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Wächter M, Kantelhardt JW, Bonsignore MR, Bouloukaki I, Escourrou P, Fietze I, Grote L, Korzybski D, Lombardi C, Marrone O, Paranicova I, Pataka A, Ryan S, Schiza SE, Sliwinski P, Steiropoulos P, Verbraecken J, Penzel T. Unique sleep-stage transitions determined by obstructive sleep apnea severity, age and gender. J Sleep Res 2019; 29:e12895. [PMID: 31347213 DOI: 10.1111/jsr.12895] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2019] [Revised: 06/06/2019] [Accepted: 06/19/2019] [Indexed: 01/21/2023]
Abstract
In obstructive sleep apnea, patients' sleep is fragmented leading to excessive daytime sleepiness and co-morbidities like arterial hypertension. However, traditional metrics are not always directly correlated with daytime sleepiness, and the association between traditional sleep quality metrics like sleep duration and arterial hypertension is still ambiguous. In a development cohort, we analysed hypnograms from mild (n = 209), moderate (n = 222) and severe (n = 272) obstructive sleep apnea patients as well as healthy controls (n = 105) from the European Sleep Apnea Database. We assessed sleep by the analysis of two-step transitions depending on obstructive sleep apnea severity and anthropometric factors. Two-step transition patterns were examined for an association to arterial hypertension or daytime sleepiness. We also tested cumulative distributions of wake as well as sleep-states for power-laws (exponent α) and exponential distributions (decay time τ) in dependency on obstructive sleep apnea severity and potential confounders. Independent of obstructive sleep apnea severity and potential confounders, wake-state durations followed a power-law distribution, while sleep-state durations were characterized by an exponential distribution. Sleep-stage transitions are influenced by obstructive sleep apnea severity, age and gender. N2 → N3 → wake transitions were associated with high diastolic blood pressure. We observed higher frequencies of alternating (symmetric) patterns (e.g. N2 → N1 → N2, N2 → wake → N2) in sleepy patients both in the development cohort and in a validation cohort (n = 425). In conclusion, effects of obstructive sleep apnea severity and potential confounders on sleep architecture are small, but transition patterns still link sleep fragmentation directly to obstructive sleep apnea-related clinical outcomes like arterial hypertension and daytime sleepiness.
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Affiliation(s)
- Marcel Wächter
- Schlafmedizinisches Zentrum, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Jan W Kantelhardt
- Institut für Physik, Martin-Luther-Universität Halle-Wittenberg, Halle, Germany
| | - Maria R Bonsignore
- PROMISE Department, University of Palermo, and National Research Council, IBIM, Palermo, Palermo, Italy
| | | | | | - Ingo Fietze
- Schlafmedizinisches Zentrum, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Ludger Grote
- Sleep Medicine Center, Sahlgrenska University Hospital, Gothenborg, Sweden
| | - Damian Korzybski
- 2nd Department of Respiratory Medicine, Institute of Tuberculosis and Lung Diseases, Warsaw, Poland
| | - Carolina Lombardi
- Istituto Auxologico Italiano, IRCCS-Milano Bicocca University, Milano, Italy
| | - Oreste Marrone
- PROMISE Department, University of Palermo, and National Research Council, IBIM, Palermo, Palermo, Italy
| | | | | | - Silke Ryan
- University College Dublin, Dublin, Ireland
| | | | - Pawel Sliwinski
- 2nd Department of Respiratory Medicine, Institute of Tuberculosis and Lung Diseases, Warsaw, Poland
| | - Paschalis Steiropoulos
- Medical School, Democritus University of Thrace, University Hospital of Alexandroupolis, Alexandroupolis, Greece
| | - Johan Verbraecken
- Antwerp University Hospital and University of Antwerp, Antwerp, Belgium
| | - Thomas Penzel
- Schlafmedizinisches Zentrum, Charité-Universitätsmedizin Berlin, Berlin, Germany
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Dos Santos Lima GZ, Lobao-Soares B, Corso G, Belchior H, Lopes SR, de Lima Prado T, Nascimento G, França ACD, Fontenele-Araújo J, Ivanov PC. Hippocampal and cortical communication around micro-arousals in slow-wave sleep. Sci Rep 2019; 9:5876. [PMID: 30971751 PMCID: PMC6458146 DOI: 10.1038/s41598-019-42100-5] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2018] [Accepted: 03/12/2019] [Indexed: 11/09/2022] Open
Abstract
Sleep plays a crucial role in the regulation of body homeostasis and rhythmicity in mammals. Recently, a specific component of the sleep structure has been proposed as part of its homeostatic mechanism, named micro-arousal. Here, we studied the unique progression of the dynamic behavior of cortical and hippocampal local field potentials (LFPs) during slow-wave sleep-related to motor-bursts (micro-arousals) in mice. Our main results comprised: (i) an abrupt drop in hippocampal LFP amplitude preceding micro-arousals which persisted until the end of motor-bursts (we defined as t interval, around 4s) and a similar, but delayed amplitude reduction in cortical (S1/M1) LFP activity occurring at micro-arousal onset; (ii) two abrupt frequency jumps in hippocampal LFP activity: from Theta (6-12 Hz) to Delta (2-4 Hz), also t seconds before the micro-arousal onset, and followed by another frequency jump from Delta to Theta range (5-7 Hz), now occurring at micro-arousal onset; (iii) a pattern of cortico-hippocampal frequency communication precedes micro-arousals: the analysis between hippocampal and cortical LFP fluctuations reveal high coherence during τ interval in a broader frequency band (2-12 Hz), while at a lower frequency band (0.5-2 Hz) the coherence reaches its maximum after the onset of micro-arousals. In conclusion, these novel findings indicate that oscillatory dynamics pattern of cortical and hippocampal LFPs preceding micro-arousals could be part of the regulatory processes in sleep architecture.
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Affiliation(s)
- Gustavo Zampier Dos Santos Lima
- Escola de Ciências e Tecnologia, Universidade Federal do Rio Grande do Norte, Natal, RN, Brazil. .,Departamento de Biofísica e Farmacologia, Universidade Federal do Rio Grande do Norte, Natal, RN, Brazil. .,Keck Laboratory for Network Physiology, Department of Physics, Boston University, Boston, MA, USA.
| | - Bruno Lobao-Soares
- Departamento de Biofísica e Farmacologia, Universidade Federal do Rio Grande do Norte, Natal, RN, Brazil
| | - Gilberto Corso
- Departamento de Biofísica e Farmacologia, Universidade Federal do Rio Grande do Norte, Natal, RN, Brazil
| | - Hindiael Belchior
- Faculdade de Ciências da Saúde do Trairí, Universidade Federal do Rio Grande do Norte, Natal, RN, Brazil
| | | | - Thiago de Lima Prado
- Instituto de Engenharia, Ciência e Tecnologia, Universidade Federal dos Vales do Jequitinhonha e Mucuri, Janaúba, MG, Brazil
| | - George Nascimento
- Departamento de Engenharia Biomédica, Universidade Federal do Rio Grande do Norte, Natal, RN, Brazil
| | | | - John Fontenele-Araújo
- Departamento de Fisiologia e Comportamento, Universidade Federal do Rio Grande do Norte, Natal, RN, Brazil
| | - Plamen Ch Ivanov
- Keck Laboratory for Network Physiology, Department of Physics, Boston University, Boston, MA, USA. .,Division of Sleep Medicine and Harvard Medical School, Brigham and Women's Hospital, Boston, MA, USA.
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Drouot X, Bridoux A, Thille AW, Roche-Campo F, Cordoba-Izquierdo A, Katsahian S, Brochard L, d'Ortho MP. Sleep continuity: a new metric to quantify disrupted hypnograms in non-sedated intensive care unit patients. CRITICAL CARE : THE OFFICIAL JOURNAL OF THE CRITICAL CARE FORUM 2014; 18:628. [PMID: 25420997 PMCID: PMC4271438 DOI: 10.1186/s13054-014-0628-4] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/01/2014] [Accepted: 10/29/2014] [Indexed: 11/10/2022]
Abstract
INTRODUCTION Sleep in intensive care unit (ICU) patients is severely altered. In a large proportion of critically ill patients, conventional sleep electroencephalogram (EEG) patterns are replaced by atypical sleep. On the other hand, some non-sedated patients can display usual sleep EEG patterns. In the latter, sleep is highly fragmented and disrupted and conventional rules may not be optimal. We sought to determine whether sleep continuity could be a useful metric to quantify the amount of sleep with recuperative function in critically ill patients with usual sleep EEG features. METHODS We retrospectively reanalyzed polysomnographies recorded in non-sedated critically ill patients requiring non-invasive ventilation (NIV) for acute hypercapnic respiratory failure. Using conventional rules, we built two-state hypnograms (sleep and wake) and identified all sleep episodes. The percentage of time spent in sleep bouts (<10 minutes), short naps (>10 and <30 minutes) and long naps (>30 minutes) was used to describe sleep continuity. In a first study, we compared these measures regarding good (NIV success) or poor outcome (NIV failure). In a second study performed on a different patient group, we compared these measurements during NIV and during spontaneous breathing. RESULTS While fragmentation indices were similar in the two groups, the percentage of total sleep time spent in short naps was higher and the percentage of sleep time spent in sleep bouts was lower in patients with successful NIV. The percentage of total sleep time spent in long naps was higher and the percentage of sleep time spent in sleep bouts was lower during NIV than during spontaneous breathing; the level of reproducibility of sleep continuity measures between scorers was high. CONCLUSIONS Sleep continuity measurements could constitute a clinically relevant and reproducible assessment of sleep disruption in non-sedated ICU patients with usual sleep EEG.
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Klerman EB, Wang W, Duffy JF, Dijk DJ, Czeisler CA, Kronauer RE. Survival analysis indicates that age-related decline in sleep continuity occurs exclusively during NREM sleep. Neurobiol Aging 2013; 34:309-18. [PMID: 22727943 PMCID: PMC3469724 DOI: 10.1016/j.neurobiolaging.2012.05.018] [Citation(s) in RCA: 42] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2011] [Revised: 05/24/2012] [Accepted: 05/27/2012] [Indexed: 11/29/2022]
Abstract
A common complaint of older persons is disturbed sleep, typically characterized as an inability to return to sleep after waking. As every sleep episode (i.e., time in bed) includes multiple transitions between wakefulness and sleep (which can be subdivided into rapid eye movement [REM] sleep and non-REM [NREM] sleep), we applied survival analysis to sleep data to determine whether changes in the "hazard" (duration-dependent probability) of awakening from sleep and/or returning to sleep underlie age-related sleep disturbances. The hazard of awakening from sleep--specifically NREM sleep--was much greater in older than in young adults. We found, however, that when an individual had spontaneously awakened, the probability of falling back asleep was not greater in young persons. Independent of bout length, the number of transitions between NREM and REM sleep stages relative to number of transitions to wake was approximately 6 times higher in young than older persons, highlighting the difficulty in maintaining sleep in older persons. Interventions to improve age-related sleep complaints should thus target this change in awakenings.
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Affiliation(s)
- Elizabeth B Klerman
- Division of Sleep Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston MA USA
| | - Wei Wang
- Division of Sleep Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston MA USA
| | - Jeanne F Duffy
- Division of Sleep Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston MA USA
| | - Derk-Jan Dijk
- Division of Sleep Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston MA USA
- Surrey Sleep Research Centre, University of Surrey, Guildford, GU2 7XP UK
| | - Charles A Czeisler
- Division of Sleep Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston MA USA
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Kirsch MR, Monahan K, Jia Weng, Redline S, Loparo KA. Entropy-Based Measures for Quantifying Sleep-Stage Transition Dynamics: Relationship to Sleep Fragmentation and Daytime Sleepiness. IEEE Trans Biomed Eng 2012; 59:787-96. [DOI: 10.1109/tbme.2011.2179032] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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Lim ASP, Yu L, Costa MD, Buchman AS, Bennett DA, Leurgans SE, Saper CB. Quantification of the fragmentation of rest-activity patterns in elderly individuals using a state transition analysis. Sleep 2011; 34:1569-81. [PMID: 22043128 DOI: 10.5665/sleep.1400] [Citation(s) in RCA: 51] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023] Open
Abstract
OBJECTIVES Recent interest in the temporal dynamics of behavioral states has spurred the development of analytical approaches for their quantification. Several analytical approaches for polysomnographic data have been described. However, polysomnography is cumbersome, perturbs behavior, and is limited to short recordings. Although less physiologically comprehensive than polysomnography, actigraphy is nonintrusive, amenable to long recordings, and suited to use in subjects' natural environments, and provides an indirect measure of behavioral state. We developed a probabilistic state transition model to quantify the fragmentation of human rest-activity patterns from actigraphic data. We then applied this to the study of the temporal dynamics of rest-activity patterns in older individuals. DESIGN Cross-sectional. SETTING Community-based. PARTICIPANTS 621 community-dwelling individuals without dementia participating in the Rush Memory and Aging Project. MEASUREMENTS AND RESULTS We analyzed actigraphic data collected for up to 11 days. We processed each record to give a series of transitions between the states of rest and activity, calculated the probabilities of such transitions, and described their evolution as a function of time. From these analyses, we derived metrics of the fragmentation of rest or activity at scales of seconds to minutes. Regression modeling of the relationship of these metrics with clinical variables revealed significant associations with age, even after adjusting for sex, body mass index, and a broad range of medical comorbidities. CONCLUSIONS Probabilistic analyses of the transition dynamics of rest-activity data provide a high-throughput, automated, quantitative, and noninvasive method of assessing the fragmentation of behavioral states suitable for large scale human and animal studies; these methods reveal age-associated changes in the fragmentation of rest-activity patterns akin to those described using polysomnographic methods.
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Affiliation(s)
- Andrew S P Lim
- Department of Neurology, Program in Neuroscience and Division of Sleep Medicine, Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA
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Abstract
STUDY OBJECTIVES Sleep continuity is commonly assessed with polysomnographic measures such as sleep efficiency, sleep stage percentages, and the arousal index. The aim of this study was to examine whether the transition rate between different sleep stages could be used as an index of sleep continuity to predict self-reported sleep quality independent of other commonly used metrics. DESIGN AND SETTING Analysis of the Sleep Heart Health Study polysomnographic data. PARTICIPANTS A community cohort. MEASUREMENTS AND RESULTS Sleep recordings on 5,684 participants were deemed to be of sufficient quality to allow visual scoring of NREM and REM sleep. For each participant, we tabulated the frequency of transitions between wake, NREM sleep, and REM sleep. An overall transition rate was determined as the number of all transitions per hour sleep. Stage-specific transition rates between wake, NREM sleep, and REM sleep were also determined. A 5-point Likert scale was used to assess the subjective experience of restless and light sleep the morning after the sleep study. Multivariable regression models showed that a high overall sleep stage transition rate was associated with restless and light sleep independent of several covariates including total sleep time, percentages of sleep stages, wake time after sleep onset, and the arousal index. Compared to the lowest quartile of the overall transition rate (<7.76 events/h), the odds ratios for restless sleep were 1.27, 1.42, and 1.38, for the second (7.77-10.10 events/h), third (10.11-13.34 events/h), and fourth (≥13.35 events/h) quartiles, respectively. Analysis of stage-specific transition rates showed that transitions between wake and NREM sleep were also independently associated with restless and light sleep. CONCLUSIONS Assessing overall and stage-specific transition rates provides a complementary approach for assessing sleep continuity. Incorporating such measures, along with conventional metrics, could yield useful insights into the significance of sleep continuity for clinical outcomes.
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Affiliation(s)
- Alison Laffan
- Departments of
Epidemiology, Johns Hopkins University, Baltimore, MD
| | - Brian Caffo
- Departments of
Biostatistics, Johns Hopkins University, Baltimore, MD
| | - Bruce J. Swihart
- Departments of
Biostatistics, Johns Hopkins University, Baltimore, MD
| | - Naresh M. Punjabi
- Departments of
Epidemiology, Johns Hopkins University, Baltimore, MD
- Departments of
Medicine, Johns Hopkins University, Baltimore, MD
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