scholarly journals Choice, Expectations, and the Placebo Effect for Sleep Difficulty

2019 ◽  
Author(s):  
Valerie Yeung ◽  
Louise Sharpe ◽  
Andrew Geers ◽  
Ben Colagiuri
Keyword(s):  
Placebo Effect ◽  
Sleep Onset ◽  
Sleep Time ◽  
Placebo Treatment ◽  
Sleep Onset Latency ◽  
Placebo Effects ◽  
Single Session ◽  
Sleep Difficulty ◽  
Insomnia Severity ◽  
Perceived Sleep Quality

Abstract Background Choice has been found to facilitate placebo effects for single-session treatments where standard placebo treatment without choice failed to elicit a placebo effect. However, it is unknown whether choice can enhance the placebo effect for treatments occurring over a period of days and where placebo effects are readily established without choice. Purpose We tested whether single or daily choice between two (placebo) treatments enhanced the placebo effect for sleep difficulty relative to no choice and no treatment over a 1 week period. Methods One-hundred and seventeen volunteers self-identifying with sleep difficulty were recruited under the guise of a hypnotic trial and randomized to one of the four groups. Self-reported outcomes included insomnia severity, fatigue, total sleep time (TST), sleep onset latency (SOL), perceived sleep quality (PSQ), and treatment satisfaction. Objective TST and SOL were assessed in a subsample via actigraphy. Results Overall, placebo treatment significantly improved insomnia severity, fatigue, and PSQ, confirming a placebo effect on these outcomes. However, both traditional and Bayesian analysis indicated no benefit of choice on the placebo effect on any sleep outcome. Mediation analysis of the overall placebo effect indicated that expectancy completely mediated the placebo effects for insomnia severity and PSQ and partially mediated the placebo effect for fatigue. Conclusion These findings suggest that choice does not enhance the placebo effect over longer treatment periods (up to 7 days) when placebo effects are readily established without choice. As such, any benefit of choice on placebo effects may be confined to quite specific circumstances. Clinical Trials Registration ACTRN12618001199202.

Choice and the Placebo Effect: A Meta-analysis

2022 ◽  
Author(s):  
Biya Tang ◽  
Kirsten Barnes ◽  
Andrew Geers ◽  
Evan Livesey ◽  
Ben Colagiuri
Keyword(s):  
Placebo Effect ◽  
Effect Size ◽  
Meta Analysis ◽  
Placebo Treatment ◽  
Placebo Effects ◽  
Sleep Difficulty ◽  
Clinical Scenarios ◽  
Health Related ◽  
Choice Frequency ◽  
Improve Patient

Abstract Background Choice has been proposed as a method of enhancing placebo effects. However, there have been no attempts to systematically evaluate the magnitude, reliability, and moderators of the influence of choice on the placebo effect. Purpose To estimate the effect size of choice on the placebo effect and identify any moderators of this effect. Methods Web of Science, PsycINFO, EMBASE, and PubMed were systematically searched from inception to May 2021 for studies comparing placebo treatment with any form of choice over its administration (e.g., type, timing) to placebo treatment without choice, on any health-related outcome. Random-effects meta-analysis was then used to estimate the effect size associated with the influence of choice on the placebo effect. Meta-regression was subsequently employed to determine the moderating effect of factors such as type of choice, frequency of choice, and size of the placebo effect without choice. Results Fifteen independent studies (N = 1,506) assessing a range of conditions, including pain, discomfort, sleep difficulty, and anxiety, met inclusion criteria. Meta-analysis revealed that choice did significantly enhance the placebo effect (Hedges’ g = 0.298). Size of the placebo effect without choice was the only reliable moderator of this effect, whereby a greater effect of choice was associated with smaller placebo effects without choice. Conclusions Treatment choice can effectively facilitate the placebo effect, but this effect appears more pronounced in contexts where the placebo effect without choice is weaker. Because most evidence to date is experimental, translational studies are needed to test whether providing choice in clinical scenarios where placebo effects are weaker may help boost the placebo effect and thereby improve patient outcomes.

scholarly journals The effect of sleep-wake intraindividial variability in digital cognitive behaviour therapy for insomnia: A mediation analysis of a large-scale RCT

SLEEP ◽  
2021 ◽  
Author(s):  
Cecilie L Vestergaard ◽  
Øystein Vedaa ◽  
Melanie R Simpson ◽  
Patrick Faaland ◽  
Daniel Vethe ◽  
...  
Keyword(s):  
Psychological Distress ◽  
Large Scale ◽  
Controlled Trial ◽  
Sleep Onset ◽  
Depression Scale ◽  
Mediating Effect ◽  
Sleep Onset Latency ◽  
Composite Measures ◽  
Cognitive Behaviour ◽  
Insomnia Severity

Abstract Study Objectives Digital Cognitive Behavioural Therapy for Insomnia (dCBT-I) is an effective treatment for insomnia. However, less is known about mediators of its benefits. The aim of the present study was to test if intraindividual variability in sleep (IIV) was reduced with dCBT-I, and whether any identified reduction was a mediator of dCBT-I on insomnia severity and psychological distress. Methods In a two-arm randomized controlled trial (RCT), 1720 adults with insomnia (dCBT-I = 867; patient education about sleep = 853) completed the Insomnia Severity Index (ISI), the Hospital Anxiety and Depression Scale (HADS) and sleep diaries, at baseline and 9-week follow-up. Changes in IIV were analysed using linear mixed modelling followed by mediation analyses of ISI, HADS, and IIV in singular sleep metrics and composite measures (Behavioural Indices (BI-Z) and Sleep-disturbance Indices (SI-Z)). Results dCBT-I was associated with reduced IIV across all singular sleep metrics, with the largest between-group effect sizes observed for sleep onset latency (SOL). Reduced IIV for SOL and wake after sleep onset had the overall greatest singular mediating effect. For composite measures, SI-Z mediated change in ISI (b = -0.74; 95% Confidence Interval (CI) -1.04 to -0.52; 13.3%) and HADS (b = -0.40; 95% CI -0.73 to -0.18; 29.2%), whilst BI-Z mediated minor changes. Conclusion Reductions in IIV in key sleep metrics mediate significant changes in insomnia severity and especially psychological distress when using dCBT-I. These findings offer important evidence regarding the therapeutic action of dCBT-I and may guide the future development of this intervention.

The effect of 4-h versus 6-h time restricted feeding on sleep quality, duration, insomnia severity and obstructive sleep apnea in adults with obesity

2021 ◽  
pp. 026010602110023
Author(s):  
Sofia Cienfuegos ◽  
Kelsey Gabel ◽  
Faiza Kalam ◽  
Mark Ezpeleta ◽  
Vicky Pavlou ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Sleep Quality ◽  
Sleep Onset ◽  
Control Group ◽  
Sleep Onset Latency ◽  
Restricted Feeding ◽  
Wake Time ◽  
Obstructive Sleep ◽  
Insomnia Severity

Background: Time restricted feeding (TRF) involves deliberately restricting the times during which energy is ingested. Preliminary findings suggest that 8–10-h TRF improves sleep. However, the effects of shorter TRF windows (4–6 h) on sleep, remain unknown. Aims: This study compared the effects of 4-h versus 6-h TRF on sleep quality, duration, insomnia severity and the risk of obstructive sleep apnea. Methods: Adults with obesity ( n = 49) were randomized into one of three groups: 4-h TRF (eating only between 3 and 7 p.m.), 6-h TRF (eating only between 1 and 7 p.m.), or a control group (no meal timing restrictions) for 8 weeks. Results: After 8 weeks, body weight decreased ( p < 0.001) similarly by 4-h TRF (–3.9 ± 0.4 kg) and 6-h TRF (–3.4 ± 0.4 kg), versus controls. Sleep quality, measured by the Pittsburgh Sleep Quality Index (PSQI), did not change by 4-h TRF (baseline: 5.9 ± 0.7; week 8: 4.8 ± 0.6) or 6-h TRF (baseline: 6.4 ± 0.8; week 8: 5.3 ± 0.9), versus controls. Wake time, bedtime, sleep duration and sleep onset latency also remained unchanged. Insomnia severity did not change by 4-h TRF (baseline: 4.4 ± 1.0; week 8: 4.7 ± 0.9) or 6-h TRF (baseline: 8.3 ± 1.2; week 8: 5.5 ± 1.1), versus controls. Percent of participants reporting obstructive sleep apnea symptoms did not change by 4-h TRF (baseline: 44%; week 8: 25%) or 6-h TRF (baseline: 47%; week 8: 20%), versus controls. Conclusion: These findings suggest that 4- and 6-h TRF have no effect on sleep quality, duration, insomnia severity, or the risk of obstructive sleep apnea.

scholarly journals 0004 TS-142: A Novel and Potent Dual Orexin Receptor Antagonist with Sleep-Promoting Effects in Rats

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A2-A2
Author(s):  
D Kambe ◽  
H Hikichi ◽  
Y Tokumaru ◽  
M Ohmichi ◽  
Y Konno ◽  
...  
Keyword(s):  
Receptor Antagonist ◽  
Half Life ◽  
Sleep Onset ◽  
Sleep Time ◽  
Sleep Onset Latency ◽  
Orexin A ◽  
Pharmacokinetic Profiles ◽  
Orexin Receptors ◽  
Elimination Half ◽  
Emg Electrodes

Abstract Introduction The orexin system plays a pivotal role in regulating sleep and wakefulness, thus, orexin receptors (OX1 and OX2 receptors) have gained much attention as promising therapeutic targets for the treatment of insomnia. We synthesized a novel and potent dual orexin receptor antagonist (DORA), ORN0829 (investigation code name as TS-142), which was designed to have short-acting effects. Here we report pharmacological and pharmacokinetic profiles of ORN0829 in rats. Methods The antagonistic activities of ORN0829 were assessed using calcium mobilization assays. Ala-orexin A-induced [Ca2+]i response was measured with CHO-K1 cells stably expressing human/rat orexin receptor. Rats implanted the EEG/EMG electrodes were orally administrated ORN0829 at doses of 1, 3 or 10 mg/kg at the dark onset and sleep-wake stages were inspected visually. In addition, pharmacokinetic profiles of ORN0829 were investigated in rats. Results ORN0829 inhibited Ala-orexin A-increased [Ca2+]i response with a Kb of 0.67/0.44 nmol/L (for human/rat OX1 receptor), and with a Kb of 0.84/0.80 nmol/L (for human/rat OX2 receptor), respectively, indicating that ORN0829 is a potent DORA with no species differences. ORN0829 dose-dependently increased total sleep time and reduced sleep onset latency at doses of 1, 3 and 10 mg/kg. Importantly, the ORN0829 levels in plasma and cerebrospinal fluid rapidly reached a maximum concentration, and decreased with an elimination half-life of less than 1 h. Conclusion The present study indicates that ORN0829 is a novel and potent DORA with sleep-promoting effects, and that it exhibits ideal pharmacokinetic profiles (rapid absorption and short half-life) in rats. A phase 2a study of TS-142 using patients with insomnia has been completed, which is presented in a separate poster. Support Taisho Pharmaceutical. Co., Ltd.

scholarly journals 1253 Multiple sleep onset REM episodes in middle age woman with excessive daytime sleepiness – Is this automatically assumed narcolepsy?

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A477-A477
Author(s):  
Kamal Patel ◽  
Bianca J Lang
Keyword(s):  
Daytime Sleepiness ◽  
Sleep Latency ◽  
Sleep Onset ◽  
Sleep Time ◽  
Multiple Sleep Latency Test ◽  
Sleep Onset Latency ◽  
Onset Latency ◽  
Obstructive Sleep ◽  
Falling Asleep ◽  
Multiple Sleep Latency

Abstract Introduction Presence of sleep onset REM episodes often raises concerns of narcolepsy. However other conditions have shown to have presence of sleep on REM episodes which include but not limited to obstructive sleep apnea, sleep wake schedule disturbance, alcoholism, neurodegenerative disorders, depression and anxiety Report of Case Here we present a case of 30 year old female with history of asthma, patent foraman ovale, migraine headache, and anxiety who presented with daytime sleepiness, falling asleep while at work, occasional scheduled naps, non-restorative sleep, sleep paralysis, and hypnopompic hallucination. Pertinent physical exam included; mallampati score of 4/4, retrognathia, high arched hard palate, crowded posterior oropharynx. She had a score of 16 on Epworth sleepiness scale. Patient previously had multiple sleep latency test at outside facility which revealed 4/5 SOREM, with mean sleep onset latency of 11.5 minutes. She however was diagnosed with narcolepsy and tried on modafinil which she failed to tolerate. She was tried on sertraline as well which was discontinued due to lack of benefit. She had repeat multiple sleep latency test work up which revealed 2/5 SOREM, with mean sleep onset latency was 13.1 minutes. Her overnight polysomnogram prior to repeat MSLT showed SOREM with sleep onset latency of 10 minutes. Actigraphy showed consistent sleep pattern overall with sufficient sleep time but was taking hydroxyzine and herbal medication. Patient did not meet criteria for hypersomnolence disorder and sleep disordered breathing. Conclusion There is possibility her medication may have played pivotal role with her daytime symptoms. We also emphasize SOREMs can be present in other disorders such as anxiety in this case and not solely in narcolepsy

scholarly journals The Cycle of Daily Stress and Sleep: Sleep Measurement Matters

2020 ◽  
Author(s):  
Danica C Slavish ◽  
Justin Asbee ◽  
Kirti Veeramachaneni ◽  
Brett A Messman ◽  
Bella Scott ◽  
...  
Keyword(s):  
Sleep Disturbances ◽  
Multilevel Models ◽  
Single Channel ◽  
Sleep Onset ◽  
Sleep Time ◽  
Sleep Diary ◽  
Sleep Onset Latency ◽  
Daily Stress ◽  
Sleep Diaries ◽  
Sleep Measurement

Abstract Background Disturbed sleep can be a cause and a consequence of elevated stress. Yet intensive longitudinal studies have revealed that sleep assessed via diaries and actigraphy is inconsistently associated with daily stress. Purpose We expanded this research by examining daily associations between sleep and stress using a threefold approach to assess sleep: sleep diaries, actigraphy, and ambulatory single-channel electroencephalography (EEG). Methods Participants were 80 adults (mean age = 32.65 years, 63% female) who completed 7 days of stressor and sleep assessments. Multilevel models were used to examine bidirectional associations between occurrence and severity of daily stress with diary-, actigraphy-, and EEG-determined sleep parameters (e.g., total sleep time [TST], sleep efficiency, and sleep onset latency, and wake after sleep onset [WASO]). Results Participants reported at least one stressor 37% of days. Days with a stressor were associated with a 14.4-min reduction in actigraphy-determined TST (β = −0.24, p = 0.030), but not with other actigraphy, diary, or EEG sleep measures. Nights with greater sleep diary-determined WASO were associated with greater next-day stressor severity (β = 0.01, p = 0.026); no other diary, actigraphy, or EEG sleep measures were associated with next-day stressor occurrence or severity. Conclusions Daily stress and sleep disturbances occurred in a bidirectional fashion, though specific results varied by sleep measurement technique and sleep parameter. Together, our results highlight that the type of sleep measurement matters for examining associations with daily stress. We urge future researchers to treat sleep diaries, actigraphy, and EEG as complementary—not redundant—sleep measurement approaches.

507 Clinical Impression of Excessive Daytime Sleepiness (EDS) at initial Sleep Medicine (SM) consultation and its clinical correlates

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A199-A200
Author(s):  
Leon Rosenthal ◽  
Raúl Aguilar Roblero
Keyword(s):  
Lower Energy ◽  
Energy Levels ◽  
Sleep Onset ◽  
Sleep Time ◽  
Clinical Impression ◽  
Sleep Onset Latency ◽  
Convenience Sample ◽  
Time In Bed ◽  
Number Of Patients ◽  
Cardinal Symptom

Abstract Introduction EDS represents a cardinal symptom in SM. Use of subjective scales are prevalent, which have a modest correlation with the MSLT. While the Clinical Global Impression has been used in research, reports of clinical impression (CI) in medical practice are lacking. We report on the CI of EDS in a convenience sample of patients undergoing initial consultation. Methods Patients reported primary, secondary symptoms and completed the Sleep Wake Activity Inventory (SWAI) prior to Tele-Medicine consultation. A SM physician completed the assessment which included ascertainment of CI of EDS (presence S+ / absence S-). Results There were 39 ♂and 13 ♀. The CI identified 26 patients in each group (S+/S-). Age (52 [14]), BMI (33 [7]), reported time in bed, sleep time, sleep onset latency and # of awakenings did not differ. All identified a primary symptom (S-: 21, S+: 19 reported snoring or a previous Dx of OSA). Sleepiness as a 1ry or 2ry symptom was identified by 0 in the S- and by 13 in the S+ groups. Refreshing quality of sleep differed (χ2 &lt;0.05): un-refreshing sleep was reported by 7 (S-) and by 13 (S+). Naps/week: 0.7 [1.5] and 1.57 [1.5] for the S-, S+ groups respectively (p&lt;0.05). A main effect (p&lt;0.01) was documented on the SWAI. We report on the Sleepiness [SS] and Energy Level [EL] scales (lower scores on the SS reflect higher sleepiness while lower scores on EL denote higher energy). Higher sleepiness (p&lt;0.01) 43 [12] and lower energy levels 24 [6] (p&lt;0.05) were documented on the S+ group (S- 61 [17], and 18 [6] respectively). Available spouse’s Epworth score on 29 patients: S- patients 5.8 [4] and S+ 10.2 [6] (p&lt;0.05). Dx of OSA was identified among all but 1 in the S+ group. Also, Insomnia was diagnosed among 11 (S-) and 19 (S+) patients (p&lt;0.05) despite only 3 and 7 (respectively) identifying it as a presenting symptom. Conclusion While snoring or previous Dx of OSA were prevalent motivations for consultation, sleepiness and insomnia were clinically relevant among a substantial number of patients. Unrefreshing sleep, daytime naps, lower energy, and higher sleepiness were ubiquitous among S+ patients. Support (if any):

scholarly journals O043 “My Fitbit tells me I don’t sleep” – Validation of a consumer-wearable device (Fitbit Charge 3TM) using gold standard in-laboratory polysomnography to assess sleep in adults presenting for medical evaluation in a sleep laboratory

2021 ◽  
Vol 2 (Supplement_1) ◽  
pp. A19-A19
Author(s):  
M Munsif ◽  
R Jumabhoy ◽  
K Rangamuwa ◽  
D Mansfield ◽  
S Drummond ◽  
...  
Keyword(s):  
Sleep Disorders ◽  
Sleep Onset ◽  
Sleep Time ◽  
Sleep Onset Latency ◽  
Medical Evaluation ◽  
Insomnia Disorder ◽  
Epoch Analysis ◽  
A Prospective Study ◽  
Screening Device ◽  
Wake State

Abstract Background There has been a rapid growth in wearable devices marketed for sleep. Trackers such as the Fitbit collect data through an accelerometer and use heart rate variability to estimate the sleep-wake state. Currently, Fitbit validation studies have only been with “healthy” adults and Insomnia Disorder. Aims The purpose of this study is to evaluate the accuracy of Fitbit Charge3TM compared to in-lab polysomnography (PSG) in patients with sleep disorders. Our hypothesis is that Fitbit Charge 3TM will perform with less sensitivity and specificity relative to PSG in the presence of sleep disorders. Methods A prospective study of patients attending a PSG through Epworth Camberwell Sleep Lab between 2019–2021 will be conducted. Fitbit Charge3TM will be worn on the wrist with concurrent PSG monitoring. Parameters measured with both PSG and Fitbit Charge3TM will include total sleep time, Sleep onset latency, wake after sleep onset and time spent in N1, N2, N3 and REM sleep (min). Standard PSG data will be evaluated to diagnose sleep-disordered breathing. Progress to date:Ethics approval has been obtained, and 110 participants have been recruited. 30-second epoch-by-epoch analysis will now be conducted. Bland-Altman analyses will be performed to assess agreement between the Fitbit and PSG. Intended outcome and impact: Our novel study findings will provide evidence to address queries regarding the accuracy of the Fitbit trackers to evaluate sleep and may support the use of Fitbit Charge3TM as an initial screening device to assess sleep duration and sleep architecture in select patients.

scholarly journals P062 Sleep parameter validation of a home-based ballistocardiograph sleep tracker

2021 ◽  
Vol 2 (Supplement_1) ◽  
pp. A41-A42
Author(s):  
M Kholghi ◽  
I Szollosi ◽  
M Hollamby ◽  
D Bradford ◽  
Q Zhang
Keyword(s):  
Total Sleep Time ◽  
Sleep Onset ◽  
Sleep Time ◽  
Daily Routine ◽  
Sleep Onset Latency ◽  
Onset Latency ◽  
Sleep Monitoring ◽  
Significant Discrepancy ◽  
Home Based ◽  
Wake Detection

Abstract Introduction Consumer home sleep trackers are gaining popularity for objective sleep monitoring. Amongst them, non-wearable devices have little disruption in daily routine and need little maintenance. However, the validity of their sleep outcomes needs further investigation. In this study, the accuracy of the sleep outcomes of EMFIT Quantified Sleep (QS), an unobtrusive and non-wearable ballistocardiograph sleep tracker, was evaluated by comparing it with polysomnography (PSG). Methods 62 sleep lab patients underwent a single clinical PSG and their sleep measures were simultaneously collected through PSG and EMFIT QS. Total Sleep Time (TST), Wake After Sleep Onset (WASO), Sleep Onset Latency (SOL) and average Heart Rate (HR) were compared using paired t-tests and agreement analysed using Bland-Altman plots. Results EMFIT QS data loss occurred in 47% of participants. In the remaining 33 participants (15 females, with mean age of 53.7±16.5), EMFIT QS overestimated TST by 177.5±119.4 minutes (p&lt;0.001) and underestimated WASO by 44.74±68.81 minutes (p&lt;0.001). It accurately measured average resting HR and was able to distinguish SOL with some accuracy. However, the agreement between EMFIT QS and PSG on sleep-wake detection was very low (kappa=0.13, p&lt;0.001). Discussion A consensus between PSG and EMFIT QS was found in SOL and average HR. There was a significant discrepancy and lack of consensus between the two devices in other sleep outcomes. These findings indicate that while EMFIT QS is not a credible alternative to PSG for sleep monitoring in clinical and research settings, consumers may find some benefit from longitudinal monitoring of SOL and HR.

scholarly journals O020 What helped you and what prevented you from getting good sleep? Contribution of daily facilitators and barriers to adolescent sleep

2021 ◽  
Vol 2 (Supplement_1) ◽  
pp. A9-A10
Author(s):  
S Maskevich ◽  
L Shen ◽  
J Wiley ◽  
S Drummond ◽  
B Bei
Keyword(s):  
Everyday Life ◽  
Sleep Onset ◽  
Sleep Time ◽  
Sleep Onset Latency ◽  
Onset Latency ◽  
Previous Night ◽  
Quality Sleep ◽  
Sleep Environment ◽  
Facilitators And Barriers ◽  
Good Sleep

Abstract Introduction This intense longitudinal study examined factors that facilitate and hinder sufficient and good quality sleep in adolescents’ everyday life. Methods 205 (54.2% female, 64.4% non-white) Year 10–12 adolescents (Mage = 16.9 ± 0.9) completed daily morning surveys and wore actigraphy over 2 school-weeks and 2 subsequent vacation-weeks. Morning surveys assessed self-reported sleep and the usage of 8 facilitators and 6 barriers of sleep from the previous night. Linear mixed-effects models examined contribution of facilitators/barriers to actigraphy and self-reported total sleep time (TST) and sleep onset latency (SOL), controlled for age, sex, race, place of birth, and study day. Schooldays/non-schooldays was included as a moderator. Results Seven facilitators and two barriers were endorsed by high proportions (&gt;30%) of adolescents as frequently (≥50% days) helping/preventing them from achieving good sleep. Facilitators predicting longer TST and shorter SOL, were: “follow body cues”, “manage thoughts and emotions”, “create good sleep environment”, “avoid activities interfering with sleep” and “plan bedtime and go to bed as planned” (only TST on schooldays). Barriers predicting shorter TST and longer SOL, were: “pre-bedtime thoughts and emotions”, “unconducive sleep environment”, “activities interfering with sleep”, “inconsistent routines” and “other household members’ activities”. Overall, facilitators or barriers explained an additional 1–5% (p-values &lt; .001) of variance beyond the covariates. Discussion Adolescents perceive a range of factors as facilitating and as preventing sufficient and good quality sleep in everyday life. These factors are predictive of their sleep duration and onset latency, and need further research to understand their functions and clinical implications.

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