Frontiers in Human Neuroscience (Mar 2021)
C-Gait for Detecting Freezing of Gait in the Early to Middle Stages of Parkinson’s Disease: A Model Prediction Study
Abstract
ObjectiveEfficient methods for assessing walking adaptability in individuals with Parkinson’s disease (PD) are urgently needed. Therefore, this study aimed to assess C-Gait for detecting freezing of gait (FOG) in patients with early- to middle-stage PD.MethodPeople with PD (PWP) diagnosis (Hoehn and Yahr stages 1–3) were recruited from April 2019 to November 2019 in Beijing Rehabilitation Hospital. The participants performed six items of walking adaptability on an instrumented treadmill augmented with visual targets and obstacles (C-Mill). The patient’s walking adaptability was evaluated by C-Gait assessment and traditional walking tests, and FOG-related indexes were collected as outcome measures. Two discriminant models were established by stepwise discriminant analysis; area under the receiver operating characteristic (ROC) curve (AUC) was used to validate the models.ResultIn total, 53 patients were included in this study. Most C-Gait assessment items had no or low correlations with traditional walking tests. The obstacle avoidance (r = −0.639, P = 0.003) and speed of adaptation (r = −0.486, P = 0.035) items could lead to FOG with high sensitivity. In addition, the C-Gait assessment model (AUC = 0.755) had slightly better discrimination of freezers from non-freezers compared with traditional walking test models (AUC = 0.672); specifically, obstacle avoidance and speed of adaptation have uniquely discriminant potential.ConclusionC-gait assessment could provide additional value to the traditional walking tests for PD. Gait adaptability assessment, as measured by C-Gait, may be able to help identify freezers in a PD population.
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