ORCID Profile
0000-0002-5890-1894
Current Organisation
Murdoch University
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Publisher: Frontiers Media SA
Date: 11-03-2021
DOI: 10.3389/FBIOE.2021.639337
Abstract: Accurately differentiating dementia subtypes, such as Alzheimer’s disease (AD) and Lewy body disease [including dementia with Lewy bodies (DLB) and Parkinson’s disease dementia (PDD)] is important to ensure appropriate management and treatment of the disease. Similarities in clinical presentation create difficulties for differential diagnosis. Simple supportive markers, such as balance assessments, may be useful to the diagnostic toolkit. This study aimed to identify differences in balance impairments between different dementia disease subtypes and normal aging using a single triaxial accelerometer. Ninety-seven participants were recruited, forming four groups: cognitive impairment due to Alzheimer’s disease (AD group n = 31), dementia with Lewy bodies (DLB group n = 26), Parkinson’s disease dementia (PDD group n = 13), and normal aging controls ( n = 27). Participants were asked to stand still for 2 minutes in a standardized position with their eyes open while wearing a single triaxial accelerometer on their lower back. Seven balance characteristics were derived, including jerk (combined, mediolateral, and anterior–posterior), root mean square (RMS combined, mediolateral, and anterior–posterior), and ellipsis. Mann–Whitney U tests identified the balance differences between groups. Receiver operating characteristics and area under the curve (AUC) determined the overall accuracy of the selected balance characteristics. The PDD group demonstrated higher RMS [combined ( p = 0.001), mediolateral ( p = 0.005), and anterior–posterior ( p = 0.001)] and ellipsis scores ( p & 0.002) than the AD group (AUC = 0.71–0.82). The PDD group also demonstrated significantly impaired balance across all characteristics ( p ≤ 0.001) compared to the controls (AUC = 0.79–0.83). Balance differences were not significant between PDD and DLB (AUC = 0.69–0.74), DLB and AD (AUC = 0.50–0.65), DLB and controls (AUC = 0.62–0.68), or AD and controls (AUC = 0.55–0.67) following Bonferroni correction. Although feasible and quick to conduct, key findings suggest that an accelerometer-based balance during quiet standing does not differentiate dementia disease subtypes accurately. Assessments that challenge balance more, such as gait or standing with eyes closed, may prove more effective to support differential diagnosis.
Publisher: Springer Science and Business Media LLC
Date: 15-05-2021
DOI: 10.1007/S00415-021-10586-7
Abstract: Pain is a common non-motor symptom in Parkinson’s disease (PD), affecting up to 85% of patients. The frequency and stability of pain over time has not been extensively studied. There is a paucity of high-quality studies investigating pain management in PD. To develop interventions, an understanding of how pain changes over the disease course is required. One hundred and fifty-four participants with early PD and 99 age-and-sex-matched controls were recruited as part of a longitudinal study (Incidence of Cognitive Impairment in Cohorts with Longitudinal Evaluation in PD, ICICLE-PD). Pain data were collected at 18-month intervals over 72 months in both groups using the Nonmotor Symptom Questionnaire (NMSQ), consisting of a binary yes/no response. Two questions from the Parkinson’s Disease Questionnaire (PDQ-39) were analysed for the PD group only. Unexplained pain was common in the PD group and occurred more frequently than in age-matched controls. ‘Aches and pains’ occurred more frequently than ‘cr s and muscle spasms’ at each time point ( p 0.001) except 54 months. This study shows that pain is prevalent even in the early stages of PD, yet the frequency and type of pain fluctuates as symptoms progress. People with PD should be asked about their pain at clinical consultations and given support with describing pain given the different ways this can present.
Publisher: Elsevier BV
Date: 12-2021
Publisher: Wiley
Date: 14-03-2022
DOI: 10.1002/MDS.28977
Abstract: Gait impairments are characteristic motor manifestations and significant predictors of poor quality of life in Parkinson's disease (PD). Neuroimaging biomarkers for gait impairments in PD could facilitate effective interventions to improve these symptoms and are highly warranted. The aim of this study was to identify neural networks of discrete gait impairments in PD. Fifty‐five participants with early‐stage PD and 20 age‐matched healthy volunteers underwent quantitative gait assessment deriving 12 discrete spatiotemporal gait characteristics and [ 18 F]‐2‐fluoro‐2‐deoxyglucose‐positron emission tomography measuring resting cerebral glucose metabolism. A multivariate spatial covariance approach was used to identify metabolic brain networks that were related to discrete gait characteristics in PD. In PD, we identified two metabolic gait‐related covariance networks. The first correlated with mean step velocity and mean step length ( pace gait network ), which involved relatively increased and decreased metabolism in frontal cortices, including the dorsolateral prefrontal and orbital frontal, insula, supplementary motor area, ventrolateral thalamus, cerebellum, and cuneus. The second correlated with swing time variability and step time variability ( temporal variability gait network ), which included relatively increased and decreased metabolism in sensorimotor, superior parietal cortex, basal ganglia, insula, hippoc us, red nucleus, and mediodorsal thalamus. Expression of both networks was significantly elevated in participants with PD relative to healthy volunteers and were not related to levodopa dosage or motor severity. We have identified two novel gait‐related brain networks of altered glucose metabolism at rest. These gait networks could serve as a potential neuroimaging biomarker of gait impairments in PD and facilitate development of therapeutic strategies for these disabling symptoms. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society
Publisher: Informa UK Limited
Date: 08-08-2023
Publisher: Informa UK Limited
Date: 09-03-2022
DOI: 10.1080/02640414.2022.2047504
Abstract: We aimed to assess one-year changes in physical fitness, health-related quality of life (HRQoL) and body mass index (BMI), encompassing the 2020 COVID-19 UK lockdowns. Data were collected (October 2019, November 2020) from 178 8-10-year-olds in Newcastle-upon-Tyne, England, 85% from England's most deprived quintile. Twenty-metre shuttle run test performance (20mSRT), handgrip strength (HGS), standing broad jump (SBJ), sit-and-reach, height, body mass, HRQoL (Kidscreen-27 questionnaire) and sports club participation were measured. BMI z-scores and overweight/obesity were calculated (≥85th centile). Paired t-tests and linear regression assessed change, adjusting for baseline BMI. Significant (p<0.001) changes were observed: increases in mean BMI (+1.5kg·m
No related grants have been discovered for Brook Galna.