842 resultados para Parkinsons-disease Result
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AIM: To document and compare current practice in nutrition assessment of Parkinson’s disease by dietitians in Australia and Canada in order to identify priority areas for review and development of practice guidelines and direct future research. METHODS: An online survey was distributed to DAA members and PEN subscribers through their email newsletters. The survey captured current practice in the phases of the Nutrition Care Plan. The results of the assessment phase are presented here. RESULTS: Eighty-four dietitians responded. Differences in practice existed in the choice of nutrition screening and assessment tools, including appropriate BMI ranges. Nutrition impact symptoms were commonly assessed, but information about Parkinson’s disease medication interactions were not consistently assessed. CONCLUSIONS: he variation in practice related to the use of screening and assessment methods may result in the identification of different goals for subsequent interventions. Even more practice variation was evident for those items more specific to Parkinson’s disease and may be due to the lack of evidence to guide practice. Further research is required to support decisions for nutrition assessment of Parkinson’s disease.
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Being able to accurately predict the risk of falling is crucial in patients with Parkinson’s dis- ease (PD). This is due to the unfavorable effect of falls, which can lower the quality of life as well as directly impact on survival. Three methods considered for predicting falls are decision trees (DT), Bayesian networks (BN), and support vector machines (SVM). Data on a 1-year prospective study conducted at IHBI, Australia, for 51 people with PD are used. Data processing are conducted using rpart and e1071 packages in R for DT and SVM, con- secutively; and Bayes Server 5.5 for the BN. The results show that BN and SVM produce consistently higher accuracy over the 12 months evaluation time points (average sensitivity and specificity > 92%) than DT (average sensitivity 88%, average specificity 72%). DT is prone to imbalanced data so needs to adjust for the misclassification cost. However, DT provides a straightforward, interpretable result and thus is appealing for helping to identify important items related to falls and to generate fallers’ profiles.
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Part I: Parkinson’s disease is a slowly progressive neurodegenerative disorder in which particularly the dopaminergic neurons of the substantia nigra pars compacta degenerate and die. Current conventional treatment is based on restraining symptoms but it has no effect on the progression of the disease. Gene therapy research has focused on the possibility of restoring the lost brain function by at least two means: substitution of critical enzymes needed for the synthesis of dopamine and slowing down the progression of the disease by supporting the functions of the remaining nigral dopaminergic neurons by neurotrophic factors. The striatal levels of enzymes such as tyrosine hydroxylase, dopadecarboxylase and GTP-CH1 are decreased as the disease progresses. By replacing one or all of the enzymes, dopamine levels in the striatum may be restored to normal and behavioral impairments caused by the disease may be ameliorated especially in the later stages of the disease. The neurotrophic factors glial cell derived neurotrophic factor (GDNF) and neurturin have shown to protect and restore functions of dopaminergic cell somas and terminals as well as improve behavior in animal lesion models. This therapy may be best suited at the early stages of the disease when there are more dopaminergic neurons for neurotrophic factors to reach. Viral vector-mediated gene transfer provides a tool to deliver proteins with complex structures into specific brain locations and provides long-term protein over-expression. Part II: The aim of our study was to investigate the effects of two orally dosed COMT inhibitors entacapone (10 and 30 mg/kg) and tolcapone (10 and 30 mg/kg) with a subsequent administration of a peripheral dopadecarboxylase inhibitor carbidopa (30 mg/kg) and L- dopa (30 mg/kg) on dopamine and its metabolite levels in the dorsal striatum and nucleus accumbens of freely moving rats using dual-probe in vivo microdialysis. Earlier similarly designed studies have only been conducted in the dorsal striatum. We also confirmed the result of earlier ex vivo studies regarding the effects of intraperitoneally dosed tolcapone (30 mg/kg) and entacapone (30 mg/kg) on striatal and hepatic COMT activity. The results obtained from the dorsal striatum were generally in line with earlier studies, where tolcapone tended to increase dopamine and DOPAC levels and decrease HVA levels. Entacapone tended to keep striatal dopamine and HVA levels elevated longer than in controls and also tended to elevate the levels of DOPAC. Surprisingly in the nucleus accumbens, dopamine levels after either dose of entacapone or tolcapone were not elevated. Accumbal DOPAC levels, especially in the tolcapone 30 mg/kg group, were elevated nearly to the same extent as measured in the dorsal striatum. Entacapone 10 mg/kg elevated accumbal HVA levels more than the dose of 30 mg/kg and the effect was more pronounced in the nucleus accumbens than in the dorsal striatum. This suggests that entacapone 30 mg/kg has minor central effects. Also our ex vivo study results obtained from the dorsal striatum suggest that entacapone 30 mg/kg has minor and transient central effects, even though central HVA levels were not suppressed below those of the control group in either brain area in the microdialysis study. Both entacapone and tolcapone suppressed hepatic COMT activity more than striatal COMT activity. Tolcapone was more effective than entacapone in the dorsal striatum. The differences between dopamine and its metabolite levels in the dorsal striatum and nucleus accumbens may be due to different properties of the two brain areas.
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Urocortin (Ucn 1), a 40 amino acid long peptide related to corticotropin releasing factor (CRF) was discovered 19 years ago, based on its sequence homology to the parent molecule. Its existence was inferred in the CNS because of anatomical and pharmacological discrepancies between CRF and its two receptor subtypes. Although originally found in the brain, where it has opposing actions to CRF and therefore confers stress-coping mechanisms, Ucn 1 has subsequently been found throughout the periphery including heart, lung, skin, and immune cells. It is now well established that this small peptide is involved in a multitude of physiological and pathophysiological processes, due to its receptor subtype distribution and promiscuity in second messenger signalling pathways. As a result of extensive studies in this field, there are now well over one thousand peer reviewed publications involving Ucn 1. In this review, we intend to highlight some of the less well known actions of Ucn 1 and in particular its role in neuronal cell protection and maintenance of the skeletal system, both by conventional methods of reviewing the literature and using bioinformatics, to highlight further associations between Ucn 1 and disease conditions. Understanding how Ucn 1 works in these tissues, will help to unravel its role in normal and pathophysiological processes. This would ultimately allow the generation of putative medical interventions for the alleviation of important diseases such as Parkinson's disease, arthritis, and osteoporosis.
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Objective To design, develop and set up a web-based system for enabling graphical visualization of upper limb motor performance (ULMP) of Parkinson’s disease (PD) patients to clinicians. Background Sixty-five patients diagnosed with advanced PD have used a test battery, implemented in a touch-screen handheld computer, in their home environment settings over the course of a 3-year clinical study. The test items consisted of objective measures of ULMP through a set of upper limb motor tests (finger to tapping and spiral drawings). For the tapping tests, patients were asked to perform alternate tapping of two buttons as fast and accurate as possible, first using the right hand and then the left hand. The test duration was 20 seconds. For the spiral drawing test, patients traced a pre-drawn Archimedes spiral using the dominant hand, and the test was repeated 3 times per test occasion. In total, the study database consisted of symptom assessments during 10079 test occasions. Methods Visualization of ULMP The web-based system is used by two neurologists for assessing the performance of PD patients during motor tests collected over the course of the said study. The system employs animations, scatter plots and time series graphs to visualize the ULMP of patients to the neurologists. The performance during spiral tests is depicted by animating the three spiral drawings, allowing the neurologists to observe real-time accelerations or hesitations and sharp changes during the actual drawing process. The tapping performance is visualized by displaying different types of graphs. Information presented included distribution of taps over the two buttons, horizontal tap distance vs. time, vertical tap distance vs. time, and tapping reaction time over the test length. Assessments Different scales are utilized by the neurologists to assess the observed impairments. For the spiral drawing performance, the neurologists rated firstly the ‘impairment’ using a 0 (no impairment) – 10 (extremely severe) scale, secondly three kinematic properties: ‘drawing speed’, ‘irregularity’ and ‘hesitation’ using a 0 (normal) – 4 (extremely severe) scale, and thirdly the probable ‘cause’ for the said impairment using 3 choices including Tremor, Bradykinesia/Rigidity and Dyskinesia. For the tapping performance, a 0 (normal) – 4 (extremely severe) scale is used for first rating four tapping properties: ‘tapping speed’, ‘accuracy’, ‘fatigue’, ‘arrhythmia’, and then the ‘global tapping severity’ (GTS). To achieve a common basis for assessment, initially one neurologist (DN) performed preliminary ratings by browsing through the database to collect and rate at least 20 samples of each GTS level and at least 33 samples of each ‘cause’ category. These preliminary ratings were then observed by the two neurologists (DN and PG) to be used as templates for rating of tests afterwards. In another track, the system randomly selected one test occasion per patient and visualized its items, that is tapping and spiral drawings, to the two neurologists. Statistical methods Inter-rater agreements were assessed using weighted Kappa coefficient. The internal consistency of properties of tapping and spiral drawing tests were assessed using Cronbach’s α test. One-way ANOVA test followed by Tukey multiple comparisons test was used to test if mean scores of properties of tapping and spiral drawing tests were different among GTS and ‘cause’ categories, respectively. Results When rating tapping graphs, inter-rater agreements (Kappa) were as follows: GTS (0.61), ‘tapping speed’ (0.89), ‘accuracy’ (0.66), ‘fatigue’ (0.57) and ‘arrhythmia’ (0.33). The poor inter-rater agreement when assessing “arrhythmia” may be as a result of observation of different things in the graphs, among the two raters. When rating animated spirals, both raters had very good agreement when assessing severity of spiral drawings, that is, ‘impairment’ (0.85) and irregularity (0.72). However, there were poor agreements between the two raters when assessing ‘cause’ (0.38) and time-information properties like ‘drawing speed’ (0.25) and ‘hesitation’ (0.21). Tapping properties, that is ‘tapping speed’, ‘accuracy’, ‘fatigue’ and ‘arrhythmia’ had satisfactory internal consistency with a Cronbach’s α coefficient of 0.77. In general, the trends of mean scores of tapping properties worsened with increasing levels of GTS. The mean scores of the four properties were significantly different to each other, only at different levels. In contrast from tapping properties, kinematic properties of spirals, that is ‘drawing speed’, ‘irregularity’ and ‘hesitation’ had a questionable consistency among them with a coefficient of 0.66. Bradykinetic spirals were associated with more impaired speed (mean = 83.7 % worse, P < 0.001) and hesitation (mean = 77.8% worse, P < 0.001), compared to dyskinetic spirals. Both these ‘cause’ categories had similar mean scores of ‘impairment’ and ‘irregularity’. Conclusions In contrast from current approaches used in clinical setting for the assessment of PD symptoms, this system enables clinicians to animate easily and realistically the ULMP of patients who at the same time are at their homes. Dynamic access of visualized motor tests may also be useful when observing and evaluating therapy-related complications such as under- and over-medications. In future, we foresee to utilize these manual ratings for developing and validating computer methods for automating the process of assessing ULMP of PD patients.
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Parkinson’s disease (PD) is an increasing neurological disorder in an aging society. The motor and non-motor symptoms of PD advance with the disease progression and occur in varying frequency and duration. In order to affirm the full extent of a patient’s condition, repeated assessments are necessary to adjust medical prescription. In clinical studies, symptoms are assessed using the unified Parkinson’s disease rating scale (UPDRS). On one hand, the subjective rating using UPDRS relies on clinical expertise. On the other hand, it requires the physical presence of patients in clinics which implies high logistical costs. Another limitation of clinical assessment is that the observation in hospital may not accurately represent a patient’s situation at home. For such reasons, the practical frequency of tracking PD symptoms may under-represent the true time scale of PD fluctuations and may result in an overall inaccurate assessment. Current technologies for at-home PD treatment are based on data-driven approaches for which the interpretation and reproduction of results are problematic. The overall objective of this thesis is to develop and evaluate unobtrusive computer methods for enabling remote monitoring of patients with PD. It investigates first-principle data-driven model based novel signal and image processing techniques for extraction of clinically useful information from audio recordings of speech (in texts read aloud) and video recordings of gait and finger-tapping motor examinations. The aim is to map between PD symptoms severities estimated using novel computer methods and the clinical ratings based on UPDRS part-III (motor examination). A web-based test battery system consisting of self-assessment of symptoms and motor function tests was previously constructed for a touch screen mobile device. A comprehensive speech framework has been developed for this device to analyze text-dependent running speech by: (1) extracting novel signal features that are able to represent PD deficits in each individual component of the speech system, (2) mapping between clinical ratings and feature estimates of speech symptom severity, and (3) classifying between UPDRS part-III severity levels using speech features and statistical machine learning tools. A novel speech processing method called cepstral separation difference showed stronger ability to classify between speech symptom severities as compared to existing features of PD speech. In the case of finger tapping, the recorded videos of rapid finger tapping examination were processed using a novel computer-vision (CV) algorithm that extracts symptom information from video-based tapping signals using motion analysis of the index-finger which incorporates a face detection module for signal calibration. This algorithm was able to discriminate between UPDRS part III severity levels of finger tapping with high classification rates. Further analysis was performed on novel CV based gait features constructed using a standard human model to discriminate between a healthy gait and a Parkinsonian gait. The findings of this study suggest that the symptom severity levels in PD can be discriminated with high accuracies by involving a combination of first-principle (features) and data-driven (classification) approaches. The processing of audio and video recordings on one hand allows remote monitoring of speech, gait and finger-tapping examinations by the clinical staff. On the other hand, the first-principles approach eases the understanding of symptom estimates for clinicians. We have demonstrated that the selected features of speech, gait and finger tapping were able to discriminate between symptom severity levels, as well as, between healthy controls and PD patients with high classification rates. The findings support suitability of these methods to be used as decision support tools in the context of PD assessment.
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Pathogenic α-synuclein (αS) gene mutations occur in rare familial Parkinson’s disease (PD) kindreds, and wild-type αS is a major component of Lewy bodies (LBs) in sporadic PD, dementia with LBs (DLB), and the LB variant of Alzheimer’s disease, but β-synuclein (βS) and γ-synuclein (γS) have not yet been implicated in neurological disorders. Here we show that in PD and DLB, but not normal brains, antibodies to αS and βS reveal novel presynaptic axon terminal pathology in the hippocampal dentate, hilar, and CA2/3 regions, whereas antibodies to γS detect previously unrecognized axonal spheroid-like lesions in the hippocampal dentate molecular layer. The aggregation of other synaptic proteins and synaptic vesicle-like structures in the αS- and βS-labeled hilar dystrophic neurites suggests that synaptic dysfunction may result from these lesions. Our findings broaden the concept of neurodegenerative “synucleinopathies” by implicating βS and γS, in addition to αS, in the onset/progression of PD and DLB.
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This article explores the use of probabilistic classification, namely finite mixture modelling, for identification of complex disease phenotypes, given cross-sectional data. In particular, if focuses on posterior probabilities of subgroup membership, a standard output of finite mixture modelling, and how the quantification of uncertainty in these probabilities can lead to more detailed analyses. Using a Bayesian approach, we describe two practical uses of this uncertainty: (i) as a means of describing a person’s membership to a single or multiple latent subgroups and (ii) as a means of describing identified subgroups by patient-centred covariates not included in model estimation. These proposed uses are demonstrated on a case study in Parkinson’s disease (PD), where latent subgroups are identified using multiple symptoms from the Unified Parkinson’s Disease Rating Scale (UPDRS).
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Background: Real-world environments comprise surfaces of different textures, densities and gradients, which can threaten postural stability and increase falls risk. However, there has been limited research that has examined how walking on compliant surfaces influences gait and postural stability in older people and PD patients. Methods: PD patients (n = 49) and age-matched controls (n = 32) were assessed using three dimensional motion analysis during self-paced walking on both firm and foam walkways. Falls were recorded prospectively over 12 months using daily falls calendars. Results: Walking on a foam surface influenced the temporospatial characteristics for all groups, but PD fallers adopted very different joint kinematics compared with controls. PD fallers also demonstrated reduced toe clearance and had increased mediolateral head motion(relative to walking velocity) compared with control participants. Conclusions: Postural control deficits in PD fallers may impair their capacity to attenuate surface-related perturbations and control head motion. The risk of falling for PD patients may be increased on less stable surfaces.
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Mixture models are a flexible tool for unsupervised clustering that have found popularity in a vast array of research areas. In studies of medicine, the use of mixtures holds the potential to greatly enhance our understanding of patient responses through the identification of clinically meaningful clusters that, given the complexity of many data sources, may otherwise by intangible. Furthermore, when developed in the Bayesian framework, mixture models provide a natural means for capturing and propagating uncertainty in different aspects of a clustering solution, arguably resulting in richer analyses of the population under study. This thesis aims to investigate the use of Bayesian mixture models in analysing varied and detailed sources of patient information collected in the study of complex disease. The first aim of this thesis is to showcase the flexibility of mixture models in modelling markedly different types of data. In particular, we examine three common variants on the mixture model, namely, finite mixtures, Dirichlet Process mixtures and hidden Markov models. Beyond the development and application of these models to different sources of data, this thesis also focuses on modelling different aspects relating to uncertainty in clustering. Examples of clustering uncertainty considered are uncertainty in a patient’s true cluster membership and accounting for uncertainty in the true number of clusters present. Finally, this thesis aims to address and propose solutions to the task of comparing clustering solutions, whether this be comparing patients or observations assigned to different subgroups or comparing clustering solutions over multiple datasets. To address these aims, we consider a case study in Parkinson’s disease (PD), a complex and commonly diagnosed neurodegenerative disorder. In particular, two commonly collected sources of patient information are considered. The first source of data are on symptoms associated with PD, recorded using the Unified Parkinson’s Disease Rating Scale (UPDRS) and constitutes the first half of this thesis. The second half of this thesis is dedicated to the analysis of microelectrode recordings collected during Deep Brain Stimulation (DBS), a popular palliative treatment for advanced PD. Analysis of this second source of data centers on the problems of unsupervised detection and sorting of action potentials or "spikes" in recordings of multiple cell activity, providing valuable information on real time neural activity in the brain.
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The somatosensory system plays an important role in balance control and age-related changes to this system have been implicated in falls. Parkinson’s disease (PD) is a chronic and progressive disease of the brain, characterized by postural instability and gait disturbance. Previous research has shown that deficiencies in somatosensory feedback may contribute to the poorer postural control demonstrated by PD individuals. However, few studies have comprehensively explored differences in somatosensory function and postural control between PD participants and healthy older individuals. The soles of the feet contain many cutaneous mechanoreceptors that provide important somatosensory information sources for postural control. Different types of insole devices have been developed to enhance this somatosensory information and improve postural stability, but these devices are often too complex and expensive to integrate into daily life. Textured insoles provide a more passive intervention that may be an inexpensive and accessible means to enhance the somatosensory input from the plantar surface of the feet. However, to date, there has been little work conducted to test the efficacy of enhanced somatosensory input induced by textured insoles in both healthy and PD populations during standing and walking. Therefore, the aims of this thesis were to determine: 1) whether textured insole surfaces can improve postural stability by enhancing somatosensory information in younger and older adults, 2) the differences between healthy older participants and PD participants for measures of physiological function and postural stability during standing and walking, 3) how changes in somatosensory information affect postural stability in both groups during standing and walking; and 4), whether textured insoles can improve postural stability in both groups during standing and walking. To address these aims, Study 1 recruited seven older individuals and ten healthy young controls to investigate the effects of two textured insole surfaces on postural stability while performing standing balance tests on a force plate. Participants were tested under three insole surface conditions: 1) barefoot; 2) standing on a hard textured insole surface; and 3), standing on a soft textured insole surface. Measurements derived from the centre of pressure displacement included the range of anterior-posterior and medial-lateral displacement, path length and the 90% confidence elliptical area (C90 area). Results of study 1 revealed a significant Group*Surface*Insole interaction for the four measures. Both textured insole surfaces reduced postural sway for the older group, especially in the eyes closed condition on the foam surface. However, participants reported that the soft textured insole surface was more comfortable and, hence, the soft textured insoles were adopted for Studies 2 and 3. For Study 2, 20 healthy older adults (controls) and 20 participants with Parkinson’s disease were recruited. Participants were evaluated using a series of physiological assessments that included touch sensitivity, vibratory perception, and pain and temperature threshold detection. Furthermore, nerve function and somatosensory evoked potentials tests were utilized to provide detailed information regarding peripheral nerve function for these participants. Standing balance and walking were assessed on different surfaces using a force plate and the 3D Vicon motion analysis system, respectively. Data derived from the force plate included the range of anterior-posterior and medial-lateral sway, while measures of stride length, stride period, cadence, double support time, stance phase, velocity and stride timing variability were reported for the walking assessment. The results of this study demonstrated that the PD group had decrements in somatosensory function compared to the healthy older control group. For electrodiagnosis, PD participants had poorer nerve function than controls, as evidenced by slower nerve conduction velocities and longer latencies in sural nerve and prolonged latency in the P37 somatosensory evoked potential. Furthermore, the PD group displayed more postural sway in both the anterior-posterior and medial-lateral directions relative to controls and these differences were increased when standing on a foam surface. With respect to the gait assessment, the PD group took shorter strides and had a reduced stride period compared with the control group. Furthermore, the PD group spent more time in the stance phase and had increased cadence and stride timing variability than the controls. Compared with walking on the firm surface, the two groups demonstrated different gait adaptations while walking on the uneven surface. Controls increased their stride length and stride period and decreased their cadence, which resulted in a consistent walking velocity on both surfaces. Conversely, while the PD patients also increased their stride period and decreased their cadence and stance period on the uneven surface, they did not increase their stride length and, hence walked slower on the uneven surface. In the PD group, there was a strong positive association between decreased somatosensory function and decreased clinical balance, as assessed by the Tinetti test. Poorer somatosensory function was also strongly positively correlated with the temporospatial gait parameters, especially shorter stride length. Study 3 evaluated the effects of manipulating the somatosensory information from the plantar surface of the feet using textured insoles in the same populations assessed in Study 2. For this study, participants performed the standing and walking balance tests under three footwear conditions: 1) barefoot; 2) with smooth insoles; and 3), with textured insoles. Standing balance and walking were evaluated using a force plate and a Vicon motion analysis system and the data were analysed in the same way outlined for Study 2. The findings showed that the smooth and textured insoles caused different effects on postural control during both the standing and walking trials. Both insoles decreased medial-lateral sway to the same level on the firm surface. The greatest benefits were observed in the PD group while wearing the textured insole. When standing under a more challenging condition on the foam surface with eyes closed, only the textured insole decreased medial-lateral sway in the PD group. With respect to the gait trials, both insoles increased walking velocity, stride length and stride time and decreased cadence, but these changes were more pronounced for the textured insoles. The effects of the textured insoles were evident under challenging conditions in the PD group and increased walking velocity and stride length, while decreasing cadence. Textured insoles were also effective in reducing the time spent in the double support and stance phases of the gait cycle and did not increase stride timing variability, as was the case for the smooth insoles for the PD group. The results of this study suggest that textured insoles, such as those evaluated in this research, may provide a low-cost means of improving postural stability in high-risk groups, such as people with PD, which may act as an important intervention to prevent falls.
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Parkinson’s disease (PD) is a progressive, chronic neurodegenerative disorder for which there is no known cure. Physical exercise programs may be used to assist with the physical management of PD. Several studies have demonstrated that community based physical therapy programs are effective in reducing physical aspects of disability among people with PD. While multidisciplinary therapy interventions may have the potential to reduce disability and improve the quality of life of people with PD, there is very limited clinical trial evidence to support or refute the use of a community based multidisciplinary or interdisciplinary programs for people with PD. A two group randomized trial is being undertaken within a community rehabilitation service in Brisbane, Australia. Community dwelling adults with a diagnosis of Idiopathic Parkinson’s disease are being recruited. Eligible participants are randomly allocated to a standard exercise rehabilitation group program or an intervention group which incorporates physical, cognitive and speech activities in a multi-tasking framework. Outcomes will be measured at 6-week intervals for a period of six months. Primary outcome measures are the Montreal Cognitive Assessment (MoCA) and the Timed Up and Go (TUG) cognitive test. Secondary outcomes include changes in health related quality of life, communication, social participation, mobility, strength and balance, and carer burden measures. This study will determine the immediate and long-term effectiveness of a unique multifocal, interdisciplinary, dual-tasking approach to the management of PD as compared to an exercise only program. We anticipate that the results of this study will have implications for the development of cost effective evidence based best practice for the treatment of people with PD living in the community.
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In the elderly, the risks for protein-energy malnutrition from older age, dementia, depression and living alone have been well-documented. Other risk factors including anorexia, gastrointestinal dysfunction, loss of olfactory and taste senses and early satiety have also been suggested to contribute to poor nutritional status. In Parkinson’s disease (PD), it has been suggested that the disease symptoms may predispose people with PD to malnutrition. However, the risks for malnutrition in this population are not well-understood. The current study’s aim was to determine malnutrition risk factors in community-dwelling adults with PD. Nutritional status was assessed using the Patient-Generated Subjective Global Assessment (PG-SGA). Data about age, time since diagnosis, medications and living situation were collected. Levodopa equivalent doses (LDED) and LDED per kg body weight (mg/kg) were calculated. Depression and anxiety were measured using the Beck’s Depression Inventory (BDI) and Spielberger Trait Anxiety questionnaire, respectively. Cognitive function was assessed using the Addenbrooke’s Cognitive Examination (ACE-R). Non-motor symptoms were assessed using the Scales for Outcomes in Parkinson's disease-Autonomic (SCOPA-AUT) and Modified Constipation Assessment Scale (MCAS). A total of 125 community-dwelling people with PD were included, average age of 70.2±9.3(35-92) years and average time since diagnosis of 7.3±5.9(0–31) years. Average body mass index (BMI) was 26.0±5.5kg/m2. Of these, 15% (n=19) were malnourished (SGA-B). Multivariate logistic regression analysis revealed that older age (OR=1.16, CI=1.02-1.31), more depressive symptoms (OR=1.26, CI=1.07-1.48), lower levels of anxiety (OR=.90, CI=.82-.99), and higher LDED per kg body weight (OR=1.57, CI=1.14-2.15) significantly increased malnutrition risk. Cognitive function, living situation, number of prescription medications, LDED, years since diagnosis and the severity of non-motor symptoms did not significantly influence malnutrition risk. Malnutrition results in poorer health outcomes. Proactively addressing the risk factors can help prevent declines in nutritional status. In the current study, older people with PD with depression and greater amounts of levodopa per body weight were at increased malnutrition risk.
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Objective: Malnutrition results in poor health outcomes, and people with Parkinson’s disease may be more at risk of malnutrition. However, the prevalence of malnutrition in Parkinson’s disease is not yet well defined. The aim of this study is to provide an estimate of the extent of malnutrition in community-dwelling people with Parkinson’s disease. Methods: This is a cross-sectional study of people with Parkinson’s disease residing within a 2 hour driving radius of Brisbane, Australia. The Subjective Global Assessment (SGA) and scored Patient Generated Subjective Global Assessment (PG-SGA) were used to assess nutritional status. Body weight, standing or knee height, mid-arm circumference and waist circumference were measured. Results: Nineteen (15%) of the participants were moderately malnourished (SGA-B). The median PG-SGA score of the SGA-B group was 8 (4 – 15), significantly higher than the SGA-A group, U=1860.5,p<.05. The symptoms most influencing intake were loss of appetite, constipation, early satiety and problems swallowing. Conclusions: As with other populations, malnutrition remains under-recognised and undiagnosed in people with Parkinson’s disease. Regular screening of nutritional status in people with Parkinson’s disease by health professionals with whom they have regular contact should occur to identify those who may benefit from further nutrition assessment and intervention.