Literature DB >> 32116261

Freezing of Gait in People with Parkinson's Disease: Nature, Occurrence, and Risk Factors.

Stephen R Lord1, Helen Bindels2, Mira Ketheeswaran3, Matthew A Brodie1, Andrew D Lawrence4, Jacqueline C T Close1,5, Alan L Whone6,7, Yoav Ben-Shlomo8, Emily J Henderson8,9.   

Abstract

BACKGROUND: Freezing of gait (FOG) is a common symptom of Parkinson's disease (PD) which can result in falls and fall related injuries, poor quality of life and reduced functional independence. It is a heterogeneous phenomenon that is difficult to quantify and eludes a unified pathophysiological framework.
OBJECTIVE: Our aim was to document the occurrence and nature of freezing, cognitive stops and stumbles in people with PD during walks with varying cognitive loads and conditions designed to elicit FOG.
METHODS: 130 people with PD walked under four conditions (normal walking, walking plus easy and hard dual-tasks, and a FOG elicitation condition. Video and accelerometry recordings were examined to document freezes and other gait disruptions.
RESULTS: Participants experienced 391 freezes, 97 cognitive stops and 73 stumbles in the trial walks; with total gait disruptions increasing with task complexity. Most freezes in the FOG elicitation condition occurred during turning and approach destination. People who experienced freezing during the walks were more likely to have Postural Instability and Gait Difficulty (PIGD) subtype, longer disease duration and more severe UPDRS part II and part III sub-scores than people who did not freeze. They also took higher doses of levodopa, reported freezing in the past month, more prior falls, had poorer executive function, poorer proprioception, slower reaction time, poorer standing and leaning balance, more depressive symptoms, lower quality of life and greater fear of falling. PD disease duration, reduced controlled leaning balance and poor proprioception were identified as independent and significant determinants of freezing in logistic regression analysis.
CONCLUSION: The multiple motor and cognitive factors identified as being associated with freezing, including poor proprioception and impaired controlled leaning balance provide new insights into this debilitating PD symptom and may contribute to potential new targets for rehabilitation.

Entities:  

Keywords:  Parkinson’s disease; dual task; freezing of gait; gait disorders

Mesh:

Year:  2020        PMID: 32116261     DOI: 10.3233/JPD-191813

Source DB:  PubMed          Journal:  J Parkinsons Dis        ISSN: 1877-7171            Impact factor:   5.568


  6 in total

1.  Parkinson's disease patients with freezing of gait have more severe voice impairment than non-freezers during "ON state".

Authors:  Qian Yu; Xiaoya Zou; Fengying Quan; Zhaoying Dong; Huimei Yin; Jinjing Liu; Hongzhou Zuo; Jiaman Xu; Yu Han; Dezhi Zou; Yongming Li; Oumei Cheng
Journal:  J Neural Transm (Vienna)       Date:  2022-01-06       Impact factor: 3.850

2.  Holocue: A Wearable Holographic Cueing Application for Alleviating Freezing of Gait in Parkinson's Disease.

Authors:  Daphne J Geerse; Bert Coolen; Jacobus J van Hilten; Melvyn Roerdink
Journal:  Front Neurol       Date:  2022-01-10       Impact factor: 4.003

3.  Classification of Parkinson's disease with freezing of gait based on 360° turning analysis using 36 kinematic features.

Authors:  Hwayoung Park; Sungtae Shin; Changhong Youm; Sang-Myung Cheon; Myeounggon Lee; Byungjoo Noh
Journal:  J Neuroeng Rehabil       Date:  2021-12-20       Impact factor: 4.262

4.  Protocol for the DeFOG trial: A randomized controlled trial on the effects of smartphone-based, on-demand cueing for freezing of gait in Parkinson's disease.

Authors:  Demi Zoetewei; Talia Herman; Marina Brozgol; Pieter Ginis; Pablo Cornejo Thumm; Eva Ceulemans; Eva Decaluwé; Luca Palmerini; Alberto Ferrari; Alice Nieuwboer; Jeffrey M Hausdorff
Journal:  Contemp Clin Trials Commun       Date:  2021-06-29

5.  Serum neurofilament light chain and postural instability/gait difficulty (PIGD) subtypes of Parkinson's disease in the MARK-PD study.

Authors:  Monika Pötter-Nerger; Janina Dutke; Susanne Lezius; Carsten Buhmann; Robert Schulz; Christian Gerloff; Jens Kuhle; Chi-Un Choe
Journal:  J Neural Transm (Vienna)       Date:  2022-01-24       Impact factor: 3.850

6.  Using Wearable Sensors and Machine Learning to Automatically Detect Freezing of Gait during a FOG-Provoking Test.

Authors:  Tal Reches; Moria Dagan; Talia Herman; Eran Gazit; Natalia A Gouskova; Nir Giladi; Brad Manor; Jeffrey M Hausdorff
Journal:  Sensors (Basel)       Date:  2020-08-10       Impact factor: 3.576

  6 in total

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