| Abstract|| |
Sleep complaints are common in hemodialysis (HD) patients. Sleep quality (SQ) is a predictor of quality of life and mortality risk in HD. The aim of this study was to examine factors that may have a role in SQ. In this cross-sectional analytic study, 138 end-stage renal disease patients receiving maintenance HD for >3 months were included. The Pittsburgh Sleep Quality Index (PSQI) was used to measure individual's SQ. Patients with a global PSQI score >5 were assumed as poor sleepers. Eighty-eight patients (64%) were classified as poor sleepers. Poor sleepers were older and more likely had diabetes. They had significantly higher serum ferritin and calcium levels and lower serum parathyroid hormone level (all P-values <0.05). The global PSQI score was positively correlated with age, serum calcium level and presence of diabetes as the underlying cause of renal failure. In the multi-variable binary regression model, presence of diabetes (Odds Ratio (OR) = 3.67, P = 0.008) and body pain (OR = 1.182, P = 0.014) were the significant independent predictors for poor SQ. Poor SQ was common among our HD patients, especially among diabetic cases and, therefore, there is a need to pay more attention to the care of this subgroup with regard to the diagnosis and management of sleep complaints.
|How to cite this article:|
Edalat-Nejad M, Jafarian N, Yousefichaijan P. Diabetic nephropathy: A strong predictor of sleep quality in hemodialysis patients. Saudi J Kidney Dis Transpl 2014;25:774-80
|How to cite this URL:|
Edalat-Nejad M, Jafarian N, Yousefichaijan P. Diabetic nephropathy: A strong predictor of sleep quality in hemodialysis patients. Saudi J Kidney Dis Transpl [serial online] 2014 [cited 2019 Nov 17];25:774-80. Available from: http://www.sjkdt.org/text.asp?2014/25/4/774/134994
| Introduction|| |
In the past two decades, sleep disorders and its predicting factors in patients on maintenance hemodialysis (HD) has attracted the attention of many researchers. According to the literature, 30-80% of HD patients have sleep disorders such as insomnia, restless leg syndrome, sleep latency and sleepiness during the day. ,,,,,,,,,,,  As shown by recent studies, there is a potential association between poor sleep and lower quality of life and increased mortality. ,,,,, 
In recent years, possible factors affecting sleep have been extensively studied, but some controversy existed. Some studies have shown the association between sleep problems and higher levels of urea, phosphate and parathyroid hormone, ,, and even some small surveys have found sleep quality (SQ) improvement after parathyroidectomy. , Also, some studies corroborated the role of inflammation in the pathogenesis of sleep distur-bance. 
The large numbers of articles that are being published about sleep disorder show that, the answer to the mystery of sleep pathogenesis and predisposing factors for insomnia still remain unresolved. Therefore, this study was carried out to investigate the association of the underlying disease of kidney failure, anthropometric parameters and various laboratory values, including parathyroid hormone (PTH) with SQ in HD patients of our university hospital.
| Subjects and Methods|| |
This cross-sectional study was performed within a HD unit of the Medical Center of Vali-Asr. All patients received daytime dialysis, and the total hours per week varied from 11 to 12.5 h. The inclusion criteria were as follows: Patients on maintenance HD three times a week for >3 months with age >18 years and those who provided informed consent.
The exclusion criteria were as follows: Presence of malignancy, active infection, uncontrolled heart failure, poor controlled diabetes (HgbA1c ≥7.6), acute medical or surgical condition that required hospitalization or operation within the prior month or patients with dementia or psychotic disorder, as diagnosed by the researcher.
All 163 patients of our university hospital center were screened for inclusion by predefined criteria. Finally, a total of 138 patients were enrolled in the study. This study was approved by the Research Ethics Review Committee of our university (No. 89-99-4) and informed consent was obtained from all participants.
Quality of sleep
SQ was determined by the Pittsburgh Sleep Quality Index (PSQI), a score derived by a self-rated questionnaire, consisting of 19 questions.  The 19-question questionnaire measures the SQ of the previous month. From the answers, seven components (each scored from 0 to 3) of subjective SQ, sleep latency, sleep duration, sleep efficiency, sleep disturbances, use of sleep medications and daytime dysfunction were calculated. The global PSQI score was calculated (0-21) from the sum of seven component scores, with higher scores indicating worse SQ. A patient with a global PSQI score >5 is considered to be a bad sleeper. In this study, patients completed this questionnaire by themselves or under the assistance of research nurses at the time when the HD was performed.
For the analysis concerning pain, patients were questioned, "How much body pains have you had during the past four weeks?" Variation of body pain among prevalent HD patients was on a scale of 0-10, where 0 represented the no pain and 10 represented the worst. The mean pain score was 4.8 and the median was 5. Therefore, we categorized patients with a pain score below 5 to be in the low pain group (42%) and those with a score of 5 or greater to be in the high pain group (58%).
Blood samples were collected prior to a HD session. Age, sex, cause of renal disease and hours of dialysis per week were determined by interview and chart review. Because of dialysis adequacy (Kt/V) variation from session to session, we used mean hours of dialysis per week for final analysis instead of once measured Kt/V. All laboratory tests were performed at the reference laboratory. Serum biochemistry was measured by standard laboratory methods. Intact parathyroid hormone (iPTH) was measured using the electro-chemiluminescence immunoassay. For all lab parameters, the mean of three consecutive months' values was considered as baseline.
| Statistical Analysis|| |
Data were summarized as the mean and standard deviation or number and percent, as appropriate. Student's t-test was used to compare the means of normally distributed variables between "good sleepers" (global PSQI ≤ 5) and "poor sleepers" (global PSQI > 5), and the Mann-Whitney U test was used for variables that were not normally distributed. Differences among categorical variables were assessed by using the χ test. The bivariate correlation test was performed to determine the association of demographic and biochemical data, with the PSQI score. For normally distributed variables, Pearson's correlation test was used; for non-normally distributed variables, Spearman's correlation test was used. Multiple linear regression with forward stepwise selection was repeated for factors that reached statistical significance (P <0.1), to identify factors independently associated with SQ. Data management and analyses were carried out using the Statistical Package for Social Sciences (SPSS), version 17. The level of significance was α = 0.05 for all comparisons.
| Results|| |
Of 168 patients available to enter the longitudinal study, 32 did not meet the inclusion criteria. The remaining 138 subjects (mean age of 59 ± 15 years, 47% male) were invited to enter the cross-sectional study. The underlying cause of renal failure was diabetic nephropathy in one-third of the cases. All the subjects attended HD for 4 h three times weekly.
Global and component PSQI scores results
In 88 cases of a total of 138 patients (64%), the global score of PSQI more than 5 was considered as poor SQ. Across categories, patients with poor SQ were older and they were more likely to be diabetic. Also, they may have a significantly lower serum iPTH and higher ferritin [Table 1]. Those with poor SQ also reported higher levels of body pain.
|Table 1: Comparison of demographic and laboratory data between good sleepers and bad sleepers.|
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There were no significant differences in SQ by gender, duration of dialysis and age. There were also no differences in SQ by level of serum albumin, serum creatinine, hematocrit and serum phosphate [Table 1].
The correlations between the global PSQI score and the other variables are shown in [Table 2]. There were weak but still significant positive correlations between global PSQI score and age, serum calcium and presence of diabetes. Although not statistically significant, there was a positive correlation with body pain and also negative correlation with serum iPTH and creatinine, with global PSQI score.
|Table 2: Demographic and laboratory variables correlation with global PSQI score|
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Characteristics associated with greater likelihood of poor SQ were considered for further analysis. Thus, variables that reached a significant correlation with the global score of sleep (P <0.1) were selected for multi-variate analysis. In the regression analysis, the only predictive factor for the quality of sleep was diabetes [Table 3]. The likelihood of sleep disturbance in diabetes was 3.67-times greater versus non-diabetics (P = 0.008).
|Table 3: Multivariable-adjusted odds ratio of predictors for the poor sleep quality.|
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Diabetic patients compared with non-diabetic patients had more complaints on components of subjective SQ, use of sleep medications and sleep disturbances. Also, they were older and had lower serum creatinine, urea, phosphorous and iPTH [Table 4]. There were no significant differences in the presence and severity of body pain; however, there was a mild correlation between fasting sugar amount and self-rating of bodily pain (r = 0.235, P = 0.014). Also, a moderate negative correlation has been observed between fasting sugar and iPTH (r = -306, P = 0.001).
|Table 4: Comparison of sleep components and laboratory data between diabetics and non-diabetics.|
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| Discussion|| |
Poor SQ is common among patients on maintenance HD. We examined the prevalence of self-reported poor sleep and patient characteristics associated with the same. The prevalence of poor SQ in our experience was 64%, which was consistent with the findings of other investigators. who have studied SQ among dialysis patients.
In addition, we investigated the association of poor SQ with the underlying cause of renal failure and certain laboratory values. Our study demonstrated that older age, diabetes and higher serum calcium were associated with poorer SQ in stable HD patients. There was also a negative correlation between iPTH and serum creatinine with poorer SQ; nevertheless, the results did not reach statistical significance. Our study also showed that diabetes was the somewhat strong independent predictor of poor SQ. In other word, diabetes increases the risk of sleep disturbance 3.67 times. Majority of previous studies have reported that sleep disorders are more common in diabetic patients than non-diabetic patients, except for a study done by Yoshioka et al,  in which they stated that it was not an independent predictive factor for poor sleep. Also, Kutner et al  found that body pain and neuropathy, which were more common in diabetics, were independent predictive factors; however; diabetes was not considered as an independent predictor of SQ. In our study, bodily pain was an independent predictor of SQ; however, severity of self-rating pain was not different in both diabetics and non-diabetics. In explaining the results obtained, we propose the possible role of some confounding factors that are usually not taken into consideration, such as medications that may have an effect on sleep such as beta-blockers as well as degree of glycemic control. As mentioned previously, despite no significant difference in the presence and severity of body pain, there was a mild correlation between fasting sugar value and body pain.
Possible factors affecting sleep have been extensively studied, but some controversies still exist. However, most studies on sleep disorders have shown a significant association of older age with poor SQ, but Unruh et al  indicated otherwise. They found that sleep disorder was more common in younger patients during the first year of dialysis. However, Sabbatini et al  showed that age over 50 years was an independent prognostic factor. In our study, age was not an independent predictive factor; however, the mean age was higher in patients with sleep disorders.
In our study, there was no difference in SQ by gender, which was consistent with most studies. ,, However, this was in contrast with the reports of Pai et al  and Elder et al,  who have reported that poor sleep was more prevalent in the female gender.
There are some conflicting results about the relationship between phosphate level and SQ. While some studies have observed serum phosphorus to be related to poor SQ, , others have failed to identify significant relationships between phosphorus and SQ. , In our study, there was no statistically significant correlation between SQ score and serum phosphorus or calcium-phosphate products.
Chiu et al  and Pai et al  found a significant and independent association between SQ and serum hemoglobin even after considering a variety of factors. However, in our study, the global PSQI score was not associated with serum albumin, hematocrit, iPTH, ferritin or duration of HD, which was consistent with the findings of most studies. ,,,,,
Some small studies have indicated the possible role of iPTH in SQ in HD patients. , De Santo et al  proposed that patients on HD requiring parathyroidectomy for intractable hyperparathyroidism comprise a good model for investigating the causative role of PTH on disordered sleep and, also, Esposito et al  have implicated that insomnia in patients with severe hyperparathyroidism is ameliorated by parathyroidectomy. As has been shown in our study, although the iPTH was significantly lower in poor sleepers, it was not an independent predictor of SQ. To justify this, it may due to the moderately negative correlation between fasting sugar and iPTH in our data analysis. Our finding was compatible with the reports of Chiu et al  and Elder et al. 
At the end, there were several limitations to this study that should be addressed. First, the only means of measuring SQ was filling out a self-rating questionnaire, and comprehensive polysomnography was not performed. Second, the possible role of alcohol consumption and smoking were not considered. However, alcohol consumption is not common in our population, but smoking was very common in men. There were no significant differences in SQ by gender in our study. Also, certain medications such as beta-blockers and statins may have influenced SQ, but the use of these drugs was not analyzed.
In conclusion, sleep disturbance was a common problem in HD patients in our center, and this study showed that diabetes was the main predictor of poor SQ. As noted, the literature review found diverse and non-uniform results in demonstrating the predictors of SQ; however, we cited studies with the same method and material for comparison. Perhaps this is due to the fact that, besides uremia and HD itself, sleep is under the influence of various other factors including different habits and behaviors, culture, economics and politics, and, to eliminate these confounding factors, further large-scale and multi-center studies are needed.
| Conclusion|| |
Because of the high prevalence of sleep disorders among dialysis patients, especially among diabetics with its negative effect on quality of life, addressing this complaint is extremely important and it is reasonable to perform screening for sleep disorders as a routine for all patients on HD.
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Arak Medical Sciences University, Arak
[Table 1], [Table 2], [Table 3], [Table 4]