K-complex morphological features in male obstructive sleep apnea-hypopnea syndrome patients

Sun, Lin; Zhang, Xiangmin; Huang, Shaoxiong; Liang, Jiuxing; Luo, Yuxi

doi:10.1016/j.resp.2017.11.004

Cited by 14 publications

(12 citation statements)

References 34 publications

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“…In the present study, we observe two categories of delta waves, KC's (<1.5 Hz) and ΔSWAK (1-4Hz), to be associated with objective daytime sleepiness measures (MSLT and PVT Lapses). Further, the association of AHI3A with KC Density but not with ΔSWAK suggests that, as other studies [41,43] have pointed out, while KC Density may be a surrogate of arousals, other morphological features of KCs such as ΔSWAK may be reflective of the sleep protective mechanism of KCs. Specifically, due to the way ΔSWAK is defined: a high ΔSWAK implies that on average KCs overnight are associated with increase in delta activity in stage N2.…”

Section: Comparison With Previous Studiesmentioning

confidence: 72%

“…Conversely, in acute OSA, KC Density, %SWA, and ΔSWAK appeared to return to baseline untreated levels, but did not reach statistical significance, perhaps due to the small size of our study. While several studies in OSA subjects have evaluated sleep EEG slow waves, including other morphological features of KCs, and reported their normalization with CPAP treatment [41,43,44,58,62], to our knowledge, this is a first study that has assessed these sleep EEG markers in acutely induced OSA with CPAP withdrawal. The previous CPAP withdrawal studies used spectral analyses of wake EEG to study the effects of sleep disruption [63].…”

Section: Comparison With Previous Studiesmentioning

confidence: 95%

“…Several studies [36][37][38][39] have reported that KCs have <1 Hz frequency, and as such it can be argued that both KCs and sleep EEG slow waves reflect PFC function. In addition, the slow-wave activity (SWA) and KC features are believed to be markers of the sleep homeostatic process and have been studied in OSA patients at baseline and after treatment with continuous positive airway pressure (CPAP) [40][41][42][43][44]. However, the changes in EEG slow waves with CPAP treatment have not been related to changes in daytime function in OSA.…”

Section: Introductionmentioning

confidence: 99%

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Slow-wave activity surrounding stage N2 K-complexes and daytime function measured by psychomotor vigilance test in obstructive sleep apnea

Parekh¹,

Mullins

Kam

et al. 2018

Sleep

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Study Objective: To better understand the inter-individual differences in neurobehavioral impairment in obstructive sleep apnea (OSA) and its treatment with continuous positive airway pressure (CPAP), we examined how changes in sleep electroencephalography (EEG) slow waves were associated with next-day psychomotor vigilance test (PVT) performance.Methods: Data from 28 OSA subjects (Apnea-Hypopnea Index with 3% desaturation and/or with an associated arousal [AHI3A] > 15/hour; AHI3A = sum of all apneas and hypopneas with 3% O 2 desaturation and/or an EEG arousal, divided by total sleep time [TST]), who underwent three full in-lab nocturnal polysomnographies (NPSGs: chronic OSA, CPAP-treated OSA, and acute OSA), and 19 healthy sleepers were assessed. Four 20-minute PVTs were performed after each NPSG along with subjective and objective assessment of sleepiness. Three EEG metrics were calculated: K-complex (KC) Density (#/minute of N2 sleep), change in slow-wave activity in 1-second envelopes surrounding KCs (ΔSWAK), and relative frontal slow-wave activity during non-rapid eye movement (NREM) (%SWA).Results: CPAP treatment of OSA resulted in a decrease in KC Density (chronic: 3.9 ± 2.2 vs. treated: 2.7 ± 1.1; p < 0.01; mean ± SD) and an increase in ΔSWAK (chronic: 2.6 ± 2.3 vs. treated: 4.1 ± 2.4; p < 0.01) and %SWA (chronic: 20.9 ± 8.8 vs. treated: 26.6 ± 8.6; p < 0.001). Cross-sectionally, lower ΔSWAK values were associated with higher PVT Lapses (chronic: rho = −0.55, p < 0.01; acute: rho = −0.46, p = 0.03). Longitudinally, improvement in PVT Lapses with CPAP was associated with an increase in ΔSWAK (chronic to treated: rho = −0.48, p = 0.02; acute to treated: rho = −0.5, p = 0.03). In contrast, OSA severity or global sleep quality metrics such as arousal index, NREM, REM, or TST were inconsistently associated with PVT Lapses. Conclusion:Changes in EEG slow waves, in particular ΔSWAK, explain inter-individual differences in PVT performance better than conventional NPSG metrics, suggesting that ΔSWAK is a night-time correlate of next-day vigilance in OSA.

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Section: Comparison With Previous Studiesmentioning

confidence: 72%

Section: Comparison With Previous Studiesmentioning

confidence: 95%

Section: Introductionmentioning

confidence: 99%

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Slow-wave activity surrounding stage N2 K-complexes and daytime function measured by psychomotor vigilance test in obstructive sleep apnea

Parekh¹,

Mullins

Kam

et al. 2018

Sleep

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“…In a previous study, patients with moderate OSA showed an inferior deceleration of SS compared to slight OSA and control groups [16]. There were differences in KC features between OSA sufferers and healthy controls [38].…”

Section: Discussionmentioning

confidence: 82%

Association between Loss of Sleep-specific Waves and Age, Sleep Efficiency, Body Mass Index, and Apnea-Hypopnea Index in Human N3 Sleep

Li¹,

Duan²,

Yan³

et al. 2020

Aging and disease

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Sleep spindles (SS) and K-complexes (KC) play important roles in human sleep. It has been reported that age, body mass index (BMI), and apnea-hypopnea index (AHI) may influence the number of SS or KC in non-rapid-eye-movement (NREM) 2 (N2) sleep. In this study, we investigated whether the loss of SS or KC is associated with the above factors in NREM 3 (N3) sleep. A total of 152 cases were enrolled from 2013 to 2017. The correlations between the number of SS or KC in N3 sleep and participants' characteristics were analyzed using Spearman rank correlation. Chi-squared test was used to assess the effects of age, sleep efficiency, and BMI on the loss of N3 sleep, N3 spindle and N3 KC. Our results showed that there were negative correlations between the number of SS in N3 sleep with age, BMI, and AHI (P < 0.001), and similar trends were found for KC as well. The loss of SS and KC in N3 sleep was related with age, BMI, and AHI (P < 0.01), as was the loss of N3 sleep (P < 0.01). However, sleep efficiency was not related with the loss of N3 sleep, SS and KC in N3 sleep (P > 0.05). The present study supports that age, BMI, and AHI are all influencing factors of SS and KC loss in human N3 sleep, but sleep efficiency was not an influencing factor in the loss of N3 sleep and the loss of SS and KC in N3 sleep.

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“…In addition, clear differences in various sleeprelated electroencephalography (EEG) patterns have been found in SAHS patients (Carvalho et al, 2014;Sun et al, 2018). Sleep fragmentation, recurrent hypoxia, and cortical arousal induced by apnea events have been associated with these EEG variations (Carvalho et al, 2014;Fatouleh et al, 2014;Chen et al, 2015;Sun et al, 2018) and may interrupt the removal of metabolic waste products from the brain by cerebrospinal fluid, which affects cognitive function (Fultz et al, 2019). Therefore, the study of brain activity during apnea can provide insights on brain dysfunction due to SAHS and related complications.…”

Section: Introductionmentioning

confidence: 99%

Sleep Electroencephalographic Response to Respiratory Events in Patients With Moderate Sleep Apnea–Hypopnea Syndrome

et al. 2020

Self Cite

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Sleep apnea-hypopnea syndrome is a common breathing disorder that can lead to organic brain injury, prevent memory consolidation, and cause other adverse mentalrelated complications. Brain activity while sleeping during respiratory events is related to these dysfunctions. In this study, we analyzed variations in electroencephalography (EEG) signals before, during, and after such events. Absolute and relative powers, as well as symbolic transfer entropy (STE) of scalp EEG signals, were calculated to unveil the activity of brain regions and information interactions between them, respectively. During the respiratory events, only low-frequency power increased during rapid eye movement (REM) stage (δ-band absolute and relative power) and N1 (δ-and θ-band absolute power, δ-band relative power) sleep. But absolute power increased in lowand medium-frequency bands (δ, θ, α, and σ bands), and relative power increased mainly in the medium-frequency band (α and σ bands) during stage N2 sleep. After the respiratory events, absolute power increased in all frequency bands and sleep stages, but relative power increased in medium and high frequencies. Regarding information interactions, the β-band STE decreased during and after events. In the γ band, the intrahemispheric STE increased during events and decreased afterward. Moreover, the interhemisphere STE increased after events during REM and stage N1 sleep. The EEG changes throughout respiratory events are supporting evidence for previous EEG knowledge of the impact of sleep apnea on the brain. These findings may provide insights into the influence of the sleep apnea-hypopnea syndrome on cognitive function and neuropsychiatric defects.

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K-complex morphological features in male obstructive sleep apnea-hypopnea syndrome patients

Cited by 14 publications

References 34 publications

Slow-wave activity surrounding stage N2 K-complexes and daytime function measured by psychomotor vigilance test in obstructive sleep apnea

Slow-wave activity surrounding stage N2 K-complexes and daytime function measured by psychomotor vigilance test in obstructive sleep apnea

Association between Loss of Sleep-specific Waves and Age, Sleep Efficiency, Body Mass Index, and Apnea-Hypopnea Index in Human N3 Sleep

Sleep Electroencephalographic Response to Respiratory Events in Patients With Moderate Sleep Apnea–Hypopnea Syndrome

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