Sleep and Breathing

, Volume 14, Issue 4, pp 387–390

How common is sleep-disordered breathing in patients with idiopathic pulmonary fibrosis?


    • Sleep Disorders Center401 General Army Hospital
  • Eleni Stagaki
    • Third Pulmonary DepartmentSismanoglion General District Hospital
  • Stavros Tryfon
    • 1st Pulmonary ClinicG.H. “G. Papanikolaou”
  • Sophia Schiza
    • Sleep Disorders Unit, Department of Thoracic Medicine, Medical SchoolUniversity of Crete
  • Anastasia Amfilochiou
    • Third Pulmonary DepartmentSismanoglion General District Hospital
  • Vlassios Polychronopoulos
    • Third Pulmonary DepartmentSismanoglion General District Hospital
  • Panagiotis Panagou
    • Sleep Disorders Center401 General Army Hospital
  • Nikolaos Galanis
    • 1st Pulmonary ClinicG.H. “G. Papanikolaou”
  • Anastasios Kallianos
    • Sleep Disorders Center401 General Army Hospital
  • Demetrios Mermigkis
    • Third Pulmonary DepartmentSismanoglion General District Hospital
  • Antony Kopanakis
    • Third Pulmonary DepartmentSismanoglion General District Hospital
  • Georgios Varouchakis
    • Sleep Disorders Center401 General Army Hospital
  • Fotis Kapsimalis
    • Sleep Disorders Center401 General Army Hospital
  • Demosthenis Bouros
    • Department of PneumonologyDemocritus Medical School University of Thrace
Short Communication

DOI: 10.1007/s11325-010-0336-5

Cite this article as:
Mermigkis, C., Stagaki, E., Tryfon, S. et al. Sleep Breath (2010) 14: 387. doi:10.1007/s11325-010-0336-5


Background and aim

The frequency of obstructive sleep apnea–hypopnea syndrome (OSAHS) in patients with idiopathic pulmonary fibrosis (IPF) remains controversial. The aim of this study was to assess the frequency of OSAHS in newly diagnosed IPF patients and to identify possible correlations with body mass index and pulmonary function testing parameters.

Materials and methods

Thirty-four newly diagnosed IPF patients were included. All subjects underwent attended overnight PSG. None of the included subjects was under any of the currently available IPF treatments or nocturnal supplemental oxygen therapy.


Total apnea–hypopnea index (AHI) was <5, 5–15, and ≥15/h of sleep in 14 (41%), 15 (44%), and five patients (15%), respectively. REM AHI was statistically significant correlated with TLC [Total lung capacity] (p = 0.03, r = −0.38). Diffusing capacity of the lung for carbon monoxide was correlated with mean oxygen saturation during sleep (p = 0.02, r = 0.39).


Sleep-disordered breathing seems frequent, although remains usually under diagnosed in IPF patients. A decrease in TLC, reflecting the severity of pulmonary restriction, might predispose IPF patients in SDB, especially during the vulnerable REM sleep period.


Idiopathic pulmonary fibrosis (IPF)Polysomnography (PSG)Obstructive sleep apnea–hypopnea syndrome (OSAHS)


Idiopathic pulmonary fibrosis (IPF) is the most frequent type among the idiopathic interstitial pneumonias, but patients with IPF have a poor prognosis (median survival of 2.8 ± 4.0 years), because no therapy has been demonstrated to be efficacious [1, 2].

The frequency of sleep-disordered breathing (SDB) in IPF remains controversial. Recent studies [35] showed a high incidence contrary to previous studies [68] that found SDB uncommon in IPF patients.

The aim of our study was to identify possible SDB in newly diagnosed IPF patients before the start of any of the commonly used IPF treatments and prior to the usually observed rapid progression of the disease. In addition we investigated any possible correlation between polysomnography parameters (apnea–hypopnea index (AHI), sleep oxygenation parameters) and pulmonary function testing (PFT) values or body mass index (BMI).

Material and methods


Thirty-four consecutive patients with IPF, (21 male and 13 female, median age 65 year, range 41–81) evaluated at four Greek Pulmonary Departments during the period of March 2007 to June 2009, participated. Patients were eligible for the study if they had histological proven IPF (usual interstitial pneumonia) on surgical lung biopsy or, in the absence of surgical biopsy, fulfillment of the recent American Thoracic Society and European Respiratory Society criteria [1]. None of the included subjects was under IPF treatment or received nocturnal supplemental oxygen therapy.

The patients had an interview by a sleep specialist. Polysomnography (PSG) was performed as part of a research protocol at the sleep center of each Pulmonary Department. None of the included subjects was referred for sleep evaluation by his treating physician. Hypertension, diabetes, coronary artery disease, GERD, and hypothyroidism were noted in 13, 2, 3, 8, and 1 patient, respectively.

PFT was performed in all patients the day before the PSG.

The Scientific Ethics Committees of all participating centers approved the study protocol, and all participants gave informed written consent.

Demographic and pulmonary function testing data are summarized in Table 1.
Table 1

Demographic, pulmonary function testing (PFT), and polysomnographic (PSG) variables


Total (n = 34)

No OSAHS (AHI < 5; n = 14)

Mild OSAHS (AHI 5–15; n = 15)

Moderate-severe OSAHS (AHI ≥ 15; n = 5)

p valuea

Age (years)

65 ± 10.6

60.9 ± 10.8

67.6 ± 11.2

68.8 ± 6.1









27.3 ± 4

27.6 ± 4.1

26.6 ± 3.3

30.5 ± 4.8



6.2 ± 2.4

5 ± 1.8

6.5 ± 2.3

8.8 ± 1.9


PFT variables

 FEV1 (%)

71.9 ± 18.7

68.8 ± 18.2

71.1 ± 17.2

74.6 ± 12.9


 FVC (%)

72.5 ± 18.1

71.1 ± 15.1

70.4 ± 15.6

72.9 ± 19.8



89.2 ± 14.2

86.8 ± 14.7

91.6 ± 10.3

92.8 ± 21.8



68.1 ± 14.9

68.7 ± 10.1

67.9 ± 16.8

68.2 ± 19.1



53.6 ± 20.9

53.7 ± 24.3

50.1 ± 18.7

58.1 ± 12.2


PSG variables


9.4 ± 8.2

3.1 ± 1.1

9.2 ± 2.9

24.6 ± 16.8



12.9 ± 13.4

5.1 ± 4.2

13.1 ± 12.5

29.2 ± 16.8



8.2 ± 8.1

2.3 ± 1.2

7.9 ± 3.1

22.1 ± 11.9


 Desat. index

9.5 ± 9.2

3.3 ± 1.5

8.6 ± 3.2

27.9 ± 9.8


 Mean oxygen sat (%)

90.9 ± 3.8

91.3 ± 4.8

90.5 ± 3.2

89.6 ± 1.9


 Nadir O2 sat. (%)

81.7 ± 5.8

85.6 ± 4.7

80.2 ± 5.7

79.6 ± 4.2


 TST with O2 sat. <90% (%)

20.8 ± 28.5

12.6 ± 22.7

23.8 ± 32.3

35.7 ± 28.3


All data are given as mean ± SD

BMI body mass index, ESS Epworth sleepiness scale, FEV1 forced expiratory volume in 1 s, FVC forced vital capacity, TLC total lung capacity, DLCO diffusing capacity of the lung for carbon monoxide,% predicted percentage of the predicted value, AHI apnea–hypopnea index, O2 sat oxygen saturated, TST total sleep time

aComparison among groups with no, mild and moderate-severe OSAHS in the ANOVA.



An attended all-night PSG was performed according to established standards [9, 10]. Multi-channel recordings of the electroencephalogram (central and occipital), electro-oculogram, electromyogram, oronasal flow (by thermistor and nasal pressure transducer), respiratory effort (by abdominal and thoracic strain gauges), oxygen saturation (pulse oximmetry), snoring, and body position were recorded on a computerized workstation (Alice 5, Respironics). Studies were scored in 30-s epochs following the new AASM criteria for sleep staging [10].The definition of apneas and hypopneas was performed by the new AASM standard criteria [10]. Both AASM hypopnea rules [10] were used. OSAHS was considered mild if the AHI was ≥5 per hour but <15 per hour, moderate-severe in AHI ≥15 per hour.

Pulmonary function testing

Spirometry (FEV1, FVC; FEV1/FVC ratio), measurement of static lung volumes (total lung capacity [TLC] by body box plethysmography) and measurement of diffusing capacity (diffusing capacity of the lung for carbon monoxide [DLCO] by the single-breath technique) were performed (Vmax22, SensorMedics, Yorba Linda, CA, USA) with the patient in the seated position according to approved standards [11].

Statistical analysis

All data are given as mean ± SD. Data were examined for normal distribution using the Kolmogorov–Smirnov test. The Pearson correlation coefficient was employed to examine the relation between PFT variables, BMI, and PSG parameters. Continuous outcome variables, such as AHI, were analyzed with a one-way analysis of variance. A p value <0.05 was considered as statistically significant.


Clinical interview

Excessive daytime sleepiness, snoring, insomnia, and witnessed apneas were reported in 20%, 38%, 44%, and 23% of the cases, respectively. Epworth sleepiness scale score was 6.2 ± 2.4.

Sleep architecture and respiratory monitoring

On PSG we noted a decrease in sleep efficiency (64.9 ± 14.5%) and REM sleep (10.1 ± 4.8%) and an increase in stage 1 sleep (15.1 ± 7.7%). Sleep macro- and microarchitecture was negatively impaired with an increased arousal index (19.9 ± 12.2/h of sleep) and wake time after sleep onset (54.4 ± 62.7 min).

The overall AHI was 9.4 ± 8.2/h of sleep. AHI 0–5, 5–15, and ≥15/h of sleep was observed in 14 (41%), 15 (44%), and five patients (15%), respectively. Sleep oxygenation abnormalities were observed even in IPF patients without evidence of SDB (Table 1).

Correlation between PFT variables/BMI and PSG parameters

Related to PFT variables only TLC values showed a statistically significant negative correlation with REM AHI (p = 0.03, r = −0.38, Fig. 1). Seven patients had TLC values within normal limits. The last may be seen in early IPF stages due to the wide range of normal TLC values (80–120% predicted) and as a result of air trapping (small airway disease and/or emphysema of the upper lobes) in case of smokers with IPF [12]. DLCO was correlated with mean oxygen saturation during sleep (p = 0.02, r = 0.39).
Fig. 1

Correlation of total lung capacity (TLC) values (% predicted) and REM AHI

The correlation between BMI and AHI showed only a statistical significant trend (p = 0.07, r = 0.33).


To the best of our knowledge this is the first prospective study investigating SDB in a newly diagnosed IPF population group before the start of any treatment (prednisone/azathioprine or alternative medical treatment and/or nocturnal oxygen therapy). An abnormal total AHI (above five respiratory events per hour of sleep) was noted in 59% of the included subjects. REM sleep appears as the most vulnerable period for SDB in IPF patients (REM AHI was above five even in patients with a normal total AHI). In addition REM AHI was statistically significant correlated with TLC.

The frequency of SDB in IPF patients is controversial with newer studies [35] showing increased OSAHS incidence in this population compared to previous studies [68] dating back 10–20 years. The use of more sensitive equipment for airflow measurement (nasal pressure transducer in addition to oronasal thermistor) and the new AASM definition of hypopneas [10] is probably the main factor explaining the different results of previous studies. In addition the use of a different IPF terminology and the diagnostic criteria (American Thoracic Society/European Respiratory statements) [1] has significantly changed the inclusion criteria for IPF patients in various studies. Our data have similarities to those recently published by Lancaster et al. [3] that show an increased incidence of OSAHS in IPF patients. In the above study forty-four of 50 subjects (88%) had OSAHS as defined by an AHI of ≥5 events per hour. Ten subjects (20%) had mild OSAHS (AHI, 5 to 15 events per hour), and 34 subjects (68%) had moderate-to-severe OSAHS (AHI >15 events per hour). Our results showed an increased OSAHS incidence in IPF patients (59% of included IPF had OSAHS with 44% having mild and 15% moderate-severe OSAHS), although not in the degree reported by Lancaster et al. [3]. A possible explanation might be related to the fact that our group did not include patients under prednisone treatment that may increase respiratory events due to changes in BMI and neck fat distribution. In addition the PFT data from the Lancaster study showed an increased IPF severity in those subjects compared to our group. Despite the above differences the main point in both studies is the increased incidence of OSAHS in IPF patients that remains usually underdiagnosed.

Restrictive pulmonary diseases like IPF are characterized by decreased lung volumes that can reduce the upper airway stability and increase resistance due to a decreased traction on the upper airway. These changes can facilitate the upper airway collapse, especially during REM sleep when functional residual capacity is further reduced due to the inactivity of the intercostal muscles [1315]. Based on this theory one would expect a significant correlation between AHI and values of PFT such as FVC and TLC. Such a correlation, based on our data, was established only between TLC and REM AHI. A decrease in TLC, reflecting the severity of pulmonary restriction, might predispose IPF patients in SDB, especially during the vulnerable REM sleep period. The lack of inverse correlation between the FVC and TLC and total AHI that reflects the severity of sleep apnea may be explained by the use of PFTs performed with the patient in the upright position. Assessment of lung volumes with the patient in the supine position has several technical difficulties although may be more accurate at predicting sleep lung volumes and may better display interdependence between the upper airway and lung volumes during sleep.

The main question rising by our study is whether IPF patients with an AHI ≥ 5, which represent the major part of our study group, should be treated with CPAP. Polysomnography is usually not performed in these patients since sleep interview is generally not very useful and excessive daytime sleepiness is reported only by the minority of such patients. In addition despite growing OSAHS awareness among healthcare providers, we believe that treating physicians may defer sleep testing because IPF is characterized by such a rapidly progressive course leading them to focus on more acute problems such as dyspnea and limitations in daily activities.

On the other hand in the absence of any effective treatment for IPF so far, the improvement of quality of life should be a primary therapeutic goal. A CPAP trial in such cases might improve quality of life parameters and should probably be the object of a future study. In cases with an AHI ≥ 15, CPAP therapy can be initiated based on currently existing criteria, although its impact in overall quality of life in this patient group remains unknown.

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© Springer-Verlag 2010