Designing a biomechanics investigation: choosing the right model.
Physical testing is commonly performed to answer important biomechanical questions in the treatment of patients with fractures and other orthopaedic conditions. However, a variety of mistakes that are made in performing such investigations can severely limit their impact. The goal of this article is to discuss important aspects of study design to consider when planning for biomechanical investigations so that the studies can provide maximal benefit to the field. The best mechanical investigations begin with a good research question, one that comes out of patient care experience, is clearly defined, and can be stated concisely. The first practical issue to be considered is often choosing the type of physical specimens to be tested to address the research question. A related issue involves determining how many specimens will be needed to answer the posed mechanical question. Cadavers are generally still the closest to the actual clinical situation, but they are limited by interspecimen variability, which often requires a matched pair design that can address only one question. Simulated bone specimens limit variability and can replicate normal and osteoporotic bone. In planning the physical testing, the critical mechanical variables involved in answering the research question must be identified and due consideration given to deciding how best to measure them. Another important issue that arises relates to whether or not single static loadings will suffice in the testing (eg, to study construct stiffness) or whether cyclic dynamic testing is necessary (eg, to study late failure likely attributable to fatigue). To summarize, experimental design should be carefully planned before initiating mechanical testing. Sample size calculations should be performed to ensure adequate power and that clinically relevant differences can be detected. This pregame analysis can save significant time and cost and greatly increase the likelihood that the results will advance knowledge.
Olson, SA; Marsh, JL; Anderson, DD; Latta Pe, LL
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