Gait analysis in patients with Parkinson's disease and motor fluctuations: Influence of levodopa and comparison with other measures of motor function

1998 ◽  
Vol 13 (6) ◽  
pp. 900-906 ◽  
Author(s):  
John D. O'Sullivan ◽  
Catherine M. Said ◽  
Louise C. Dillon ◽  
Marion Hoffman ◽  
Andrew J. Hughes
2021 ◽  
pp. 026921552199052
Author(s):  
Zonglei Zhou ◽  
Ruzhen Zhou ◽  
Wen Wei ◽  
Rongsheng Luan ◽  
Kunpeng Li

Objective: To conduct a systematic review evaluating the effects of music-based movement therapy on motor function, balance, gait, mental health, and quality of life among individuals with Parkinson’s disease. Data sources: A systematic search of PubMed, Embase, Cochrane Library, Web of Science, PsycINFO, CINAHL, and Physiotherapy Evidence Database was carried out to identify eligible papers published up to December 10, 2020. Review methods: Literature selection, data extraction, and methodological quality assessment were independently performed by two investigators. Publication bias was determined by funnel plot and Egger’s regression test. “Trim and fill” analysis was performed to adjust any potential publication bias. Results: Seventeen studies involving 598 participants were included in this meta-analysis. Music-based movement therapy significantly improved motor function (Unified Parkinson’s Disease Rating Scale motor subscale, MD = −5.44, P = 0.002; Timed Up and Go Test, MD = −1.02, P = 0.001), balance (Berg Balance Scale, MD = 2.02, P < 0.001; Mini-Balance Evaluation Systems Test, MD = 2.95, P = 0.001), freezing of gait (MD = −2.35, P = 0.039), walking velocity (MD = 0.18, P < 0.001), and mental health (SMD = −0.38, P = 0.003). However, no significant effects were observed on gait cadence, stride length, and quality of life. Conclusion: The findings of this study show that music-based movement therapy is an effective treatment approach for improving motor function, balance, freezing of gait, walking velocity, and mental health for patients with Parkinson’s disease.


2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Gloria Vergara-Diaz ◽  
Jean-Francois Daneault ◽  
Federico Parisi ◽  
Chen Admati ◽  
Christina Alfonso ◽  
...  

AbstractParkinson’s disease (PD) is a neurodegenerative disorder characterized by motor and non-motor symptoms. Dyskinesia and motor fluctuations are complications of PD medications. An objective measure of on/off time with/without dyskinesia has been sought for some time because it would facilitate the titration of medications. The objective of the dataset herein presented is to assess if wearable sensor data can be used to generate accurate estimates of limb-specific symptom severity. Nineteen subjects with PD experiencing motor fluctuations were asked to wear a total of five wearable sensors on both forearms and shanks, as well as on the lower back. Accelerometer data was collected for four days, including two laboratory visits lasting 3 to 4 hours each while the remainder of the time was spent at home and in the community. During the laboratory visits, subjects performed a battery of motor tasks while clinicians rated limb-specific symptom severity. At home, subjects were instructed to use a smartphone app that guided the periodic performance of a set of motor tasks.


Author(s):  
Pei Huang ◽  
Yuan-Yuan Li ◽  
Jung E. Park ◽  
Ping Huang ◽  
Qin Xiao ◽  
...  

ABSTRACT: We investigated the effects of botulinum toxin on gait in Parkinson’s disease (PD) patients with foot dystonia. Six patients underwent onabotulinum toxin A injection and were assessed by Burke–Fahn–Marsden Dystonia Rating Scale (BFMDRS), visual analog scale (VAS) of pain, Timed Up and Go (TUG), Berg Balance Test (BBT), and 3D gait analysis at baseline, 1 month, and 3 months. BFMDRS (p = 0.002), VAS (p = 0.024), TUG (p = 0.028), and BBT (p = 0.034) were improved. Foot pressures at Toe 1 (p = 0.028) and Midfoot (p = 0.018) were reduced, indicating botulinum toxin’s effects in alleviating the dystonia severity and pain and improving foot pressures during walking in PD.


2021 ◽  
Vol 14 ◽  
pp. 175628642110185
Author(s):  
Susan J. Thanabalasingam ◽  
Brandan Ranjith ◽  
Robyn Jackson ◽  
Don Thiwanka Wijeratne

Background: Recent changes to the legal status of cannabis across various countries have renewed interest in exploring its use in Parkinson’s disease (PD). The use of cannabinoids for alleviation of motor symptoms has been extensively explored in pre-clinical studies. Objective: We aim to systematically review and meta-analyze literature on the use of medical cannabis or its derivatives (MC) in PD patients to determine its effect on motor function and its safety profile. Methods: We reviewed and analyzed original, full-text randomized controlled trials (RCTs) and observational studies. Primary outcomes were change in motor function and dyskinesia. Secondary outcomes included adverse events and side effects. All studies were analyzed for risk of bias. Results: Fifteen studies, including six RCTs, were analyzed. Of these, 12/15 (80%) mention concomitant treatment with antiparkinsonian medications, most commonly levodopa. Primary outcomes were most often measured using the Unified Parkinson Disease Rating Scale (UPDRS) among RCTs and patient self-report of symptom improvement was widely used among observational studies. Most of the observational data lacking appropriate controls had effect estimates favoring the intervention. However, the controlled studies demonstrated no significant motor symptom improvement overall. The meta-analysis of three RCTs, including a total of 83 patients, did not demonstrate a statistically significant improvement in UPDRS III score variation (MD −0.21, 95% CI −4.15 to 3.72; p = 0.92) with MC use. Only one study reported statistically significant improvement in dyskinesia ( p < 0.05). The intervention was generally well tolerated. All RCTs had a high risk of bias. Conclusion: Although observational studies establish subjective symptom alleviation and interest in MC among PD patients, there is insufficient evidence to support its integration into clinical practice for motor symptom treatment. This is primarily due to lack of good quality data.


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