scholarly journals Identifying Parkinson’s disease subtypes with motor and non-motor symptoms via model-based multi-partition clustering

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Fernando Rodriguez-Sanchez ◽  
Carmen Rodriguez-Blazquez ◽  
Concha Bielza ◽  
Pedro Larrañaga ◽  
Daniel Weintraub ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Age Of Onset ◽  
Real Life ◽  
Motor Symptoms ◽  
Excessive Sweating ◽  
Model Based ◽  
Disease Subtypes ◽  
Partition Clustering ◽  
Non Motor Symptoms

AbstractIdentification of Parkinson’s disease subtypes may help understand underlying disease mechanisms and provide personalized management. Although clustering methods have been previously used for subtyping, they have reported generic subtypes of limited relevance in real life practice because patients do not always fit into a single category. The aim of this study was to identify new subtypes assuming that patients could be grouped differently according to certain sets of related symptoms. To this purpose, a novel model-based multi-partition clustering method was applied on data from an international, multi-center, cross-sectional study of 402 Parkinson’s disease patients. Both motor and non-motor symptoms were considered. As a result, eight sets of related symptoms were identified. Each of them provided a different way to group patients: impulse control issues, overall non-motor symptoms, presence of dyskinesias and pyschosis, fatigue, axial symptoms and motor fluctuations, autonomic dysfunction, depression, and excessive sweating. Each of these groups could be seen as a subtype of the disease. Significant differences between subtypes (P< 0.01) were found in sex, age, age of onset, disease duration, Hoehn & Yahr stage, and treatment. Independent confirmation of these results could have implications for the clinical management of Parkinson’s disease patients.

scholarly journals Identifying Parkinson’s disease subtypes with motor and non-motor symptoms via model-based multi-partition clustering

2021 ◽  
Author(s):  
Fernando Rodriguez-Sanchez ◽  
Carmen Rodriguez-Blazquez ◽  
Concha Bielza ◽  
Pedro Larrañaga ◽  
Daniel Weintraub ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Age Of Onset ◽  
Real Life ◽  
Motor Symptoms ◽  
Excessive Sweating ◽  
Model Based ◽  
Disease Subtypes ◽  
Partition Clustering ◽  
Non Motor Symptoms

Abstract Identification of Parkinson’s disease subtypes may help understand underlying disease mechanisms and provide personalized management. Although clustering methods have been previously used for subtyping, they have reported generic subtypes of limited relevance in real life practice because patients do not always fit into a single category. The aim of this study was to identify new subtypes assuming that patients could be grouped differently according to certain sets of related symptoms. To this purpose, a novel model-based multi-partition clustering method was applied on data from an international, multi-center, cross-sectional study of 402 Parkinson’s disease patients. Both motor and non-motor symptoms were considered. As a result, eight sets of related symptoms were identified. Each of them provided a different way to group patients: impulse control issues, overall non-motor symptoms, presence of dyskinesias and pyschosis, fatigue, axial symptoms and motor fluctuations, autonomic dysfunction, depression, and excessive sweating. Each of these groups could be seen as a subtype of the disease. Significant differences between subtypes (p < 0.01) were found in sex, age, age of onset, disease duration, and Hoehn & Yahr stage. Independent confirmation of these results could have implications for the clinical management of Parkinson’s disease patients.

scholarly journals Screening Patients with Early Stage Parkinson’s Disease Using a Machine Learning Technique: Measuring the Amount of Iron in the Basal Ganglia

2020 ◽  
Vol 10 (23) ◽  
pp. 8732
Author(s):  
Seon Lee ◽  
Se-Hong Oh ◽  
Sun-Won Park ◽  
Chaewon Shin ◽  
Jeehun Kim ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Grey Matter ◽  
Early Stage ◽  
Support Vector ◽  
Motor Symptoms ◽  
Model Based ◽  
Svm Model ◽  
Deep Grey Matter ◽  
Non Motor Symptoms

The purpose of this study was to determine whether a support vector machine (SVM) model based on quantitative susceptibility mapping (QSM) can be used to differentiate iron accumulation in the deep grey matter of early Parkinson’s disease (PD) patients from healthy controls (HC) and Non-Motor Symptoms Scale (NMSS) scores in early PD patients. QSM values on magnetic resonance imaging (MRI) were obtained for 24 early PD patients and 27 age-matched HCs. The mean QSM values in deep grey matter areas were used to construct SVM and logistic regression (LR) models to differentiate between early PD patients and HCs. Additional SVM and LR models were constructed to differentiate between low and high NMSS scores groups. A paired t-test was used to assess the classification results. For the differentiation between early PD patients and HCs, SVM had an accuracy of 0.79 ± 0.07, and LR had an accuracy of 0.73 ± 0.03 (p = 0.027). SVM for NMSS classification had a fairly high accuracy of 0.79 ± 0.03, while LR had 0.76 ± 0.04. An SVM model based on QSM offers competitive accuracy for screening early PD patients and evaluates non-motor symptoms, which may offer clinicians the ability to assess the progression of motor symptoms in the patient population.

scholarly journals Parkinson's Disease Subtypes Identified from Cluster Analysis of Motor and Non-motor Symptoms

2017 ◽  
Vol 9 ◽  
Author(s):  
Jesse Mu ◽  
Kallol R. Chaudhuri ◽  
Concha Bielza ◽  
Jesus de Pedro-Cuesta ◽  
Pedro Larrañaga ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Cluster Analysis ◽  
Parkinson's Disease ◽  
Motor Symptoms ◽  
Disease Subtypes ◽  
Non Motor Symptoms

scholarly journals THE IMPACT OF BRAZILIAN SAMBA ON PARKINSON’S DISEASE: ANALYSIS BY THE DISEASE SUBTYPES

2020 ◽  
Vol 26 (1) ◽  
pp. 25-29
Author(s):  
Ana Cristina Tillmann ◽  
Alessandra Swarowsky ◽  
Alexandro Andrade ◽  
Jéssica Moratelli ◽  
Leonessa Boing ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Rating Scale ◽  
Control Group ◽  
Positive Trend ◽  
Motor Symptoms ◽  
Significant Difference ◽  
Disease Subtypes ◽  
The Impact ◽  
Non Motor Symptoms

ABSTRACT Introduction: People with Parkinson's disease constantly have low levels of physical activity. Dancing has become increasingly important for treating the disease and can help improve non-motor symptoms. Objective: To analyze the influence of Brazilian samba on the non-motor symptoms of PD according to TD and PGID subtypes. Methods: A 12-week, non-randomized clinical trial, through comparison with a control group. The 23 individuals who agreed to participate in the activities formed the experimental group (EG) and the 24 individuals who opted not to participate in the Brazilian samba classes comprised the control group (CG). A questionnaire was applied, composed of validated instruments. Mini Mental State Examination – MMSE; HY – Disability Scale; Unified Parkinson's Disease Rating Scale – UPDRS 1 and total values; Parkinson's Disease Questionnaire – PDQ-39, Parkinson's Disease Sleep Scale – PDSS; Beck Depression Inventory – BDI; Fatigue Severity Scale – FSS and Magnitude of Perceived Changes. Results: After the twelve weeks of intervention, it was observed that the EG showed improvement in the scores of all the tests. The comparison between groups, however, indicated a significant difference in the post-UPDRS1 period in which the EG presented improvement in cognitive impairment, while the CG presented a deficit in these values. The results of the division between disease subtypes show a greater change in the values between individuals of the TD group, when comparing the EG with the CG. For the EG, the greatest difference between pre- and post- intervention was fatigue. Conclusion: There was a positive trend in all the variables studied after the application of the protocol. This demonstrates that interventions such as dance may have greater effects on non-motor symptoms, depending on the expected progression of the disease. The scarcity of studies that use this approach in their analyses may explain the lack of evidence in this symptomatology related to dance. Level of evidence II; Therapeutic studies – Investigating the results of treatment.

scholarly journals Non-motor symptoms in essential tremor, akinetic rigid and tremor-dominant subtypes of Parkinson’s disease

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0245918
Author(s):  
Ali S. Shalash ◽  
Eman Hamid ◽  
Hanan Elrassas ◽  
Eshak I. Bahbah ◽  
Alia H. Mansour ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Essential Tremor ◽  
Rating Scale ◽  
Age Of Onset ◽  
Urinary Symptoms ◽  
Motor Symptoms ◽  
Dominant Type ◽  
Highly Correlated ◽  
Non Motor Symptoms

Objectives To compare non-motor symptoms (NMSs) among patients with essential tremor (ET), Parkinson’s disease (PD) subtypes (akinetic-rigid type (ART) and tremor-dominant type (TDT)), and healthy controls. Patients and methods This retrospective study included 129 participants, 72 PD (33 PD-ART, 33 PD-TDT, and 6 Mixed), 29 ET patients, and 28 controls. PD patients were assessed by the unified Parkinson’s disease rating scale (UPDRS), Hoehn, and Yahr scale (H&Y), while ET patients were evaluated by the Fahn Tolosa Marin Tremor Rating Scale. All subjects were evaluated by non-motor symptoms scale (NMSS) for NMSs and Beck depression inventory (BDI) for depression. Results PD subtypes groups, ET, and controls were age and gender-matched. Compared to controls, all PD, PD subtypes, and ET showed significantly worse most of NMSs (p<0.001) and depression. Compared to ET, all PD and PD-ART had significantly worse gastrointestinal (p = 0.002), urinary symptoms (p = 0.001, p = 0.003) and depression (p = 0.002) and PD-TDT worse depression, while ET patients showed worse memory/attention than PD subtypes. Total NMSS of ET is highly correlated to depression and moderately to tremor severity and age of onset, while total of NMSS is highly correlated to depression, disease severity, and disability. Conclusion The current study demonstrated several comparable domains of NMSs of PD subtypes and ET, except worse gastrointestinal and urinary symptoms among PD-ART. Identifying different NMSs profiles is important for predicting, better assessing, and tailoring management of ET and PD subtypes.

scholarly journals The Parkinson’s Real-World Impact Assessment (PRISM) Study: A European Survey of the Burden of Parkinson’s Disease in Patients and their Carers

2021 ◽  
pp. 1-15
Author(s):  
Eduardo Tolosa ◽  
Georg Ebersbach ◽  
Joaquim J. Ferreira ◽  
Olivier Rascol ◽  
Angelo Antonini ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Impact Assessment ◽  
Real World ◽  
European Countries ◽  
Life Questionnaire ◽  
Motor Symptoms ◽  
Non Motor Symptoms

Background: A greater understanding of the everyday experiences of people with Parkinson’s disease (PD) and their carers may help improve clinical practice. Objective: The Parkinson’s Real-world Impact assesSMent (PRISM) study evaluated medication use, health-related quality of life (HRQoL) and the use of healthcare resources by people with PD and their carers. Methods: PRISM is an observational cross-sectional study, in which people with PD and their carers completed an online survey using structured questionnaires, including the Parkinson’s Disease Quality of Life Questionnaire (PDQ-39), Non-Motor Symptoms Questionnaire (NMSQuest) and Zarit Burden Interview (ZBI). Results: Data were collected from 861 people with PD (mean age, 65.0 years; mean disease duration, 7.7 years) and 256 carers from six European countries. People with PD reported a large number of different co-morbidities, non-motor symptoms (mean NMSQuest score, 12.8), and impaired HRQoL (median PDQ-39 summary score, 29.1). Forty-five percent of people with PD reported at least one impulse control behaviour. Treatment patterns varied considerably between different European countries. Levodopa was taken in the last 12 months by 85.9% of participants, and as monotherapy by 21.8% . Carers, who were mostly female (64.8%) and the partner/spouse of the person with PD (82.1%), reported mild to moderate burden (mean ZBI total score, 26.6). Conclusions: The PRISM study sheds light on the lives of people with PD and those who care for them, re-emphasising the many challenges they face in everyday life. The study also provides insights into the current treatment of PD in Europe.

scholarly journals Study of cognitive impairment and genetic polymorphism of SLC41A1 (rs11240569 allele) in Parkinson’s disease in Upper Egypt: case-control study

2021 ◽  
Vol 57 (1) ◽  
Author(s):  
Hamdy N. El-Tallawy ◽  
Tahia H. Saleem ◽  
Wafaa M. Farghaly ◽  
Heba Mohamed Saad Eldien ◽  
Ashraf Khodaery ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Cognitive Impairment ◽  
Case Control Study ◽  
Case Control ◽  
Control Group ◽  
Motor Symptoms ◽  
And Control ◽  
Non Motor Symptoms ◽  
Control Study

Abstract Background Parkinson’s disease is one of the neurodegenerative disorders that is caused by genetic and environmental factors or interaction between them. Solute carrier family 41 member 1 within the PARK16 locus has been reported to be associated with Parkinson’s disease. Cognitive impairment is one of the non-motor symptoms that is considered a challenge in Parkinson’s disease patients. This study aimed to investigate the association of rs11240569 polymorphism; a synonymous coding variant in SLC41A1 in Parkinson’s disease patients in addition to the assessment of cognitive impairment in those patients. Results In a case -control study, rs11240569 single nucleotide polymorphisms in SLC41A1, genes were genotyped in 48 Parkinson’s disease patients and 48 controls. Motor and non-motor performance in Parkinson's disease patients were assessed by using the Movement Disorder Society-Sponsored Revision of the Unified Parkinson’s Disease Rating Scale (MDS-UPDRS). The genotype and allele frequencies were compared between the two groups and revealed no significant differences between case and control groups for rs11240569 in SLC41A1 gene with P value .523 and .54, respectively. Cognition was evaluated and showed the mean ± standard deviation (SD) of WAIS score of PD patients 80.4 ± 9.13 and the range was from 61 to 105, in addition to MMSE that showed mean ± SD 21.96 ± 3.8. Conclusion Genetic testing of the present study showed that rs11240569 polymorphism of SLC41A1 gene has no significant differences in distributions of alleles and genotypes between cases and control group, in addition to cognitive impairment that is present in a large proportion of PD patients and in addition to the strong correlation between cognitive impairment and motor and non-motor symptoms progression.

scholarly journals Weeding through the haze: a survey on cannabis use among people living with Parkinson’s disease in the US

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Megan P. Feeney ◽  
Danny Bega ◽  
Benzi M. Kluger ◽  
A. Jon Stoessl ◽  
Christiana M. Evers ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Scientific Evidence ◽  
Symptom Control ◽  
Cannabis Use ◽  
Symptom Improvement ◽  
Motor Symptoms ◽  
The Us ◽  
Alternative Means ◽  
Non Motor Symptoms

AbstractSymptomatic management of Parkinson’s disease (PD) is complex and many symptoms, especially non-motor symptoms, are not effectively addressed with current medications. In the US, cannabis has become more widely available for medical and recreational use, permitting those in the PD community to try alternative means of symptom control. However, little is known about the attitudes towards, and experiences with, cannabis use among those living with PD. To address this shortcoming, we distributed an anonymous survey to 7,607 people with PD in January 2020 and received 1339 responses (17.6%). 1064 complete responses were available for analysis. Respondents represented 49 states with a mean age of 71.2 years (±8.3) and mean PD duration of 7.4 years (±6.2). About a quarter of respondents (24.5%) reported cannabis use within the previous six months. Age and gender were found to be predictors of cannabis use in this sample (Age OR = 0.95, 95% CI 0.93 to 0.97; Male OR = 1.44, 95% CI 1.03 to 2.03). Users reported learning about cannabis use from the internet/news (30.5%) and friends or other people with PD (26.0%). Cannabis users were more likely to report insufficient control of their non-motor symptoms with prescription medications than non-users (p = 0.03). Cannabis was primarily used for PD (63.6%) and was most often used to treat nonmotor symptoms of anxiety (45.5%), pain (44.0%), and sleep disorders (44.0%). However, nearly a quarter of users (23.0%) also reported they had stopped cannabis use in the previous six months, primarily due to a lack of symptom improvement (35.5%). Three quarters of respondents (75.5%) did not use cannabis, primarily because there was a lack of scientific evidence supporting efficacy (59.9%). Our results suggest that the lack of formal guidance or research evidence about cannabis for PD may in part underlie inconsistencies in both use and reported effectiveness.

scholarly journals A mobile app for tracking non-motor symptoms of people with Parkinson’s disease: A usability study

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 890-890
Author(s):  
JuHee Lee ◽  
Yujin Suh ◽  
Yielin Kim
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Tracking System ◽  
Smart Phone ◽  
Telephone Counseling ◽  
Mobile App ◽  
Motor Symptoms ◽  
Hand Tremor ◽  
Non Motor Symptoms

Abstract Smart phone-based technology for people with Parkinson’s disease has been developed worldwide. Unmonitored non-motor symptoms decrease quality of life of people with Parkinson’s disease, so the needs for technology to manage non-motor symptoms are increasing. The technology is needed to detect subtle changes in non-motor symptoms by healthcare professional. There is no mobile app which manage comprehensive symptoms of Parkinson’s disease including non-motor symptoms. It is necessary to develop a new tracking system that can effectively manage non-motor symptoms as well as motor symptoms of Parkinson’s disease. We developed a prototype of mobile app for Android smartphones, with cooperation with Mazelone company. we also have shaped functions for monitoring of motor symptoms and medication adherence. It also provided a section for caregivers to use on behalf of people with Parkinson’s disease who have difficulty to use app due to hand tremor. Through Delphi technique, we obtained content validity from eight medical and nursing experts on the contents of the application. We provided regular telephone counseling to improve and encourage their app usage. Fifteen participants used the app for 6 weeks. To evaluate usability of mobile app, we provided constructed questionnaire and conducted individual telephone interview. A mobile app for tracking non-motor symptoms demonstrated high usability and satisfaction. We learned lessons about facilitators and barriers when implementing an app such as perception and acceptance of mobile technology. The mobile app will improve continuum of care. Future studies need to improve the contents and refine technical approach for people with Parkinson’s disease.

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