1 Institute of Behavioral Sciences, Semmelweis University, Budapest, Hungary, 2 First Department of Internal Medicine, Semmelweis University, Budapest, Hungary, 3 Division of Nephrology, Faculty of Medicine, University of Toronto, Toronto, Canada, 4 Semmelweis University Fresenius Medical Care Dialysis Center, Budapest, Hungary, 5 Department of Transplantation and Surgery, Semmelweis University, Budapest, Hungary and6 Sleep Research Laboratory, Department of Psychiatry, University of Toronto, Toronto, Canada
Correspondence and offprint requests to: Marta Novak, MD, Toronto Western Hospital, UHN, 399 Bathurst St, Toronto, ON M5T 2S8, Canada. E-mail: novis{at}hu.inter.net
![]() |
Abstract |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Methods. Data were obtained from 333 patients on chronic maintenance dialysis. To assess the prevalence of RLS, we used the RLS Questionnaire (RLSQ). The Athens Insomnia Scale (AIS) was used to assess insomnia and QoL was measured with the Kidney Disease Quality-of-Life Questionnaire.
Results. The prevalence of RLS was 14%. The number of comorbid conditions was significantly higher in patients with vs without RLS (median: three vs two; P<0.05). RLS patients were twice as likely to have significant insomnia as patients without RLS (35% vs 16%; P<0.05). Furthermore, RLS was associated with impaired overall sleep quality (median AIS score: 8 vs 4; P<0.01) and poorer QoL. RLS was a significant and independent predictor of several of the QoL domains after statistical adjustment for clinical and socio-demographic covariables. Importantly, this association remained significant even after adjusting for sleep quality.
Conclusions. RLS is associated with poor sleep, increased odds for insomnia and impaired QoL in patients on maintenance dialysis. Based on the present results, we suggest that both sleep-related and sleep-independent factors may confer the effect of RLS on QoL.
Keywords: insomnia; maintenance dialysis; quality of life; restless legs syndrome
![]() |
Introduction |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
The prevalence of RLS is estimated to be between 5 and 15% in the general population [7]. Previous studies have shown a 1262% prevalence in patients with end-stage renal disease (ESRD) [2,3,6,8,9]. These large variations could be attributed, in part, to the heterogeneity of the study populations and also to differences in the definitions of RLS and the tools used to diagnose the syndrome. Clinical diagnostic criteria for RLS have been established by the International RLS Study Group (IRLSSG) and were modified recently [1]. The four minimal criteria of the disorder are:
In the more recent papers that applied the IRLSSG diagnostic criteria, the prevalence of the disorder in the ESRD population was reported to be between 10 and 20%; however, the definitions of the disorder used in those reports were still quite variable [2,9]. Based on the IRLSSG criteria, a diagnostic questionnaire [RLS Questionnaire (RLSQ)] was developed by Allen and Earley [7,10]. The instrument may provide a relatively simple tool to detect RLS in a uniform and comparable manner.
In the general population, the prevalence of RLS increases with age, and women are more frequently affected than men. In a recent report, RLS was associated significantly with social status, worse somatic and mental health and diabetes [7,11]. Other potential correlates of RLS in both the general population and in patients with kidney disease are anaemia and iron deficiency [7]. In patients with ESRD, under-dialysis, iron deficiency and vitamin deficiency may predispose to the disorder [2,12].
Validated instruments to detect specific sleep disorders were used rarely in the earlier surveys assessing sleep complaints in patients with ESRD. A simple, easy-to-administer questionnaire, the Athens Insomnia Scale (AIS), based on the International Classification of Diseases criteria, recently has been established as a useful instrument to measure insomnia in epidemiological studies [13]. In this work, the AIS was used to assess the association of clinically significant insomnia and of specific insomnia symptoms and RLS.
In this study, we assessed the prevalence and correlates of RLS, and also the association of RLS with insomnia and specific sleep complaints using standard validated questionnaires in a sample of patients on maintenance dialysis. We also analysed the relationship between RLS and health-related QoL using the Kidney Disease Quality-of-Life Questionnaire (KDQoL).
![]() |
Subjects and methods |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Demographic information and details concerning the medical history were collected at enrolment when information was obtained about age, gender, level of education, aetiology of ESRD, the presence or absence of diabetes and other comorbidities. The patients completed a battery of validated questionnaires during the dialysis sessions or while waiting for their treatment.
Dialysis-related data were extracted from the medical records and included single pool Kt/V (spKt/V) and vintage, i.e. time elapsed since starting dialysis treatment. Patients were asked to report if they suffered from any of the following comorbid conditions: heart disease, vascular disorder, bone disease, lung disorder, eye disorder, paraesthesias, diabetes mellitus or other conditions. The self-reported comorbidity score was calculated by summing the number of comorbid conditions reported by the patients.
The study was approved by the Ethics Committee of Semmelweis University. Before enrolment, the patients received detailed written and verbal information regarding the aims and protocol of the study.
Assessment of RLS
Symptoms of RLS were identified by using the RLSQ, a patient-completed instrument that has been shown to be a reliable screening tool for RLS [10]. The RLSQ was also used in a recent epidemiological survey [7]. The patients were asked to complete the first part of the questionnaire that included the diagnostic questions. The result was considered positive only if the patient met all the diagnostic criteria. If the questionnaire was not filled completely or the patient did not follow the instructions, the scale was not scored and the information was considered missing.
Assessment of insomnia
The AIS was used to assess sleep complaints and to identify possible cases of clinically significant insomnia. The AIS consists of eight items. The first five items cover night-time symptoms of insomnia (difficulty initiating sleep, difficulty maintaining sleep and early morning awakening) and three items probe daytime consequences of disturbed sleep (well-being, functioning capacity and daytime sleepiness). A recent publication suggested that a cut-off score of 10 provides acceptable sensitivity and specificity based on a prevalence of insomnia of 10% [13]. The Hungarian version of the AIS was prepared following recommended procedures. Internal consistency of the Hungarian version of the AIS was excellent (Cronbach alpha = 0.86) and testretest validation showed a good overall reproducibility (r = 0.716) [15].
The AIS was used to assess individual sleep complaints, to measure overall sleep quality and also to identify cases of potentially significant insomnia using a cut-off of 10 suggested by Soldatos et al. [13]. Night-time insomnia symptoms were classified as difficulty initiating sleep, difficulty maintaining sleep or early awakening.
Health-related QoL
The KDQoL questionnaire was used to assess health-related QoL. The KDQoLSF includes both the 36-item Short-Form Health Survey (SF-36) general measures (eight domains) and 11 domains specific to patients with kidney disease. The KDQoL has been translated into many languages and has been used extensively in dialysis patients, most recently in the multicontinental DOPPS study [16]. The Hungarian version of the KDQoL has been prepared by the FACIT translation group, which followed the FACIT translation methodology [17]. The internal consistency of the individual sub-scales and testretest reliability was similar to the original tool and to other translations. The questionnaire was scored according to the scoring manual. On all scales, the possible scores range from 0 to 100; higher scores indicate better functioning or better QoL.
Statistical analysis
Statistical analysis was carried out using the SPSS 10.0 software. Continuous variables were compared using Student's t-test or the MannWhitney U-test and categorical variables were analysed with the chi-square test or the Fisher exact test, as appropriate. Analysis of variance testing with Bonferroni correction for multiple comparisons was used to analyse the relationship between continuous and categorical variables. Univariate analysis was performed using the Pearson or Spearman correlation analysis, as appropriate. For multivariate analysis, linear or logistic regression was used.
![]() |
Results |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
|
RLS was identified in 45 patients (14%). Most of the socio-demographic characteristics and the clinical parameters were similar between the groups with vs without the condition (Table 1). Specifically, the distribution of gender and the level of education were similar in the group with vs without RLS. Mean age in the two groups was similar. RLS was not associated with the presence of anaemia, iron deficiency (assessed by serum ferritin) or lower serum albumin.
Patients with RLS had somewhat higher median intact parathyroid hormone (iPTH; P<0.05); however, the proportion of clinically significant secondary hyperparathyroidism (iPTH >300 pg/ml) was not different between the two groups. The mean spKt/V and also the proportion of patients with inadequate dialysis dose (spKt/V<1.2) were similar in patients with vs without RLS, although the difference in the latter analysis approached statistical significance [39 vs 25%; odds ratio: 1.706; 95% confidence interval (CI): 0.9852.954; P = 0.058].
RLS was not associated with the presence of diabetes mellitus (Table 1). The number of self-reported comorbid conditions, however, was significantly higher in patients with RLS vs in individuals without this syndrome (P<0.05; Table 1). The prevalence of RLS increased significantly with increasing number of self-reported comorbidities (Figure 1).
|
RLS, insomnia and specific sleep complaints
RLS patients were twice as likely to have significant insomnia as patients without RLS (35 vs 16%; P<0.05; Table 1). Furthermore, patients with RLS had significantly higher AIS scores than patients without this syndrome (median: 8 vs 4; P<0.01).
Patients with RLS more frequently reported the presence of the specific sleep problems assessed by the individual AIS items (Figure 2). Almost 90% of the patients with RLS reported problems with sleep initiation whereas only 50% of the patients without RLS had a similar complaint (P<0.01). Similarly, more than two-thirds of the patients with RLS vs 4045% of the patients without the condition reported problems with sleep fragmentation and early awakening (P<0.01). Daytime consequences of poor sleep (impaired well-being or functioning capacity and sleepiness) were also significantly more frequent complaints in patients with vs without RLS (P<0.01; Figure 2).
|
|
|
|
|
![]() |
Discussion |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
The RLSQ was not completed or was completed only partially by a substantial proportion of patients. As the non-participant group was somewhat older and there were more women in that group, the true prevalence of RLS may be somewhat higher than observed. At the same time, we did not find an association between age or gender vs RLS; therefore, we suggest that the bias introduced by the relatively high number of non-participants might not be too large. Although completion of all the questions requires some focusing and attention, we believe that the response rate can be improved substantially in an interview-like setting where the RLSQ is the main focus of the encounter. In this study, the RLSQ was given as part of a larger battery of questionnaires and this may be one explanation for the high proportion of non-participants.
Large epidemiological studies have identified several correlates of RLS in the general population: the prevalence of the condition was higher in the elderly and in women [11], but this was not seen in all studies. Some studies found an association between the presence of RLS and lower socio-economic status [18]. In our population, RLS was not associated with gender, age or education. Somatic or psychiatric comorbidity has also been associated with RLS in several reports [8,19]. Laboratory and clinical factors were reportedly associated with RLS in dialysis patients in recent studies [9,12]; however, none of those were found consistently to be associated with the syndrome across the studies. We found somewhat higher iPTH and higher number of self-reported comorbid conditions in patients with RLS compared with the group without the condition. Importantly, we also found a significant association between self-reported comorbidity and RLS in a large sample of kidney-transplanted patients [21]. Furthermore, inadequate dialysis dose was associated marginally with RLS in a multivariate logistic regression model. None of the other factors assessed, however, were associated independently with RLS in multivariate analysis. These findings might suggest that in dialysis patients uraemia is the most important, overwhelming risk factor for RLS and, therefore, the association of any other factor with the condition is difficult to detect. Furthermore, because of the relatively low prevalence of RLS, the statistical power of most studies (including ours) might have been inadequate to detect relatively subtle associations.
Anaemia and iron deficiency have been linked to RLS; however, more recent studies have failed to confirm those earlier findings [3,12]. In our study, RLS was not associated with serum haemoglobin level or the presence of iron deficiency (assessed by serum ferritin). The routine use of erythropoietin and relatively large doses of intravenous iron in this population may explain the lack of that expected association as suggested by others [20]. Notably, iron deficiency was a significant independent predictor of RLS in kidney-transplanted patients, in whom intravenous iron was not used routinely [21]. It is also possible that parameters used to assess peripheral iron stores might not reflect brain iron metabolism properly and it is brain and not peripheral iron that might be associated with RLS, as suggested by recent studies [22].
An association between RLS and insomnia in patients on maintenance dialysis has been suggested already by a few papers [46]. Ours is the first report, however, using standard, validated tools to assess these sleep problems in the dialysis population. We report here that patients with RLS are twice as likely to have clinically significant insomnia as dialysis patients without RLS. Furthermore, patients with RLS reported more frequent and more severe insomnia symptoms. Importantly, daytime consequences of disturbed sleep, assessed by the AIS, were also reported more frequently by RLS patients. These results are consistent with the notion that RLS interferes with sleep, resulting in impaired daytime well-being, increased daytime sleepiness and reduced mental and physical functioning capacity.
Unruh et al. [3] have reported recently that RLS was associated with significantly impaired health-related QoL. Using the KDQoL questionnaire, we confirmed and extended their findings. Similarly to their results, RLS in the present study was associated independently with impaired QoL along several domains of the SF-36 general questionnaire after adjustment for several demographic and clinical variables. In addition, we showed here that RLS was associated independently with impaired QoL also along kidney disease-related QoL domains. The difference along most of the domains analysed was quite substantial and was likely to be clinically significant. It has been suggested previously that a 5-point difference on the scales of the KDQoL corresponds to clinically important and perceivable differences in the QoL [16].
The use of the AIS allowed us to analyse the complex relationship between RLS, sleep and QoL in more detail. Importantly, we found that the association between RLS and impaired QoL was partly independent of insomnia or sleep quality (Table 3). These results suggest that RLS symptoms that are not exclusively related to sleep, specifically paraesthesias, discomfort and restlessness, may also have a significant negative impact on the QoL of patients suffering from the syndrome.
Our study is notable for the use of standard, validated tools to assess RLS and insomnia along with a widely used instrument to assess several domains of QoL in patients with CKD. The instruments we used to identify patients with RLS showed excellent sensitivity and specificity in an earlier study [10].
Several limitations of this report should also be noted. The cross-sectional design precludes any directional or causal conclusions. Furthermore, RLS is best diagnosed by an experienced clinician. However, the use of standard, validated questionnaires may still be necessary and useful in studies involving large numbers of patients. We did not have information on peripheral neuropathy, number of pregnancies in women and some other variables that could potentially be associated with RLS. Finally, the proportion of patients who did not complete the RLSQ was substantial in this study, but given the relatively minor differences between the participant and non-participant groups, it is unlikely that this introduced a systematic bias that would distort our conclusions.
In summary, we used the RLSQ for the first time to identify dialysis patients with RLS. The prevalence of RLS was 14%, comparable to recent reports in similar populations. RLS was associated independently with increased odds for clinically significant insomnia, impaired overall sleep quality and poorer QoL after statistical adjustment for clinical and socio-demographic covariables. Importantly, this association remained significant even after adjusting for sleep quality, suggesting that both sleep-related and sleep-independent factors may confer the effect of RLS on QoL.
![]() |
Acknowledgments |
---|
Conflict of interest statement. None declared.
![]() |
References |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
|