020 Postural sway as a measure of disease severity in parkinson’s disease

IntroductionThe severity of Parkinson’s disease (PD) is difficult to assess accurately owing to the lack of a robust biological marker of disease progression, with consequent implications for prognosis and treatment. The current standard measure is the Unified Parkinson’s Disease Rating Scale (UPDRS) but this is hampered by considerable variability between observers and within subjects. Postural sway correlates well with complex brain functioning in other conditions. This study aimed to investigate the correlation of postural sway with the UPDRS and other non-motor measures of disease severity in patients with PD.Methods28 patients with PD (mean age 68 years, range 54–91; 18 male) underwent tests of cognition and quality of life [Montreal Cognitive Assessment (MoCA), Neuropsychiatry Unit Cognitive Assessment (NUCOG) and Parkinson’s Diseases Questionnaire (PDQ-39–1)], assessment of postural sway using a force plate, and assessment of clinical status using the motor component of the UPDRS.ResultsSway path length showed strong correlations with PDQ-39–1, MoCA and the verbal fluency component of the NUCOG (r=0.63,–0.75 and −0.57, respectively; p=0.002,<0.001 and 0.002, respectively) and, to a lesser degree, with the UPDRS III (r=0.45, p=0.018).ConclusionPostural sway shows potential as a sensitive measure of disease severity and brain function in PD, either alone or in combination with other measures. It appears to correlate better with measures of cognition, both general and executive (verbal fluency), and the PDQ measure of disease severity than with the motor component of the UPDRS.

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Postural sway correlates with cognition and quality of life in Parkinson’s disease

BMJ Neurology Open ◽

10.1136/bmjno-2020-000086 ◽

2020 ◽

Vol 2 (2) ◽

pp. e000086

Author(s):

Deborah Apthorp ◽

Alex Smith ◽

Susanne Ilschner ◽

Robin Vlieger ◽

Chandi Das ◽

...

Keyword(s):

Quality Of Life ◽

Parkinson’S Disease ◽

Parkinson's Disease ◽

Cognitive Assessment ◽

Rating Scale ◽

Postural Sway ◽

Disease Status ◽

Underlying Disease ◽

Eyes Closed

BackgroundThe severity of Parkinson’s disease (PD) is difficult to assess objectively owing to the lack of a robust biological marker of underlying disease status, with consequent implications for diagnosis, treatment and prognosis. The current standard tool is the Unified Parkinson’s Disease Rating Scale (MDS-UPDRS), but this is hampered by variability between observers and within subjects. Postural sway has been shown to correlate with complex brain functioning in other conditions. This study aimed to investigate the relationship between postural sway, MDS-UPDRS and other non-motor measures of disease severity in patients with PD.Method25 patients with PD and 18 age-matched controls participated in the study. All participants underwent assessment of postural sway using a force plate, with eyes open and closed. In addition, participants underwent tests of cognition and quality of life: Montreal Cognitive Assessment (MoCA), Neuropsychiatry Unit Cognitive Assessment (NUCOG) and, for the patients, the Parkinson’s Disease Questionnaire (PDQ-39–1), and assessment of clinical status using the motor component of the MDS-UPDRS.ResultsPatients swayed significantly more than controls. This was most obvious in the eyes-closed condition. Sway path length showed strong correlations with PDQ-39–1, MoCA and the verbal fluency component of the NUCOG, and, to a lesser degree, with the UPDRS-III in patients with PD.ConclusionThese results suggest that motor and non-motor symptoms of PD are associated in patients, and, in particular, that postural sway shows potential as a possible measure of underlying disease status in PD, either alone or in combination with other measures.

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Stereopsis Deficits in Parkinson’s Disease and Their Clinical Implications

10.21203/rs.3.rs-106032/v1 ◽

2020 ◽

Author(s):

Fang Ba ◽

Tina T. Sang ◽

Jaleh Fatehi ◽

Wenjing He ◽

Emanuel Mostofi ◽

...

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Disease Severity ◽

Rating Scale ◽

Disease Status ◽

Cognitive Status ◽

Control Group ◽

Motor Disorder ◽

Healthy Control ◽

Stereo Acuity

Abstract Background: Parkinson's disease (PD) is not exclusively a motor disorder. Among non-motor features, PD patients possess sensory visual dysfunctions. Stereopsis deficit can significantly impact patients' motor performance. However, it is not routinely tested, and its significance is under-investigated. Studying stereopsis using reliable 3D stimuli may help determine its implications in disease status in PD.The objective of the study is to investigate stereopsis abnormalities in PD with reliable and more physiological tools, and their correlation with indicators of PD severity. Methods: Twenty-four healthy control and 20 PD participants were first evaluated for visual acuity, visual field, contrast acuity, and stereoperception with 2D and Titmus stereotests, followed by the assessment with the 3D active shutter system. The correlation between stereopsis and disease severity, Unified Parkinson’s disease rating scale motor scores (UPDRS-III), levodopa equivalent daily dose (LEDD), course of disease and cognitive status were evaluated using univariate regression models. Results: Screening visual tests did not reveal any differences between PD and control group. With the 3D active shutter system, PD patients demonstrated significantly worse stereopsis (i.e p=0.002, 26 seconds of arc). There was a trend that UPDRS-III and LEDD negatively correlate with the stereo acuity, suggesting poorer stereoperception is related to disease severity. Preserved cognitive function correlated with more intact stereo acuity. Conclusion: With more reliable and physiological tools, PD patients exhibit poorer stereopsis. These deficits reflected PD motor and cognitive status. How stereopsis relates to gait, fall risks and navigation warrants more investigations in the future.

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Zonisamide Administration Improves Fatty Acid β-Oxidation in Parkinson’s Disease

Cells ◽

10.3390/cells8010014 ◽

2018 ◽

Vol 8 (1) ◽

pp. 14 ◽

Cited By ~ 2

Author(s):

Shin-Ichi Ueno ◽

Shinji Saiki ◽

Motoki Fujimaki ◽

Haruka Takeshige-Amano ◽

Taku Hatano ◽

...

Keyword(s):

Mass Spectrometry ◽

Parkinson’S Disease ◽

Parkinson's Disease ◽

Disease Severity ◽

Rating Scale ◽

Statistical Significance ◽

Experimental Studies ◽

Time Of Flight ◽

Metabolome Analysis ◽

Flight Mass Spectrometry

Although many experimental studies have shown the favorable effects of zonisamide on mitochondria using models of Parkinson’s disease (PD), the influence of zonisamide on metabolism in PD patients remains unclear. To assess metabolic status under zonisamide treatment in PD, we performed a pilot study using a comprehensive metabolome analysis. Plasma samples were collected for at least one year from 30 patients with PD: 10 without zonisamide medication and 20 with zonisamide medication. We performed comprehensive metabolome analyses of plasma with capillary electrophoresis time-of-flight mass spectrometry and liquid chromatography time-of-flight mass spectrometry. We also measured disease severity using Hoehn and Yahr (H&Y) staging and the Unified Parkinson’s Disease Rating Scale (UPDRS) motor section, and analyzed blood chemistry. In PD with zonisamide treatment, 15 long-chain acylcarnitines (LCACs) tended to be increased, of which four (AC(12:0), AC(12:1)-1, AC(16:1), and AC(16:2)) showed statistical significance. Of these, two LCACs (AC(16:1) and AC(16:2)) were also identified by partial least squares analysis. There was no association of any LCAC with age, disease severity, levodopa daily dose, or levodopa equivalent dose. Because an upregulation of LCACs implies improvement of mitochondrial β-oxidation, zonisamide might be beneficial for mitochondrial β-oxidation, which is suppressed in PD.

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Voice Assessments for Detecting Patients with Parkinson’s Diseases in Different Stages

International Journal of Electrical and Computer Engineering (IJECE) ◽

10.11591/ijece.v8i6.pp4265-4271 ◽

2018 ◽

Vol 8 (6) ◽

pp. 4265

Author(s):

Elmehdi Benmalek ◽

Jamal Elmhamdi ◽

Abdelilah Jilbab

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Rating Scale ◽

Principal Component ◽

Support Vector ◽

Speech Signal Processing ◽

Parkinson’S Diseases ◽

Wide Range ◽

Signal Processing Algorithms ◽

Linear Svm

<p class="IJASEITParagraph">Recently, a wide range of speech signal processing algorithms (dysphonia measures) aiming to detect patients with Parkinson’s disease (PD). So we have computed 19 dysphonia measures from sustained vowels collected from 375 voice samples from healthy and people suffer from PD. All the features are analysed and the more relevant ones are selected by the Principal component analysis (PCA) to classify the subjects in 4 classes according to the UPDRS (unified Parkinson’s disease Rating Scale) score. We used k-folds cross validation method with (k=4) validation scheme; 75% for training and 25% for testing, along with the Support Vector Machines (SVM) with its different types of kernels. The best result obtained was 92.5% using the PCA and the linear SVM.</p>

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The Association of Olfactory Dysfunction With Depression, Cognition, and Disease Severity in Parkinson's Disease

Frontiers in Neurology ◽

10.3389/fneur.2021.779712 ◽

2021 ◽

Vol 12 ◽

Author(s):

Ting-Chun Fang ◽

Ming-Hong Chang ◽

Chun-Pai Yang ◽

Yi-Huei Chen ◽

Ching-Heng Lin

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Cognitive Impairment ◽

Disease Severity ◽

Rating Scale ◽

Statistical Significance ◽

Olfactory Dysfunction ◽

University Of Pennsylvania ◽

Disease Rating ◽

The University

Background: Non-motor subtypes of Parkinson's disease (PD) include the limbic, cognitive, and brainstem phenotype, which may have different pathological pathways with olfaction. In this work, we aim to clarify the association between olfactory dysfunction, depression, cognition, and disease severity in PD.Methods: A total of 105 PD subjects were included and divided into anosmia and non-anosmic groups, using the University of Pennsylvania Smell Identification Test (UPSIT). All patients were evaluated with the movement disorder society unified Parkinson's disease rating scale (MDS-UPDRS), the Beck depression inventory (BDI)-II, and the Montreal cognitive assessment (MoCA).Results: The BDI-II and UPSIT scores had a trend of reverse correlation without statistical significance (β-coefficient −0.12, p = 0.232). However, the odds ratio (OR) in anosmia was 2.74 (95% CI 1.01–7.46) for depression and 2.58 (95% CI 1.06–6.29) for cognitive impairment. For the MDS-UPDRS total and Part 3 score, the anosmia had a β-coefficient of 12.26 (95% CI 5.69–18.82) and 8.07 (95% CI 3.46–12.67), respectively. Neither depression nor cognitive impairment is associated with motor symptoms.Conclusion: More severe olfactory dysfunction in PD is associated with cognitive impairment and greater disease severity. Depression in PD may involve complex pathways, causing relatively weak association with olfactory dysfunction.

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Treadmill training and kinesiotherapy versus conventional physiotherapy in Parkinson’s disease: a pragmatic study

Fisioterapia em Movimento ◽

10.1590/1980-5918.032.ao01 ◽

2019 ◽

Vol 32 ◽

Cited By ~ 1

Author(s):

Thiago da Silva Rocha Paz ◽

Fernando Guimarães ◽

Vera Lúcia Santos de Britto ◽

Clynton Lourenço Correa

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Rating Scale ◽

Statistical Tests ◽

Clinical Status ◽

Functional Independence ◽

Treadmill Training ◽

Clinical Aspects ◽

Group 12 ◽

Conventional Physiotherapy

Abstract Introduction: Physiotherapy has been identified in the literature as an important treatment for individuals with Parkinson’s disease (PD) to improve functional capacity. Little is discussed about the physiotherapy practice environment for this population. Objective: To assess pragmatically the effects of two physiotherapy protocols: Conventional Physiotherapy (CP) and Treadmill Training and Kinesiotherapy (TTK) in PD patients. Method: Twenty-four PD patients classified from 1 to 3 on the Hoehn and Yahr scale were randomly distributed into two groups. In CP group (12 patients), exercises aimed to improve range of motion, bradykinesia, postural adjustments and gait. In TTK group (12 patients), exercises aimed to improve physical fitness, mobility and functional independence. The treatments were performed for 50 minutes, twice a week for 14 weeks. The following evaluations were performed before and after the interventions: Unified Parkinson’s Disease Rating Scale (UPDRS); gait speed (GS); up stairs (US) and down stairs (DS) tests; timed get-up-and-go test (TUG) and 6-Minute Walk Distance Test (6-MWDT). Sociodemographic and clinical data were presented as descriptive analysis. Variables with normal and non-normal distributions were analyzed by specific statistical tests. Results: Intragroup analysis showed significant results for the TTK group (TUG, US, DS, GS, UPDRS total and UPDRS II) and for the CP group only UPDRS total. Intergroup analysis was favorable for the TTK group (TUG, US, DS, 6-MWDT). Conclusion: CP group improved the patients’ general clinical status, while treadmill and kinesiotherapy improved the physical-functional and clinical aspects.

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Objective Quantification of Neuromotor Symptoms in Parkinson's Disease: Implementation of a Portable, Computerized Measurement Tool

Parkinson s Disease ◽

10.4061/2010/760196 ◽

2010 ◽

Vol 2010 ◽

pp. 1-6 ◽

Cited By ~ 14

Author(s):

Spyridon Papapetropoulos ◽

Heather L. Katzen ◽

Blake K. Scanlon ◽

Alexandra Guevara ◽

Carlos Singer ◽

...

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Reaction Time ◽

Rating Scale ◽

Postural Sway ◽

Evaluation Research ◽

Force Plate ◽

Primary Objective ◽

Measurement Tool ◽

Data Logger

Quantification of neuromotor symptoms with device-based measures provides a useful supplement to clinical evaluation. Research using the CATSYS has established its utility as a computerized measurement system to quantify neuromotor function. The primary objective of this study is to provide technical guidance on the use of the CATSYS in Parkinson's disease (PD). Forty-four patients with idiopathic PD and 28 healthy controls were prospectively recruited and evaluated with CATSYS, a portable, Windows-based system consisting of a data logger and four different sensors (tremor pen, touch recording plate, reaction time handle, and force plate for balance recording) for quantification of neuromotor functions. CATSYS discriminated between PD and controls on measurements of rest/postural tremor, pronation/supination, finger tapping, simple reaction time, and postural sway intensity and velocity. CATSYS measurements using the proposed test battery were associated with relevant clinician-rated Unified Parkinson's disease rating scale (UPDRS) items assessing tremor and bradykinesia. More work is warranted to establish CATSYS as a diagnostic/monitoring instrument in movement disorders using the proposed technical approaches.

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Muscle strength and executive function as complementary parameters for the assessment of impairment in Parkinson's disease

Arquivos de Neuro-Psiquiatria ◽

10.1590/0004-282x20130175 ◽

2013 ◽

Vol 71 (12) ◽

pp. 948-954

Author(s):

Dannyel Barbirato ◽

Alessandro Carvalho ◽

Narahyana Bom de Araujo ◽

Jose Vicente Martins ◽

Andrea Deslandes

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Executive Function ◽

Disease Severity ◽

Rating Scale ◽

Motor Impairment ◽

Cognitive Status ◽

Cognitive Capacity ◽

Response To Treatment ◽

The Relationship

Objective To evaluate the relationship between the quantitative results of functional and cognitive performance of patients with Parkinson's disease (PD) and disease severity; and to study the relationship between patients' functional and cognitive capacity and motor impairment (Unified Parkinson's Disease Rating Scale - UPDRS III). Method Twenty-nine subjects clinically diagnosed with PD were classified into three groups according to disease severity using the modified Hoehn and Yahr Scale (H&Y). They were submitted to functional (Senior Fitness Test) and neuropsychological tests. Stepwise regression analysis showed a significant association between H&Y and upper limb strength (r 2 =0.30; p=0.005) and executive function (r 2 =0.37; p=0.004). In relation to UPDRS III, there was a significant association between lower limb strength (r 2 =0.27; p=0.010) and global cognitive status (r 2 =0.24; p=0.024). Conclusion The implementation of simple tests of functional capacity associated with neuropsychological testing can help to assess disease severity and motor impairment, and can be used to monitor the response to treatment in PD.

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Predicting Longitudinal Disease Severity for Individuals with Parkinson’s Disease using Functional MRI and Machine Learning Prognostic Models

10.1101/2020.04.20.050971 ◽

2020 ◽

Author(s):

Kevin P. Nguyen ◽

Vyom Raval ◽

Alex Treacher ◽

Cooper Mellema ◽

Frank Yu ◽

...

Keyword(s):

Machine Learning ◽

Parkinson’S Disease ◽

Parkinson's Disease ◽

Disease Severity ◽

Clinical Decision Making ◽

Rating Scale ◽

Neurodegenerative Disorder ◽

Clinical Severity ◽

Predictive Values ◽

Updrs Score

AbstractParkinson’s disease is the second most common neurodegenerative disorder and is characterized by the loss of ability to control voluntary movements. Predictive biomarkers of progression in Parkinson’s Disease are urgently needed to expedite the development of neuroprotective treatments and facilitate discussions about disease prognosis between clinicians and patients. Resting-state functional magnetic resonance imaging (rs-fMRI) shows promise in predicting progression, with derived measures, including regional homogeneity (ReHo) and fractional amplitude of low frequency fluctuations (fALFF), having been previously been associated with current disease severity. In this work, ReHo and fALFF features from 82 Parkinson’s Disease subjects are used to train machine learning predictors of baseline clinical severity and progression at 1 year, 2 years, and 4 years follow-up as measured by the Movement Disorder Society Unified Depression Rating Scale (MDS-UPDRS) score. This is the first time that rs-fMRI and machine learning have been combined to predict future disease progression. The machine learning models explain up to 30.4% (R2 = 0.304) of the variance in baseline MDS-UPDRS scores, 55.8% (R2 = 0.558) of the variance in year 1 scores, and 47.1% (R2 = 0.471) of the variance in year 2 scores with high statistical significance (p < 0.0001). For distinguishing high- and low-progression individuals (MDS-UPDRS score above or below the median), the models achieve positive predictive values of up to 71% and negative predictive values of up to 84%. The models learn patterns of ReHo and fALFF measures that predict better and worse prognoses. Higher ReHo and fALFF in regions of the default motor network predicted lower current severity and lower future progression. The rs-fMRI features in the temporal lobe, limbic system, and motor cortex were also identified as predictors. These results present a potential neuroimaging biomarker that accurately predicts progression, which may be useful as a clinical decision-making tool and in future trials of neuroprotective treatments.

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