Research on artificial intelligence in shoulder and elbow surgery is increasing

Using 3D Printing Technology to Design Split-Piece Sleeve Prosthesis in the Revision Surgery of Tumor-Type Total Elbow Prosthetic Fractures: A Case Report

BACKGROUND

Revision of tumor-type prosthetic fractures is very challenging in clinical work. Traditional repair methods may not be able to meet the needs of complex cases or cause greater bone damage. Therefore, more effective and reliable solutions need to be found.

CASE PRESENTATION

This study presents a novel revision technique for managing fractures of tumor-type total elbow prostheses. A 57-year-old female patient was diagnosed with a left distal humeral bone tumor accompanied by pathological fracture and underwent customized tumor-type total elbow prosthesis arthroplasty. After 5 years, she experienced pain and encountered difficulty in flexing the left elbow while lifting heavy objects. The X-ray examination revealed a fracture of the distal humeral prosthesis. As a response, the elbow joint was initially explored, and the damaged component of the prosthesis was extracted. Subsequently, we utilized 3D printing technology to design a split-piece sleeve prosthesis and effectively restored the fractured left distal humerus implant. During the 2-year follow-up, The X-ray demonstrated satisfactory positioning of the prosthesis, which remained securely affixed without any indications of loosening. The Mayo Elbow Performance Score (MEPS) reached 80 points, the Musculoskeletal Tumor Society (MSTS) attained a score of 28 points, and the range of motion of the elbow was measured between 25° and 110°, revealing favorable functional outcomes.

CONCLUSION

The utilization of a 3D printed split-piece sleeve prosthesis presents a viable clinical treatment strategy for addressing fractures in tumor-type elbow prostheses.

Advanced Home-Based Shoulder Rehabilitation: A Systematic Review of Remote Monitoring Devices and Their Therapeutic Efficacy

Shoulder pain represents the most frequently reported musculoskeletal disorder, often leading to significant functional impairment and pain, impacting quality of life. Home-based rehabilitation programs offer a more accessible and convenient solution for an effective shoulder disorder treatment, addressing logistical and financial constraints associated with traditional physiotherapy. The aim of this systematic review is to report the monitoring devices currently proposed and tested for shoulder rehabilitation in home settings. The research question was formulated using the PICO approach, and the PRISMA guidelines were applied to ensure a transparent methodology for the systematic review process. A comprehensive search of PubMed and Scopus was conducted, and the results were included from 2014 up to 2023. Three different tools (i.e., the Rob 2 version of the Cochrane risk-of-bias tool, the Joanna Briggs Institute (JBI) Critical Appraisal tool, and the ROBINS-I tool) were used to assess the risk of bias. Fifteen studies were included as they fulfilled the inclusion criteria. The results showed that wearable systems represent a promising solution as remote monitoring technologies, offering quantitative and clinically meaningful insights into the progress of individuals within a rehabilitation pathway. Recent trends indicate a growing use of low-cost, non-intrusive visual tracking devices, such as camera-based monitoring systems, within the domain of tele-rehabilitation. The integration of home-based monitoring devices alongside traditional rehabilitation methods is acquiring significant attention, offering broader access to high-quality care, and potentially reducing healthcare costs associated with in-person therapy.

Utility of Artificial Intelligence in Orthopedic Surgery Literature Review: A Comparative Pilot Study

OBJECTIVE

Literature reviews are essential to the scientific process and allow clinician researchers to advance general knowledge. The purpose of this study was to evaluate if the artificial intelligence (AI) programs ChatGPT and Perplexity.AI can perform an orthopedic surgery literature review.

MATERIALS AND METHODS

Five different search topics of varying specificity within orthopedic surgery were chosen for each search arm to investigate. A consolidated list of unique articles for each search topic was recorded for the experimental AI search arms and compared with the results of the control arm of two independent reviewers. Articles in the experimental arms were examined by the two independent reviewers for relevancy and validity.

RESULTS

ChatGPT was able to identify a total of 61 unique articles. Four articles were not relevant to the search topic and 51 articles were deemed to be fraudulent, resulting in 6 valid articles. Perplexity.AI was able to identify a total of 43 unique articles. Nineteen were not relevant to the search topic but all articles were able to be verified, resulting in 24 valid articles. The control arm was able to identify 132 articles. Success rates for ChatGPT and Perplexity. AI were 4.6% (6 of 132) and 18.2% (24 of 132), respectively.

CONCLUSION

The current iteration of ChatGPT cannot perform a reliable literature review, and Perplexity.AI is only able to perform a limited review of the medical literature. Any utilization of these open AI programs should be done with caution and human quality assurance to promote responsible use and avoid the risk of using fabricated search results. [Orthopedics. 2024;47(3):e125-e130.].