Purpose: To establish consensus statements via a modified Delphi process about ethics, transparency, regulation and best practices for the use of orthobiologics in clinical practice for musculoskeletal pathology.
Methods: A consensus process on the regulation of orthobiologics at the provider-level was conducted using a modified Delphi technique. Twenty orthopaedic surgeons, sports medicine physicians, or basic scientists participated. Each participant was a Biologic Association member organization representative and asked to participate due to their active interest in the field of orthobiologics. Levels of consensus were delineated according to the number of votes for each statement: no consensus, <80%; consensus, 80% to 89%; strong consensus, 90% to 99%; unanimous, 100%.
Results: The twenty-six consensus statements on orthobiologics resulted in 14 achieving unanimous consensus, 8 achieving strong consensus, 3 achieving consensus, and 1 did not achieve consensus. Overall, 85% of the statements reached either a unanimous or strong consensus. Of the statements regarding communication and transparency, 9 reached unanimous consensus, including information to convey and helpful tools to describe current orthobiologics, persistent misinformation, use of the word "stem cells", "off-label" use, and problems with the present regulatory environment. Five statements discussing the regulation of novel orthobiologics achieved unanimous consensus. These statements highlighted research regulation, safety, and suggested improvements to regulatory issues. The statement that did not achieve any consensus was on the regulatory processes that should be in place by an institution providing novel orthobiologic treatments. No statement reached a unanimous agreement on cost or ethical considerations.
Conclusions: This study successfully identified key consensus statements emphasizing the importance of ethics, transparency, and regulation in the use of orthobiologics, with 85% of statements reaching unanimous or strong consensus. These findings underscore the need for standardized communication, improved regulatory frameworks, and enhanced safety measures while highlighting persistent challenges in addressing cost and ethical considerations.
Level Of Evidence: Level V, Expert Opinion.
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http://dx.doi.org/10.1016/j.arthro.2025.01.062 | DOI Listing |
J Med Ethics
March 2025
Institute for Ethics, History and Philosophy of Medicine, Hannover Medical School, Hannover, Germany.
Informed consent in surgical settings requires not only the accurate communication of medical information but also the establishment of trust through empathic engagement. The use of large language models (LLMs) offers a novel opportunity to enhance the informed consent process by combining advanced information retrieval capabilities with simulated emotional responsiveness. However, the ethical implications of simulated empathy raise concerns about patient autonomy, trust and transparency.
View Article and Find Full Text PDFJMIRx Med
March 2025
Stelmith, LLC, 2333 Aberdeen Pl, Carollton, TX, 75007, United States, 1 9459001314.
Background: The increasing integration of artificial intelligence (AI) systems into critical societal sectors has created an urgent demand for robust privacy-preserving methods. Traditional approaches such as differential privacy and homomorphic encryption often struggle to maintain an effective balance between protecting sensitive information and preserving data utility for AI applications. This challenge has become particularly acute as organizations must comply with evolving AI governance frameworks while maintaining the effectiveness of their AI systems.
View Article and Find Full Text PDFJ Med Internet Res
March 2025
Inverness College, University of the Highlands and Islands, Inverness, GB.
Background: Artificial intelligence (AI) is rapidly transforming healthcare, offering significant advancements in patient care, clinical workflows, and nursing education. While AI has the potential to enhance health outcomes and operational efficiency, its integration into nursing practice and education raises critical ethical, social, and educational challenges that must be addressed to ensure responsible and equitable adoption.
Objective: This umbrella review aims to evaluate the integration of AI into nursing practice and education, with a focus on ethical and social implications, and to propose evidence-based recommendations to support the responsible and effective adoption of AI technologies in nursing.
Radiologie (Heidelb)
March 2025
Klinik für Diagnostische und Interventionelle Radiologie, Universitätsklinikum Freiburg, Hugstetterstr. 55, 79106, Freiburg, Deutschland.
Background: Large Language Models (LLMs) like ChatGPT, Llama and Claude are transforming healthcare by interpreting complex text, extracting information, and providing guideline-based support. Radiology, with its high patient volume and digital workflows, is a ideal field for LLM integration.
Objective: Assessment of the potential of LLMs to enhance efficiency, standardization, and decision support in radiology, while addressing ethical and regulatory challenges.
Int Nurs Rev
March 2025
Geriatric Nursing Department, Faculty of Nursing, Cairo University, Cairo, Egypt.
Aim: This study explored the ethical boundaries and data-sharing practices in artificial intelligence (AI)-enhanced nursing from the perspective of Arab nurses.
Background: Although AI offers advancements in clinical decision-making and operational efficiency, it also presents challenges such as ethical dilemmas, data privacy concerns, and technical issues. These challenges are being addressed through continuous education, the development of robust ethical guidelines, and the implementation of transparent data-sharing practices METHODS: A qualitative approach was employed, adhering to the Standards for Reporting Qualitative Research (SRQR) guidelines.
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