scholarly journals 1250 Agrypnia Excitata in a Patient with Paraneoplastic Autoimmune Encephalitis

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A476-A476
Author(s):  
J L Sanchez ◽  
S Saeed ◽  
H Battistini
Keyword(s):  
Eye Movement ◽  
Rem Sleep ◽  
Sleep Latency ◽  
Delirium Tremens ◽  
Sleep Onset ◽  
Autoimmune Encephalitis ◽  
Cystic Teratoma ◽  
Low Grade ◽  
Rapid Eye Movement ◽  
Stage 1

Abstract Introduction Agrypnia Excitata (AE) is a syndrome characterized by loss of sleep with permanent motor and autonomic hyper activation. This case describes this peculiar syndrome in a patient with paraneoplastic autoimmune encephalitis. Report of Case DG is a 35 yr old male with a history of anti-Ma2 limbic encephalitis secondary to cystic teratoma of the left testis diagnosed 6 months prior to presenting in Sleep Clinic. His parents described significant sleep disturbances including short sleep and wake periods throughout the day and night with no apparent pattern, acting out dreams, motor activity during sleep including pulling at his clothes or using his hands to manipulate invisible objects. Additionally they described low-grade fevers, and severe hyperphagia. Polysomnogram showed absence of slow-wave sleep and what appeared to be an admixture of stage 1 non-rapid eye movement (NREM) with rapid-eye movement (REM) sleep. Multiple sleep-latency testing (MSLT) demonstrated a mean sleep latency of 5.2 minutes and four sleep-onset REM periods (SOREMPs). Magnetic resonance imaging of the brain revealed persistent inflammation of the mesial temporal lobes and hippocampal region. Cerebral spinal fluid testing showed persistent anti-Ma2 antibodies. Based on this clinical presentation we made a diagnosis of Agrypnia Excitata. Conclusion Agrypnia Excitata is a syndrome characterized by loss of the normal sleep-wake rhythm. Sleep consists of the disappearance of spindle-delta activities, and persistent stage 1 NREM sleep mixed with recurrent episodes of REM sleep. The second hallmark of AE is persistent motor and autonomic hyperactivity observed during wake and sleep. AE has been described in three distinct clinical syndromes: Morvan Syndrome (autoimmune encephalitis), Fatal Familial Insomnia, and Delirium tremens. The pathogenesis of AE consists of intra-limbic disconnection releasing the hypothalamus and brainstem reticular formation from cortico-limbic inhibitory control. In autoimmune encephalitis, antibodies that act on voltage-gated potassium channels within the limbic system have been implicated in the pathophysiology.

Combining information on nocturnal rapid eye movement sleep latency and atonia to facilitate diagnosis of pediatric narcolepsy type 1

SLEEP ◽  
2020 ◽  
Author(s):  
Alessandro Silvani ◽  
Stefano Vandi ◽  
Fabio Pizza ◽  
Elena Antelmi ◽  
Raffaele Ferri ◽  
...  
Keyword(s):  
Children And Adolescents ◽  
Eye Movement ◽  
Rem Sleep ◽  
Pediatric Patients ◽  
Sleep Latency ◽  
Diagnostic Delay ◽  
Nonlinear Function ◽  
Identification Accuracy ◽  
Rapid Eye Movement

Abstract Study Objectives The diagnosis of narcolepsy type 1 (NT1) at its onset in children and adolescents is often difficult, with substantial diagnostic delay. We aimed to test and validate the effectiveness of rapid eye movement (REM) sleep latency (REML), the REM sleep atonia index (RAI), and their combination for the automatic identification of pediatric patients with NT1 based on the standard scoring of nocturnal polysomnograms. Methods A retrospective cohort of 71 pediatric patients with NT1 and 42 controls was subdivided in test and validation cohorts. A novel index (COM) was developed as a nonlinear function of REML and RAI. The effectiveness of REML, RAI, and COM in identifying patients with NT1 was assessed with receiver operating characteristic (ROC) curves. Results REML, RAI, and COM significantly identified patients with NT1 both in the test and validation cohorts. Optimal thresholds that maximized identification accuracy were estimated in the test cohort (REML, 49.5 min; RAI, 0.91; COM, 4.57 AU) and validated in the other cohort. COM performed significantly better in identifying patients with NT1 than either REML or RAI, with ROC area under the curve of 94%–100%, sensitivity 85%–96%, and specificity 92%–100%, and with good night-to-night agreement (Cohen’s k = 0.69). Conclusions The analysis of REML, RAI, and particularly their combination in the COM index may help shorten diagnostic delay of NT1 in children and adolescents based on the standard scoring of nocturnal polysomnography.

scholarly journals 0738 Advance Taper of Antidepressants Prior to Multiple Sleep Latency Testing Increases the Number of Sleep-Onset Rapid Eye Movement Periods and Reduces Mean Sleep Latency

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A281-A281
Author(s):  
B Kolla ◽  
M Jahani Kondori ◽  
M Silber ◽  
H Samman ◽  
S Dhankikar ◽  
...  
Keyword(s):  
Eye Movement ◽  
Sleep Latency ◽  
Sleep Onset ◽  
Initial Assessment ◽  
Rapid Eye Movement ◽  
Regression Analyses ◽  
Practice Parameters ◽  
The Impact ◽  
Multiple Sleep Latency ◽  
Multiple Sleep Latency Testing

Abstract Introduction Patients presenting with excessive sleepiness are frequently on antidepressant medication(s). While practice parameters recommend discontinuation of antidepressants prior to multiple sleep latency testing (MSLT), data examining the impact of tapering these medications on MSLT results are limited. Methods Adult patients who underwent MSLT at Mayo Clinic Rochester, Minnesota, between 2014-2018 were included. Clinical and demographic characteristics, medications, including use of rapid eye movement suppressing antidepressants (REMS-AD) at assessment and during testing, actigraphy and polysomnography data were manually abstracted. The difference in number of sleep-onset rapid eye movement periods (SOREMS), proportion with ≥2 SOREMS and mean sleep latency (MSL) in patients who were on REMS-AD and discontinued prior to testing versus those who remained on REMS-AD were examined. At our center, all antidepressants are discontinued 2 weeks prior to MSLT wherever feasible; fluoxetine is stopped 4 weeks prior. Regression analyses accounting for demographic, clinical and other medication-related confounders were performed. Results A total of 502 patients (age=38.18±15.90 years; 67% female) underwent MSLT; 178 (35%) were on REMS-AD at the time of assessment. REMS-AD were discontinued prior to testing in 121/178 (70%) patients. Patients tapered off REMS-AD were more likely to have ≥2 SOREMS (OR-12.20; 95%CI=1.60-92.94) compared to patients who remained on REMS-AD at the time of the MSLT. They also had shorter MSL (8.77±0.46 vs 10.21±0.28; p>0.009) and higher odds of having ≥2 SOREMS (OR=2.22; 95%CI=1.23-3.98) compared to patients not on REMS-AD at initial assessment. These differences persisted after regression analyses accounting for confounders. Conclusion Patients who taper off REMS-AD prior to MSLT are more likely to demonstrate ≥2SOREMs and have a shorter MSL. Pending further prospective investigations, clinicians should preferably withdraw REMs-AD before an MSLT. If this is not done, the test interpretation should include a statement regarding the potential effect of the drugs on the results. Support None

scholarly journals Vesicular GABA-transporter neurons in the zona incerta are maximally active during non rapid-eye movement (NREM) and rapid-eye movement (REM) sleep

2020 ◽  
Author(s):  
Carlos Blanco-Centurion ◽  
SiWei Luo ◽  
Aurelio Vidal-Ortiz ◽  
Priyattam J. Shiromani
Keyword(s):  
Eye Movement ◽  
Lateral Hypothalamus ◽  
Rem Sleep ◽  
Sleep Onset ◽  
Nrem Sleep ◽  
Zona Incerta ◽  
Imaging Method ◽  
Rapid Eye Movement ◽  
Gaba Transporter

AbstractSleep and wake are opposing behavioral states controlled by the activity of specific neurons. The neurons responsible for sleep/wake control have not been fully identifed due to the lack of in-vivo high throughput technology. We use the deep-brain calcium (Ca2+) imaging method to identify activity of hypothalamic neurons expressing the vesicular GABA transporter (vGAT), a marker of GABAergic neurons. vGAT-cre mice (n=5) were microinjected with rAAV-FLEX-GCaMP6M into the lateral hypothalamus and 21d later the Ca2+ influx in vGAT neurons (n=372) was recorded in freely-behaving mice during waking (W), NREM and REM sleep. Post-mortem analysis revealed the lens tip located in the zona incerta/lateral hypothalamus (ZI-LH) and the change in fluorescence of neurons in the field of view was as follows: 54.9% of the vGAT neurons had peak fluorescence during REM sleep (REM-max), 17.2% were NREM-max, 22.8% were wake-max while 5.1% were both wake+REM max. Thus, three quarters of the recorded vGAT neurons in the ZI-LH were most active during sleep. In the NREM-max group Ca2+ fluorescence anticipated the initiation of NREM sleep onset and remained high throughout sleep (NREM and REM sleep). In the REM-max neurons Ca2+fluorescence increased before the onset of REM sleep and stayed elevated during the episode. Activation of the vGAT NREM-max neurons in the zona incerta and dorsal lateral hypothalamus would inhibit the arousal neurons to initiate and maintain sleep.

Two cases of HLA‐DR2‐negative hypersomnia manifesting sleep‐onset rapid eye movement periods in the multiple sleep latency test

1999 ◽  
Vol 53 (2) ◽  
pp. 295-297
Author(s):  
Yasushi Yoshida ◽  
Kenji Kuroda ◽  
Masaharu Mandai ◽  
Seiji Satani ◽  
Narutsugu Emura ◽  
...  
Keyword(s):  
Eye Movement ◽  
Sleep Latency ◽  
Sleep Onset ◽  
Multiple Sleep Latency Test ◽  
Rapid Eye Movement ◽  
Multiple Sleep Latency

Sleep onset rapid-eye-movement episodes in narcolepsy: REM sleep pressure or nonREM-REM sleep dysregulation?

1992 ◽  
Vol 1 (4) ◽  
pp. 245-250 ◽  
Author(s):  
MEHDI TAFTI ◽  
ERIC VILLEMIN ◽  
BERTRAND CARLANDER ◽  
ALAIN BESSET ◽  
MICHEL BILLIARD
Keyword(s):  
Eye Movement ◽  
Rem Sleep ◽  
Sleep Onset ◽  
Rapid Eye Movement

scholarly journals Validation of Fitbit Charge 2 Sleep and Heart Rate Estimates Against Polysomnographic Measures in Shift Workers: Naturalistic Study (Preprint)

2020 ◽  
Author(s):  
Benjamin Stucky ◽  
Ian Clark ◽  
Yasmine Azza ◽  
Walter Karlen ◽  
Peter Achermann ◽  
...  
Keyword(s):  
Heart Rate ◽  
Eye Movement ◽  
Shift Work ◽  
Rem Sleep ◽  
Sleep Onset ◽  
Data Access ◽  
Sleep Stages ◽  
Rapid Eye Movement ◽  
Limits Of Agreement ◽  
Shift Workers

BACKGROUND Multisensor fitness trackers offer the ability to longitudinally estimate sleep quality in a home environment with the potential to outperform traditional actigraphy. To benefit from these new tools for objectively assessing sleep for clinical and research purposes, multisensor wearable devices require careful validation against the gold standard of sleep polysomnography (PSG). Naturalistic studies favor validation. OBJECTIVE This study aims to validate the Fitbit Charge 2 against portable home PSG in a shift-work population composed of 59 first responder police officers and paramedics undergoing shift work. METHODS A reliable comparison between the two measurements was ensured through the data-driven alignment of a PSG and Fitbit time series that was recorded at night. Epoch-by-epoch analyses and Bland-Altman plots were used to assess sensitivity, specificity, accuracy, the Matthews correlation coefficient, bias, and limits of agreement. RESULTS Sleep onset and offset, total sleep time, and the durations of rapid eye movement (REM) sleep and non–rapid-eye movement sleep stages N1+N2 and N3 displayed unbiased estimates with nonnegligible limits of agreement. In contrast, the proprietary Fitbit algorithm overestimated REM sleep latency by 29.4 minutes and wakefulness after sleep onset (WASO) by 37.1 minutes. Epoch-by-epoch analyses indicated better specificity than sensitivity, with higher accuracies for WASO (0.82) and REM sleep (0.86) than those for N1+N2 (0.55) and N3 (0.78) sleep. Fitbit heart rate (HR) displayed a small underestimation of 0.9 beats per minute (bpm) and a limited capability to capture sudden HR changes because of the lower time resolution compared to that of PSG. The underestimation was smaller in N2, N3, and REM sleep (0.6-0.7 bpm) than in N1 sleep (1.2 bpm) and wakefulness (1.9 bpm), indicating a state-specific bias. Finally, Fitbit suggested a distribution of all sleep episode durations that was different from that derived from PSG and showed nonbiological discontinuities, indicating the potential limitations of the staging algorithm. CONCLUSIONS We conclude that by following careful data processing processes, the Fitbit Charge 2 can provide reasonably accurate mean values of sleep and HR estimates in shift workers under naturalistic conditions. Nevertheless, the generally wide limits of agreement hamper the precision of quantifying individual sleep episodes. The value of this consumer-grade multisensor wearable in terms of tackling clinical and research questions could be enhanced with open-source algorithms, raw data access, and the ability to blind participants to their own sleep data.

scholarly journals Selectively driving cholinergic fibers optically in the thalamic reticular nucleus promotes sleep

eLife ◽  
2016 ◽  
Vol 5 ◽  
Author(s):  
Kun-Ming Ni ◽  
Xiao-Jun Hou ◽  
Ci-Hang Yang ◽  
Ping Dong ◽  
Yue Li ◽  
...  
Keyword(s):  
Eye Movement ◽  
Nicotinic Acetylcholine Receptors ◽  
Rem Sleep ◽  
Sleep Onset ◽  
Cholinergic Neurons ◽  
Nrem Sleep ◽  
Gabaergic Neurons ◽  
Thalamic Reticular Nucleus ◽  
Reticular Nucleus ◽  
Rapid Eye Movement

Cholinergic projections from the basal forebrain and brainstem are thought to play important roles in rapid eye movement (REM) sleep and arousal. Using transgenic mice in which channelrhdopsin-2 is selectively expressed in cholinergic neurons, we show that optical stimulation of cholinergic inputs to the thalamic reticular nucleus (TRN) activates local GABAergic neurons to promote sleep and protect non-rapid eye movement (NREM) sleep. It does not affect REM sleep. Instead, direct activation of cholinergic input to the TRN shortens the time to sleep onset and generates spindle oscillations that correlate with NREM sleep. It does so by evoking excitatory postsynaptic currents via α7-containing nicotinic acetylcholine receptors and inducing bursts of action potentials in local GABAergic neurons. These findings stand in sharp contrast to previous reports of cholinergic activity driving arousal. Our results provide new insight into the mechanisms controlling sleep.

scholarly journals Glutamatergic neurons in the preoptic hypothalamus promote wakefulness, destabilize NREM sleep, suppress REM sleep, and regulate cortical dynamics

2020 ◽  
Author(s):  
Alejandra Mondino ◽  
Viviane Hambrecht-Wiedbusch ◽  
Duan Li ◽  
A. Kane York ◽  
Dinesh Pal ◽  
...  
Keyword(s):  
Eye Movement ◽  
Rem Sleep ◽  
Preoptic Area ◽  
Sleep Onset ◽  
Nrem Sleep ◽  
State Transitions ◽  
Rapid Eye Movement ◽  
Cortical Dynamics ◽  
Glutamatergic Neurons ◽  
Conditional Expression

ABSTRACTClinical and experimental data from the last nine decades indicate that the preoptic area of the hypothalamus is a critical node in a brain network that controls sleep onset and homeostasis. By contrast, we recently reported that a group of glutamatergic neurons in the lateral and medial preoptic area increases wakefulness, challenging the long-standing notion in sleep neurobiology that the preoptic area is exclusively somnogenic. However, the precise role of these subcortical neurons in the control of behavioral state transitions and cortical dynamics remains unknown. Therefore, in this study we used conditional expression of excitatory hM3Dq receptors in these preoptic glutamatergic (Vglut2+) neurons and show that their activation initiates wakefulness, decreases non-rapid eye movement (NREM) sleep, and causes a persistent suppression of rapid eye movement (REM) sleep. Activation of preoptic glutamatergic neurons also causes a high degree of NREM sleep fragmentation, promotes state instability with frequent arousals from sleep, and shifts cortical dynamics (including oscillations, connectivity, and complexity) to a more wake-like state. We conclude that a subset of preoptic glutamatergic neurons may initiate -but not maintain- arousals from sleep, and their inactivation may be required for NREM stability and REM sleep generation. Further, these data provide novel empirical evidence supporting the conclusion that the preoptic area causally contributes to the regulation of both sleep and wakefulness.

Polysomnographic measures of sleep moderate the relationship between depression and pain

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 8526-8526 ◽  
Author(s):  
K. P. Parker ◽  
D. L. Bliwise ◽  
J. Dalton ◽  
W. Harris ◽  
S. Jain ◽  
...  
Keyword(s):  
Pain Intensity ◽  
Eye Movement ◽  
Rem Sleep ◽  
Sleep Latency ◽  
Sleep Cycle ◽  
Rapid Eye Movement ◽  
Nocturnal Sleep ◽  
Tumor Stages ◽  
The Mean ◽  
The Relationship

8526 Background: We explored the effects of polysomnographic measures of nocturnal sleep on depression and pain in advanced cancer patients taking opioids. Methods: The sample included 72 subjects (solid tumor, Stages III/IV) with a mean age of 55.9 (9.1); 39 were male. All were taking opioids. Subjects underwent ambulatory polysomnography for 48 hours in their homes. Nocturnal sleep parameters included total sleep time (minutes); sleep efficiency (SE; %); sleep latency (SL; minutes); rapid-eye-movement sleep latency (REML; minutes); the percentages (%) of non-rapid eye movement (NREM) Stages 1, 2, and slow wave sleep (SWS, 3 & 4), and REM sleep; and the number of awakenings > 60 seconds. Subjects kept an opioid diary, data from which were converted into a mean hourly morphine equivalent dose (HMED). Subjects also completed the Brief Pain Inventory (BPI) and the Beck Depression Inventory (BDI). Descriptive, correlation, and regression procedures were used for data analysis. Results: Subjects had a mean nocturnal sleep period of 400.1 ± 97.4 minutes. The SL was normal at 26.5 ± 42.6 minutes but the SE was low (77.5 ± 13.2%). Most sleep was light NREM Stages 1 and 2 with decreased amounts of deep SWS (0.3 ± 2.7%) and REM sleep (14.4 ± 8.5%). The REML was prolonged at 149.1 ± 105.1 minutes. The mean BPI scores for pain intensity and interference were 4.4 ± 1.4 and 5.0 ± 2.1, respectively. The mean BDI score was 13.7 ± 7.9. The average HMED was .59 ± .1. Controlling for age and gender, regression analyses revealed that SWS and REM sleep moderated the relationship between depression and pain. Those with more SWS had lower depression levels in spite of higher pain intensity (t = -2.8, p = .007) while those with more REM sleep had lower depression levels despite higher pain interference (t = -2.0, p = .045). Controlling for pain intensity and interference, HMED was positively associated with Stage 1 % (r = .36, p = .001) and the number of nocturnal awakenings > 60 seconds (r = .28, p = .019). Conclusions: Opioids may lighten and disrupt sleep altering sleep cycle progression. The resulting decrements in SWS and REM sleep may lead to increased depression and enhanced pain. Consideration of the timing and dosing of opioids in relationship to nocturnal sleep may decrease depression and subsequently optimize pain management. No significant financial relationships to disclose.

scholarly journals Validation of Fitbit Charge 2 Sleep and Heart Rate Estimates Against Polysomnographic Measures in Shift Workers: Naturalistic Study

10.2196/26476 ◽  
2021 ◽  
Vol 23 (10) ◽  
pp. e26476
Author(s):  
Benjamin Stucky ◽  
Ian Clark ◽  
Yasmine Azza ◽  
Walter Karlen ◽  
Peter Achermann ◽  
...  
Keyword(s):  
Heart Rate ◽  
Eye Movement ◽  
Shift Work ◽  
Rem Sleep ◽  
Sleep Onset ◽  
Data Access ◽  
Sleep Stages ◽  
Rapid Eye Movement ◽  
Limits Of Agreement ◽  
Shift Workers

Background Multisensor fitness trackers offer the ability to longitudinally estimate sleep quality in a home environment with the potential to outperform traditional actigraphy. To benefit from these new tools for objectively assessing sleep for clinical and research purposes, multisensor wearable devices require careful validation against the gold standard of sleep polysomnography (PSG). Naturalistic studies favor validation. Objective This study aims to validate the Fitbit Charge 2 against portable home PSG in a shift-work population composed of 59 first responder police officers and paramedics undergoing shift work. Methods A reliable comparison between the two measurements was ensured through the data-driven alignment of a PSG and Fitbit time series that was recorded at night. Epoch-by-epoch analyses and Bland-Altman plots were used to assess sensitivity, specificity, accuracy, the Matthews correlation coefficient, bias, and limits of agreement. Results Sleep onset and offset, total sleep time, and the durations of rapid eye movement (REM) sleep and non–rapid-eye movement sleep stages N1+N2 and N3 displayed unbiased estimates with nonnegligible limits of agreement. In contrast, the proprietary Fitbit algorithm overestimated REM sleep latency by 29.4 minutes and wakefulness after sleep onset (WASO) by 37.1 minutes. Epoch-by-epoch analyses indicated better specificity than sensitivity, with higher accuracies for WASO (0.82) and REM sleep (0.86) than those for N1+N2 (0.55) and N3 (0.78) sleep. Fitbit heart rate (HR) displayed a small underestimation of 0.9 beats per minute (bpm) and a limited capability to capture sudden HR changes because of the lower time resolution compared to that of PSG. The underestimation was smaller in N2, N3, and REM sleep (0.6-0.7 bpm) than in N1 sleep (1.2 bpm) and wakefulness (1.9 bpm), indicating a state-specific bias. Finally, Fitbit suggested a distribution of all sleep episode durations that was different from that derived from PSG and showed nonbiological discontinuities, indicating the potential limitations of the staging algorithm. Conclusions We conclude that by following careful data processing processes, the Fitbit Charge 2 can provide reasonably accurate mean values of sleep and HR estimates in shift workers under naturalistic conditions. Nevertheless, the generally wide limits of agreement hamper the precision of quantifying individual sleep episodes. The value of this consumer-grade multisensor wearable in terms of tackling clinical and research questions could be enhanced with open-source algorithms, raw data access, and the ability to blind participants to their own sleep data.

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