Sleep deprivation can cause hyperalgesia, and the mechanisms involve glutamic acid, dopamine, serotonin, metabotropic glutamate receptor subtype 5, adenosine A2A receptor, nicotinic acetylcholine receptor, opioid receptor, brain-derived neurotrophic factor, melatonin, etc. The mechanisms of hyperalgesia caused by sleep deprivation are complex. The current treatment methods are mainly to improve sleep and relieve pain. This paper reviews the mechanism and treatment progress of hyperalgesia induced by sleep deprivation, and aims to provide scientific evidence for the treatment of hyperalgesia caused by sleep deprivation.
ObjectivesTo review the value of sleep deprivation EEG methodology in the diagnosis of epilepsy.MethodsSuch databases as Pubmed, MEDLINE, The Cochrane Library, Wanfang, VIP and CNKI Data are searched electronically and comprehensively for literature on the diagnosis of epilepsy by sleep deprivation EEG from inception to January 2021. Two reviewers independently screened literature according to the inclusion and exclusion criteria, extracted data, and assessed methodological quality. Then, meta-analysis was performed using Stata software.ResultsA total of 14studies involving 1221 patients were included in total. The results of meta-analysis showed that: Duration of sleep deprivation and effect value of positive rate [ r=0.670, 95%CI (0.664, 0.696), P<0.001 ], duration of the awake period records and effect value of positive rate [ r=0.659, 95%CI (0.596, 0.722), P<0.001 ], duration of sleep period records and effect value of positive rate [ r=0.67, 95%CI(0.619, 0.721), P<0.001 ], with significant differences.ConclusionsThe duration of sleep deprivation, the awake period records, and the sleep period records of sleep deprivation EEG examination, sleep deprivation time between 16 h to 24 h, the awake recording time ≥30 min, and the sleep recording time ≥ 60 min (≤ 3 h) can obviously improve the positive rate of sleep deprivation EEG.
Objective To systematically review the rate of sleep deprivation in children and adolescents in China from 2004 to 2019. Methods PubMed, The Cochrane Library, EMbase, Web of Science, CBM, CNKI and WanFang Data databases were searched to collect cross-sectional studies on the sleep deprivation rate of children and adolescents in China from inception to July 15th, 2021. Two researchers independently screened literature, extracted data and evaluated the risk of bias of the included studies. Meta-analysis was then performed by using Stata 15.0 software. Results A total of 45 cross-sectional studies were included, with a total sample size of 769 918 participants, of whom 587 457 reported sleep deprivation. The results of meta-analysis showed that the sleep deprivation rate of Chinese children and adolescents was 61% (95%CI 55% to 68%). Subgroup analysis indicated that the sleep deprivation rates were 62% for female children and 59% for male children. The rate was 84% in junior high school, 80% in high school and 64% in primary school. The rates in south China, southwest China, northwest China, north China, east China and central China were 68%, 62%, 61%, 57%, 57% and 54%, respectively. The rate of sleep deficiency based on "health requirements for daily study time of primary and junior school students" was the highest at 74% (95% CI 70% to 79%). The cumulative meta-analysis by time showed that the sleep deprivation rate had gradually stabilized and approached 60% since 2011. Conclusion Current evidence shows that the sleep deprivation rate of Chinese children and adolescents is high. Due to the limited quality and quantity of included studies, more high-quality studies are needed to verify the above conclusion.
Difference of chronotypes makes influence to cognitive performance of individuals in routine duties. In this paper, 55 subjects with different chronotypes were subjected to continuous sleep deprivation for 30 h by using the constant routine protocol, during which core body temperature was measured continuously, and subjective sleepiness self-rating and the performance of selective attention were measured hourly. The results showed that the phase difference of core body temperature has no significant difference, yet the amplitude and term difference among the three chronotypes are significant. There was an advance in phase between subjective sleepiness self-rating and core body temperature, and the self-rating sleepiness of evening type came the latest, and the self-rating sleepiness of morning type dissipated the fastest. The response time of selective attention showed a 2 h phase delay with subjective sleepiness self-rating. And the analysis of core body temperature showed that the later the chronotype was, the greater the phase delay was. The correct rate of selective attention of different chronotypes were inconsistent with delay of subjective sleepiness self-rating and core body temperature. We provide reference for industry, aviation, military, medical and other fields to make a more scientific scheduling/ shifting based on cognitive performance characteristics of different chronotypes.