Sleep disorders and illness intrusiveness in patients on chronic dialysis

Istvan Mucsi1,2,3, Miklos Zs. Molnar, MD1,4, Janos Rethelyi1, Eszter Vamos1, Gabor Csepanyi1, Gyorgyi Tompa5, Szabolcs Barotfi1,6, Adrienn Marton2 and Marta Novak1,7

1 Psychonephrology Study Group, Institute of Behavioral Sciences and 2 1st Department of Internal Medicine, Semmelweis University Budapest, 4 2nd Department of Internal Medicine, St Margaret Hospital, 5 Nephrocentrum Foundation and 6 Quintiles Hungary Ltd, Budapest, Hungary, 3 Department of Medicine, Faculty of Medicine and 7 Sleep Research Laboratory, Department of Psychiatry, University Health Network, University of Toronto, Canada

Correspondence and offprint requests to: Dr Istvan Mucsi, 21 Mayfair Avenue, Apt. 414, Toronto, ON M5N 2N5 Canada. Email: mucsist{at}net.sote.hu



   Abstract
 Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 References
 
Background. The prevalence of sleep problems (insomnia, restless legs syndrome, periodic limb movements in sleep and sleep apnoea) has been shown to be high in patients with end-stage renal disease (ESRD) and might contribute to impaired quality of life in this population.

Methods. In a cross-sectional study using self-administered questionnaires, we examined the prevalence of sleep disorders and assessed their effect on different aspects of health-related quality of life in a sample of Hungarian patients on maintenance dialysis.

Results. Our data confirm that sleep problems are frequent in patients with ESRD; 65% of the patients reported symptoms of at least one specific sleep disorder; insomnia was the most common sleep complaint with 49%, the prevalence of sleep apnoea was 32% and the prevalence of restless legs syndrome was 15%. Co-morbidity, assessed by the End-Stage Renal Disease Severity Index, was shown to be an independent predictor of sleep disorders. Patients with sleep disorders reported higher illness intrusiveness and worse self-perceived health than those without sleep problems. The presence of sleep disorders was an independent predictor of illness intrusiveness, an important determinant of health-related quality of life.

Conclusion. Sleep disorders are important determinants of illness intrusiveness and health-related quality of life in patients with ESRD. Sleep problems may be treated successfully; therefore, more attention should be paid to assessing these problems in this patient population.

Keywords: illness intrusiveness; insomnia; restless legs syndrome; self-perceived health; sleep apnoea; sleep disorders



   Introduction
 Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 References
 
Sleep complaints and their aetiology in patients with end-stage renal disease (ESRD) have received increasing attention over the last 10 years. Several studies have shown that disorders of sleep and wakefulness are prevalent in these patients. Earlier reports suggested that 30–80% of these patients complain of sleep-related problems, including insomnia, restless legs syndrome (RLS), periodic limb movements in sleep (PLMS) and sleep apnoea syndrome (SAS) [1].

Earlier studies reported large variations in the prevalence of the different sleep disorders. This could be attributed in part to the heterogeneity of the study populations and also to differences of the definitions and criteria of sleep disorders. Furthermore, validated instruments to detect specific sleep disorders were not used in most of the earlier surveys assessing sleep complaints in patients with ESRD. In those works, the presence or absence of sleep problems was determined by asking only a few questions about the key symptoms of sleep disorders. Insomnia and RLS can be diagnosed relatively easily from the history and hetero-anamnesis. However, validated sleep questionnaires may be helpful for the assessment of patients with sleep disorders. Recently, specific self-administered tools have been developed and validated to screen and/or diagnose SAS and RLS [2,3].

Recent evidence suggests a potential link between sleep deprivation, poor sleep quality and sleep disorders, and increased mortality. In renal patients, PLMS and RLS have been shown to be independent predictors of mortality [4,5]. SAS might have a special significance since it may contribute to the increased cardiovascular morbidity and mortality of patients with ESRD. Sleep apnoea might also play a role in the development of specific symptoms (cognitive impairment and other neuropsychiatric problems, and fatigue) which previously were attributed to uraemia. Furthermore, nocturnal hypoxaemia recently has been shown to predict fatal and non-fatal cardiovascular events in chronic dialysis patients [6].

Symptoms and complications of the disease and also treatment factors have an important effect on quality of life (QoL) as perceived by the patients. QoL has been recognized as an independent and important predictor of patient morbidity and mortality. Certain sleep disorders cause excessive daytime sleepiness (EDS) that will have a negative impact on many aspects of everyday life. Furthermore, studies have suggested that sleep disorders may contribute to impaired QoL. Recently, this correlation has also been demonstrated in patients with ESRD [7,8].

The QoL of patients with ESRD is influenced by many clinical and psychosocial factors. Many of those important factors will modulate self-rated health (SRH), that reflects the subjective perception of overall health status determined in part by the ‘objective’ severity of the disease and also by the subjective characteristics of the patient. SRH has been shown consistently to predict survival in a variety of patient populations even after controlling for known prognostic factors. Furthermore, SRH corresponds significantly to objective indicators of health among ESRD patients [9].

Illness intrusiveness was introduced as a concept to represent illness-induced disruptions to lifestyles, activities and interests that compromise QoL [10]. Psychological and social factors act as moderator variables that influence the magnitude of illness intrusiveness occasioned by disease and treatment factors.

The aim of our study was to determine the prevalence of specific sleep disorders in patients on maintenance dialysis. Furthermore, we wanted to analyse predictors of sleep disorders in this population. Finally, we studied the effect of sleep problems on important determinants of health-related QoL, such as SRH and illness intrusiveness. According to our hypothesis, sleep disorders would have a negative impact on important aspects of QoL in patients on maintenance dialysis. In our population, insomnia was the most common sleep problem and the prevalence of sleep disorders was similar to previously reported data. We showed that the severity of co-morbid conditions was an independent predictor of the presence of sleep disorders. Independent of other parameters, sleep disorders had a negative impact on illness intrusiveness.



   Subjects and methods
 Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 References
 
In two dialysis centres in Budapest, 78 out-patients on maintenance dialysis completed a self-administered questionnaire assessing the presence of sleep-related problems, self-perceived health and illness intrusiveness. The study population has been recruited from two dialysis units. All the patients dialysed for at least 3 months in a free-standing dialysis unit in Budapest (58 patients) were approached and asked to participate in the survey; 57 of them agreed to participate. In addition, 22 patients dialysed for at least 3 months at the FMC-SE Dialysis Centre at the 1st Department of Internal Medicine of the Semmelweis University Budapest were asked to participate; 21 of them agreed. This latter group were selected as their primary nephrologist was one of the authors (I.M.). No pre-defined selection criteria have been applied other than (i) willingness and ability to participate; and (ii) receiving chronic dialyisis for at least 3 months at the time of the study. Data describing the basic socio-demographic characteristics of the patients and the most important laboratory parameters were also tabulated.

The study has been approved by the Ethics Committee of the Semmelweis University. Before enrolment, patients received detailed written and verbal information regarding the aims and protocol of the study. Patients completed the questionnaire during or before dialysis sessions. A trained research assistant provided help if necessary.

Assessment of sleep disorders
To assess insomnia, we evaluated the presence and frequency of the most frequent symptoms (such as difficulty falling asleep or maintaining sleep, non-refreshing sleep, inadequate sleep duration). Patients were considered insomniacs if they reported at least one of the symptoms to be ‘frequent’.

Symptoms of SAS were assessed using the Berlin Sleep Apnoea Questionnaire [2]. Based on the answers to the questionnaire, patients are categorized as high or low risk for SAS. RLS was diagnosed by using the RLS Diagnostic Scale [3]. PLMS, which often occurs together with RLS, has been assessed by the presence of two key symptoms, such as rapid, repeated leg kicks during sleep observed by the bed partner and awakenings during the night because of leg movements. Patients indicating both symptoms as ‘frequent’ were considered as having PLMS.

Assessment of daytime sleepiness
Excessive sleepiness was assessed by the Epworth Sleepiness Scale (ESS) [11]. The scale aims to determine how much a person feels sleepy in every-day situations. Higher scores indicate more sleepiness, and scores above 8 indicate significant sleepiness.

Health-related quality of life
Self-perceived health, an important aspect of health-related QoL, was measured using the visual analogue scale (VAS) of the EuroQOL scale [12]. This is a scale with 0–100 range where patients indicate their actual health status as they currently perceive it (100 corresponds to the best and 0 the worst possible health).

Illness intrusiveness was assessed using the Illness Intrusiveness Ratings Scale (IIRS), which assesses the extent to which one's ‘illness and/or its treatment interfere’ with 13 life domains central to QoL. The scale has been used in different patient populations with various chronic conditions including renal patients, and it has been proven to have excellent psychometric properties [13]. Validation of the Hungarian version of the IIRS has been completed by our group recently (M. Novak et al., submitted).

Laboratory parameters and socio-demographic data
Data on the weekly dialysis time, time since the start of dialysis, history of previous transplant, as well as sex, age, body weight and the frequency of hypnotic intake were tabulated. Serum albumin, haemoglobin, serum iron, type of renal disease and dialysis dose (Kt/V) were extracted from the patients’ charts.

Co-morbidity
The severity of co-morbid conditions was assessed with the ‘End-Stage Renal Disease Severity Index’ (ESRD-SI) [14]. The ESRD-SI is completed by the patients’ primary nephrologist. The nephrologist is asked to rate the severity of 12 common co-morbid conditions on scales ranging from 0 to 10. The conditions evaluated in the scale are: cardiac disease, cerebrovascular disease, peripheral vascular disease, peripheral neuropathy, bone disease, respiratory disorders, impaired vision, autonomic neuropathy and gastrointestinal symptoms, dialysis-related events, diabetes and other undefined conditions. This instrument has been shown to be a reliable indicator of co-morbidity in ESRD [15].

Statistics
Statistical analysis was carried out using the SPSS software. Results are shown as mean±SD or median (min–max) if the distribution of data deviated from normal. Groups with and without sleep disorders were compared with Student's t-test, analysis of variance (ANOVA) or the Mann–Whitney U-test, as appropriate. The {chi}2 square test was used to analyse categorical variables. Predictors of sleep disorders and survival were assessed using logistic regression analysis. Predictors of daytime sleepiness, SRH and IIRS were determined using linear regression analysis with stepwise inclusion of variables.



   Results
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 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 References
 
The main characteristics of the patients enrolled in the study are shown in Table 1. Although the sample is small and has not been selected randomly, the main socio-demographic characteristics are similar overall to the characteristics of the Hungarian dialysis population. In a recently completed study, we obtained data on 630 patients dialysed in 10 dialysis units in Budapest. The basic characteristics of our sample presented herein are very similar to the characteristics of the larger cohort (data not shown).


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Table 1. Demographic and clinical characteristics of the patients and average scores of the scales employed

 
Of the 80 patients approached, 78 (97.5%) agreed to participate in the study. Information on the underlying renal disease leading to ESRD was extracted from the charts: 6% of the patients had chronic glomerulonephritis, 15% chronic pyelonephritis, 12% polycystic kidney disease, 27% diabetic nephropathy, 6% ischaemic nephropathy, 13% hypertensive nephropathy and 11% other diseases. In 10% of the patients, we could not identify the underlying renal disease.

Prevalence and predictors of sleep disorders
We found a high prevalence of sleep disorders in our sample: similarly to previous reports, insomnia was the most common sleep disorder, with 49% of the patients reporting symptoms of this condition. Based on the Berlin Questionnaire, 32% of the patients were classified as high risk for sleep apnoea, whereas RLS was diagnosed in 15% of the participants. The prevalence of sleep-related movement disorders (RLS and PLMS together) was 30% and in further analysis this group was considered instead of the RLS group. Overall, 65% of the patients showed symptoms of at least one sleep problem and 21% of them reported more than one.

Demographic and laboratory data of patients with and without sleep disorders (insomnia, risk for sleep apnoea and RLS/PLMS) are shown in Table 2. Demographic parameters and laboratory data did not differ between the groups with or without sleep disorders. The distribution of men and women did not differ in patients with or without insomnia, patients with high vs low risk for sleep apnoea and patients with movement disorders vs no movement disorders. We also found no differences in the prevalence of sleep disorders amongst patients with or without diabetes.


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Table 2 Demographic and clinical characteristics of patients with and without sleep disorders

 
Co-morbidity in the sample, as assessed with the ESRD-SI, showed a negative correlation with serum albumin (r = –0.259, P<0.05), which is a well-known indicator of nutritional status and of overall health of the patients. The co-morbidity index of the groups with any of the sleep disorders was higher than that of the groups without sleep problems (insomnia, 19±11 vs 14±1; apneoa, 22±12 vs 14±10; movement disorder, 23±11 vs 14±11; P<0.05 in each case, Student's t-test). Similar associations were evident when patients were grouped according to the number of sleep disorders reported (no sleep disorder, one, or two or more sleep disorders) (Figure 1): the co-morbidity score increased gradually with increasing number of reported sleep disorders (11±9 vs 16±11 vs 23±10 for patients with no, one, or two or more sleep problems, respectively; P<0.01, ANOVA).



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Fig. 1. Association between the co-morbidity index and sleep disorders. The co-morbidity index of patients with sleep disorders is significantly higher than that of patients without sleep disorders (ANOVA).

 
In a multivariate logistic regression model (including gender, age, diabetes, time since start of dialysis, haemoglobin, serum albumin, Kt/V, ESRD-SI and body weight as independent variables), only the co-morbidity score (ESRD-SI) was a significant and unique predictor of sleep disorders after controlling for all other variables included in the model. For high risk of sleep apnoea, body weight was also a significant and unique independent predictor. For RLS/PLMS, a 5-point increase of the ESRD-SI score corresponded to an odds ratio (OR) of 1.5 [95% confidence interval (CI) 1.1–1.9, P<0.01]. For SAS, a 5-point increase of the ESRD-SI score corresponded to an OR of 1.5 (95% CI 1.1–2.1, P<0.05), and the OR for an increase of 10 kg body weight was 1.9 (95% CI 1.1–3.5, P<0.05). In our model, none of the demographic or clinical parameters we examined correlated significantly and uniquely with insomnia.

Consequences of sleep disorders
EDS is one important consequence of sleep disorders. Daytime sleepiness (ESS score >8) was observed in 31% of the patients. Sleepiness scores did not differ between patients with or without insomnia. Patients with high risk for both sleep apnoea and movement disorders had a significantly higher level of sleepiness than patients without these problems [median for apnoea vs no apnoea: 8 (1–16) vs 4.5 (0–18) and for movement disorders vs no movement disorders: 8.5 (0–17) vs 4 (0–18), P<0.05, Mann–Whitney U-test]. Furthermore, when ESS was compared across the groups having no sleep disorder, one, or more than one sleep problem, the ESS score rose continuously and significantly with increasing number of sleep disorders (Figure 2; P<0.05, Kruskal–Wallis test).



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Fig. 2. Consequences of sleep disorders. Patients with one or more sleep disorder had a significantly higher degree of daytime sleepiness (ESS), higher illness intrusiveness (IIRS) and lower self-perceived health (VAS), compared with patients without sleep disorders (mean±SD). Differences between groups are significant regarding all three variables, P<0.01 (ANOVA and Kruskal–Wallis test, respectively).

 
Interestingly, co-morbidity (measured with ESRD-SI) correlated significantly with ESS (r = 0.309, P<0.01), but there was no significant correlation between ESS vs age or ESS vs any of the laboratory parameters (haemoglobin, serum albumin and Kt/V). Furthermore, in a logistic regression model, only the co-morbidity score, but not the individual sleep problems, correlated independently with sleepiness.

SRH is an important component of health-related QoL. In our sample, SRH was assessed with a VAS from the EuroQOL tool. SRH correlated positively with serum albumin (r = 0.340), and negatively with co-morbidity (r = –0.474) and daytime sleepiness (r = –0.295, P<0.01 for all cases). Patients with sleep disorders reported significantly worse SRH than patients without those conditions (Figure 2, P<0.05, ANOVA). However, using a multivariate linear regression model with ESRD-SI, age, gender, presence of diabetes, time since the start of dialysis, serum albumin, Kt/V, serum haemoglobin and the presence of sleep disorders as independent variables, sleep disorders no longer predicted SRH after correction for other variables. At the same time, SRH remained significantly correlated with co-morbidity (ß = –0.461, P<0.001) and at a near significant level with serum albumin (ß = 0.220, P = 0.072) after controlling for all other variables included in the model (Table 3).


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Table 3. Linear regression model using self-perceived heath (VAS) or illness intrusiveness (IIRS) as independent variables, respectively

 
Illness intrusiveness represents illness-induced disruptions to lifestyles and activities and is thought to be a fundamental determinant of health-related QoL. As expected, co-morbidity correlated positively with illness intrusiveness (r = 0.331, P<0.05). Illness intrusiveness was higher in patients with sleep disorders as compared with those without sleep problems (44±14 vs 36±15 for insomnia vs no insomnia, and 49±17 vs 37±13 for RLS/PLMS vs no RLS/PLMS, respectively, P<0.05; 44±15 vs 38±15 for SAS, P = NS). There was a significant trend for higher illness intrusiveness with increasing number of sleep problems (Figure 2; P<0.05, ANOVA). Illness intrusiveness correlated positively with daytime sleepiness (r = 0.351, P<0.01). In a linear regression model with the IIRS score as the dependent variable, the presence of sleep disorders (the combined variable) and gender were shown to be independent predictors of illness intrusiveness (ß = 0.398, P<0.01 and ß = –0.255, P = 0.03, for sleep problems and gender, respectively) (Table 3).



   Discussion
 Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 References
 
The aim of our study was to assess the prevalence of the most important sleep disorders and examine their predictors in a Hungarian sample of haemodialysis patients. Furthermore, we wanted to study the relationship between sleep disorders and different aspects of health-related QoL.

We are aware of some limitations of our study. Although most studies in renal patients have been conducted in even smaller samples than ours, a significant limitation of our work is the relatively small number of patients involved. Therefore, the negative findings of our study need to be interpreted with caution: where we did not find an expected association, it may simply be a consequence of low statistical power. Despite this potential handicap, we would like to emphasize that we found a clear association between the severity of co-morbidity and the presence of sleep disorders. Furthermore, we have shown that sleep disorders are independent determinants of QoL in patients on maintenance haemodialysis. We currently are conducting two large-scale studies that will illuminate further the clinical significance of sleep disorders among renal patients.

We studied the association between several factors and sleep disorders; furthermore, we analysed the correlation between sleep problems and QoL. Although it is tempting to conclude that impaired sleep may lead to impaired QoL, the cross-sectional design of our study does not allow us to suggest a causal relationship. Prospective studies are needed to answer some of the questions raised, amongst others, by the current study.

Insomnia and RLS can be diagnosed from the history and from the typical symptoms. Overnight polysomnograpy is needed, however, for the definitive diagnosis of sleep apnoea and PLMS. Polysomnography is considered an expensive and not readily available procedure, and might even be difficult to carry out with severely ill patients. It is therefore important to have reliable screening tools to identify these disorders in populations at significant risk. The Berlin Questionnaire has been validated with polygraphy [2] and the RLS Diagnostic Questionnaire has been validated against a diagnostic interview [3]; both these measures may be useful to screen patients at risk.

The prevalence of the specific sleep disorders in our sample was similar to previously published findings. The majority (65%) of the patients reported some sleep problems, and 21% reported more than one disorder. Symptoms suggesting the presence of sleep-related movement disorders (RLS and PLMS) were found in about one-third of patients. Similar frequencies were reported for symptoms of sleep apnoea.

We found no association between sleep disorders and the gender of the patients after correcting for other variables in this sample of chronic haemodialysis patients. This was somewhat surprising. Earlier epidemiological studies showed that insomnia symptoms occur more frequently (~1.5- to 2-fold) in women compared with men. Sleep apnoea is generally more common in men in the general population. Furthermore, the prevalence of sleep disorders generally increases with age, but we did not observe this tendency either. Our study does not provide a firm explanation for the lack of these associations. There may be a specific modifying effect of the renal disease on the pathophysiology of sleep disorders, as suggested by others [16]. The pathophysiology of certain sleep disorders (insomnia, RLS, PLMS, and central and obstructive sleep apnoea) may differ in the general population and in the medically ill. This ‘renal disease-specific’ factor(s) may be reflected partly in the high prevalence of sleep disorders, and partly in the lack of the ‘age effect’ and ‘gender effect’ observed in the general population. The existence of these potential factors is supported by the observations of Hanley and Pierratos [17], in that symptoms of SAS improved dramatically after switching patients from conventional haemodialysis to nocturnal home haemodialysis that provides superb blood purification. Further along these lines, we found that the prevalence of RLS is significantly less in patients living with a functioning renal graft compared with those on maintenance dialysis (M. Zs. Molnar et al., in preparation).

There is a wide variety of potential underlying causes of insomnia symptoms in renal patients, including biological, lifestyle and/or psychological factors. Pathophysiological factors (uraemia per se, iron or folic acid deficiency, diabetes, neuropathy, etc.) have been proposed for RLS and PLMS in this patient population [1]. Benz et al. [4] suggested that uraemia might not be the underlying cause but, rather, a trigger of RLS in patients predisposed to the disease. As for the sleep-related breathing disorders, it is possible that the much less prevalent apnoeas, such as central sleep apnoea, are more common in renal patients than expected, but they are not recognized because polysomnograpy is not carried out. A few studies have suggested that the prevalences of both central and obstructive sleep apnoea may be significantly higher in patients on maintenance dialysis than in the general population (50–80% vs 2–4%) [18].

In the present study, the severity of co-morbidity in haemodialysis patients was an independent risk factor for specific sleep disorders. Higher numbers and increasingly severe co-morbid disorders were associated with an increased likelihood of one or more specific sleep problems. This association was statistically significant for each sleep disorder and remained significant after statistical adjustment for co-variables. Although we can offer no clear explanation for the underlying mechanism, it is plausible that chronic pain caused by some of the chronic conditions present may play a role. Respiratory consequences of cardiovascular diseases, recurrent symptoms caused by co-morbid disorders or side effects of medications used to treat co-morbid conditions may also interfere with sleep.

In this work, we also analysed some of the consequences of sleep disorders. One such ‘outcome’ is daytime sleepiness assessed with the ESS. Our findings support the well-known observation that patients with chronic insomnia do not necessarily complain of pathological sleepiness, probably due to the adaptation to chronic sleep deprivation. We did observe, however, significantly increased pathological sleepiness, as indicated by the ESS, in both the apnoea and the RLS/PLMS groups. Increased daytime sleepiness caused by these problems may interfere severely with normal daily life, and this may be one factor mediating the observed effect of sleep disorders on illness intrusiveness and QoL.

We examined the relationship between sleep disorders and QoL utilizing multiple approaches. To our knowledge, there are only three, recently published studies that have examined the relationship between sleep disorders and QoL in renal patients [7,8,19]. As observed in the present study, earlier studies also found that poor sleep quality and presence of sleep disorders were associated with impaired QoL in patients on maintenance haemodialysis.

Many authors consider SRH as an important determinant of health-related QoL. Measurement of SRH is simple and it is an important indicator both of general health and of the prognosis for various chronic conditions. SRH taps information which is not necessarily picked up by conventional ‘objective’ clinical parameters. As a result, many authors have proposed that SRH should be assessed routinely in clinical and epidemiological studies. In the current study, the VAS scores from the EuroQoL questionnaire correlated significantly and uniquely with co-morbidity (the ESRD-SI).

Health-related QoL is a complex concept that is determined by somatic, psychological, cultural and social factors. Our findings are in accord with this conceptual model. Co-morbidity (and serum albumin, an indicator of overall somatic status at P<0.07) correlated independently with SRH but not with illness intrusiveness. Illness-induced lifestyle disruptions compromise QoL in a more complex way. Illness intrusiveness was associated with several of the variables reflecting a patient's health status in bi-variate analyses, but these associations were no longer significant in multivariate analysis. Alternatively, this negative finding might have been the result of the low statistical power of our study.

At the same time, it is important to note that for each sleep disorder, illness intrusiveness was significantly higher than in patients with no sleep disorder. This strong association underlines the importance of these currently neglected problems. Recently, some studies have reported similar results. As compared with dialysis patients with sound sleep, patients with inadequate sleep report more psychological distress, greater illness intrusiveness and worse QoL [7,8,20]. When considered in the context of those reported by others, the present findings clearly demonstrate that sleep disorders and sleep quality are important determinants of QoL in patients on chronic haemodialysis. This important effect is notable, because sleep disorders can be treated successfully. Improved sleep may, in turn, improve patients’ QoL.



   Acknowledgments
 
We are indebted to the patients dialysed at the Nephrocentrum Dialysis Center and the Fresenius Medical Care-Semmelweis University Dialysis Center for their participation in the study, to the nurses of these units for their help during the survey and to Klára Berta and Kálmán Polner, directors of the two units, for their support. We thank Colin M. Shapiro, Gerald M. Devins and Kenneth Mah for critically reading the manuscript and for their useful comments. Part of this work was presented in abstract form at the ASN 33rd Annual Meeting in Toronto, Canada in 2000. The study was supported by grants from the National Scientific Research Funds (OTKA TS 040889, OTKA T038409, NKFP 1/002/2001-NM, MI) and the Ministry of Health (ETT 240/2000-NM). The study was also supported by unrestricted grants from Janssen-Cilag/Division of Johnson-Johnson Ltd and from Sanofi-Synthélabo Corp. I.M. is a Békésy Postdoctoral Fellow of the Hungarian Ministry of Education. M.Zs.M. is recipient of a research scholarship from the Hungarian Kidney Foundation. M.N. received a research fellowship from MRC Healthcare (Canada).

Conflict of interest statement. Istuan Mucsi has a contract with Fresenius Medical Care Hungary Ltd. to work as a Nephrologist for the company.



   References
 Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 References
 

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Received for publication: 24. 8.03
Accepted in revised form: 19.12.03