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NDT Advance Access originally published online on February 3, 2007
Nephrology Dialysis Transplantation 2007 22(4):1190-1197; doi:10.1093/ndt/gfl748
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© The Author [2007]. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

The predictors of central and obstructive sleep apnoea in haemodialysis patients

Takeshi Tada1, Kengo Fukushima Kusano1, Aiko Ogawa1, Jun Iwasaki1, Satoru Sakuragi1, Isao Kusano2, Seiko Takatsu3, Masashi Miyazaki3 and Tohru Ohe1

1Department of Cardiology, University of Okayama Graduate School of Medicine, 2Fukushima Naika Clinic and 3Saiwaicho Memorial Hospital, Okayama, Japan

Correspondence and offprint requests to: Takeshi Tada, MD, Department of Cardiology, Okayama University Graduate School of Medicine, 2-5-1 Shikatacho, Okayama 700-8558, Japan. Email: gmd17011{at}cc.okayama-u.ac.jp



   Abstract
Top
 Abstract
Introduction
 Subjects and methods
 Results
 Discussion
 References
 
Background. Sleep apnoea (SA) is often observed in haemodialysis patients, but there have been few studies on types of SA and their predictors. We therefore investigated the prevalence and types of SA and the associations between types of SA and clinical factors in haemodialysis patients.

Methods. We initially examined nocturnal oxygen desaturation index (ODI) (desaturation of >4%/events per hour) in 119 haemodialysis patients (68 males, mean age of 61.4 years). Patients with ODI of more than five were diagnosed as having SA. Then, 30 patients underwent polysomnography and we measured Apnoea–hypopnoea index (AHI), which was calculated as the number of apnoeas plus hypopnoeas per hour of sleep. Clinical characteristics were examined in all patients.

Results. Forty-one (34.5%) of the 119 patients had SA. Twenty-seven (22.7%) of the 119 patients had SA with subjective symptoms such as daytime somnolence and snoring. There was a significant difference between body mass index (BMI) in patients with SA and that in patients without SA (22.5 vs 19.8 kg/m2, P < 0.001). There were significantly higher prevalences of hypertension (85.4 vs 66.7%, P < 0.05) and diabetes mellitus (36.6 vs 10.3%, P < 0.01) in patients with SA than those in patients without SA. Multivariable analysis showed that BMI was independently associated with the occurrence of SA (OR 1.20, 95% CI 1.05–1.38). Mean AHI of 30 patients who underwent polysomnography was 53.2 ± 28.9 [central apnoea, 4.1 ± 5.6 (8%); obstructive apnoea, 21.7 ± 21.5 (42%); mixed apnoea, 4.9 ± 8.0 (9%); hypopnoea, 21.4 ± 15.5 (41%)]. The number of obstructive apnoea events per hour was significantly correlated with BUN (r = 0.490, P < 0.01), Cr (r = 0.418, P < 0.05) and BMI (r = 0.489, P < 0.01) and was inversely correlated with serum bicarbonate (r = –0.646, P < 0.01) and brain natriuretic peptide (BNP) (r = –0.481, P < 0.01). The number of central apnoea events per hour was correlated inversely with PaO2 (r = –0.393, P < 0.05) and PaCO2 (r = –0.388, P < 0.05) and tended to be correlated with cardiothoracic ratio (CTR) (r = 0.347, P = 0.060).

Conclusions. There is a high prevalence of SA in haemodialysis patients. The dominant type of SA in haemodialysis patients is obstructive sleep apnoea (OSA). Uraemia (BUN, Cr), metabolic acidosis (serum bicarbonate) and BMI are good predictors of OSA. PaO2, PaCO2 and CTR are good predictors of central sleep apnoea (CSA). Good management of these factors might improve SA in haemodialysis patients.

Keywords: sleep apnoea syndrome; obstructive sleep apnoea; central sleep apnoea; haemodialysis



   Introduction
Top
 Abstract
 Introduction
Subjects and methods
 Results
 Discussion
 References
 
Sleep apnoea syndrome (SAS) is a common disease. A survey has shown that 9% of women and 24% of men of middle age are affected by sleep-disordered breathing, diagnosed by an apnoea–hypopnoea index (AHI) of more than five. Male sex and obesity were strongly associated with the presence of sleep-disordered breathing [1].

There are three types of sleep apnoea (SA): obstructive sleep apnoea (OSA), central sleep apnoea (CSA) and mixed apnoea [2]. There are many differences in pathogenic mechanism and complications between OSA and CSA.

It has been reported that OSA is strongly associated with cardiovascular risk factors, including obesity, hypertension, hyperlipidaemia and diabetes mellitus [3]. It has also been reported that OSA is associated with a high incidence of cardiovascular diseases, including coronary artery disease and stroke [4]. Although the mechanisms by which OSA is correlated with cardiovascular diseases are unclear, there is evidence that OSA is associated with oxidative stress and inflammatory factors [5,6] that play an important role in the development of atherosclerosis.

CSA has a high prevalence in chronic heart failure (CHF) patients with left ventricular dysfunction [7]. The AHI is a powerful independent predictor of poor prognosis in patients with CHF [8]. CHF leads to pulmonary congestion that activates lung vagal irritant receptors and stimulates hyperventilation and hypocapnia. Arousals cause further abrupt increases in ventilation and drive PaCO2 below the threshold for ventilation, triggering a central apnoea. CSAs are sustained by recurrent arousals resulting from apnoea-induced hypoxia and the increased effort to breathe during the ventilatory phase because of pulmonary congestion and reduced lung compliance [9].

The prevalence of SA in haemodialysis patients is high [10] and SA has an adverse effect on the quality of life in haemodialysis patients [11]. Zoccali et al. [12] reported that nocturnal hypoxaemia due to SA is associated with important cardiovascular risk factors such as the non-dipping arterial pressure profile and left ventricular hypertrophy in haemodialysis patients. Recent studies have shown that SA is associated with hypertension and severe coronary artery disease in haemodialysis patients [13,14], but there have been few studies on types of SA and their predictors in haemodialysis patients. This study was therefore carried out to investigate the prevalence and types of SA and the association between types of SA and clinical factors in haemodialysis patients.



   Subjects and methods
Top
 Abstract
 Introduction
 Subjects and methods
Results
 Discussion
 References
 
Patient characteristics
Two hundred eleven patients, who had end-stage renal disease and had been receiving maintenance haemodialysis treatment for at least 3 months in two hospitals in Okayama (Fukushima Naika Clinic and Saiwaicho Memorial Hospital) during the period February 2005 to October 2005, were asked to participate to this study. Patients with a history of SAS or pulmonary disease were excluded.

One hundred nineteen patients (68 males and 51 females, mean age of 61.4 ± 10.8 years) participated in this study. They were all out-patients and dialysed three times a week for about 4 h each with a bicarbonate buffered dialysate.

We initially performed nocturnal oximetry over one haemodialysis night at home using a pulse oximeter in all 119 haemodialysis patients. Then we performed polysomnography over a night (of a haemodialysis day) or two consecutive nights (of a haemodialysis day and a non-haemodialysis day) in 30 haemodialysis patients who agreed to undergo polysomnography.

Clinical characteristics including age, sex, subjective symptoms (daytime somnolence and snoring), aetiology of renal failure, BMI, smoking status, medications, cardiothoracic ratio (CTR), duration of haemodialysis, the mean of dialysis doses in three haemodialysis sessions of the week (mean dialysis dose), laboratory parameters (haemoglobin and serum albumin) and coexistence of hypertension, hyperlipidaemia, diabetes mellitus, atrial fibrillation and peripheral artery disease were examined in all patients.

We also examined clinical data, including left ventricular ejection fraction (LVEF) and left ventricular mass index assessed by 2D echocardiography, blood gas analysis, haemoglobin, serum albumin, blood urea nitrogen (BUN), serum creatinine (Cr), plasma brain natriuretic peptide (BNP), haemoglobin A1c (HbA1c) and C-reactive protein for patients who underwent polysomnography.

Blood samples of all patients were drawn at the start of a dialysis session. Blood samples, including the samples of blood gas analysis, of 30 patients who underwent polysomnography for detailed examination were drawn within 30 min after the end of polysomnographic studies. All laboratory parameters were measured using standard laboratory techniques with automatic analyser.

Pulse oximetry test for primary diagnostic examination
Nocturnal oximetry was performed over one night at home using a pulse oximeter (Pulsox-24M, Teijin Ltd.) placed on the subject's finger with a flexible probe. The oximeter detected 12 data points per minute, with each point representing the lowest saturation determined for a 5 s interval. Baseline oxygen saturation was defined as the mean oxygen saturation of the previous minute. A desaturation event was defined as a fall in saturation of >4% below the baseline saturation level or a fall in saturation of >4% during the 90–100% saturation interval. The signals were digitized and recorded by means of software included with the oximeter. We removed artifacts due to body movement by using a data analysing system (DS-M) included with the pulse oximeter.

Four percent oxygen desaturation index (4% ODI) was calculated as the number of desaturation events per hour of sleep, and patients with (4% ODI) of more than five were diagnosed as having SA [15,16].

Polysomnography for detailed examination
Polysomnography was performed over a night (of a haemodialysis day) or two consecutive nights (of a haemodialysis day and a non-haemodialysis day) using Alice4 (Respironics Inc., PA, USA), which records naso-oral airflow, chest and abdominal wall excursions, oxygen saturation, body position, electro-oculogram, electroencephalogram, electromyogram of the submental muscles, electromyogram of the anterior tibialis muscle of both legs and electrocardiogram. Arousals were scored according to accepted definitions [17]. Apnoea was defined as complete cessation of airflow for >10 s. Hypopnoea was defined as reduction of airflow by >50% associated with fall in oxygen saturation of >3% or arousal. Apnoea–hypopnoea events were classified into four types; OSA, CSA, mixed apnoea and hypopnoea. OSA was defined as the absence of airflow in the presence of rib cage and abdominal excursions. CSA was defined as the absence of rib cage and abdominal excursions with an absence of airflow. Mixed apnoea was defined as the absence of airflow that were initially associated with an absence of rib cage and abdominal excursions and that persisted upon resumption of rib cage and abdominal excursions indicating upper airway obstruction. AHI was calculated as the number of apnoeas plus hypopnoeas per hour of sleep. CSA index was defined as the number of CSA per hour of sleep. OSA index was defined as the number of OSA per hour of sleep. Mixed apnoea index was defined as the number of mixed apnoea per hour of sleep. Hypopnoea index was defined as the number of hypopnoea per hour of sleep. Patients with AHI of more than five at least in one night study were diagnosed as having SA [2].

CSA-dominant patients (CSA patients) were defined as patient CSA index of more than five. Other patients were defined as OSA-dominant patients (OSA patients).

Data analysis
The data expressed as means ± SD. Inter-group comparison was done by the {chi}2 independence test or Fisher's exact probability test, and difference in mean values was tested by Student's t-test, at a critical level of 5% or lower. If the non-normal distribution of data was confirmed by the one sample Kolmogorov–Smirnov test, a Mann–Whitney U-test was performed. To assess the independent predictor of the occurrence of SA, multivariable logistic regression analysis was performed for all 119 patients. To assess the predictors of the severity of SA, the relationship between AHI, OSA index, CSA index and other variables was evaluated by Spearman's rank correlation analysis. All data were analysed using SPSS software.



   Results
Top
 Abstract
 Introduction
 Subjects and methods
 Results
Discussion
 References
 
We examined ODI in 119 haemodialysis patients (68 males and 51 females, mean age of 61.4 ± 10.8 years). Our patients’ clinical characteristics are shown in Table 1. The renal diseases in our patients included chronic glomerulonephritis in 71 (59.7%) patients, diabetic nephropathy in 24 (20.2%), polycystic kidney in seven (5.9%), pregnancy-related renal disease in six (5.0%), nephrosclerosis in four (3.4%), gout kidney in two (1.7%), IgA nephropathy in two (1.7%), purpura nephritis in two (1.7%) and chronic pyelonephritis in one (0.8%). Sixty-two of 119 patients (52.1%) had some subjective symptoms such as daytime somnolence and snoring.


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  		Table 1. Clinical characteristics of patients (n = 119)

 
The prevalence of SA in haemodialysis patients and their clinical characteristics
Forty-one (34.5%) of the 119 patients had 4% ODI of more than five and were diagnosed as having SA. Twenty-seven (22.7%) of the 119 patients had SA with subjective symptoms such as daytime somnolence and snoring. There was a significant difference between BMI in patients with SA and those in patients without SA (22.5 vs 19.8 kg/m2, P < 0.001) (Table 2). Patients with SA tended to have a larger mean dialysis dose than did patients without SA (2.8 ± 1.1 vs 2.5 ± 0.9 l, P = 0.056) (Table 2). No difference was found between patients with and those without SA in age, sex, duration of haemodialysis and CTR (Table 2). No medications affected the prevalence of SA.


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  		Table 2. Clinical characteristics of patients with and without SA (n = 119)

 
There were significantly higher prevalences of hypertension (85.4 vs 66.7%, P < 0.05) and diabetes mellitus (36.6 vs 10.3%, P < 0.01) in patients with SA than in patients without SA, but no difference was found between patients with SA and those without SA in prevalence of hyperlipidaemia, atrial fibrillation or peripheral artery disease (Table 2).

Multivariable analysis showed that BMI was independently associated with occurrence of SA (OR 1.20, 95% CI 1.05–1.38, P = 0.008) (Table 2).

The severity and types of SA in haemodialysis patients
Thirty patients underwent polysomnography. All of them had AHI of more than five at least in the one night study. Mean AHI was 53.2 ± 28.9 [CSA index, 4.1 ± 5.6 (8%); OSA index, 21.7 ± 21.5 (42%); mixed apnoea index, 4.9 ± 8.0 (9%); hypopnoea index, 21.4 ± 15.5 (41%)] (Figure 1).


Figure 1
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  		Fig. 1. Distribution of four types of apnoea–hypopnoea events in 30 haemodialysis patients who underwent polysomnography. CSA, central sleep apnoea; OSA, obstructive sleep apnoea.

 
The association between AHI and clinical factors in haemodialysis patients
AHI was significantly correlated with BUN (r = 0.436, P < 0.05), Cr (r = 0.475, P < 0.01) and BMI (r = 0.408, P < 0.05), and was inversely correlated with serum bicarbonate (r = –0.600, P < 0.01) and BNP (r = –0.406, P < 0.05) (Table 3).


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  		Table 3. The correlation between AHI and clinical factors (n = 30)

 
OSA index was significantly correlated with BUN (r = 0.490, P < 0.01), Cr (r = 0.418, P < 0.05) and BMI (r = 0.489, P < 0.01), and was inversely correlated with serum bicarbonate (r = –0.646, P < 0.01) and BNP (r = –0.481, P < 0.01) (Table 3).

CSA index was inversely correlated with PaO2 (r = –0.393, P < 0.05) and PaCO2 (r = –0.388, P < 0.05) and tended to be correlated with CTR (r = 0.347, p = 0.060) (Table 3).

The difference of clinical factors between CSA and OSA patients
Of 30 patients, eight were defined as CSA patients with CSA index more than five. The other 22 patients were defined as OSA patients. CSA patients had a larger CTR than did OSA patients (52.1 vs 46.9%, P < 0.05). CSA patients tended to have a higher prevalence of atrial fibrillation (25 vs 0%, P = 0.064). No difference was found in other variables between CSA and OSA patients (Table 4).


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  		Table 4. The difference of clinical factors between CSA and OSA patients

 
The difference of AHI between haemodialysis night and non-haemodialysis night
Nineteen patients underwent polysomnography over two consecutive nights. There was no significant difference between the values of AHI on two nights in any of the patients (Figure 2A). However, in CSA patients, AHI on the non-haemodialysis night was significantly higher than on the haemodialysis night (67.8 vs 57.5, P < 0.05) Figure 2B. No difference was found in OSA patients (Figure 2C).


Figure 2
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  		Fig. 2. Difference of the value of apnoea–hypopnoea index (AHI) between on a haemodialysis night and on a non-haemodialysis night. (A) There was no significant difference between the values of AHI on two nights in any of the patients. (B) In CSA patients, AHI on the non-haemodialysis night was significantly higher than that on the haemodialysis night. (C) No difference was found in OSA-dominant patients. CSA, central sleep apnoea; OSA, obstructive sleep apnoea.

 


   Discussion
Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
References
 
Our study showed that there was a high prevalence of SA (34.5%) which is consistent with the results of previous studies [10,14,18]; the reason for the high prevalence is unclear. Some studies have suggested that uraemic toxins, metabolic acidosis, chronic hypocapnia, amino-acid metabolism abnormalities and hormone imbalance are associated with the occurrence of SA in haemodialysis patients [19–21], but few studies have shown an association between AHI and clinical factors in haemodialysis patients. Our study showed that metabolic acidosis (serum bicarbonate), uraemia (BUN, Cr) and BMI had significant associations with AHI in 30 haemodialysis patients. PaO2, PaCO2 and CTR were associated with CSA index, while metabolic acidosis, uraemic toxins and BMI were associated with the OSA index.

Our study showed that PaO2 and PaCO2 were correlated inversely with the CSA index and that CTR tended to be correlated with the CSA index. Moreover, CSA patients had larger CTR than did OSA patients, and patients with SA tended to receive a larger mean dialysis dose than did patients without SA. These results suggest that the fluid overload causes pulmonary congestion leading to the activation of lung vagal irritant receptors and that compensatory hyperventilation might trigger CSA in haemodialysis patients. This mechanism of occurrence of CSA in haemodialysis patients might be similar to that in CHF patients [9].

Millman et al. [20] showed that there was a correlation between the degree of azotaemia (BUN and Cr) and AHI in six haemodialysis patients. Our study showed that uraemia (BUN and Cr) was correlated with OSA index in 30 haemodialysis patients but that it was not correlated with CSA index. The mechanism of occurrence of OSA by uraemia is unknown, but Fein et al. [21] described a patient who presented with severe OSA associated with uraemia, which significantly resolved following intensive haemodialysis. They suggested that the occurrence of OSA by uraemia was caused by excessive reduction in airway muscle tone due to a generalized depressive effect of uraemic toxins on the central nervous system during sleep, and to an instability of respiratory control due to central effects of uraemia leading to discoordination of diaphragm and upper airway muscle activity [21].

Our study showed that serum bicarbonate was also correlated inversely with OSA index. The reason is unclear, but Sharp et al. [22] showed that metabolic acidosis induced by acetazolamide converted central apnoea to obstructive apnoea, and they suggested that metabolic acidosis might stimulate the activity of the bellows muscles (diaphragm, intercostals, scalene) to a greater extent than it stimulates the upper airway muscles, resulting in upper airway closure. Haemodialysis patients may be predisposed to upper-airway occlusion due to airway oedema, which is associated with fluid overload, and to reduced muscle tone, which is associated with uraemic toxins [21]. In this condition, inappropriate respiratory drive due to metabolic acidosis might likely cause OSA.

Langevin et al. [23] reported that OSA in a haemodialysis patient improved after renal transplantation. Hanly and Pierratos [24] reported that nocturnal haemodialysis decreased serum creatinine concentration, increased serum bicarbonate concentration and improved not only CSA but also OSA in patients with chronic renal failure. These results might support that uraemic toxins and metabolic acidosis had important roles in the occurrence of OSA.

In our study, BMI was an independent predictor of occurrence of SA and was significantly correlated with AHI and OSA index. The mean BMI of the patients with SA in our study was higher than that of the patients without SA (22.5 vs 19.8 kg/m2), but the mean BMI of the SA patients was rather low compared with the mean BMI of Japanese epidemiological study cohort (22.5 vs 23.0 kg/m2) [25]. In our study, BMI was significantly correlated with BUN (r = 0.669, P < 0.001) and Cr (r = 0.598, P < 0.001) and was inversely correlated with serum bicarbonate (r = –0.768, P < 0.001). These overlapping correlations with other clinical factors that exacerbate the severity of SA might make BMI a strong predictor of the occurrence of SA in haemodialysis patients. We supposed that the high BMI in the patients with SA in our study might mean that not obesity but high uraemic toxins and low serum bicarbonate cause upper-airway obstruction.

Our study showed that BNP was inversely correlated with OSA index. We supposed that it was not because BNP had a direct effect on OSA but because it was significantly correlated with uraemic toxins and inversely with serum bicarbonate (data not shown).

Mendelson et al. [10] showed that there was no significant difference between the values of AHI on haemodialysis nights and non-haemodialysis nights and they concluded that conventional haemodialysis treatment could not acutely improved SA. In our study, CSA patients had lower AHI on haemodialysis nights than on non-haemodialysis nights. No difference was found in OSA patients. These results suggest that haemodialysis can acutely improve CSA but not OSA. The reason is unclear, but we thought that it might be because the respiratory response to the change in fluid overload that caused CSA was quicker than the respiratory response to the change in uraemic toxins that caused OSA.

There have been few studies on types of SA in haemodialysis patients. Hanly and Pierratos [24] showed an even distribution of central, obstructive and mixed respiratory events in haemodialysis patients. Meanwhile de Oliveira Rodrigues et al. [14] reported that obstructive apnoea was the predominant finding and that central apnoea was 6.2% of total apnoea–hypopnoea events. Our study using polysomnography also showed that OSA was dominant in haemodialysis patients. We found that volume overload exacerbated the CSA in haemodialysis patients and that mean CTR of our patients who underwent polysomnography was 48.3%. It was unclear why the OSA was dominant in our study, but one reason might be that good management of body fluid volume decreased CSA in our patients. We showed that CSA index was inversely correlated with PaCO2 and that OSA index was inversely correlated with serum bicarbonate. Moreover, we found that PaCO2 was significantly correlated with serum bicarbonate (data not shown). These results suggest that the occurrence of CSA and OSA are mutually related and that it is difficult to distinguish clearly between CSA dominant patients and OSA dominant patients. In fact, our study showed that the patients we defined as CSA patients had a high OSA index. We therefore, could not find a difference between clinical factors in CSA patients and those in OSA patients except for CTR and atrial fibrillation (Table 4). We have the impression that OSA occurs commonly due to uraemic toxins and metabolic acidosis in haemodialysis patients and that CSA occurs secondary to clinical factors such as fluid overload, hypoxia and hypocapnia. Atrial fibrillation has a significant association with CSA in congestive heart failure patients [7]. Our results suggest that atrial fibrillation might have an important role in occurrence of CSA in haemodialysis patients.

We used pulse oximetry to establish the diagnosis of SA, and not all of the patients underwent polysomnography. Although the formal diagnosis of SA requires polysomnographic studies, Series et al. [26] showed that nocturnal of home oximetry is helpful in ruling out the diagnosis SA in patients clinically suspected of having SA. Oeverland et al. [16] showed that pulse oximetry is sufficient to establish a diagnosis of moderate-severe SA with AHI above 15. We therefore used pulse oximetry as an initial diagnostic test for SA in haemodialysis patients.

When we investigated the types of SA in the 30 patients, we did not take mixed apnoea and hypopnoea into consideration because there is no consensus on how to classify them into a CSA or OSA component.

We took the samples of blood gas analysis in 30 patients who underwent polysomnography within 30 min after the end of polysomnographic studies. So, the value of PaCO2 and PaO2 might change compared with the value of those during sleep. But the value of serum bicarbonate might not change because it changes slowly. We found that PaCO2 and PaO2 were inversely correlated with CSA index, but could not find a difference between the mean value of PaCO2 and PaO2 in CSA patients and those in OSA patients. If we had obtained the blood samples during sleep, we might have observed a different result in terms of PaCO2 and PaO2.

In conclusion, there is a high prevalence of SA with high prevalence of hypertension and diabetes mellitus in haemodialysis patients. OSA is the dominant type of SA in haemodialysis patients. Uraemia (BUN, Cr), metabolic acidosis (serum bicarbonate) and BMI are good predictors of OSA. PaO2, PaCO2 and CTR are good predictors of CSA. Good management of these factors might improve SA in haemodialysis patients.



   Acknowledgment
 
The authors thank Saori Nobusada, Yumiko Makita, Yuka Toda, Hiroshi Minabe (Department of Central Clinical Laboratory, Okayama University Hospital), Yoshikiyo Takaoka (Teijin Ltd.), Kokoro Matsuzaki (Fuji Respironics Co., Ltd.), and technical staffs of Fukushima Naika Clinic and Saiwaicho Memorial Hospital) for their excellent technical assistance.

Conflict of interest statement. None declared.



   References
Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 References
 

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Received for publication: 12. 7.06
Accepted in revised form: 13.11.06


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T. Masuda, M. Murata, S. Honma, Y. Iwazu, M. Ogura, A. Onishi, K. Shimada, E. Kusano, and Y. Asano
Pulse oximetry is useful for screening sleep apnoea syndrome in dialysis patients
NDT Plus, May 13, 2008; (2008) sfn052v1.
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