Despite the vast quantities of published artificial intelligence (AI) algorithms that target trauma and orthopaedic applications, very few progress to inform clinical practice. One key reason for this is the lack of a clear pathway from development to deployment. In order to assist with this process, we have developed the Clinical Practice Integration of Artificial Intelligence (CPI-AI) framework – a five-stage approach to the clinical practice adoption of AI in the setting of trauma and orthopaedics, based on the IDEAL principles (. https://www.ideal-collaboration.net/. ). Adherence to the framework would provide a robust
High-quality randomised controlled trials (RCTs)
evaluating surgical therapies are fundamental to the delivery of
evidence-based orthopaedics. Orthopaedic clinical trials have unique
challenges; however, when these challenges are overcome, evidence
from trials can be definitive in its impact on surgical practice.
In this review, we highlight several issues that pose potential
challenges to orthopaedic investigators aiming to perform surgical randomised
controlled trials. We begin with a discussion on trial design issues,
including the ethics of sham surgery, the importance of sample size,
the need for patient-important outcomes, and overcoming expertise
bias. We then explore features surrounding the execution of surgical
randomised trials, including ethics review boards, the importance
of organisational frameworks, and obtaining adequate funding. Cite this article:
