scholarly journals Newly detected rapid eye movement associated sleep apnea after coronavirus disease 2019 as a possible cause for chronic fatigue: two case reports

2021 ◽  
Vol 15 (1) ◽  
Author(s):  
Andreas Rembert Koczulla ◽  
Antje Stegemann ◽  
Rainer Gloeckl ◽  
Sandra Winterkamp ◽  
Bernd Sczepanski ◽  
...  

Abstract Background Coronavirus disease 2019 has become a health problem spreading worldwide with pandemic characteristics since March 2020. Post coronavirus disease 2019 symptoms are more frequent than initially expected, with fatigue as an often-mentioned issue. Case presentations We describe a 32-year-old white male and a 55-year-old white female who suffered from post coronavirus disease 2019 fatigue syndrome. On polysomnography, rapid eye movement associated sleep apnea with an increased hypopnea index during rapid eye movement phases of 36.8 and 19.5 events per hour was found. Based on the patients’ burdensome fatigue symptoms, we initiated automatic positive airway pressure therapy, which diminished sleep apnea (rapid eye movement index: 0.0 in both patients) and, consequently, also the fatigue symptoms. Conclusions Since sleep apnea and coronavirus disease 2019 are both associated with fatigue, a screening for sleep apnea might be considered in coronavirus disease 2019 patients with fatigue syndrome.

2015 ◽  
Author(s):  
Sudhansu Chokroverty

Recent research has generated an enormous fund of knowledge about the neurobiology of sleep and wakefulness. Sleeping and waking brain circuits can now be studied by sophisticated neuroimaging techniques that map different areas of the brain during different sleep states and stages. Although the exact biologic functions of sleep are not known, sleep is essential, and sleep deprivation leads to impaired attention and decreased performance. Sleep is also believed to have restorative, conservative, adaptive, thermoregulatory, and consolidative functions. This review discusses the physiology of sleep, including its two independent states, rapid eye movement (REM) and non–rapid eye movement (NREM) sleep, as well as functional neuroanatomy, physiologic changes during sleep, and circadian rhythms. The classification and diagnosis of sleep disorders are discussed generally. The diagnosis and treatment of the following disorders are described: obstructive sleep apnea syndrome, narcolepsy-cataplexy sydrome, idiopathic hypersomnia, restless legs syndrome (RLS) and periodic limb movements in sleep, circadian rhythm sleep disorders, insomnias, nocturnal frontal lobe epilepsy, and parasomnias. Sleep-related movement disorders and the relationship between sleep and psychiatric disorders are also discussed. Tables describe behavioral and physiologic characteristics of states of awareness, the international classification of sleep disorders, common sleep complaints, comorbid insomnia disorders, causes of excessive daytime somnolence, laboratory tests to assess sleep disorders, essential diagnostic criteria for RLS and Willis-Ekbom disease, and drug therapy for insomnia. Figures include polysomnographic recording showing wakefulness in an adult; stage 1, 2, and 3 NREM sleep in an adult; REM sleep in an adult; a patient with sleep apnea syndrome; a patient with Cheyne-Stokes breathing; a patient with RLS; and a patient with dream-enacting behavior; schematic sagittal section of the brainstem of the cat; schematic diagram of the McCarley-Hobson model of REM sleep mechanism; the Lu-Saper “flip-flop” model; the Luppi model to explain REM sleep mechanism; and a wrist actigraph from a man with bipolar disorder. This review contains 14 highly rendered figures, 8 tables, 115 references, and 5 MCQs.


CHEST Journal ◽  
2009 ◽  
Vol 135 (4) ◽  
pp. 957-964 ◽  
Author(s):  
Danny J. Eckert ◽  
Atul Malhotra ◽  
Yu L. Lo ◽  
David P. White ◽  
Amy S. Jordan

2015 ◽  
Author(s):  
Sudhansu Chokroverty

Recent research has generated an enormous fund of knowledge about the neurobiology of sleep and wakefulness. Sleeping and waking brain circuits can now be studied by sophisticated neuroimaging techniques that map different areas of the brain during different sleep states and stages. Although the exact biologic functions of sleep are not known, sleep is essential, and sleep deprivation leads to impaired attention and decreased performance. Sleep is also believed to have restorative, conservative, adaptive, thermoregulatory, and consolidative functions. This review discusses the physiology of sleep, including its two independent states, rapid eye movement (REM) and non–rapid eye movement (NREM) sleep, as well as functional neuroanatomy, physiologic changes during sleep, and circadian rhythms. The classification and diagnosis of sleep disorders are discussed generally. The diagnosis and treatment of the following disorders are described: obstructive sleep apnea syndrome, narcolepsy-cataplexy sydrome, idiopathic hypersomnia, restless legs syndrome (RLS) and periodic limb movements in sleep, circadian rhythm sleep disorders, insomnias, nocturnal frontal lobe epilepsy, and parasomnias. Sleep-related movement disorders and the relationship between sleep and psychiatric disorders are also discussed. Tables describe behavioral and physiologic characteristics of states of awareness, the international classification of sleep disorders, common sleep complaints, comorbid insomnia disorders, causes of excessive daytime somnolence, laboratory tests to assess sleep disorders, essential diagnostic criteria for RLS and Willis-Ekbom disease, and drug therapy for insomnia. Figures include polysomnographic recording showing wakefulness in an adult; stage 1, 2, and 3 NREM sleep in an adult; REM sleep in an adult; a patient with sleep apnea syndrome; a patient with Cheyne-Stokes breathing; a patient with RLS; and a patient with dream-enacting behavior; schematic sagittal section of the brainstem of the cat; schematic diagram of the McCarley-Hobson model of REM sleep mechanism; the Lu-Saper “flip-flop” model; the Luppi model to explain REM sleep mechanism; and a wrist actigraph from a man with bipolar disorder. This review contains 14 highly rendered figures, 8 tables, 115 references, and 5 MCQs.


SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A214-A215
Author(s):  
C Zhang ◽  
H Xu ◽  
J Zou ◽  
J Guan ◽  
H Yi ◽  
...  

Abstract Introduction Obstructive sleep apnea (OSA) is increasingly associated with insulin resistance. The underlying pathophysiology remains unclear but rapid eye movement (REM) sleep has been hypothesized to play a key role. To investigate the associations of insulin resistance with respiratory events and sleep duration during REM sleep, 4,062 Han Chinese individuals with suspected OSA were screened and 2,899 were analyzed. Methods We screened 4,062 participants with suspected OSA who underwent polysomnography in our sleep center from 2009 to 2016. Polysomnographic variables, biochemical indicators, and physical measurements were collected. Logistic regression analyses were conducted to determine the odds ratios (ORs) and 95% confidence intervals (95% CIs) for insulin resistance as assessed by hyperinsulinemia, the homeostasis model assessment of insulin resistance (HOMA-IR), fasting insulin resistance index (FIRI), and Bennet’s insulin sensitivity index (ISI). Results The final analyses included 2,899 participants. After adjusting for age, gender, body mass index, waist circumference, mean arterial pressure, smoking status, alcohol consumption, and the apnea and hypopnea index during non-REM sleep (AHINREM), the results revealed that AHI during REM sleep (AHIREM) was independently associated with insulin resistance; across higher AHIREM quartiles, the ORs (95% CIs) for hyperinsulinemia were 1.340 (1.022, 1.757), 1.210 (0.882, 1.660), and 1.632 (1.103, 2.416); those for abnormal HOMA-IR were 1.287 (0.998, 1.661), 1.263 (0.933, 1.711), and 1.556 (1.056, 2.293); those for abnormal FIRI were 1.386 (1.048, 1.835), 1.317 (0.954, 1.818), and 1.888 (1.269, 2.807); and those for abnormal Bennet’s ISI were 1.297 (1.003, 1.678), 1.287 (0.949, 1.747), and 1.663 (1.127, 2.452) (P < 0.01 for all linear trends). Additionally, the results showed that for every 1-h increase in REM duration, the risk of hyperinsulinemia decreased by 22.3% (P < 0.05). Conclusion The present study demonstrated that AHIREM was independently associated with hyperinsulinemia and abnormal HOMA-IR, FIRI, and Bennet’s ISI. Additionally, REM sleep duration was independently associated with hyperinsulinemia. Support This study was supported by Grants-in-aid from Shanghai Municipal Commission of Science and Technology (No.18DZ2260200).


2009 ◽  
Vol 141 (2) ◽  
pp. 304-305
Author(s):  
Baran Acar ◽  
Mehmet Ali Babademez ◽  
Bulent Ciftci ◽  
Hayriye Karabulut ◽  
Riza Murat Karasen

Author(s):  
Catarina Marques ◽  
Daniela Machado ◽  
Inês Franco ◽  
Inês Sanches ◽  
Regina Monteiro ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document