Headache and sleep: Shared pathophysiological mechanisms

Objective The objective of the current article is to review the shared pathophysiological mechanisms which may underlie the clinical association between headaches and sleep disorders. Background The association between sleep and headache is well documented in terms of clinical phenotypes. Disrupted sleep-wake patterns appear to predispose individuals to headache attacks and increase the risk of chronification, while sleep is one of the longest established abortive strategies. In agreement, narcoleptic patients show an increased prevalence of migraine compared to the general population and specific familial sleep disorders have been identified to be comorbid with migraine with aura. Conclusion The pathophysiology and pharmacology of headache and sleep disorders involves an array of neural networks which likely underlie their shared clinical association. While it is difficult to differentiate between cause and effect, or simply a spurious relationship the striking brainstem, hypothalamic and thalamic convergence would suggest a bidirectional influence.

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Tormented Sunrises

Sleep Disorders ◽

10.1093/med/9780190671099.003.0022 ◽

2019 ◽

pp. 418-434

Author(s):

Maha Alattar

Keyword(s):

Obstructive Sleep Apnea ◽

Sleep Apnea ◽

General Population ◽

Sleep Disorders ◽

Headache Disorders ◽

Distinct Subset ◽

Obstructive Sleep ◽

High Prevalence ◽

The Relationship

This chapter covers the relationship between sleep-related headaches and sleep disorders such as obstructive sleep apnea (OSA). Sleep apnea headache (SAH), a type of sleep-related headache that is classified in the International Classification of Headache Disorders, is a distinct subset of headache that is caused by OSA and occurs distinctly on awakening. Once recognized, treatment of OSA is associated with significant improvement in, and often resolution of, SAH. Given the high prevalence of headaches in the general population, sleep disorders must be considered in the evaluation of patients with headaches. A comprehensive sleep evaluation should be an integral part of the assessment of headache disorders. Sleep apnea headache and other types of headaches associated with sleep are reviewed in this chapter.

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Automatic sleep staging using heart rate variability, body movements, and recurrent neural networks in a sleep disordered population

SLEEP ◽

10.1093/sleep/zsaa048 ◽

2020 ◽

Vol 43 (9) ◽

Cited By ~ 1

Author(s):

Pedro Fonseca ◽

Merel M van Gilst ◽

Mustafa Radha ◽

Marco Ross ◽

Arnaud Moreau ◽

...

Keyword(s):

Neural Networks ◽

Heart Rate ◽

Heart Rate Variability ◽

Sleep Disorders ◽

Recurrent Neural Networks ◽

Clinical Diagnostics ◽

Sleep Staging ◽

Substantial Agreement ◽

Body Movements ◽

Wide Range

Abstract Study Objectives To validate a previously developed sleep staging algorithm using heart rate variability (HRV) and body movements in an independent broad cohort of unselected sleep disordered patients. Methods We applied a previously designed algorithm for automatic sleep staging using long short-term memory recurrent neural networks to model sleep architecture. The classifier uses 132 HRV features computed from electrocardiography and activity counts from accelerometry. We retrained our algorithm using two public datasets containing both healthy sleepers and sleep disordered patients. We then tested the performance of the algorithm on an independent hold-out validation set of sleep recordings from a wide range of sleep disorders collected in a tertiary sleep medicine center. Results The classifier achieved substantial agreement on four-class sleep staging (wake/N1–N2/N3/rapid eye movement [REM]), with an average κ of 0.60 and accuracy of 75.9%. The performance of the sleep staging algorithm was significantly higher in insomnia patients (κ = 0.62, accuracy = 77.3%). Only in REM parasomnias, the performance was significantly lower (κ = 0.47, accuracy = 70.5%). For two-class wake/sleep classification, the classifier achieved a κ of 0.65, with a sensitivity (to wake) of 72.9% and specificity of 94.0%. Conclusions This study shows that the combination of HRV, body movements, and a state-of-the-art deep neural network can reach substantial agreement in automatic sleep staging compared with polysomnography, even in patients suffering from a multitude of sleep disorders. The physiological signals required can be obtained in various ways, including non-obtrusive wrist-worn sensors, opening up new avenues for clinical diagnostics.

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Migraine Without Aura and Migraine with Aura Are Distinct Clinical Entities: A Study of Four Hundred and Eighty-Four Male and Female Migraineurs From the General Population

Cephalalgia ◽

10.1046/j.1468-2982.1996.1604239.x ◽

1996 ◽

Vol 16 (4) ◽

pp. 239-245 ◽

Cited By ~ 204

Author(s):

MB Russell ◽

BK Rasmussen ◽

K Fenger ◽

J Olesen

Keyword(s):

General Population ◽

Migraine With Aura ◽

Migraine Without Aura ◽

International Headache Society ◽

Age At Onset ◽

Age Groups ◽

Bright Light ◽

Expected Number ◽

Normal Distributions ◽

Precipitating Factor

The clinical characteristics of migraine without aura (MO) and migraine with aura (MA) were compared in 484 migraineurs from the general population. We used the criteria of the International Headache Society. The lifetime prevalence of MO was 14.7% with a M:F ratio of 1:2.2; that of MA was 7.9% with a M:F ratio of 1:1.5. The female preponderance was significant in both MO and MA. The female preponderance was present in all age groups in MA, but was first apparent after menarche in MO, suggesting that female hormones are an initiating factor in MO, but not likely so in MA. The age at onset of MO followed a normal distribution, whereas the age at onset of MA was bimodally distributed, which could be explained by a composition of two normal distributions. The estimated separation between the two groups of MA was at age 26 years among the females and age 31 years among the males. The observed number of persons with co-occurrence of MO and MA was not significantly different from the expected number. The specificity and importance of premonitory symptoms are questioned, but prospective studies are needed. Bright light was a precipitating factor in MA, but not in MO. Menstruation was a precipitating factor in MO, but not likely in MA. Both MO and MA improved during pregnancy. The clinical differences indicate that MO and MA are distinct entities.

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Sleep disorders in multiple sclerosis

10.1093/med/9780199682003.003.0033 ◽

2017 ◽

Author(s):

Luigi Ferini-Strambi ◽

Sara Marelli

Keyword(s):

Quality Of Life ◽

Multiple Sclerosis ◽

General Population ◽

Sleep Disturbance ◽

Sleep Disorders ◽

Depression Symptoms ◽

Appropriate Treatment ◽

Immunological Factors ◽

Clinical Awareness

Though often unrecognized, sleep disorders in MS are seen at higher frequency than the general population, and they may contribute to pain, fatigue and depression—symptoms commonly observed in MS patients. Since several immunological factors in serum have been implicated in the development of sleep disorders, and MS is proven to be characterized by immune abnormalities, the notion that MS and sleep disorders share a similar background seems reasonable. Investigation of sleep disorders in MS is important, especially considering that the treatment of sleep disturbance may contribute to a reduction in debilitating symptoms, such as fatigue. Thus, an increased clinical awareness and appropriate treatment of sleep disorders in the MS population may significantly improve the overall quality of life in these patients.

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Interviewer Effects Among Older Respondents in the European Social Survey

International Journal of Public Opinion Research ◽

10.1093/ijpor/edy031 ◽

2018 ◽

Vol 31 (4) ◽

pp. 609-625 ◽

Cited By ~ 2

Author(s):

Koen Beullens ◽

Geert Loosveldt ◽

Caroline Vandenplas

Keyword(s):

General Population ◽

Elderly People ◽

European Social Survey ◽

Age Group ◽

Quality Of Data ◽

Main Hypothesis ◽

Social Survey ◽

Interviewer Effects ◽

Current Article

Abstract The proportion of elderly people in general population samples is increasing. Therefore, it is becoming more important to pay special attention to older respondents when assessing the quality of data. The main hypothesis of the current article is that interviewer effects are higher in the older age-group. We use data collected in 13 countries during Round 7 of the European Social Survey. The results support the supposition that older respondents tend to need more clarification, are more prone to misunderstand the questions, and are likely to have longer interviews. In line with the expectations, we also observe that among older respondents, particularly those aged 71 and above, interviewer effects are more common than among younger respondents.

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The association between alcohol consumption and sleep disorders among older people in the general population

Scientific Reports ◽

10.1038/s41598-020-62227-0 ◽

2020 ◽

Vol 10 (1) ◽

Cited By ~ 1

Author(s):

Annie Britton ◽

Linda Ng Fat ◽

Aidan Neligan

Keyword(s):

Alcohol Consumption ◽

General Population ◽

Older People ◽

Sleep Disorders

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Impact of Sleep Disorders and Other Factors on the Quality of Life in General Population

The Journal of Nervous and Mental Disease ◽

10.1097/nmd.0000000000000968 ◽

2019 ◽

Vol 207 (5) ◽

pp. 333-339 ◽

Cited By ~ 10

Author(s):

Souheil Hallit ◽

Aline Hajj ◽

Hala Sacre ◽

Gloria Al Karaki ◽

Diana Malaeb ◽

...

Keyword(s):

Quality Of Life ◽

General Population ◽

Sleep Disorders

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Bullying, sleep/wake patterns and subjective sleep disorders: Findings from a cross-sectional survey

Chronobiology International ◽

10.3109/07420528.2013.877475 ◽

2014 ◽

Vol 31 (4) ◽

pp. 542-553 ◽

Cited By ~ 34

Author(s):

Violaine Kubiszewski ◽

Roger Fontaine ◽

Catherine Potard ◽

Guillaume Gimenes

Keyword(s):

Sleep Disorders ◽

Cross Sectional Survey ◽

Cross Sectional ◽

Subjective Sleep ◽

Wake Patterns

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Empirical Inference of Numerical Information into Causal Strategy Models by Means of Artificial Intelligence

Distributed Artificial Intelligence, Agent Technology, and Collaborative Applications - Advances in Intelligent Information Technologies ◽

10.4018/978-1-60566-144-5.ch016 ◽

2011 ◽

pp. 290-313

Author(s):

Christian Hillbrand

Keyword(s):

Artificial Intelligence ◽

Neural Networks ◽

Time Series ◽

Forecasting Model ◽

Empirical Validation ◽

Functional Dependencies ◽

Cause And Effect ◽

Decision Supporting ◽

Approximate Simulation

The motivation for this chapter is the observation that many companies build their strategy upon poorly validated hypotheses about cause and effect of certain business variables. However, the soundness of these cause-and-effect-relations as well as the knowledge of the approximate shape of the functional dependencies underlying these associations turns out to be the biggest issue for the quality of the results of decision supporting procedures. Since it is sufficiently clear that mere correlation of time series is not suitable to prove the causality of two business concepts, there seems to be a rather dogmatic perception of the inadmissibility of empirical validation mechanisms for causal models within the field of strategic management as well as management science. However, one can find proven causality techniques in other sciences like econometrics, mechanics, neuroscience, or philosophy. Therefore this chapter presents an approach which applies a combination of well-established statistical causal proofing methods to strategy models in order to validate them. These validated causal strategy models are then used as the basis for approximating the functional form of causal dependencies by the means of Artificial Neural Networks. This in turn can be employed to build an approximate simulation or forecasting model of the strategic system.

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