Patients were excluded if they had entrapment secondary to trauma, iatrogenic injury, or if they had had superficial fibular decompression alone without CFN decompression. After applying exclusion criteria, 17 patients remained in the cohort.

Results: Mean ultrasound cross-sectional area and side-to-side (STS) ratios were significantly higher in those with abnormal compound muscle action potential (CMAP) amplitudes versus those with normal CMAP amplitudes. The probability of having an abnormal CMAP amplitude when STS ratio was abnormal was 18 times greater compared with those with normal STS ratio. With each unit increase in STS ratio, CMAP amplitude was reduced by 2.79 mV.

Conclusions: This retrospective review found that ultrasound may provide complementary diagnostic information to EMG/NCS for compressive neuropathy of the CFN. Further study is needed to examine the relationship between ultrasound findings for CFN compressive neuropathy and results of surgical decompression.

Background: Younger patients are more likely than older patients to experience shoulder instability and to rely on online educational resources. Although the Internet has increased patient access to medical information, this may not translate to increased health literacy. Purpose: We sought to analyze the quality and readability of online information on shoulder instability. Methods: We conducted a Google search using 6 terms related to shoulder instability. We collected the first 20 non-sponsored results for each term. Readability was evaluated using the Flesch Reading Ease (FRE), Flesch-Kincaid Grade Level (FKGL), and Gunning Fox Index (GFI) instruments. Quality was assessed using a Quality Grading Sheet (QGS) and the validated DISCERN instrument. Results: A total of 64 of 120 patient educational materials (PEMs) met the inclusion criteria. The mean FKGL, FRE, and GFI scores were 9.45 ± 0.552, 50.51 ± 3.4, and 11.5 ± 0.6, respectively. The mean DISCERN score and QGS rating were 33.09 ± 2.02 and 10.52 ± 1.28, respectively. While 49 (76.6%) articles discussed operative treatment for persistent shoulder instability, only 4 (6.3%) mentioned risks associated with surgery. Non-institutional sources had higher DISCERN scores than those from medical institutions. Conclusions: This review of online shoulder instability-related PEMs suggests that many do not meet current recommendations, with an average quality rating of "poor" and a mean ninth-grade reading level. Surgeons should be aware of the relative paucity of information on the risks and outcomes associated with operative treatment of shoulder instability contained in these PEMs.