ABSTRACT
Sleep problems have become a common health problem nowadays, and researches on sleep disorders have become a hot topic. Polysomnography (PSG) is the most commonly used method of sleep monitoring in sleep research, but its operation process is cumbersome and complicated, which is likely to cause "first night effect", affecting the compliance of the subjects and the reliability of the monitoring results. In 2005, the cardiopulmonary coupling (CPC) technique based on electrocardiogram signals was used for sleep assessment for the first time, and now it has been widely used in sleep monitoring and analysis of patients with sleep apnea syndrome, sleep disorders, insomnia, depression or other sleep-related diseases and the healthy people, to some extent making up for the lack of traditional PSG technology. It has the advantages of simplifying the operation and improving the sensitivity of the information effectively. However, CPC technique also has the limitations in target crowd, function and use, which can be improved by the developments of CPC algorithm and the cross-system integration of nerve in the future.
ABSTRACT
Sleep problems have become a common health problem nowadays,and researches on sleep disorders have become a hot topic.Polysomnography (PSG) is the most commonly used method of sleep monitoring in sleep research,but its operation process is cumbersome and complicated,which is likely to cause "first night effect",affecting the compliance of the subjects and the reliability of the monitoring results.In 2005,the cardiopulmonary coupling (CPC) technique based on electrocardiogram signals was used for sleep assessment for the first time,and now it has been widely used in sleep monitoring and analysis of patients with sleep apnea syndrome,sleep disorders,insomnia,depression or other sleep-related diseases and the healthy people,to some extent making up for the lack of traditional PSG technology.It has the advantages of simplifying the operation and improving the sensitivity of the information effectively.However,CPC technique also has the limitations in target crowd,function and use,which can be improved by the developments of CPC algorithm and the cross-system integration of nerve in the future.
ABSTRACT
Objective To explore the relationship between the respiratory disturbance index (RDI) detected by cardiopulmonary coupling (CPC) and all parameters of polysomnography (PSG), and to analyze the correlation of the two different analytical techniques for the interpretation of sleep breathing events.Methods In this case-control study, the patients′ CPC and PSG were simultaneously recorded at the Sleep Clinic at Changzheng Hospital from Janunary 2016 to December 2016.Effective recordings were obtained from 292 patients (male/female: 173/119).According to PSG, these patients were divided into two groups: obstructive sleep apnea hyponea syndrome (OSAHS) group (n=173, aged (50.1±13.3) years) and non-OSAHS group (n=119, aged (50.5±11.7) years).All the PSG parameters and the RDI detected by CPC were compared between the two groups.Pearson correlation was used to analyze the relationship between the CPC-RDI and polysomnography parameters, and Bland-Altman chart was used to test the correlation of the two methods.The receiver operator characteristic curve was used to research the value of CPC-RDI in diagnosis of OSAHS.Results The OSAHS group showed higher levels of total sleep time (TST, (445.94±82.64) min), apnea times ((108.16±35.70)/h), hypopnea rate ((55.62±17.44)/h), apnea hyponea index (AHI, (22.78±20.73)/h), Epworth Sleeping Scale (ESS) scores ((11.21±5.30) scores), CPC-RDI ((32.98±22.19)/h) compared with the non-OSAHS group ((417.21±96.10) min,t=2.730;(7.89±5.41)/h,t=30.384;(11.05±2.23)/h, t=27.709;(5.51±3.11)/h,t=9.014;(7.61±2.29)scores,t=6.973;(11.16±8.63)/h,t=10.205, all P<0.01), and a significant decrease in N1 latency ((14.79±9.29) min vs (18.18±8.98)min, t=-3.106), N3% ((6.53±4.95)% vs(8.83±7.29)%,t=-3.212) and the lowest oxygen saturation (SaO2;(77.91±12.21)% vs(92.72±5.17)%, t=-12.479, all P<0.05 respectively).Pearson correlation analysis indicated that RDI was positively correlated with TST, N2 sleeping time, N3 sleeping time, AHI, microarousals index, leg movements index, and ESS scores (P<0.01 respectively).Remarkably, the correlation between CPC-RDI and PSG-AHI was excellent (r=0.801, P<0.01), and CPC-RDI was negatively correlated with lowest SaO2 (r=-0.765, P<0.01).Bland-Altman showed that the points in the limits of agreement accounted for more than 95% of all points.If CPC-RDI is higher than 18.95, the subjects were more likely with OSAHS.The sensitivity was 62.9% and the specificity was 88.7%.In addition, the enhanced low-frequency coupling parameters in the CPC analysis technique can clearly analyze the central respiratory rhythm disturbance.Conclusions CPC technology is an effective assessment technology to diagnose sleep-disordered breathing, and correlates well with AHI detected by traditional PSG.It shows the advantage of screening for central sleep apnea.
ABSTRACT
OBJECTIVES: To characterize sleep of subjects with obstructive sleep apnea syndrome (OSA) with insomnia compared to OSA without insomnia in terms of polysomnography (PSG) and cardiopulmonary coupling (CPC) analysis. METHODS: Subjects with OSA (apnea-hypopnea index, AHI > or =5 /h, n=200) were enrolled and divided into subjects OSA with insomnia (OSA-I) and subjects with OSA only (OSA-O). OSA-I complained of difficulty falling and/or staying asleep at an initial interview in clinic. We compared demographics including mood states, daytime sleepiness, PSG, and CPC parameters between groups, and performed correlation analyses between PSG and CPC parameters for each group. RESULTS: Female ratio was higher in OSA-I than OSA-O. OSA-I were older and slimmer than OSA-O. OSA-O were much drowsier (Epworth Sleepiness Scale 10.0 vs. 6.8). However, mood states were not different between two groups. OSA-I showed significantly longer sleep latency and lower sleep efficiency than OSA-O. Despite of higher arousal index (AI) and AHI of OSA-O, wakefulness after sleep onset was greater in OSA-I. There was no significant difference of CPC parameters between two groups after adjustment of AHI. In correlation analyses, low frequency coupling and high frequency coupling duration were associated with AHI, AI, and lowest SaO2 in both groups. CONCLUSIONS: OSA-I demonstrated more fragmented sleep architecture and disruptive sleep in spite of lower sleep-disordered breathing related distress than OSA-O. CPC analysis is unable to differentiate sleep patterns of OSA subjects with or without insomnia. It is needed to explore factors causing fragmented sleep architecture and disruptive sleep rather than respiratory disturbances in OSA subjects complaining of insomnia.
Subject(s)
Female , Humans , Arousal , Demography , Polysomnography , Sleep Apnea Syndromes , Sleep Apnea, Obstructive , Sleep Initiation and Maintenance Disorders , WakefulnessABSTRACT
OBJECTIVES: To compare the sleep quality in the view of polysomnography (PSG) and cardiopulmonary coupling (CPC) analysis in subjects with restless legs syndrome (RLS) versus with psychophysiological insomnia (PPI). METHODS: The PSG data of 109 subjects with RLS and 86 with PPI (apnea-hypopnea index <5 /h) were collected. All subjects reported sleep onset and maintenance insomnia. CPC parameters were obtained using CPC analyzer in RemLogic. Sleep spectrogram by CPC analyses categorized sleep as "stable" [high-frequency coupling (HFC), 0.1-0.4 Hz] and "unstable" [low-frequency coupling (LFC), 0.1-0.01 Hz], independent of sleep stages. We compared PSG and CPC parameters between two groups and performed correlation analyses to find the PSG parameters to affect CPC parameters. RESULTS: In PSG parameters, subjects with PPI showed significantly longer sleep latency (14.2+/-20.06 vs. 27.5+/-34.96, p<0.001), and decreased sleep efficiency (SE, 80.5+/-14.96 vs. 76.5+/-14.45, p=0.009) than RLS. CPC parameters were not significantly different between groups. In both groups HFC was positively correlated with total sleep time and SE and was negatively associated with time of wake after sleep onset in both groups. Meanwhile, very LFC showed the opposite results to HFC with the same PSG parameters. CONCLUSIONS: Although subjects with RLS or PPI present sleep onset and maintenance insomnia, objective sleep quality was worse in PPI than RLS. It suggests that CPC as a factor to differentiate sleep quality between the RLS and the PPI has a limited role.