Session Information
Date: Monday, June 20, 2016
Session Title: Parkinsonism, MSA, PSP (secondary and parkinsonism-plus)
Session Time: 12:30pm-2:00pm
Location: Exhibit Hall located in Hall B, Level 2
Objective: The study aimed to examine whether the video-polysomnography (vPSG) could provide some clues for differentiating atypical Parkinsonian syndromes (APS) from Parkinson’s disease (PD) among alpha-synucleinopathies (SPs).
Background: REM sleep without atonia (RSWA) is an essential diagnostic feature of RBD on PSG. It has been reported that the higher surface EMG activity were associated with longer PD disease duration and greater disease severity and suggest it as a PD biomarker. However, little is known about the clinical correlates of RSWA in APS. One study suggests that a higher RSWA percentage was found in MSA than PD. And whether the amount of RSWA could be a potential marker for differentiating APS from PD hasn’t been well understood.
Methods: The study group comprised 24 APS patients (4 dementia of lewy bodies, 20 multiple system atrophy), 32 patients with PD matched for age, sex, and the percentage of rapid eye movement (REM) sleep behavior disorder (RBD) were selected for comparison. All patients were evaluated by Mini Mental Status Examination (MMSE), the Montreal Cognitive Assessment (MoCA, Beijing Version), Epworth Sleepiness Scale (ESS) and Pittsburgh Sleep Quality Index (PSQI), and underwent a whole night vPSG and clinical evaluation. We manually quantified the tonic and phasic chin electromyogram (EMG) activity during REM sleep of each patient. Then, we compared the clinical characteristics and vPSG parameters between the two groups.
Results: There were no significant differences between the two groups in clinical characteristics and sleep architecture.
| before ajustment for AHI | after ajustment for AHI | |||||
| APS (n=24) | PD (n=32) | P | APS (n=18) | PD (n=25) | P | |
| Age (year) | 67.875±7.146 | 65.781±5.586 | 0.224a | 68.111±7.888 | 65.800±5.958 | 0.280a |
| Gender male (%) | 12(50) | 16(50) | 1.000b | 9 (50) | 13(52) | 0.897b |
| RBD percentage (%) | 62.5 | 56.3 | 0.638b | 72.2 | 68.0 | 0.766b |
| BMI (kg/m2) | 21.917±3.624 | 22.866±3.056 | 0.293a | 21.922±3.970 | 22.452±3.145 | 0.628a |
| Disease duration (month) | 33.833±17.512 | 44.188±28.522 | 0.123a | 34.333±18.787 | 45.240±29.466 | 0.175a |
| Hoehn-Yahr stage | – | 2.016±0.767 | – | – | 2.060±0.726 | – |
| UPDRS total score | – | 34.219±13.229 | – | – | 36.440±13.141 | – |
| LEDs (mg/day) | 433.771±251.382 | 360.906±152.037 | 0.217a | 443.028±239.607 | 376.960±135.644 | 0.257a |
| ESS score | 7.333±4.815 | 6.406±3.917 | 0.431a | 7.111±4.739 | 7.160±4.007 | 0.971a |
| PSQI score | 6.792±4.354 | 7.938±4.048 | 0.315a | 6.222±4.110 | 8.520±4.124 | 0.078a |
| MMSE score | 24.875±4.523 | 26.000±3.455 | 0.296a | 24.722±4.787 | 25.600±3.640 | 0.498a |
| MOCA score | 21.125±5.245 | 23.375±4.851 | 0.103a | 20.667±5.531 | 23.040±4.895 | 0.145a |
| Education (year) | 8.750±4.954 | 8.531±3.379 | 0.845a | 7.889±4.676 | 8.360±3.650 | 0.712a |
| before ajustment for AHI | after ajustment for AHI | |||||
| APS (n=24) | PD (n=32) | P | APS (n=18) | PD (n=25) | P | |
| Awakenings (n) | 17.667±7.394 | 22.344±9.213 | 0.046a | 17.444±5.953 | 22.000±9.730 | 0.086a |
| TST (min) | 333.667±80.581 | 356.625±98.363 | 0.355a | 319.028±74.922 | 361.940±100.683 | 0.134a |
| SE (%) | 62.233±14.888 | 68.738±15.351 | 0.118a | 58.628±13.792 | 70.128±14.334 | 0.012a |
| SL (min) | 16.000(9.500,32.500) | 5.250(0.625,15.875) | 0.005b | 16.750(9.500,31.500) | 4.500(0.500,12.500) | 0.002b |
| REML (min) | 148.729±99.823 | 132.406±91.832 | 0.529a | 147.389±104.295 | 123.200±91.875 | 0.426a |
| W (min) | 120.167±53.859 | 114.781±79.380 | 0.776a | 131.889±48.150 | 112.360±84.698 | 0.384a |
| REM (%) | 16.679±11.543 | 15.844±7.513 | 0.744a | 17.589±12.331 | 15.436±7.890 | 0.489a |
| NREM1 (%) | 23.954±13.330 | 21.340±16.817 | 0.533a | 23.344±11.408 | 22.284±18.170 | 0.828a |
| NREM2 (%) | 44.367±15.514 | 45.734±14.789 | 0.739a | 43.294±14.498 | 44.268±16.043 | 0.839a |
| NREM3 (%) | 14.988±12.150 | 17.084±10.181 | 0.486a | 15.761±13.203 | 18.016±10.735 | 0.541a |
| Arousal index | 8.413±7.197 | 7.675±7.385 | 0.710a | 6.322±4.410 | 6.148±6.382 | 0.921a |
| AHI (/h) | 2.450(0.000,16.600) | 0.000(0.000,0.650) | 0.031b | 0.000(0.000,4.730) | 0.000(0.000,1.350) | 0.475b |
| Minimal SaO2 (%) | 88.875±4.712 | 91.406±3.004 | 0.027a | 90.722±3.196 | 91.760±2.773 | 0.263a |
| Mean SaO2 (%) | 94.792±1.865 | 95.625±1.699 | 0.087a | 94.889±1.967 | 95.800±1.555 | 0.097a |
| Time (SaO2<90%) during sleep (%) | 0.050(0.000,3.975) | 0.000(0.000,0.000) | 0.013b | 0.000(0.000,1.200) | 0.000(0.000,0.000) | 0.069b |
| Tonic EMG density (%) | 35.055±27.950 | 11.825±13.412 | 0.001a | 37.017±27.539 | 14.315±14.072 | 0.004a |
| Phasic EMG density (%) | 9.994±13.518 | 7.306±9.310 | 0.382a | 9.840±12.298 | 7.873±9.393 | 0.555a |
Conclusions: Tonic chin EMG density could be a potential marker for differentiating APS from PD among SPs.
To cite this abstract in AMA style:
Y. Wang, K.P. Xiong, Y. Shen, P.C. He, C.J. Mao, J. Li, J.Y. Huang, C.F. Liu. Could tonic chin electromyogram density be a potential marker for differentiating atypical Parkinsonian syndromes from Parkinson’s disease among alpha-synucleinopathies? [abstract]. Mov Disord. 2016; 31 (suppl 2). https://www.mdsabstracts.org/abstract/could-tonic-chin-electromyogram-density-be-a-potential-marker-for-differentiating-atypical-parkinsonian-syndromes-from-parkinsons-disease-among-alpha-synucleinopathies/. Accessed June 14, 2025.« Back to 2016 International Congress
MDS Abstracts - https://www.mdsabstracts.org/abstract/could-tonic-chin-electromyogram-density-be-a-potential-marker-for-differentiating-atypical-parkinsonian-syndromes-from-parkinsons-disease-among-alpha-synucleinopathies/