Sleep stage transition dynamics reveal specific stage 2 vulnerability in insomnia

Yishul Wei, Michele A. Colombo, Jennifer R. Ramautar, Tessa F. Blanken, Ysbrand D. Van Der Werf, Kai Spiegelhalder, Bernd Feige, Dieter Riemann, Eus J.W. Van Someren

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Study Objectives: Objective sleep impairments in insomnia disorder (ID) are insufficiently understood. The present study evaluated whether whole-night sleep stage dynamics derived from polysomnography (PSG) differ between people with ID and matched controls and whether sleep stage dynamic features discriminate them better than conventional sleep parameters. Methods: Eighty-eight participants aged 21-70 years, including 46 with ID and 42 age- and sex-matched controls without sleep complaints, were recruited through www.sleepregistry.nl and completed two nights of laboratory PSG. Data of 100 people with ID and 100 age- and sex-matched controls from a previously reported study were used to validate the generalizability of findings. The second night was used to obtain, in addition to conventional sleep parameters, probabilities of transitions between stages and bout duration distributions of each stage. Group differences were evaluated with nonparametric tests. Results: People with ID showed higher empirical probabilities to transition from stage N2 to the lighter sleep stage N1 or wakefulness and a faster decaying stage N2 bout survival function. The increased transition probability from stage N2 to stage N1 discriminated people with ID better than any of their deviations in conventional sleep parameters, including less total sleep time, less sleep efficiency, more stage N1, and more wake after sleep onset. Moreover, adding this transition probability significantly improved the discriminating power of a multiple logistic regression model based on conventional sleep parameters. Conclusions: Quantification of sleep stage dynamics revealed a particular vulnerability of stage N2 in insomnia. The feature characterizes insomnia better than - and independently of - any conventional sleep parameter.

Original languageEnglish
Article numberzsx117
JournalSleep
Volume40
Issue number9
DOIs
Publication statusPublished - 2017

Cite this

Wei, Yishul ; Colombo, Michele A. ; Ramautar, Jennifer R. ; Blanken, Tessa F. ; Van Der Werf, Ysbrand D. ; Spiegelhalder, Kai ; Feige, Bernd ; Riemann, Dieter ; Van Someren, Eus J.W. / Sleep stage transition dynamics reveal specific stage 2 vulnerability in insomnia. In: Sleep. 2017 ; Vol. 40, No. 9.
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title = "Sleep stage transition dynamics reveal specific stage 2 vulnerability in insomnia",
abstract = "Study Objectives: Objective sleep impairments in insomnia disorder (ID) are insufficiently understood. The present study evaluated whether whole-night sleep stage dynamics derived from polysomnography (PSG) differ between people with ID and matched controls and whether sleep stage dynamic features discriminate them better than conventional sleep parameters. Methods: Eighty-eight participants aged 21-70 years, including 46 with ID and 42 age- and sex-matched controls without sleep complaints, were recruited through www.sleepregistry.nl and completed two nights of laboratory PSG. Data of 100 people with ID and 100 age- and sex-matched controls from a previously reported study were used to validate the generalizability of findings. The second night was used to obtain, in addition to conventional sleep parameters, probabilities of transitions between stages and bout duration distributions of each stage. Group differences were evaluated with nonparametric tests. Results: People with ID showed higher empirical probabilities to transition from stage N2 to the lighter sleep stage N1 or wakefulness and a faster decaying stage N2 bout survival function. The increased transition probability from stage N2 to stage N1 discriminated people with ID better than any of their deviations in conventional sleep parameters, including less total sleep time, less sleep efficiency, more stage N1, and more wake after sleep onset. Moreover, adding this transition probability significantly improved the discriminating power of a multiple logistic regression model based on conventional sleep parameters. Conclusions: Quantification of sleep stage dynamics revealed a particular vulnerability of stage N2 in insomnia. The feature characterizes insomnia better than - and independently of - any conventional sleep parameter.",
keywords = "Binary classification, Feature selection, Hypnogram, Insomnia disorder, Markov chain, Non-REM sleep, Polysomnography, Sleep architecture, Sleep fragmentation, Sleep stage",
author = "Yishul Wei and Colombo, {Michele A.} and Ramautar, {Jennifer R.} and Blanken, {Tessa F.} and {Van Der Werf}, {Ysbrand D.} and Kai Spiegelhalder and Bernd Feige and Dieter Riemann and {Van Someren}, {Eus J.W.}",
year = "2017",
doi = "10.1093/sleep/zsx117",
language = "English",
volume = "40",
journal = "Sleep",
issn = "0161-8105",
publisher = "American Academy of Sleep Medicine",
number = "9",

}

Wei, Y, Colombo, MA, Ramautar, JR, Blanken, TF, Van Der Werf, YD, Spiegelhalder, K, Feige, B, Riemann, D & Van Someren, EJW 2017, 'Sleep stage transition dynamics reveal specific stage 2 vulnerability in insomnia' Sleep, vol. 40, no. 9, zsx117. https://doi.org/10.1093/sleep/zsx117

Sleep stage transition dynamics reveal specific stage 2 vulnerability in insomnia. / Wei, Yishul; Colombo, Michele A.; Ramautar, Jennifer R.; Blanken, Tessa F.; Van Der Werf, Ysbrand D.; Spiegelhalder, Kai; Feige, Bernd; Riemann, Dieter; Van Someren, Eus J.W.

In: Sleep, Vol. 40, No. 9, zsx117, 2017.

Research output: Contribution to journalArticleAcademicpeer-review

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T1 - Sleep stage transition dynamics reveal specific stage 2 vulnerability in insomnia

AU - Wei, Yishul

AU - Colombo, Michele A.

AU - Ramautar, Jennifer R.

AU - Blanken, Tessa F.

AU - Van Der Werf, Ysbrand D.

AU - Spiegelhalder, Kai

AU - Feige, Bernd

AU - Riemann, Dieter

AU - Van Someren, Eus J.W.

PY - 2017

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N2 - Study Objectives: Objective sleep impairments in insomnia disorder (ID) are insufficiently understood. The present study evaluated whether whole-night sleep stage dynamics derived from polysomnography (PSG) differ between people with ID and matched controls and whether sleep stage dynamic features discriminate them better than conventional sleep parameters. Methods: Eighty-eight participants aged 21-70 years, including 46 with ID and 42 age- and sex-matched controls without sleep complaints, were recruited through www.sleepregistry.nl and completed two nights of laboratory PSG. Data of 100 people with ID and 100 age- and sex-matched controls from a previously reported study were used to validate the generalizability of findings. The second night was used to obtain, in addition to conventional sleep parameters, probabilities of transitions between stages and bout duration distributions of each stage. Group differences were evaluated with nonparametric tests. Results: People with ID showed higher empirical probabilities to transition from stage N2 to the lighter sleep stage N1 or wakefulness and a faster decaying stage N2 bout survival function. The increased transition probability from stage N2 to stage N1 discriminated people with ID better than any of their deviations in conventional sleep parameters, including less total sleep time, less sleep efficiency, more stage N1, and more wake after sleep onset. Moreover, adding this transition probability significantly improved the discriminating power of a multiple logistic regression model based on conventional sleep parameters. Conclusions: Quantification of sleep stage dynamics revealed a particular vulnerability of stage N2 in insomnia. The feature characterizes insomnia better than - and independently of - any conventional sleep parameter.

AB - Study Objectives: Objective sleep impairments in insomnia disorder (ID) are insufficiently understood. The present study evaluated whether whole-night sleep stage dynamics derived from polysomnography (PSG) differ between people with ID and matched controls and whether sleep stage dynamic features discriminate them better than conventional sleep parameters. Methods: Eighty-eight participants aged 21-70 years, including 46 with ID and 42 age- and sex-matched controls without sleep complaints, were recruited through www.sleepregistry.nl and completed two nights of laboratory PSG. Data of 100 people with ID and 100 age- and sex-matched controls from a previously reported study were used to validate the generalizability of findings. The second night was used to obtain, in addition to conventional sleep parameters, probabilities of transitions between stages and bout duration distributions of each stage. Group differences were evaluated with nonparametric tests. Results: People with ID showed higher empirical probabilities to transition from stage N2 to the lighter sleep stage N1 or wakefulness and a faster decaying stage N2 bout survival function. The increased transition probability from stage N2 to stage N1 discriminated people with ID better than any of their deviations in conventional sleep parameters, including less total sleep time, less sleep efficiency, more stage N1, and more wake after sleep onset. Moreover, adding this transition probability significantly improved the discriminating power of a multiple logistic regression model based on conventional sleep parameters. Conclusions: Quantification of sleep stage dynamics revealed a particular vulnerability of stage N2 in insomnia. The feature characterizes insomnia better than - and independently of - any conventional sleep parameter.

KW - Binary classification

KW - Feature selection

KW - Hypnogram

KW - Insomnia disorder

KW - Markov chain

KW - Non-REM sleep

KW - Polysomnography

KW - Sleep architecture

KW - Sleep fragmentation

KW - Sleep stage

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