REM sleep behavior disorder portends poor prognosis in Parkinson’s disease: A systematic review

Kim, Yoon; Kim, Young Eun; Park, Eunok; Shin, Chaewon; Kim, Han Joon; Jeon, Beomseok

doi:10.1016/j.jocn.2017.09.019

Cited by 48 publications

(39 citation statements)

References 83 publications

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“…For comparison, we have also computed the slow-to-fast frequency power ratio, normally defined as Here we computed it as the ratio of power in the interval [4,8) Hz (θ) frequencies versus [8,32) Hz (α+β), which we saw gave much better performance than the canonical one (which produced barely significant four-group p<0.05 Kruskal-Wallis statistical test results).…”

Section: Resultsmentioning

confidence: 99%

“…RBD has an estimated prevalence of 15-60% in PD and has been proposed to define a subtype of PD with relatively poor G. Ruffini prognosis, reflecting a brainstem-dominant route of pathology progression (v. [4] and references therein) with a higher risk for dementia or hallucinations. PD with RBD is characterized by more profound and extensive pathology-not limited to the brainstem-,with higher synuclein deposition in both cortical and sub-cortical regions.…”

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confidence: 99%

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Algorithmic complexity of EEG for prognosis of neurodegeneration in idiopathic rapid eye movement behavior disorder (RBD)

Ruffini

Ibañez

Kroupi

et al. 2017

Preprint

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Objectives: Idiopathic REM sleep behavior disorder (RBD) is a serious risk factor for neurodegenerative processes such as Parkinson's disease (PD). We investigate the use of EEG algorithmic complexity derived metrics for its prognosis. Methods:We analyzed resting state EEG data collected from 114 idiopathic RBD patients and 83 healthy controls in a longitudinal study forming a cohort in which several RBD patients developed PD or dementia with Lewy bodies.Multichannel data from ∼5 minute recordings was converted to spectrograms and their algorithmic complexity estimated using Lempel-Ziv-Welch compression (LZW).Results: Complexity measures and entropy rate displayed statistically significant differences between groups. Results are compared to those using the ratio of slow to fast frequency power, which they are seen to complement by displaying increased sensitivity even when using a few EEG channels.Conclusions: Poor prognosis in RBD appears to be associated with decreased * Corresponding author, giulio.ruffini@neuroelectrics.com, +1 617-899 6911 Preprint submitted to Clinical NeurophysiologyDecember 10, 2017. CC-BY-ND 4.0 International license peer-reviewed) is the author/funder. It is made available under a The copyright holder for this preprint (which was not . http://dx.doi.org/10.1101/200543 doi: bioRxiv preprint first posted online Oct. 9, 2017; complexity of EEG spectrograms stemming in part from frequency power imbalances and cross-frequency amplitude coupling.Significance: Algorithmic complexity metrics provide a robust, powerful and complementary way to quantify the dynamics of EEG signals in RBD with links to emerging theories of brain function stemming from algorithmic information theory.

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Section: Resultsmentioning

confidence: 99%

mentioning

confidence: 99%

Algorithmic complexity of EEG for prognosis of neurodegeneration in idiopathic rapid eye movement behavior disorder (RBD)

Ruffini

Ibañez

Kroupi

et al. 2017

Preprint

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“…Several primary or secondary neurodegenerative diseases as for example, Alzheimer's disease (AD; Grinberg et al, ), Parkinson's disease (Grinberg, Rueb, Alho, & Heinsen, ), progressive supranuclear palsy (Williams & Lees, ), multisystem atrophy (Ghorayeb et al, ), amyotrophic lateral sclerosis (Warabi, Hayashi, Nagao, & Shimizu, ) and multiple sclerosis (MS; Noseworthy, Lucchinetti, Rodriguez, & Weinshenker, ), can affect the BS or its substructures. During these diseases, progressive neurodegeneration of BS structures can result in dysphagia, dysarthria, autonomic dysfunction and other symptoms that influence not only the patient's quality of life but also survival (Grinberg et al, ; Kim et al, ).…”

Section: Introductionmentioning

confidence: 99%

Accurate, rapid and reliable, fully automated MRI brainstem segmentation for application in multiple sclerosis and neurodegenerative diseases

Sander

Pezold

Andermatt

et al. 2019

Human Brain Mapping

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Neurodegenerative disorders, such as Alzheimer's disease (AD) and progressive forms of multiple sclerosis (MS), can affect the brainstem and are associated with atrophy that can be visualized by MRI. Anatomically accurate, large‐scale assessments of brainstem atrophy are challenging due to lack of automated, accurate segmentation methods. We present a novel method for brainstem volumetry using a fully‐automated segmentation approach based on multi‐dimensional gated recurrent units (MD‐GRU), a deep learning based semantic segmentation approach employing a convolutional adaptation of gated recurrent units. The neural network was trained on 67 3D‐high resolution T1‐weighted MRI scans from MS patients and healthy controls (HC) and refined using segmentations of 20 independent MS patients' scans. Reproducibility was assessed in MR test–retest experiments in 33 HC. Accuracy and robustness were examined by Dice scores comparing MD‐GRU to FreeSurfer and manual brainstem segmentations in independent MS and AD datasets. The mean %‐change/SD between test–retest brainstem volumes were 0.45%/0.005 (MD‐GRU), 0.95%/0.009 (FreeSurfer), 0.86%/0.007 (manually edited segmentations). Comparing MD‐GRU to manually edited segmentations the mean Dice scores/SD were: 0.97/0.005 (brainstem), 0.95/0.013 (mesencephalon), 0.98/0.006 (pons), 0.95/0.015 (medulla oblongata). Compared to the manual gold standard, MD‐GRU brainstem segmentations were more accurate than FreeSurfer segmentations (p < .001). In the multi‐centric acquired AD data, the mean Dice score/SD for the MD‐GRU‐manual segmentation comparison was 0.97/0.006. The fully automated brainstem segmentation method MD‐GRU provides accurate, highly reproducible, and robust segmentations in HC and patients with MS and AD in 200 s/scan on an Nvidia GeForce GTX 1080 GPU and shows potential for application in large and longitudinal datasets.

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“…Orthostatic hypotension was consistently associated with RBD. Meanwhile motor fluctuation was not clearly associate with RBD [ 19 ].…”

Section: Discussionmentioning

confidence: 99%

Prevalence and Clinical Characteristics of Probable REM Behavior Disorder in Thai Parkinson’s Disease Patients

Gomutbutra

Kanjanaratanakorn

Tiyapun

2018

Parkinson's Disease

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Background Previous studies have shown that Parkinson's disease (PD) patients who have REM behavior disorder (PD with RBD) might be a PD subtype since they have different symptom clusters and disease trajectories from PD without RBD. Objective To study the prevalence of PD with pRBD and to compare the clinical characteristics with PD without pRBD. The feasibility of clinical interview of items adopted from the Mayo Sleep Questionnaire was also to be determined. Methods A total of 140 Parkinson's patients visiting neurological clinics during January to December 2016 were enrolled in this study. “Probable RBD (pRBD)” was defined as present when the patient answered “yes” to a question adapted from the first Mayo Sleep Questionnaire (MSQ). The demographic data, motor symptoms, and nonmotor symptoms were obtained. Results The prevalence of pRBD among this study's PD patients was 48.5% (68 out of the total of 140). The median onset of RBD before PD diagnosis was 5 years (range: 0–11 years). By comparison of PD with pRBD and PD without pRBD, this study showed significant difference in the levodopa equivalent dose (742 mg/day versus 566 mg/day; p < 0.01), prevalence of symptomatic orthostatic hypotension (35.3% versus 8.3%; p < 0.01). The multivariable analysis found that pRBD is independently associated with orthostatic hypotension (OR = 5.02, p < 0.01). Conclusion. The findings regarding prevalence and main clinical features of PD with pRBD in this study were similar to those of a previous study of PD with polysomnogram- (PSG-) proven RBD. This study hypothesized that interviewing by adopted MSQ may be a cost-effective tool for screening RBD. Further studies with direct comparison are needed.

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REM sleep behavior disorder portends poor prognosis in Parkinson’s disease: A systematic review

Cited by 48 publications

References 83 publications

Algorithmic complexity of EEG for prognosis of neurodegeneration in idiopathic rapid eye movement behavior disorder (RBD)

Algorithmic complexity of EEG for prognosis of neurodegeneration in idiopathic rapid eye movement behavior disorder (RBD)

Accurate, rapid and reliable, fully automated MRI brainstem segmentation for application in multiple sclerosis and neurodegenerative diseases

Prevalence and Clinical Characteristics of Probable REM Behavior Disorder in Thai Parkinson’s Disease Patients

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