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Authors = Irene Litvan

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22 pages, 724 KiB  
Review
Cognitive Impairment in Parkinson’s Disease: Epidemiology, Clinical Profile, Protective and Risk Factors
by Paulina Gonzalez-Latapi, Ece Bayram, Irene Litvan and Connie Marras
Behav. Sci. 2021, 11(5), 74; https://doi.org/10.3390/bs11050074 - 13 May 2021
Cited by 74 | Viewed by 13685
Abstract
Cognitive impairment is a common non-motor symptom in Parkinson’s Disease (PD) and an important source of patient disability and caregiver burden. The timing, profile and rate of cognitive decline varies widely among individuals with PD and can range from normal cognition to mild [...] Read more.
Cognitive impairment is a common non-motor symptom in Parkinson’s Disease (PD) and an important source of patient disability and caregiver burden. The timing, profile and rate of cognitive decline varies widely among individuals with PD and can range from normal cognition to mild cognitive impairment (PD-MCI) and dementia (PDD). Beta-amyloid and tau brain accumulation, oxidative stress and neuroinflammation are reported risk factors for cognitive impairment. Traumatic brain injury and pesticide and tobacco exposure have also been described. Genetic risk factors including genes such as COMT, APOE, MAPT and BDNF may also play a role. Less is known about protective factors, although the Mediterranean diet and exercise may fall in this category. Nonetheless, there is conflicting evidence for most of the factors that have been studied. The use of inconsistent criteria and lack of comprehensive assessment in many studies are important methodological issues. Timing of exposure also plays a crucial role, although identification of the correct time window has been historically difficult in PD. Our understanding of the mechanism behind these factors, as well as the interactions between gene and environment as determinants of disease phenotype and the identification of modifiable risk factors will be paramount, as this will allow for potential interventions even in established PD. Full article
(This article belongs to the Special Issue Parkinson’s Disease and Cognition)
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12 pages, 3217 KiB  
Article
Assessment of Motor Dysfunction with Virtual Reality in Patients Undergoing [123I]FP-CIT SPECT/CT Brain Imaging
by Jeanne P. Vu, Ghiam Yamin, Zabrina Reyes, Alex Shin, Alexander Young, Irene Litvan, Pengtao Xie and Sebastian Obrzut
Tomography 2021, 7(2), 95-106; https://doi.org/10.3390/tomography7020009 - 26 Mar 2021
Cited by 2 | Viewed by 3663
Abstract
[123I]FP-CIT SPECT has been valuable for distinguishing Parkinson disease (PD) from essential tremor. However, its performance for quantitative assessment of motor dysfunction has not been established. A virtual reality (VR) application was developed and compared with [123I]FP-CIT SPECT/CT for [...] Read more.
[123I]FP-CIT SPECT has been valuable for distinguishing Parkinson disease (PD) from essential tremor. However, its performance for quantitative assessment of motor dysfunction has not been established. A virtual reality (VR) application was developed and compared with [123I]FP-CIT SPECT/CT for detection of severity of motor dysfunction. Forty-four patients (21 males, 23 females, age 64.5 ± 12.4) with abnormal [123I]FP-CIT SPECT/CT underwent assessment of bradykinesia, activities of daily living, and tremor with VR. Support vector machines (SVM) machine learning models were applied to VR and SPECT data. Receiver operating characteristic (ROC) analysis demonstrated greater area under the curve (AUC) for VR (0.8418, 95% CI 0.6071–0.9617) compared with brain SPECT (0.5357, 95% CI 0.3373–0.7357, p = 0.029) for detection of motor dysfunction. Logistic regression identified VR as an independent predictor of motor dysfunction (Odds Ratio 326.4, SE 2.17, p = 0.008). SVM for prediction of the Unified Parkinson’s Disease Rating Scale Part III (UPDRS-III) demonstrated greater R-squared of 0.713 (p = 0.008) for VR, compared with 0.0764 (p = 0.361) for brain SPECT. This study demonstrates that VR can be safely used in patients prior to [123I]FP-CIT SPECT imaging and may improve prediction of motor dysfunction. This test has the potential to provide a simple, objective, quantitative analysis of motor symptoms in PD patients. Full article
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17 pages, 561 KiB  
Review
Fall Prediction and Prevention Systems: Recent Trends, Challenges, and Future Research Directions
by Ramesh Rajagopalan, Irene Litvan and Tzyy-Ping Jung
Sensors 2017, 17(11), 2509; https://doi.org/10.3390/s17112509 - 1 Nov 2017
Cited by 131 | Viewed by 23358
Abstract
Fall prediction is a multifaceted problem that involves complex interactions between physiological, behavioral, and environmental factors. Existing fall detection and prediction systems mainly focus on physiological factors such as gait, vision, and cognition, and do not address the multifactorial nature of falls. In [...] Read more.
Fall prediction is a multifaceted problem that involves complex interactions between physiological, behavioral, and environmental factors. Existing fall detection and prediction systems mainly focus on physiological factors such as gait, vision, and cognition, and do not address the multifactorial nature of falls. In addition, these systems lack efficient user interfaces and feedback for preventing future falls. Recent advances in internet of things (IoT) and mobile technologies offer ample opportunities for integrating contextual information about patient behavior and environment along with physiological health data for predicting falls. This article reviews the state-of-the-art in fall detection and prediction systems. It also describes the challenges, limitations, and future directions in the design and implementation of effective fall prediction and prevention systems. Full article
(This article belongs to the Special Issue Wearable and Ambient Sensors for Healthcare and Wellness Applications)
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19 pages, 321 KiB  
Review
Environmental Exposures and Parkinson’s Disease
by Sirisha Nandipati and Irene Litvan
Int. J. Environ. Res. Public Health 2016, 13(9), 881; https://doi.org/10.3390/ijerph13090881 - 3 Sep 2016
Cited by 184 | Viewed by 14224
Abstract
Parkinson’s disease (PD) affects millions around the world. The Braak hypothesis proposes that in PD a pathologic agent may penetrate the nervous system via the olfactory bulb, gut, or both and spreads throughout the nervous system. The agent is unknown, but several environmental [...] Read more.
Parkinson’s disease (PD) affects millions around the world. The Braak hypothesis proposes that in PD a pathologic agent may penetrate the nervous system via the olfactory bulb, gut, or both and spreads throughout the nervous system. The agent is unknown, but several environmental exposures have been associated with PD. Here, we summarize and examine the evidence for such environmental exposures. We completed a comprehensive review of human epidemiologic studies of pesticides, selected industrial compounds, and metals and their association with PD in PubMed and Google Scholar until April 2016. Most studies show that rotenone and paraquat are linked to increased PD risk and PD-like neuropathology. Organochlorines have also been linked to PD in human and laboratory studies. Organophosphates and pyrethroids have limited but suggestive human and animal data linked to PD. Iron has been found to be elevated in PD brain tissue but the pathophysiological link is unclear. PD due to manganese has not been demonstrated, though a parkinsonian syndrome associated with manganese is well-documented. Overall, the evidence linking paraquat, rotenone, and organochlorines with PD appears strong; however, organophosphates, pyrethroids, and polychlorinated biphenyls require further study. The studies related to metals do not support an association with PD. Full article
(This article belongs to the Special Issue Environmental Neurotoxicology)
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