Issue Navigator

Volume 14 No. 10
Earn CME
Accepted Papers

Scientific Investigations

Breathing Irregularity Is Independently Associated With the Severity of Obstructive Sleep Apnea in Patients With Multiple System Atrophy

Hideaki Nakayama, MD, PhD1,2; Satoshi Hokari, MD, PhD2; Yasuyoshi Ohshima, MD, PhD2; Takayuki Matsuto, MD, PhD3; Takayoshi Shimohata, MD, PhD4
1Department of Respiratory Medicine, Tokyo Medical University, Tokyo, Japan; 2Department of Respiratory Medicine and Infectious Diseases, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan; 3Department of Laboratory Medicine, Niigata University School of Medicine, Niigata, Japan; 4Department of Neurology and Geriatrics, Gifu University Graduate School of Medicine, Gifu, Japan


Study Objectives:

Multiple system atrophy (MSA) is a neurodegenerative disease characterized by the combination of cerebellar ataxia, parkinsonism, and autonomic disturbance. Patients with MSA frequently have sleep-disordered breathing. In some patients with MSA, central sleep apnea manifests during the disease's natural course or as a treatment effect. Breathing instability may be involved in the development of obstructive sleep apnea (OSA); therefore, we investigated whether breathing instability affects the severity of OSA in patients with MSA.


Patients with MSA and a control group of individuals who were matched for age, body mass index (BMI), and supine apnea-hypopnea index (AHI) were recruited. Breathing instability was evaluated by using polysomnography to determine the irregular pattern with approximate entropy (ApEn) of chest respiratory movements during wakefulness before sleep onset. The ApEn values were compared between the groups. The severity of OSA was evaluated with background parameters and ApEn values by regression analysis.


Twenty patients with MSA (9 men; mean age, 61 years; BMI, 24.1 kg/m2; supine AHI, 37.9 events/h) were compared to the control group. The ApEn values were higher in the patients with MSA than those in the control group (1.28 versus 1.11; P < .05). Multiple regression analysis showed that supine AHI was associated with ApEn values but not with BMI in patients with MSA and associated with BMI but not with ApEn values in the individuals in the control group.


Patients with MSA had more breathing irregularity. In patients with MSA, breathing instability may be a more influential factor for OSA than BMI.


A commentary on this article appears in this issue on page 1641.


Nakayama H, Hokari S, Ohshima Y, Matsuto T, Shimohata T. Breathing irregularity is independently associated with the severity of obstructive sleep apnea in patients with multiple system atrophy. J Clin Sleep Med. 2018;14(10):1661–1667.


Current Knowledge/Study Rationale: Patients with multiple system atrophy have a high frequency of sleep-disordered breathing, especially obstructive sleep apnea, even if they are lean. We assessed the relationship between obstructive sleep apnea and breathing instability in patients with multiple system atrophy.

Study Impact: Breathing irregularity occurs in patients with multiple system atrophy and is associated with the severity of obstructive sleep apnea. In patients with multiple system atrophy, breathing instability was more involved in the development of obstructive sleep apnea, compared to obesity.


Multiple system atrophy (MSA) is an adult-onset neurodegenerative disease characterized by cerebellar ataxia, levodopa-unresponsive parkinsonism, and autonomic disturbance.1 Patients with MSA frequently have sleep-disordered breathing (SDB),2 which is a major problem among them. The most common SDB conditions are laryngeal stridor and obstructive sleep apnea (OSA).3

It has been demonstrated that upper airway (UA) muscle response, breathing instability, arousability, and UA anatomy interact with each other and are involved in the pathophysiology of OSA.4 Therefore, several phenotypes of OSA exist.

In some research, patients with MSA were not considered obese (BMI < 26 kg/m2), but they had high frequency of OSA (37% to 65%).2,5 Some have overt central events after the obstruction is removed by continuous positive airway pressure treatment6 or after tracheostomy,7 which is referred to as complex sleep apnea and demonstrates the involvement of breathing control. In other patients, OSA converts to central sleep apnea during the clinical course of the disease.8 This phenomenon suggests the involvement of a respiratory center abnormality in the clinical course of MSA. We assume that breathing instability is associated with the development of OSA in patients with MSA.

One method to evaluate breathing instability is to measure loop gain, which is the ratio of the ventilatory response to ventilatory disturbance.9 However, this method of measuring breathing instability is time consuming and effort dependent.10 Therefore, it is primarily performed on a research basis. Evaluating breathing instability using an easier method would be preferable. One method, called approximate entropy (ApEn), is a promising measurement method; it was developed as a measure of system complexity and predictability,11 and has been applied in clinical cardiovascular studies.1214

We hypothesized that breathing instability would be more involved in the existence and the severity of OSA in patients with MSA. Therefore, we evaluated the ApEn values and the association of ApEn values with the severity of OSA in patients with MSA compared to matched controls.


Study Participants

This study included Japanese patients in whom probable MSA was diagnosed, based on the consensus diagnostic criteria,1 who were admitted to Niigata University Medical and Dental Hospital (Niigata, Japan) between the years 2007 and 2011. Their disease duration and laryngeal stridor were assessed, and disease severity was evaluated based on the Unified Multiple System Atrophy Rating Scale (UMSARS).15 Patients with MSA were compared to individuals (control group) who were matched for age, body mass index (BMI), and supine apneahypopnea index (AHI) derived from our sleep apnea database between the years 2006 and 2012. However, individuals with cardiovascular, cerebrovascular, and/or psychiatric disease(s), and those in whom any medication known to affect sleep, breathing, or muscle control was administered were excluded from the control group. This study was approved by the Ethics Committee of the Niigata University School of Medicine (Niigata, Japan). Written informed consent was obtained from all participants.



Standard polysomnography (PSG) was conducted using a Somno Star apparatus (Sensor Medics, Yorba Linda, California, United States) to obtain electroencephalographic measurements (C3-A2, O2-A1, Cz-A1). Right and left electro-oculograms and surface electromyograms (EMG) of the sub-mental and bilateral tibialis anterior muscles were obtained. A tracheal microphone (TM-106A, Nihon Kohden, Tokyo, Japan) was used to record breathing sounds during sleep. Oral-nasal airflow was assessed using oronasal thermal sensors and nasal pressure transducers. Respiratory movement was measured with respiratory inductance plethysmography. A chest band was applied around the rib cage at the level of the nipple. Measurements of arterial blood oxygen saturation (SpO2) were obtained using a fingertip pulse oximeter. Electrocardiograms were also obtained. Periodic leg movements were assessed using anterior tibialis movement sensors. The PSG records were evaluated by clinical technologists who were certified by the Japanese Society of Sleep Research. Sleep stages, arousals, and respiratory events were manually scored based on the 1999 recommendations of the American Academy of Sleep Medicine Task Force16 and the American Sleep Disorders Association.17 These recommendations define apnea as a complete cessation of airflow lasting ≥ 10 seconds, hypopnea as an airflow reduction of ≥ 50% or an airflow reduction of < 50% but with > 3% oxygen desaturation or an arousal, and OSA as an AHI ≥ 5 episodes/h with obstructive events constituting > 50% of the respiratory events. To avoid the effect of sleeping position, OSA severity was assessed only in the supine position.

Assessment of Breathing Instability

Breathing stability is a regular pattern of breathing movement. When a disturbance occurs, the sequential breathing response increases then decreases, followed by the opposite pattern, before the breathing gradually returns to the previous regular pattern.

Therefore, the disappearance of breathing stability results in an irregular pattern. The morphology of the breathing pattern was evaluated by using ApEn. A low ApEn value indicated predictability and regularity in a time series, whereas a high ApEn value indicated an unpredictable and random variation.

Two and one-half minutes of artifact-free respiratory movement before falling sleep was selected for each individual by one trained technologist. The stable respiratory signal was identified using the respiratory signal itself as well as chin and limb EMG to detect any body movements. When the amplitude of the EMG signal was high, that part of the signal was considered to be associated with movement and inappropriate for analysis. The signals from respiratory movements were stored on a hard disk and digitized at sampling rates of 10 Hz for respiratory movement. The ApEn values of respiratory movement were computed based on the method described by Pincus,11 by using original software developed by one author (TM) in the current study. The mathematical details have been described in previous studies.18,19 The ApEn was computed, as follows:

in which the variable m represented the vector length, r represented the filter factor, and N represented the number of data points. In this study, N was 1500 (ie, 150 seconds); the set r was set at 0.2 times the standard deviation of the original data series; and m was 2.18,19

Statistical Analysis

All results are expressed as the mean ± standard deviation. The ApEn values between the patients with MSA and the those in the control group were compared by using the Wilcoxon test. To assess which variables were associated with AHI, we first performed univariate linear regression with the BMI, age, and ApEn values of each group. Furthermore, to determine the independent predictors, multiple linear regression was then performed using these three variables. To ascertain any effect of medication on patients with MSA, secondary models of multiple linear regression were built where the nonsignificant variables were removed and a variable added for each type of medication. In patients with MSA, we also assessed the association of ApEn with disease duration, disease severity, or the existence of laryngeal stridor.

A value of P < .05 was significant. Statistical analysis was performed with JMP version 11.0.0 (SAS Institute Japan, Tokyo, Japan).


Twenty consecutive patients with MSA and 20 matched controls were selected. Their demographic backgrounds are shown in Table 1. Patients with MSA received medications such as taltirelin (10 cases) or levodopa (8 cases) for their cerebellar ataxia or parkinsonism, or minor tranquilizers (4 cases). There was no statistical difference in sexual prominence between the groups.

Demographic profile.


table icon
Table 1

Demographic profile.

(more ...)

Figure 1 shows an example of the chest band signal during wakefulness for two patients with MSA. Patient A had an ApEn value of 0.74 and supine AHI 10.5 events/h. Patient B had an ApEn value of 1.56 and supine AHI 32.6 events/h.

RIP-chest tracing before sleep onset in two patients with MSA.

The respiratory pattern is more irregular in the lower panel (Patient B). MSA = multiple system atrophy, RIP = respiratory inductive plethysmography.


Figure 1

RIP-chest tracing before sleep onset in two patients with MSA.

(more ...)

The average interval between the end of the extracted respiratory signal and sleep onset time in patients with MSA and the controls was 7.7 ± 4.3 minutes and 11.1 ± 10.4 minutes, respectively (data not shown).

Figure 2 shows that the ApEn values were significantly larger among patients with MSA than among those in the control group (1.28 ± 0.24 versus 1.11 ± 0.20, P < 0.05). This finding indicated greater breathing irregularity among patients with MSA than among those in the control group.

The ApEn values in patients with MSA and in the control group.

Values are presented as mean ± standard deviation. Asterisk indicates statistical significance: * = P < .05. ApEn = approximate entropy, MSA = multiple system atrophy.


Figure 2

The ApEn values in patients with MSA and in the control group.

(more ...)

As shown in Figure 3, the supine AHI value was positively correlated with the ApEn values (r = .47, P < .05) but not with BMI in patients with MSA. By contrast, the supine AHI value was positively correlated with BMI (r = .67, P < .05) but not with ApEn values in the patients in the control group. Furthermore, based on multiple regression analysis, the ApEn value was the only independent factor for supine AHI in patients with MSA (ApEn β = 50.6, standard error [SE] = 23.8, P < .05; Age β = 0.96, SE = 0.80, P = .25; BMI β = 1.7, SE = 1.3, P = .19), whereas BMI was the only independent factor for supine AHI in the controls (ApEn β = −18.3, SE = 23.3, P = .44; Age β = 0.64, SE = 0.78, P = .43; BMI β = 6.6, SE = 1.1, P < .0001). Even after two patients with cardiovascular disease were excluded, there was a still significant relationship between ApEn and supine AHI in patients with MSA in both the univariate and multiple regression analyses. Secondary models of multiple regression were built to examine the association between supine AHI and each type of medication (levodopa, taltirelin, minor tranquilizers, or any neuroactive or psychoactive medication) in addition to ApEn in patients with MSA. ApEn was an independent factor for supine AHI irrespective of medication in all the secondary models. Moreover, levodopa was also an independent factor (ApEn β = 51.6, SE = 21.9, P < .05, no use of levodopa β = 11.7, SE = 5.3, P < .05).

Association of approximate entropy and body mass index with supine apnea-hypopnea index in patients with MSA and in the controls.

AHI = apnea-hypopnea index, ApEn = approximate entropy, BMI = body mass index, MSA = multiple system atrophy, n.s. = not significant.


Figure 3

Association of approximate entropy and body mass index with supine apnea-hypopnea index in patients with MSA and in the controls.

(more ...)

There was no relationship between ApEn values and UMSARS, disease duration, or existence of laryngeal stridor in patients with MSA.


Our study demonstrated that, based on their larger ApEn values, patients with MSA have more breathing irregularity during wakefulness before sleep onset compared to those in the control group and that supine AHI was associated with ApEn values but not with BMI in patients with MSA, whereas supine AHI was associated with BMI but not with ApEn values in patients in the control group. This finding suggested that an intrinsic pathophysiology in the respiratory control system for breathing rhythm is more involved in OSA in patients with MSA.

The pathophysiology of OSA is composed of four factors: anatomical UA collapsibility, UA muscle response, breathing instability, and arousability. Wellman et al.10 proposed that these factors theoretically and experimentally influence the severity of OSA (ie, the AHI) during sleep. In general, the most important factor is anatomical collapsibility of the UA, which is primarily caused by obesity and/or the facial bone structure (eg, retrognathia). Among the controls, the BMI was the only contributor to the AHI in this study.

However, Eckert et al.4 also reported that breathing instability was another important factor and tended to be higher in patients with OSA than in control individuals with similar UA collapsibility. In the current study, breathing instability was evaluated using entropy analysis in which ventilation was analyzed qualitatively rather than quantitatively. There have been only a few reports on ApEn applied to respiration in relation to sleep.18,19 Burioka et al. reported ApEn values from respiratory movement during wakefulness and sleep in young healthy men.18 ApEn values during stage IV sleep were smaller than when participants were awake with their eyes closed (1.13 ± 0.14 versus 1.39 ± 0.14, P < .01). When breathing is more stable in slow wave sleep, the ApEn value is smaller. In our study, there was a difference in the ApEn values computed from the respiratory movement data between the patients with MSA and the controls. These findings demonstrated greater complexity and less predictability in patients with MSA than in the controls. Therefore, patients with MSA had more breathing irregularity.

Breathing irregularity during wakefulness occurs in several diseases and conditions such as heart failure,2022 cerebral infarction,23,24 high altitude,25,26 and opioid treatment.27,28 Yamauchi et al.29 also reported that breathing irregularity occurs in patients with mixed apnea-dominant OSA, compared to patients with obstructive apnea-dominant OSA, when they evaluated the breathing pattern during wakefulness before sleep onset by using simple entropy, a type of entropy analysis.

The ApEn values were assumed to reflect breathing instability; however, it is unclear whether breathing instability (as indicated by elevated ApEn values) causes OSA or is an outcome of OSA. Younes30 and Loewen et al.31 suggest that breathing instability results from SDB because breathing instability improved with treatment by continuous positive airway pressure in some patients. However, Orr et al.32 proposed that lowering the loop gain—for example, by administering oxygen and acetazolamide—is associated with an improvement in OSA severity. These findings indicate that breathing instability might result from, as well as cause, OSA.

In this study, no relationship existed between the ApEn values and disease duration or MSA severity (based on the UMSARS scores), although anatomical degeneration of the brainstem has been reported in patients with MSA.33 Our study revealed that breathing irregularity was more involved in OSA in patients with MSA with a mean disease duration of less than 4 years. Therefore, respiratory control dysregulation may be involved in OSA in the early stage of MSA. However, further study is needed to clarify this possibility.

Study Limitations

This study has some limitations. First, only data that were obtained in the supine position were compared. The total AHI was likely lower (but not significantly) in the control group. Body position affects the severity of SDB; therefore, we examined the relationship between total AHI and ApEn. We found that the total AHI was associated with BMI, but not with the ApEn value in the control group (data not shown). Therefore, it was reasonable to compare data obtained only in the supine position because the ApEn value was evaluated in the supine position.

Second, cephalometric evaluations were not conducted in this study. Most patients were not affected by obesity; therefore, anatomical UA collapsibility may have been attributable to facial bone structure (eg, retrognathia). However, it was difficult to perform cephalometry in all patients with MSA because they had physical disabilities such as orthostatic hypotension. No patient had a small jaw, based on their facial appearance. Therefore, we do not believe there was a difference in facial bone structure between the patients with MSA and the control group.

Third, there may be ethnic differences among patients with MSA: the MSA cerebellar (MSA-C) type is predominant in Japan, whereas the MSA parkinsonian (MSA-P) type is predominant in Europe and the United States.34,35 In our study, there was no difference in ApEn values between patients with MSA-C and MSA-P (1.31 ± 0.25 versus 1.21 ± 0.21).

Fourth, the duration to evaluate ApEn in our study was different from that used in other studies. In one study,29 approximately 5 minutes of stable respiratory signal data before sleep onset were extracted. In other studies,18,19 three different 60-second artifact-free epochs of respiratory movement were selected for each study participant. However, no convention exists regarding the duration to evaluate ApEn values. Richman and Moorman36 suggested that more than 1000 data points were sufficient to evaluate breathing irregularity by using ApEn. In our study, the duration of every period of stable awake breathing before sleep onset was extracted for as long as possible in all of our PSG studies. Data points of the duration (ie, 2.5 minutes) at a sampling rate of 10 Hz (N = 1500) were sufficient and reasonable for analysis.

Fifth, all the epochs were scored for state (in this case, wakefulness using standard criteria) by PSG technologists blinded to group assignment. It was reported that the reliability of scoring of sleep stage was high, and wakefulness in particular had the highest percentage of positive agreement.37 However, as the process from wakefulness to sleep is not stepwise, but rather more linear38 (ie, the epochs extracted might be scored as wakefulness without reaching a full epoch of stage 1), a slight difference of the state may have affected the ApEn values. Further study is needed to verify this point.

Sixth, the sampling of the analyzed recordings was extracted before sleep and the matching to controls was performed randomly and analyzed in the same manner. In this regard, there may be a bias since the recordings were acquired before sleep. Although comparing signals from two separate time points in each patient would be a good internal control, we could not obtain them from every patient because there was not always sufficient time from lights off to sleep onset during PSG. Therefore, we extracted the sampling of stable respiratory signals during the wakefulness period nearest to sleep onset in each patient. Burioka et al. reported that the ApEn measurements were well replicated among the three estimates obtained at separate 3-minute epochs for each study participant during each stage of consciousness in healthy young men.18 However, a study to examine the similarity of ApEn values of respiratory movement at separate time points during quiet wakefulness in patients with MSA and/or OSA is needed.

Seventh, patients with MSA received some medications because the patients were unable to undergo PSG without them. Based on the results of the second model analyses, patients who used levodopa had less supine AHI than those who did not. We believe that this difference is attributable to the MSA type rather than an effect of the medication because levodopa was used for the symptoms of parkinsonism and there was less presence and severity of sleep-disordered breathing in patients with MSA-P than with MSA-C.2 Actually, in this study, patients with MSA-P had lower mean AHI than those with MSAC (14.0 ± 13.5 versus 46.0 ± 27.4 events/h, P < .05). However, we cannot deny the possibility that the medications might have affected consciousness level and breathing in these patients with MSA.


The approach using entropy showed that patients with MSA had more breathing irregularity. The greater the breathing irregularity, the more severe was the OSA (which was an independent variable) in patients with MSA compared to those in the control group.


All authors have read and approved the manuscript. This study was partly supported by the Japan Society for the Promotion of Science (grant number, 26507011). The sponsor had no role in the design of the study, the collection and analysis of the data, or the preparation of the manuscript. The authors report no conflicts of interest.



apnea-hypopnea index


approximate entropy


body mass index


multiple system atrophy


obstructive sleep apnea




sleep-disordered breathing


Unified Multiple System Atrophy Rating Scale


The authors thank Tazuko Kikuya for her help with data collection and Editage ( for English language editing. Author contributions: HN and TS contributed substantially to the study design; HN, SH, YO, and TS to data acquisition; HN, SH, and TM to data analysis; and HN, SH, YO, TM, and TS to the writing of the manuscript. HN has full access to all data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.



Gilman S, Low PA, Quinn N, et al. Consensus statement on the diagnosis of multiple system atrophy. J Neurol Sci. 1999;163(1):94–98. [PubMed]


Vetrugno R, Provini F, Cortelli P, et al. Sleep disorders in multiple system atrophy: a correlative video-polysomnographic study. Sleep Med. 2004;5(1):21–30. [PubMed]


Gaig C, Iranzo A. Sleep-disordered breathing in neurodegenerative diseases. Curr Neurol Neurosci Rep. 2012;12(2):205–217. [PubMed]


Eckert DJ, White DP, Jordan AS, Malhotra A, Wellman A. Defining phenotypic causes of obstructive sleep apnea. Identification of novel therapeutic targets. Am J Respir Crit Care Med. 2013;188(8):996–1004. [PubMed Central][PubMed]


Shimohata T, Shinoda H, Nakayama H, et al. Daytime hypoxemia, sleep-disordered breathing, and laryngopharyngeal findings in multiple system atrophy. Arch Neurol. 2007;64(6):856–861. [PubMed]


Suzuki M, Saigusa H, Shibasaki K, Kodera K. Multiple system atrophy manifesting as complex sleep-disordered breathing. Auris Nasus Larynx. 2010;37(1):110–113. [PubMed]


Jin K, Okabe S, Chida K, et al. Tracheostomy can fatally exacerbate sleep-disordered breathing in multiple system atrophy. Neurology. 2007;68(19):1618–1621. [PubMed]


Ohshima Y, Nakayama H, Matsuyama N, et al. Natural course and potential prognostic factors for sleep-disordered breathing in multiple system atrophy. Sleep Med. 2017;34:13–17. [PubMed]


Khoo MC. Determinants of ventilatory instability and variability. Respir Physiol. 2000;122(2-3):167–182. [PubMed]


Wellman A, Eckert DJ, Jordan AS, et al. A method for measuring and modeling the physiological traits causing obstructive sleep apnea. J Appl Physiol. 2011;110(6):1627–1637. [PubMed Central][PubMed]


Pincus SM. Approximate entropy as a measure of system complexity. Proc Natl Acad Sci U S A. 1991;88(6):2297–2301. [PubMed Central][PubMed]


Hogue CW Jr, Domitrovich PP, Stein PK, et al. RR interval dynamics before atrial fibrillation in patients after coronary artery bypass graft surgery. Circulation. 1998;98(5):429–434. [PubMed]


Korpelainen JT, Sotaniemi KA, Makikallio A, Huikuri HV, Myllyla VV. Dynamic behavior of heart rate in ischemic stroke. Stroke. 1999;30(5):1008–1013. [PubMed]


Schuckers SA. Use of approximate entropy measurements to classify ventricular tachycardia and fibrillation. J Electrocardiol. 1998;31 Suppl:101–105


Wenning GK, Tison F, Seppi K, et al. Development and validation of the Unified Multiple System Atrophy Rating Scale (UMSARS). Mov Disord. 2004;19(12):1391–1402. [PubMed]


Sleep-related breathing disorders in adults: recommendations for syndrome definition and measurement techniques in clinical research. The Report of an American Academy of Sleep Medicine Task Force. Sleep. 1999;22(5):667–689. [PubMed]


EEG arousals: scoring rules and examples: a preliminary report from the Sleep Disorders Atlas Task Force of the American Sleep Disorders Association. Sleep. 1992;15(2):173–184. [PubMed]


Burioka N, Cornelissen G, Halberg F, et al. Approximate entropy of human respiratory movement during eye-closed waking and different sleep stages. Chest. 2003;123(1):80–86. [PubMed]


Tamaki H, Miura M, Nakamoto S, et al. Approximate entropy of respiratory movements in human newborns during different sleep states. Yonago Acta Med. 2016;59(1):89–91. [PubMed Central][PubMed]


Leung RS, Bradley TD. Sleep apnea and cardiovascular disease. Am J Respir Crit Care Med. 2001;164(12):2147–2165. [PubMed]


Bradley TD, Floras JS. Sleep apnea and heart failure: Part II: central sleep apnea. Circulation. 2003;107(13):1822–1826. [PubMed]


Caples SM, Garcia-Touchard A, Somers VK. Sleep-disordered breathing and cardiovascular risk. Sleep. 2007;30(3):291–303. [PubMed]


Hardavella G, Stefanache F, Ianovici N. Cheyne stokes respiration in stroke patients. Rev Med Chir Soc Med Nat Iasi. 2006;110(1):82–87. [PubMed]


Cherniack NS, Longobardo G, Evangelista CJ. Causes of Cheyne-Stokes respiration. Neurocrit Care. 2005;3(3):271–279. [PubMed]


Netzer NC, Strohl KP. Sleep and breathing in recreational climbers at an altitude of 4200 and 6400 meters: observational study of sleep and patterning of respiration during sleep in a group of recreational climbers. Sleep Breath. 1999;3(3):75–82. [PubMed]


Eckert DJ, Jordan AS, Merchia P, Malhotra A. Central sleep apnea: pathophysiology and treatment. Chest. 2007;131(2):595–607. [PubMed Central][PubMed]


Teichtahl H, Wang D. Sleep-disordered breathing with chronic opioid use. Expert Opin Drug Saf. 2007;6(6):641–649. [PubMed]


Pattinson KT. Opioids and the control of respiration. Br J Anaesth. 2008;100(6):747–758. [PubMed]


Yamauchi M, Tamaki S, Yoshikawa M, et al. Differences in breathing patterning during wakefulness in patients with mixed apnea-dominant vs obstructive-dominant sleep apnea. Chest. 2011;140(1):54–61. [PubMed Central][PubMed]


Younes M. CrossTalk proposal: elevated loop gain is a consequence of obstructive sleep apnoea. J Physiol. 2014;592(14):2899–2901. [PubMed]


Loewen A, Ostrowski M, Laprairie J, et al. Determinants of ventilatory instability in obstructive sleep apnea: inherent or acquired? Sleep. 2009;32(10):1355–1365. [PubMed Central][PubMed]


Orr JE, Edwards BA, Malhotra A. CrossTalk opposing view: Loop gain is not a consequence of obstructive sleep apnoea. J Physiol. 2014;592(Pt 14):2903–2905. [PubMed Central]


Benarroch EE. Brainstem respiratory control: substrates of respiratory failure of multiple system atrophy. Mov Disord. 2007;22(2):155–161. [PubMed]


Watanabe H, Saito Y, Terao S, et al. Progression and prognosis in multiple system atrophy: an analysis of 230 Japanese patients. Brain. 2002;125(Pt 5):1070–1083. [PubMed]


Wenning GK, Ben Shlomo Y, Magalhaes M, Daniel SE, Quinn NP. Clinical features and natural history of multiple system atrophy. An analysis of 100 cases. Brain. 1994;117(Pt 4):835–845


Richman JS, Moorman JR. Physiological time-series analysis using approximate entropy and sample entropy. Am J Physiol Heart Circ Physiol. 2000;278(6):H2039–H2049. [PubMed]


Whitney CW, Gottlieb DJ, Redline S, et al. Reliability of scoring respiratory disturbance indices and sleep staging. Sleep. 1998;21(7):749–757. [PubMed]


Younes M, Ostrowski M, Soiferman M, et al. Odds ratio product of sleep EEG as a continuous measure of sleep state. Sleep. 2015;38(4):641–654. [PubMed Central][PubMed]