Objective: To investigate the parameters predicting turning dysfunction in individuals with Parkinson’s disease (PD).
Background: Turning deficit in PD has significant implications particularly regarding increase in the risk of falling. Turning assessment is used to study turning deficit in individuals with PD. This assessment is embedded within a larger-scale balance assessment, associated research being mainly carried out using camera-based and wearable sensors. Clinical and research assessments are not prevalent in regular physiotherapy evaluation, however, several parameters pertinent to turning have been reported, including turning duration, number of steps, step length, step size, and stop frequency. To the best of our knowledge, no research into turning prediction has been conducted to define turning parameters and establish a diagnosis of PD using Movement Disorders Society – Unified Parkinson’s disease Rating Scale (MDS-UPDRS).
Method: Turning parameters included total steps, step duration, step size and step frequency, demographic data included age and body mass index (BMI). The data were analyzed for any correlations using a linear regression model and the Movement Disorders Society – Unified Parkinson’s disease Rating Scale (MDS-UPDRS). Variance between groups was analyzed using a one-way ANOVA. All statistical analyses were carried out using the R Stats Package.
Results: Twenty individuals with PD and 20 healthy age-matched controls were used for PD prediction (1). Positive correlations were found between step frequency and the MDS-UPDRS score (r = 0.6) and step duration and MDS-UPDRS score (r = 0.4). Step size showed a negative correlation. These results indicate that increasing step frequency and step duration can increase the MDS-UPDRS score whereas the smaller the step size the lower the MDS-UPDRS score. The aim is to simplify the MDS-UPDRS model so using linear regression and ANOVA, we identified the most powerful predictors. From this model we found that step duration is the most influential parameter (p < 0.0001), with step frequency also having a significant influence (p = 0.048).
Conclusion: The results indicate the possibility of robustly simplifying the MDS-UPDRS criteria by using only two turning parameters; step duration and step size. This finding will improve the detection of PD for neurological referral enhancing early PD diagnosis.
References: (1) Khobkhun F, Santiago PRP, Tahara AK, Srivanitchapoom P, Richards J. An investigation of the contribution of different turn speeds during standing turns in individuals with and without Parkinson’s disease. Sci Rep 12, 22566 (2022). https://doi.org/10.1038/s41598-022-27217-4
To cite this abstract in AMA style:
F. Khobkhun, A. Hirunkitti, T. Prasertsakul. Prediction of turning characteristics parameters into Parkinson’s disease [abstract]. Mov Disord. 2023; 38 (suppl 1). https://www.mdsabstracts.org/abstract/prediction-of-turning-characteristics-parameters-into-parkinsons-disease/. Accessed September 7, 2024.« Back to 2023 International Congress
MDS Abstracts - https://www.mdsabstracts.org/abstract/prediction-of-turning-characteristics-parameters-into-parkinsons-disease/