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1.
Dev Med Child Neurol ; 65(9): 1157-1173, 2023 09.
Article in English | MEDLINE | ID: mdl-36750309

ABSTRACT

AIM: To explore altered structural and functional connectivity and network organization in cerebral palsy (CP), by clinical CP subtype (unilateral spastic, bilateral spastic, dyskinetic, and ataxic CP). METHOD: PubMed and Embase databases were systematically searched. Extracted data included clinical characteristics, analyses, outcome measures, and results. RESULTS: Sixty-five studies were included, of which 50 investigated structural connectivity, and 20 investigated functional connectivity using functional magnetic resonance imaging (14 studies) or electroencephalography (six studies). Five of the 50 studies of structural connectivity and one of 14 of functional connectivity investigated whole-brain network organization. Most studies included patients with unilateral spastic CP; none included ataxic CP. INTERPRETATION: Differences in structural and functional connectivity were observed between investigated clinical CP subtypes and typically developing individuals on a wide variety of measures, including efferent, afferent, interhemispheric, and intrahemispheric connections. Directions for future research include extending knowledge in underrepresented CP subtypes and methodologies, evaluating the prognostic potential of specific connectivity and network measures in neonates, and understanding therapeutic effects on brain connectivity.


Subject(s)
Cerebral Palsy , Infant, Newborn , Humans , Muscle Spasticity , Brain , Magnetic Resonance Imaging/methods
2.
Lancet Neurol ; 17(6): 559-568, 2018 06.
Article in English | MEDLINE | ID: mdl-29699914

ABSTRACT

Non-motor symptoms (NMS) of Parkinson's disease can be predominant as the disease advances, thereby constituting a major source of disease burden for patients and caregivers. However, current understanding of NMS is incomplete, particularly as a result of the absence of standardisation of outcome definitions and the heterogeneity of the risk factors that are assessed. The best data on risk factors for NMS in Parkinson's disease come from longitudinal studies, with the strongest evidence identifying factors for cognitive impairment and dementia, hallucinations, depression, apathy, excessive daytime sleepiness, insomnia, and impulse-control disorders. Cognitive impairment, hallucinations, and depression have several common risk factors, and many other NMS share a few risk factors, showing the interdependence between NMS with advancing Parkinson's disease. Disease severity, sex, age, and antiparkinsonian medication might have roles in the development of different NMS, although only antiparkinsonian medication is potentially modifiable. Until disease-modifying therapies are developed, increased knowledge of risk factors could ameliorate early identification of patients who are at an increased risk of developing specific NMS and potentially allow improvement of symptom management or prevention of specific NMS.


Subject(s)
Parkinson Disease/complications , Parkinson Disease/psychology , Apathy , Cognitive Dysfunction/etiology , Dementia/etiology , Depressive Disorder/etiology , Disruptive, Impulse Control, and Conduct Disorders/etiology , Humans , Risk Factors , Sleep Wake Disorders/etiology
3.
Parkinsonism Relat Disord ; 33: 51-57, 2016 12.
Article in English | MEDLINE | ID: mdl-27639814

ABSTRACT

INTRODUCTION: Insomnia is a debilitating symptom in Parkinson's disease (PD) that has been scarcely investigated in a longitudinal design. Knowledge of factors associated with occurrence of insomnia may provide clues for an increased understanding of underlying pathophysiology and facilitate early detection. The objective of this study is to examine the course and factors associated with longitudinal changes in insomnia severity in patients with PD. METHODS: Analyses were performed in data of the SCOPA-PROPARK cohort, a 5-year longitudinal cohort study (2003-2011) of 421 PD patients who have been examined annually. Linear mixed models were used to identify factors associated with longitudinal changes in scores of the SCOPA-SLEEP-Nighttime sleep (NS) problems section. A generalized estimating equations (GEE) analysis was performed to determine which baseline variables were associated with the different aspects of insomnia (sleep initiation or maintenance difficulty). RESULTS: Baseline SCOPA-SLEEP-NS scores were available for 412 patients, of whom 110 (27%) had insomnia (i.e. score ≥ 7). Of the remaining 302 patients, 99 (33%) developed insomnia at some point during follow-up. More severe depressive symptoms, motor fluctuations, higher dopamine agonist doses and sleep medication use were independently associated with higher SCOPA-SLEEP-NS scores over time. GEE analysis did not identify an unique set of determinants that affected specific aspects of insomnia. CONCLUSION: The presence of depressive symptoms, motor fluctuations and the use of higher doses of dopamine agonists are associated with more severe insomnia. Attention to these aspects could potentially contribute to a better management of insomnia symptoms in PD.


Subject(s)
Parkinson Disease/complications , Sleep Initiation and Maintenance Disorders/diagnosis , Sleep Initiation and Maintenance Disorders/etiology , Aged , Cohort Studies , Female , Humans , Linear Models , Longitudinal Studies , Male , Middle Aged , Risk Factors , Severity of Illness Index
4.
J Neurol ; 263(6): 1215-25, 2016 Jun.
Article in English | MEDLINE | ID: mdl-27126456

ABSTRACT

Depression is one of the most common non-motor symptoms in Parkinson's disease (PD). A thorough understanding of factors associated with depressive symptomatology may facilitate early detection and guide future intervention strategies. The objective of the study was to determine associated and predictive factors of depression in patients with PD. Analyses were performed in data of the SCOPA-PROPARK cohort, a 5-year hospital-based longitudinal cohort of over 400 PD patients who have been examined annually. Linear mixed models using data of all patients were used to identify factors associated with longitudinal changes in Beck Depression Inventory (BDI) scores. A survival analysis using data of patients without depression at baseline was performed to identify risk factors for future depression (i.e. BDI ≥ 15). The proportion of patients with depression was approximately 20 % and remained stable during follow-up, with approximately half of cases showing a persistent course. Female gender, more severe disability, more severe motor fluctuations, autonomic and cognitive dysfunction, poorer nighttime sleep and daytime sleepiness were independently associated with higher BDI scores over time. Higher baseline BDI score, daytime sleepiness and a higher levodopa dosage were risk factors for future depression. Depression is common in PD, where it may follow a persistent or non-persistent course. Apart from motor fluctuations and levodopa dose, depressive symptoms in PD are mainly associated with factors of non-dopaminergic origin. This suggests that depression in PD is an inherent consequence of the progressive pathobiology of the disease, which may render its treatment with currently available treatment options difficult.


Subject(s)
Depression/diagnosis , Depression/epidemiology , Parkinson Disease/diagnosis , Parkinson Disease/epidemiology , Cross-Sectional Studies , Depression/etiology , Disability Evaluation , Disease Progression , Female , Follow-Up Studies , Humans , Linear Models , Longitudinal Studies , Male , Middle Aged , Netherlands/epidemiology , Parkinson Disease/complications , Parkinson Disease/psychology , Prognosis , Prospective Studies , Psychiatric Status Rating Scales , Risk Factors , Sex Factors , Survival Analysis
5.
Parkinsonism Relat Disord ; 24: 34-40, 2016 Mar.
Article in English | MEDLINE | ID: mdl-26846609

ABSTRACT

INTRODUCTION: Excessive daytime sleepiness (EDS) is a common feature of Parkinson's disease (PD) that contributes to the disease burden and increases risk of harm. The aim of this study was to examine persistency, cross-sectional and longitudinal associations, and risk factors for EDS in patients with PD. METHODS: Analyses were performed on data from the SCOPA-PROPARK cohort, a 5-year hospital-based longitudinal cohort of over 400 PD patients who were examined annually. Cross-sectional analyses were conducted to evaluate differences between patients with and without EDS at baseline, while linear mixed models using data of all patients were used to identify factors associated with longitudinal changes in SCOPA-SLEEP-Daytime Sleepiness (SCOPA-SLEEP-DS) scores. A survival analysis was done using data of patients without EDS at baseline to identify risk factors for future EDS. RESULTS: EDS proved a non-persistent symptom, although persistency and the proportion of patients with EDS increased with longer follow-up. At baseline 43% of patients had EDS, while 46% of patients without EDS at baseline developed this symptom during follow-up. Male gender, poorer nighttime sleep, cognitive and autonomic dysfunction, hallucinations, less severe dyskinesias, dose of dopamine agonists and use of antihypertensives were associated with higher EDS scores over time, while use of benzodiazepines was associated with lower scores. Baseline SCOPA-SLEEP-DS score and PIGD phenotype were risk factors for future EDS. CONCLUSION: With longer disease duration a large proportion of patients develop EDS. Some risk factors are modifiable and patients should be monitored to improve quality of life and reduce risk of harm.


Subject(s)
Disorders of Excessive Somnolence/etiology , Parkinson Disease/complications , Aged , Cross-Sectional Studies , Disability Evaluation , Female , Humans , Longitudinal Studies , Male , Middle Aged , Retrospective Studies , Risk Factors , Severity of Illness Index , Statistics, Nonparametric , Surveys and Questionnaires , Survival Analysis
6.
Parkinsonism Relat Disord ; 20(9): 980-5, 2014 Sep.
Article in English | MEDLINE | ID: mdl-25024059

ABSTRACT

OBJECTIVE: Aim of this study was to identify risk factors for the development of dementia in patients with Parkinson's disease (PD). METHODS: A broad range of motor and non-motor features was assessed at baseline and the following five years in 406 PD patients. Cross-sectional analyses of baseline data and longitudinal analyses of follow-up data were performed to identify risk factors for dementia. RESULTS: Thirty-two percent of patients (n = 129) had dementia at baseline, while 26% of patients (n = 68) without dementia at baseline developed dementia during follow-up. Univariate survival analysis showed that higher age, fewer years of education, longer disease duration, higher age-at-onset, higher levodopa dose, higher Hoehn & Yahr stage, presence of dyskinesias, excessive daytime sleepiness (EDS), presence of hallucinations, and more severe autonomic and depressive symptoms were associated with an increased risk of dementia. Higher baseline Postural-Instability-and-Gait-Difficulty scores were also associated with an increased risk of dementia, whereas no effect of tremor severity was found. These findings largely corresponded with the variables that were associated with the presence of dementia at baseline. In a stepwise regression model, higher age at baseline, fewer years of education, higher daily levodopa dose and excessive daytime sleepiness (EDS) emerged as independent risk factors of future dementia. CONCLUSIONS: In this large prospective cohort study, we identified a combination of potentially interacting risk factors for dementia in PD that are associated with higher age and more advanced disease.


Subject(s)
Dementia/diagnosis , Dementia/etiology , Parkinson Disease/complications , Adult , Age of Onset , Aged , Aged, 80 and over , Cohort Studies , Cross-Sectional Studies , Dementia/drug therapy , Female , Humans , Levodopa/therapeutic use , Male , Middle Aged , Neuropsychological Tests , Parkinson Disease/drug therapy , Prospective Studies , Risk Factors
7.
Mov Disord ; 28(6): 755-62, 2013 Jun.
Article in English | MEDLINE | ID: mdl-23520046

ABSTRACT

The aim of this study was to identify risk factors for the development of hallucinations in patients with Parkinson's disease (PD). A broad range of motor and nonmotor features was assessed at baseline and during the following 5 years in 386 PD patients. Cross-sectional analyses of baseline data and longitudinal analyses of follow-up data were performed to identify risk factors for hallucinations in PD. Twenty-one percent of the patients had hallucinations at baseline, whereas 46% of the patients without hallucinations at baseline developed this feature during follow-up. Univariate survival analysis showed that older age, female sex, less education, higher age at onset, and more severe motor and cognitive impairment, depression, daytimes sleepiness, autonomic dysfunction, and motor fluctuations and dyskinesias, as well as higher daily levodopa dose, were associated with the risk of developing hallucinations. This largely corresponds with the features that were associated with the presence of hallucinations at baseline. In a stepwise regression model, older age at onset, female sex, excessive daytime sleepiness, autonomic dysfunction, and dyskinesias emerged as independent risk factors for developing hallucinations. Female sex, autonomic dysfunction, motor fluctuations, and dyskinesias have not been reported as risk factors in previous studies. These findings lend support to the notion that hallucinations in PD are caused by a combination of risk factors that are associated with (the interaction between) older age and more advanced disease. The identification of female sex as a risk factor for developing of hallucinations in PD is a new finding and should be verified in future studies.


Subject(s)
Hallucinations/epidemiology , Hallucinations/etiology , Parkinson Disease/complications , Parkinson Disease/epidemiology , Aged , Cohort Studies , Cross-Sectional Studies , Female , Hallucinations/mortality , Humans , Kaplan-Meier Estimate , Male , Middle Aged , Neuropsychological Tests , Parkinson Disease/mortality , Proportional Hazards Models , Psychiatric Status Rating Scales , Risk Factors
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