If you don't remember your password, you can reset it by entering your email address and clicking the Reset Password button. You will then receive an email that contains a secure link for resetting your password
If the address matches a valid account an email will be sent to __email__ with instructions for resetting your password
Department of Diseases of the Thorax, GB Morgagni Hospital, Asl Romagna, Forlì, ItalyDepartment of Respiratory Diseases & Allerg, Aarhus University Hospital, Aarhus, Denmark
Poor sleep quality is associated with poor QoL in IPF patients.
•
Poor sleep quality is predicted by variables associated with SDB.
•
IPF patients with more severe SDB have worse QoL compared to SDB-free or OSAS-only.
Abstract
Purpose
the study aims at describing the role of sleep disordered breathing (SDB) on daytime symptoms, quality of sleep and quality of life (QoL) in patients with moderate-severe IPF.
Methods
we enrolled 34 consecutive room air breathing IPF outpatients who received a full-night polysomnography. The following questionnaires were administered: Epworth Sleepiness Score (ESS), Pittsburg Sleep Quality Index (PSQI), StGeorge's Questionnaire (StGQ).
Results
patients were classified in 3 groups:Group A (NO-SDB, 9 patients), Group B(OSAS without sleep–related hypoxemia, 17 patients), Group C(OSAS with sleep–related hypoxemia, 8 patients). Although sleep parameters showed no significant differences among the 3 groups, worse measures were found in group C. 50% of patients (17/34) reported a StGQ score indicating a reduced QoL and the StGQ score was significantly higher in group C patients compared to group A (p < 0.05). In the stepwise multiple regression analysis, 75% of StGQ score variability was significantly predicted by FVC(Forced Vital Capacity) %, DLco (diffusion lung capacity for carbon monoxide)%, PSQI and ESS.
Conclusions
in patients with IPF both subjective and polysomnographic poor sleep quality are extremely common features, they are predicted by variables associated with SBD severity and are linked to low QoL. IPF with more severe SDB present poor sleep quality and a worse QoL compared to SDB-free or OSAS-only.
Idiopathic pulmonary fibrosis (IPF) is a specific form of chronic, progressive fibrosing interstitial pneumonia of unknown cause, occurring primarily in older adults, limited to the lungs, and associated with the histopathologic and/or radiologic pattern of usual interstitial pneumonia [
The interaction between environmental stressors and genetic predisposition determines the activation of multiple pathogenetic pathways driving to the development of fibrosis [
Heterogeneous clinical features and a highly variable course with inter-individual variability impair our ability to predict prognosis, and the clinical spectrum of this disease, its morbidity and mortality are influenced also by the coexistence of multiple comorbidities that are now better recognized [
] and in the last official guidelines for the diagnosis and management of IPF obstructive sleep apnea-hypopnea syndrome (OSAS) has been recognized for the first time as an important comorbidity [
Fatigue, caused by the disease itself, is a common and frequently disabling complaint in these patients. Moreover, comorbidities, medication, depression and poor sleep quality are potential underestimated causes of fatigue [
The present investigation aims at describing, in a group of moderate-severe IPF with preserved balance of gas exchange at rest, the role of SDB (OSAS with and without sleep hypoxemia) on daytime symptoms, quality of sleep and QoL.
2. Patients and methods
The study was carried out at the Forlì Hospital Pulmonary Operative Unit sleep laboratory between March 2014 and December 2014. The institutional Ethical Commitee Area Vasta Romagna/IRST approved the study (protocol nr.2014/42024).
We enrolled 34 consecutive room air breathing IPF outpatients (26 men and 8 women); mean age, 68.74 ± 9.23 years) diagnosed according to the international IPF report [
]. No patient was treated with steroids. All patients received a complete respiratory function assessment and a full-night unattended polysomnographic study in hospital (Titanium – Embla Systems). Sleep stages and respiratory events were scored according to the AASM 2.1 rules [
]. CAP is the neurophysiological translation of unstable sleep and is composed of arousal-related electroencephalography (EEG) features classified into three subtypes: A1 (clusters of K-complexes and delta bursts), subtypes A2 (mixture of slow and fast EEG rhythms), subtypes A3 (dominant EEG alpha and beta rhythms). Subtypes A2 and A3 coincide with the conventional American Academy Sleep Medicine (AASM) arousals [
]. The following questionnaires were administered to collect symptoms related to diurnal vigilance, sleep disturbances and quality of life: Epworth Sleepiness Score (ESS) for the evaluation of subjective excessive daytime sleepiness [
]. The PSQI questionnaire is a validated instrument for differentiating “poor” from “good” sleep, with higher scores reflective of poorer sleep quality. A total score of 5 or greater is indicative of poor sleep quality [
Data are presented using descriptive statistics (median and interquartile values). Differences among groups were tested by analysis of variance-Kruskal Wallis test, while post-hoc analysis was performed, when appropriate, by means of Dunn's Multiple Comparison Test.
Linear correlations between ESS-PSQI-StGQ scores and anthropometric, respiratory function and sleep data were assessed by the Spearman's test. Backward stepwise multiple regression analysis were performed to identify the variable independently related to ESS, PSQI and StCQ scores.
The level for statistical significance was established at p < 0.05. All statistical analyses were performed using IBM SPSS statistic 19.
3. Results
Twenty-five patients (73.5% of total sample) met the criteria for the diagnosis of OSAS: 11 with a moderate to severe form and 8 with an associated sleep-related hypoxemia. Patients were classified in 3 groups: Group A (NO-SBD, 9 patients), Group B (OSAS without sleep–related hypoxemia, 17 patients), Group C (OSAS with sleep–related hypoxemia, 8 patients). Anthropometric, respiratory function data are reported in Table 1.
Table 1Anthropometric parameters, respiratory functional data. Parameters are reported as median value (interquartile range).
Whole group 34pz
GroupA 9pz
GroupB 17pz
GroupC 8pz
ANOVA (Kruskal Wallis test and Dunn's Multiple Comparison Test)
Age
69.68 (64.77–74.71)
68 (59–71)
73.00 (64.00–76.50)
71.50 (66.50–77.75)
ns
BMI
21.91 (19.68–24.95)
20.83 (19.54–23.04)
22.67 (19.30–22.76)
23.24 (20.34–27.04)
ns
Neck circumference
41 .00 (39.00–42.00)
41.00 (37.50–42.00)
41.00 (39.50–42.50)
40.00 (37.50–41.75)
ns
Mallampati
1.00 (1.00–2.25)
1.00 (1.00–2.00)
1.00 (1.00–3.00)
1.00 (1.00–3.00)
ns
FVC%
75.50 (56.75–87.00)
80.00 (57.00–89.50)
76.00 (59.00–88.50)
68.50 (44.00–81.00)
ns
FEV1%
82.00 (62.75–95.50)
83.00 (56.00–104.50)
76.00 (59.00–88.50)
71.50 (47.75–92.50)
ns
DLco
43.50 (31.00–52.25)
46.00 (34.00–65.50)
51.00 (33.50–52.50)
33.00 (30.25–41.00)
ns
6 MWtest meters
420.00 (300.00–480.00)
420.00 (280.00–510.00)
450.00 (420.00–480.00)
300.00 (180.00–375.00)
P0,0085 B vs C p < 0.05
Awake SpO2
96.00 (95.00–97.00)
96.00 (95.00–97.00)
95.00 (94.00–97.00)
96.00 (95–96.26)
paO2
76.50 (65.20–84.00)
74.70 (66.90–83.55)
80.45 (75.63–86.98)
63.45 (58.10–73.45)
P 0,0087 A vs C P < 0.05
paCO2
38.90 (35.70–40.00)
37.10 (35.63–39.38)
39.90 (36.60–40.95)
37.80 (35.08–42.20)
ns
GAP index
4.00 (3.00–5.00)
3.00 (3.00–5.00)
4.00 (3.00–5.00)
5.00 (4.25–5.00)
ns
GAP stage
2.00 (1.00–2.00)
1.00 (1.00–2.00)
2.00 (1.00–2.00)
2.00 (2.00–2.00)
ns
Abbreviations: BMI: body mass index, FVC: forced vital capacity, FEV1: forced expiratory volume in the first second, DLco: diffusion lung capacity for carbon monoxide, 6 MWtest meters:6 min walking test meters, Awake SpO2: pulse-oximetry O2-saturation in wakefulness and supine position for a period of 20 min, paO2 partial pressure of oxygen in the blood, paCO2: partial pressure of carbon dioxide in the blood, GAP index: gender age physiology index, GAP stage: severity stage based on GAP index.
Overall, the group C patients showed the most severe functional impairment, which reached significance for 6 mWT meters and rest wakefulness PaO2. Polysomnographic data are reported in Table 2 and Table 3. Although no significant differences were found among groups for sleep parameters, both conventional and CAP measures were worse in group C patients. Data relative to daytime sleepiness, sleep and QoL are reported in Table 4.
Table 2Respiratory polysomnographic data. Parameters are reported as median value (interquartile range).
Wakefulness
Whole Group in TST
Group A in TST
Group B in TST
Group C in TST
Kruskal Wallis Test and Dunn's Multiple Comparison Test
Table 3Sleep polysomnographic data. Parameters are reported as median value (interquartile range).
Whole group
Group A
Group B
Group C
Kruskal Wallis Test and Dunn's Multiple Comparison Test
SL (min)
13.50 (6.50–13.50)
14.00 (11.00–38.75)
14.00 (7.00–21.25)
6.00 (3.27–24.98)
ns
REM L (min)
71.00 (59.75–112.3)
67.50 (54.00–106.30)
68.50 (51.75–105.50)
105.50 (65.50–164.00)
ns
TST (min)
373,50 (295.00–441.50)
375.0 (293.5–439.8)
422.00 (285.80–454.50)
342.80 (291.60–434.60)
ns
NREM (min)
319.00 (238.00–366.00)
319.0 (274.5–366.3)
298.50 (225.30–375.00)
307.8 (237.30–387.80)
ns
REM (min)
55.00 (32.00–84.00)
55.50 (33.75–81.25)
66.40 (37.00–95.50)
45.75 (15.63–70.00)
ns
N1 (%)
15.68 (11.64–19.50)
14.67 (10.28–17.65)
16.53 (11.57–19.83)
17.15 (13.56–28.12)
ns
N2 (%)
37.36 (33.60–47.80)
39.04 (29.61–49.06)
34.82 (31.43–39.15)
42.42 (35.32–49.79)
ns
N3 (%)
29.25 (20.16–35.14)
26.93 (18.76–38.18)
30.12 (29.52–35.22)
22.04 (12.05–29.73)
ns
REM (%)
14.56 (11.06–19.14)
14.93 (11.36–18.82)
18.60 (12.62–22.08)
11.91 (6.26–17.38)
ns
SE (%)
68.10 (53.80–76.00)
71.30 (57.65–74.70)
71.80 (47.55–76.15)
55.35 (50.35–74.43)
ns
WASO (min)
168.20 (120.40–252.70)
130.80 (88.45–193.60)
159.00 (123.70–232.90)
248.7 (135.40–284.70)
ns
PLM Index (n/h)
18.65 (1.70–32.98)
4.50 (0.27–48.73)
20.10 (2.60–26.25)
26.35 (3.67–47.15)
ns
CAP time (min)
94.00 (63.60–151.80)
86.70 (55.55–131.00)
75.50 (58.80–143.00)
118.5 (76.03–223.5)
ns
CAP rate (%)
29.30 (17.40–48.60)
27.50 (18.25–43.30)
29.30 (16.15–41.70)
49.55 (27.78–71.60)
ns
A1 (n)
40.5 (23.25–101)
53 (16–115)
41 (20,5–81)
39 (27,5–124)
ns
A2 (n)
30 (14,75–62)
30 (13,5–59)
20 (14–57.5)
32.5 (19.75–66)
ns
A3 (n)
100.5 (67.75–129)
78 (61–118)
99 (52.5–145)
121 (90.25–280)
ns
Awakenings (n)
22.50 (13.75–34.00)
21.00 (13.50–25.50)
22.00 (10.50–34.00)
35.50 (21.50–37.50)
ns
Abbreviations. SL (min): minutes of sleep latency, REM L (min): minutes of rapid eye movement latency, TST (min): minutes of total sleep time, NREM (min): minutes of time spent in non rapid eye movements sleep, REM (min): minutes of time spent in rapid eye movements sleep, N1(%): percentage of time spent in stage 1 of non rapid eye movements sleep, N2(%): percentage of time spent in stage 2 of non rapid eye movements sleep, N3(%): percentage of time spent in stage 3 of non rapid eye movements sleep, REM(%) sleep: percentage of time spent in rapid eye movements sleep, SE(%):sleep efficiency, WASO: minutes of wake time after sleep onset, CAP time (min): minutes of time spent in CAP, CAP rate (%): percentage of NREM sleep spent in CAP, A1(n): number of CAP-phase A1in total sleep time, A2(n): number of CAP-phase A2 in total sleep time A3(n): number of CAP-phase A3 in total sleep time.
The mean ESS score in the whole sample was very low: the only 3 patients (8%) who reported an ESS score > 10 belonged to group C. ESS was significantly correlated RDI (r = 0.37, p = 0.03), PLM Index (r = 041, p = 0.02), number of awakenings (r = 0.38, p = 0.03), CAP parameters (CAP time r = 0.43, p = 0.01; rate r = 0.4, p = 0.02; total number of A phases r = 0.41, p = 0.016; n° of subtypes A3 r = 0.52,p = 0.001). A significant correlation was found also between ESS and StGQ scores (r = 0.4, p = 0.02). In the stepwise multiple regression analysis, the amount of CAP A3 phases was the only predictor of ESS (β = 0.57; R2 = 0.31, p < 0.0001). In turn, the number of CAP A3 subtypes was predicted only by RDI (β = 0.6; R2 = 0.37, p < 0.0001) (Fig. 1).
Fig. 1Multiple stepwise regression. In the box on the left an IPF patient hypnogram with repetitive awakenings, in the box on the right a 120 s PSG epoch of the same patient with CAP A phases.
Forty-seven percent of patients (16/34) reported a PSQI score >5 (PSQI+), mostly in group C (62.5%) (Table 4).
Comparing PSQI+ and PSQI- no differences were found for sex, age, BMI, respiratory functions and sleep measures, as well as for clinical data (gender age physiology index [GAP] and ESS score), except for higher StGQ scores (median 58.80 [39.45–75.93] vs 36.34 [29.07–53.60; p = 0.026) and NREM sleep duration (median 343.5 min [293.6–392.2] vs 273.5 min [219–336.9]; p < 0.05). Overall, the PSQI score was significantly correlated with the amount of NREM sleep (r = 0.39; p = 0.019), number of awakenings (r = 0.41; p = 0.015), and number of A3 phases (r = 0.41; p = 0.015). In the stepwise multiple regression analysis, the number of awakenings was the only significant independent variable of the PSQI (β = 0.47 R2 = 0.230, p = 0.004). In turn the number of awakenings was predicted only by apnea index (AI) (β = 0.40, R2 = 0.164, p = 0.019) (Fig. 1).
3.3 Quality of life
Fifty percent of patients (17/34) reported a StGQ score above the 95° of centile of the normal values from the general healty population [
] indicating a reduced quality of life: As detailed in Table 4, the median StGQ score was significantly higher in group C patients compared to group A (p < 0,05). StGQ + patients showed worse values of respiratory disturbance index (RDI) in comparison to StGQ– patients (median17.1 [9.99–26.55] vs 6.1 [3.35–14.8], p = 0.02) as well as apnea hypopnea index (AHI) (median 13.45 [5.67–20.00] vs 2.58 [0.53–8.9], p = 0.009), awake pulse-oximetry O2-saturation (SpO2) (median 93.00 [89.75–94.75] vs 96.00 [94.00–97], p = 0.015), ODI (median 14.20 [5.80–0.65] vs 2.50 [0.35–10.05], p = 0.015), CAP time (median 123.4 [69.55–184.3] vs 68.90 [59.25–106.4], p < 0.05), number of phase A3 subtypes (median 119.00 [79.5–187.5] vs 78 [43.50–108], p = 0.01.
The StGQ score was significantly correlated with forced vital capacity (FVC)% (r – 52, p < 0.01), diffusion lung capacity for carbon monoxide (DLco)% (r −0.629, p = 0.001), 6 min walking test (6 MWtest) meters (r −0.43, p = 0.02), GAP index (r = 0.44,p = 0.008), PSQI score (r = 0.52, p = 0.001), ESS (r = 0.4, p = 0.02), RDI (r = 0.41,p = 0.01), AHI (r = 0.44,p < 0.01), awake SpO2 (r-0.59,p = 0.001), mean sleep pulse-oximetry O2-saturation (SpaO2) (r-0.46,p < 0.01), O2-saturation mean cumulative percentage time at SaO2 < 90% (CT<90%) (r = 0.43,p = 0.01), ODI (r = 0.41, p = 0.01), number of awakenings (r = 0.4, p = 0.02) CAP time (r = 0.44,p < 0.01), number of A3 subtypes (r = 0.49, p < 0.01): As shown in Table 5, in the stepwise multiple regression analysis the 75% of StGQ score variability was significantly predicted by FVC%, DLco%, PSQI and ESS (Fig. 1).
Our data did support the hypothesis that sleep apnea determines reduced sleep quality and accordingly reduces the quality of life in these patients. The present study found that both subjective and polysomnographic poor sleep quality are a topical factor of reduced quality of life in patients with IPF. In particular, reduced sleep quality appears strictly related to sleep fragmentation (increase of number of awakenings) and OSAS severity.
Previous studies investigated the role of sleep in the development of reduced quality of life in IPF patients with conflicting results. Sleep alteration in IPF patients has been related to systemic inflammation, treatment side effects, age, comorbidities, depression, sleep apnea or sleep fragmentation [
] reported higher scores of ESS, PSQI and SF36 in IPF patients compared to the general population. They also found a significant correlation between PSQI score and some domains of SF36, but the objective causes of reduced sleep quality were not investigated due to the lack of polysomnographic assessment.
Regarding the relationship between pulso-oximetry parameters and QoL in a small sample size study on IPF patients, Mermigkis et al. [
] investigated the relationship between sleep alteration, both subjective or objective and daytime functioning based on the presence of fatigue and the impact of excessive sleepiness on multiple activities of daily living. They found a correlation between severity of some nocturnal pulse-oximetry parameters and severity of physical and social functioning impairment, but could not identify predictors of reduced sleep quality.
In our data, none of the polysomnographic pulso-oximetry parameters was associated with subjective sleep quality (PSQI) or with ESS in simple correlation tests. Regarding the StGQ score, SpaO2 and CT <90% weakly correlated in the simple correlation test but were not confirmed as independent variables in the stepwise multiple regression analysis. In other chronic pulmonary diseases, such as COPD, worse nocturnal pulso-oximetry parameters do not correlate with QoL [
Influence of nocturnal oxygen therapy on quality of life in patients with COPD and isolated sleep-related hypoxemia: a prospective, placebo-controlled cross-over trial.
We used the ICSD3 standardized definition of sleep-related hypoxia (time of sleep ≤ 88% for ≥ 5 min), which clearly identifies the presence of non-OSA sleep breathing disorder. In the natural history of other chronic pulmonary diseases, such as COPD [
], hypoxemia in sleep precedes severe hypoxia in wakefulness and at rest. We have found this severity disease progression model also in the IPF. Our patients did not have severe hypoxemia at rest in wake but about the respiratory sleep disorder we found three groups: without respiratory sleep disorders (group A), with OSA (group B) and with sleep related hypoxia and OSA (group C). In group C, OSA was also more severe than group B (moderate -severe vs mild-moderate) (Table 2). In our recent study we have shown that IPF patients with double respiratory sleep disorder (sleep related hypoxia and OSA) are burdened by the worst mortality and clinical progression curves, and this type of respiratory sleep disorder emerged as an independent variable of the increased mortality risk in the cox regression analysis [
]. The data that we present in this work show that the StG score worsens from group A to group B and group C, that is with the worsening of both the waking function and the respiratory sleep disorder. However, multiple regression analysis showed that the group membership (in particular the double respiratory sleep disorder) was not an independent variable of the StG score. In contrast, sleep fragmentation, ESS and some of the severity parameters of OSA emerged as independent variables of the StG score (Fig. 1).
In IPF patients with concomitant moderate-severe OSAS treated with CPAP, Mermigkis et al. [
]. Features of increased discontinuity (WASO) and instability (CAP time, CAP rate) were major alterations, while sleep duration and sleep depth appeared less impaired. A number of studies have ascertained the deep impact of nocturnal respiratory events on CAP parameters, not only in the field of OSAS [
The cyclic alternating pattern demonstrates increased sleep instability and correlates with fatigue and sleepiness in adults with upper airway resistance syndrome.
]. CAP is a physiological component of NREM sleep, which reflects a condition of balanced arousal instability. The three subtypes of CAP offer flexible options of reactivity to perturbing events of any nature, e.g., noise, epilepsy, movement, pain, breathing [
]. In relation to the ongoing NREM stage and to the intensity and significance of the perturbation, the sleeping brain reacts with a CAP sequence and exploits the most suitable phase A subtype [
], generally expressing subtypes A1 and A2 for the milder background (UARS), and subtypes A3 for the more severe conditions (OSAS). The severity of SDB was associated with the level of sleep disruption showing a clear worsening trend among groups: A > B > C (Table 3).
Excessive daytime sleepiness is surprisingly uncommon in this kind of patients. In agreement with data reported in the recent paper by Gille et al. [
], only 8.8% of patients enrolled in the present study reported a ESS score higher than 10. In contrast, SDB are frequently co-morbid in IPF (73.5%): OSAS occurred in 47% of our patients, and in 26.4% of the patients, OSAS was associated with a sleep-related hypoxemia (group C).
The severity of SDB and of sleep disruption was associated with the worse clinical pictures and the poorest PSQI score. Although significance was not reached, the patients of group C (double SDB and worse OSAS) showed the poorest ESS, PSQI scores compared to the patients of group A (without SDB) and group B (only OSAS). Consistently, the 16 patients PSQI + presented poorer StGQ scores compared to the 18 PSQI- patients and the 17 patients with abnormal StGQ score showed a higher amount of obstructive events and more severe sleep disruption compared to the 17 StGQ-.
Overall, these findings support the hypothesis that sleep disruption and instability caused by SDB play a relevant role on the clinical picture and reduced QoL in patients with IPF.
Besides FVC% and DLco% (parameters expressing fibrosis severity), statistical analysis identified PSQI and ESS as independent variables of the StGQ score and allowed to interpret a large part of the variability (75%) of the StGQ score.
According to the multiple stepwise regression, the amount of A3 subtypes (parameter of sleep fragmentation) was the predictor of the ESS, while only RDI (parameter of OSAS severity) was an independent variable of the amount of A3 subtypes. The number of awakenings (sleep deconstruction parameter) was the only predictor of the PSQI and the AI (parameter of OSAS severity) was the independent variable of the number of awakenings (Fig. 1).
To our knowledge this is the first study that accurately reconstructs the pathophysiological relationship that connects the SDB with QoL in IPF patients through intermediary and consequential mechanisms represented by sleep fragmentation and symptoms, as explored by ESS and PSQI.
5. Limitations
The limited number of patients studied may have influenced the statistical tests, in particular, it is possible that part of the non-statistical significance was due to the under sizing of the sample. Our results will be confirmed by analysis on more numerous groups, hopefully coming from different centers. However our findings are in line with the existing literature and with the fact that IPF is a rare disease and not easy to recruit. A further limitation could be attributed to the single-night polysomnographic setting, especially in the light of the well-known first night effect, which may influence sleep structural parameters, especially WASO and SE%. However, this reflects clinical routine as most laboratories perform one-night diagnostic sleep studies.
6. Conclusions
Both subjective and objective poor sleep quality are extremely common in patients with IPF and are predicted by variables associated with SDB. Further, poor sleep quality is associated with poor QoL and IPF patients with more severe SDB have worse QoL compared to SDB-free or OSAS-only.
Clinicians should dedicate greater attention to IPF patients when SDB is suspected and, in the absence of an effective therapy for IPF, optimizing the QoL could become a primary therapeutic goal. In this perspective, the diagnosis and treatment of SDB could significantly improve the QoL of IPF patients [
]. The first evidence that treatment of comorbidities such as OSAS can improve the QoL and influence mortality in IPF patients with a difference in survival rates between good and poor CPAP compliant patients was carried out in a recently published multi-center study [
The authors declare that they have no conflict of interest.
Ethical approval
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
Informed consent
Informed consent was obtained from all individual participants included in the study.
Take home message
Poor sleep quality in IPF is predicted by SBD and is linked to low QoL.
References
Raghu G.
Collard H.R.
Egan J.J.
et al.
An official ATS/ERS/JRS/ALAT statement: idiopathic pulmonary fibrosis: evidence-based guidelines for diagnosis and management.
Influence of nocturnal oxygen therapy on quality of life in patients with COPD and isolated sleep-related hypoxemia: a prospective, placebo-controlled cross-over trial.
The cyclic alternating pattern demonstrates increased sleep instability and correlates with fatigue and sleepiness in adults with upper airway resistance syndrome.
30010-1&id=gr1.jpg){kind=link}