“…A detailed description of algorithms developed for auto-detection of NRH episodes and the association between abnormal NRH and Parkinsonian spectrum disorder subgroups were previously described. 16 Briefly, the automated detection of NRH utilized variability thresholds applied to each 30-second epoch to ensure EMG bursts attributed to sleep disordered breathing arousals were not mischaracterized as NRH. A NRH block required four of six contiguous epochs to have satisfied the threshold criteria.…”
Section: Methodsmentioning
confidence: 99%
“…Abnormal NRH was based on the empirically derived threshold > 5% of sleep time. 16 Figure 2 ( a ) A 1-hour epoch presenting the Chin EMG, LEOG, REOG and EEG signals, with the relative EEG power spectral distributions for alpha (pink), sigma (green), beta (brown) and EMG (black). The increase in relative EMG power corresponds with two reassigned to stage NRH.…”
Section: Methodsmentioning
confidence: 99%
“… 13 , 14 In patients with suspected neurodegenerative disorders, the staging of sleep can be especially challenging due to elevated muscle activity and reduced spindle activity, which makes accurate stage distinction difficult. 15 , 16 Additionally, scoring of RSWA requires specialized training and is laborious and time intensive. 17 , 18 To date, estimates of the prevalence and clinical significance of iRBD have been limited by the difficulty and cost of screening larger community samples with PSG.…”
Section: Introductionmentioning
confidence: 99%
“…We also explored the diagnostic concordance between iRBD and non-REM hypertonia (NRH) a SP biomarker found to be significantly associated with Parkinsonian spectrum neurodegenerative disorders independent of age, sex and antidepressant medications. 16 NRH was discovered in the frontal electroencephalography signal during what visually appeared to be stage N2 or N3 sleep, but with periodic, persistently elevated EMG power relative to delta, theta, and sigma bands.…”
Purpose
This study aimed to establish the diagnostic accuracy of a previously validated sleep staging system in patients with probable isolated REM sleep behavior disorder (iRBD), and to compare physicians’ diagnoses of iRBD based on REM sleep without atonia (RSWA) to non-REM hypertonia (NRH), a sleep measure independently associated with Parkinsonian spectrum disorders.
Patients and Methods
Twenty-six patients with a history of dream enactment behavior underwent a diagnostic PSG with simultaneous Sleep Profiler (SP) acquisition at two sites. PSG and SP records were sleep staged, and two sleep neurologists independently diagnosed iRBD based on the presence or absence of polysomnographic identified RSWA. Comparisons for PSG vs SP sleep staging and the qualitative presence or absence of PSG-based RSWA vs automated SP-detected NRH was performed using kappa coefficients (
k
), positive and negative percent agreements (PPA and NPA), and chi-square tests.
Results
The kappa scores from Sites-1 and −2 for PSG vs SP staging were different for Wake (
k
=0.82 vs 0.65), N2 (
k
=0.63 vs 0.72) and REM (
k
=0.83 vs.0.72). The by-site kappa values for stage N3 increased from 0.72 and 0.37 to 0.88 and 0.74 after PSG records were reedited. The kappa values for between-physician agreement in iRBD diagnoses were fair (k = 0.22). The agreement between each physician’s iRBD diagnoses and NRH were also fair (
k
=0.29 and 0.22). Abnormal NRH agreed with at least one physician’s iRBD diagnosis in 83% of the records. The PPA resulting from between-physician iRBD agreement was stronger and the NPA weaker than the values obtained from comparison of each physician’s iRBD diagnosis and abnormal NRH.
Conclusion
The potential utility of RSWA and stage N3 as neurodegenerative disorder biomarkers was influenced by between-site variability in visual scoring. The degree to which NRH was associated with iRBD was similar to the between-physician agreement in their diagnosis of iRBD using RSWA.
“…A detailed description of algorithms developed for auto-detection of NRH episodes and the association between abnormal NRH and Parkinsonian spectrum disorder subgroups were previously described. 16 Briefly, the automated detection of NRH utilized variability thresholds applied to each 30-second epoch to ensure EMG bursts attributed to sleep disordered breathing arousals were not mischaracterized as NRH. A NRH block required four of six contiguous epochs to have satisfied the threshold criteria.…”
Section: Methodsmentioning
confidence: 99%
“…Abnormal NRH was based on the empirically derived threshold > 5% of sleep time. 16 Figure 2 ( a ) A 1-hour epoch presenting the Chin EMG, LEOG, REOG and EEG signals, with the relative EEG power spectral distributions for alpha (pink), sigma (green), beta (brown) and EMG (black). The increase in relative EMG power corresponds with two reassigned to stage NRH.…”
Section: Methodsmentioning
confidence: 99%
“… 13 , 14 In patients with suspected neurodegenerative disorders, the staging of sleep can be especially challenging due to elevated muscle activity and reduced spindle activity, which makes accurate stage distinction difficult. 15 , 16 Additionally, scoring of RSWA requires specialized training and is laborious and time intensive. 17 , 18 To date, estimates of the prevalence and clinical significance of iRBD have been limited by the difficulty and cost of screening larger community samples with PSG.…”
Section: Introductionmentioning
confidence: 99%
“…We also explored the diagnostic concordance between iRBD and non-REM hypertonia (NRH) a SP biomarker found to be significantly associated with Parkinsonian spectrum neurodegenerative disorders independent of age, sex and antidepressant medications. 16 NRH was discovered in the frontal electroencephalography signal during what visually appeared to be stage N2 or N3 sleep, but with periodic, persistently elevated EMG power relative to delta, theta, and sigma bands.…”
Purpose
This study aimed to establish the diagnostic accuracy of a previously validated sleep staging system in patients with probable isolated REM sleep behavior disorder (iRBD), and to compare physicians’ diagnoses of iRBD based on REM sleep without atonia (RSWA) to non-REM hypertonia (NRH), a sleep measure independently associated with Parkinsonian spectrum disorders.
Patients and Methods
Twenty-six patients with a history of dream enactment behavior underwent a diagnostic PSG with simultaneous Sleep Profiler (SP) acquisition at two sites. PSG and SP records were sleep staged, and two sleep neurologists independently diagnosed iRBD based on the presence or absence of polysomnographic identified RSWA. Comparisons for PSG vs SP sleep staging and the qualitative presence or absence of PSG-based RSWA vs automated SP-detected NRH was performed using kappa coefficients (
k
), positive and negative percent agreements (PPA and NPA), and chi-square tests.
Results
The kappa scores from Sites-1 and −2 for PSG vs SP staging were different for Wake (
k
=0.82 vs 0.65), N2 (
k
=0.63 vs 0.72) and REM (
k
=0.83 vs.0.72). The by-site kappa values for stage N3 increased from 0.72 and 0.37 to 0.88 and 0.74 after PSG records were reedited. The kappa values for between-physician agreement in iRBD diagnoses were fair (k = 0.22). The agreement between each physician’s iRBD diagnoses and NRH were also fair (
k
=0.29 and 0.22). Abnormal NRH agreed with at least one physician’s iRBD diagnosis in 83% of the records. The PPA resulting from between-physician iRBD agreement was stronger and the NPA weaker than the values obtained from comparison of each physician’s iRBD diagnosis and abnormal NRH.
Conclusion
The potential utility of RSWA and stage N3 as neurodegenerative disorder biomarkers was influenced by between-site variability in visual scoring. The degree to which NRH was associated with iRBD was similar to the between-physician agreement in their diagnosis of iRBD using RSWA.
“…Focusing on specific aspects of sleep disorders in dementia has allowed researchers to identify specific sleep disturbances associated with these conditions. For example, researchers have found that non‐REM sleep with hypertonia may serve as a diagnostic biomarker for Lewy body dementia and Parkinson's disease with dementia (Levendowski et al, 2022). Sleep deprivation and sleep disturbances have also been associated with Parkinson's disease, with more than 60% of patients experiencing sleep issues (Louter et al, 2012; Maggi et al, 2023).…”
In countries around the world, sleep deprivation represents a widespread problem affecting school‐age children, teenagers, and adults. Acute sleep deprivation and more chronic sleep restriction adversely affect individual health, impairing memory and cognitive performance as well as increasing the risk and progression of numerous diseases. In mammals, the hippocampus and hippocampus‐dependent memory are vulnerable to the effects of acute sleep deprivation. Sleep deprivation induces changes in molecular signaling, gene expression and may cause changes in dendritic structure in neurons. Genome wide studies have shown that acute sleep deprivation alters gene transcription, although the pool of genes affected varies between brain regions. More recently, advances in research have drawn attention to differences in gene regulation between the level of the transcriptome compared with the pool of mRNA associated with ribosomes for protein translation following sleep deprivation. Thus, in addition to transcriptional changes, sleep deprivation also affects downstream processes to alter protein translation. In this review, we focus on the multiple levels through which acute sleep deprivation impacts gene regulation, highlighting potential post‐transcriptional and translational processes that may be affected by sleep deprivation. Understanding the multiple levels of gene regulation impacted by sleep deprivation is essential for future development of therapeutics that may mitigate the effects of sleep loss.
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