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Fall History and Gait Variability can Predict Falls in Individuals With Parkinson’s Disease

L. Ma, P. Chan (Beijing, China)

Meeting: 2019 International Congress

Abstract Number: 963

Keywords: Parkinsonism

Session Information

Date: Tuesday, September 24, 2019

Session Title: Parkinsonisms and Parkinson-Plus

Session Time: 1:45pm-3:15pm

Location: Agora 3 West, Level 3

Objective: To understand the risk factors for falls in PD patients; To explore clinical indicators and Mobility Lab parameters that can predict falls in patients with PD. To evaluate the predictive accuracy of the parameters.

Background: Falls could seriously affect the quality of life of the Parkinson’s disease (PD) patients and clinicians should focus more on how to detect patients with high fall risk as early as possible. Gait disturbance is known one risk factor of the fall of PD patients. With the newly developed sensor technology, more accurate and objective evaluation equipments for gait have been developed, such as Mobility Lab, which uses wireless sensors and receiver to capture multiple parameters for data analysis. This is a preliminary prospective study aimed to use Mobility Lab to evaluate the gait and predict fall in patients with PD. In combination of other clinical information, we hope to find more parameters that can predict falls.

Method: We enrolled 51 PD patients and collected their clinic information, then evaluated the gait. During 6 months of follow-up, the falls’ information was collected. A single factor analysis was used to find the risk factors and parameters related to the fall of PD patients, and the accuracy of parameters to predict falls was evaluated by Receiver Operating Characteristic curve.

Results: 1) This study has found that long disease duration and higher Hoehn & Yahr(H-Y) stage, freezing of gait(FOG) and postural instability and high MDS-UPDRS II score were risk factors for falls.2) The predictive accuracy of fall history is high with the Area Under Curve (AUC) of 0.955.3) Coefficient of variation of Cadence, Gait Cycle Time, Swing, Stance, range of motion (RoM) Shank, RoM Trunk Sagittal can predict falls of PD patients, with the AUC of 0.6990.695, 0.708, 0.732, 0.736, 0.604 respectively.

Conclusion: 1) Disease duration, H-Y stage, freezing of gait, postural instability, MDS-UPDRS II score and fall history are related to the fall incidence of PD patients;2) Fall history is still the strongest predictor of falls for PD patients;3) Gait variability is a risk factor for falls in Parkinson’s disease and needs further investigation.

To cite this abstract in AMA style:

L. Ma, P. Chan. Fall History and Gait Variability can Predict Falls in Individuals With Parkinson’s Disease [abstract]. Mov Disord. 2019; 34 (suppl 2). https://www.mdsabstracts.org/abstract/fall-history-and-gait-variability-can-predict-falls-in-individuals-with-parkinsons-disease/. Accessed June 14, 2025.
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