Normative dataset selection affects gait profile scores of children with cerebral palsy

Abstract

IntroductionThe Gait Profile Score (GPS) requires a comparative dataset, to identify altered mechanics in persons with a gait abnormality. This gait index has been shown to be useful for identifying gait pathology prior to the assessment of treatment outcomes. Though studies have shown differences in kinematic normative datasets between different testing sites, there is limited information available on the changes in GPS score based on normative dataset selection. The aim of this study was to quantify the influence of normative reference data from two institutions, on the GPS and Gait Variable Scores (GVS), calculated on the same group of patients with Cerebral Palsy. MethodsSeventy patients (Avg. age: 12.1 ± 2.9) diagnosed with CP underwent gait analysis during walking at a self-selected speed at Scottish Rite for Children (SRC). GPS and GVS scores were determined using normative kinematic data at a self-selected speed from, 83 typically developing children ages 4–17 from Gillette, and the same age range of children from SRC’s normative dataset. Average normalized speed was compared between institutions. Signed rank tests were performed on the GPS and GVS scores using each institution’s dataset. Spearman’s correlations between scores using SRC and Gillette were determined within GMFCS level. ResultsNormalized speed was comparable between each institution’s datasets. Within each GMFCS level, significant differences when using SRC vs. Gillette were found in most scores (p < 0.05). Scores were moderately to strongly correlated within each GMFCS level (range ρ = 0.448–0.998). ConclusionsSignificant statistical differences were found in GPS and GVS scores but were within the range of previously reported variation across multiple sites. Caution and consideration may need to be taken when reporting GPS and GVS scores that are calculated utilizing different normative datasets as these scores may not be equivalent.