Accelerometric analysis of gait abnormalities in golden retriever muscular dystrophy (GRMD) dogs is of limited sensitivity, and produces highly complex data. The use of discriminant analysis may enable simpler and more sensitive evaluation of treatment benefits in this important preclinical model.
Here, the authors describe a new method of 3D accelerometric gait analysis using linear discriminant analysis (LDA). They discuss the choice of dependent and independent variables and describe how to represent the results in a manner that can be understood by a broad range of users, including those unfamiliar with LDA. They also demonstrate the validity of this method by reanalysing data from a previous study regarding immunosuppressive treatment in GRMD dogs.
Accelerometry was performed twice monthly between the ages of 2 and 12 months on 8 healthy and 20 GRMD dogs. Seven accelerometric parameters were analysed using linear discriminant analysis (LDA). Manipulation of the dependent and independent variables produced three distinct models. The ability of each model to detect gait alterations and their pattern change with age was tested using a leave-one-out cross-validation approach.
Their model identified significant effect of immunosuppressive treatments on gait quality, corroborating the original findings, with the added advantages of direct statistical analysis with greater sensitivity and more comprehensible data representation.
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