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Published ahead of print on August 8, 2007
Clin J Am Soc Nephrol 2: 919-925, 2007
© 2007 American Society of Nephrology
doi: 10.2215/CJN.00820207

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Clinical Nephrology

Pain, Sleep Disturbance, and Quality of Life in Patients with Chronic Kidney Disease

Scott D. Cohen, Samir S. Patel, Prashant Khetpal, Rolf A. Peterson, and Paul L. Kimmel

Division of Renal Diseases and Hypertension, Department of Medicine, George Washington University Medical Center, Washington, DC

Address correspondence to: Dr. Paul L. Kimmel, Division of Renal Diseases and Hypertension, Department of Medicine, George Washington University Medical Center, 2150 Pennsylvania Avenue NW, Washington, DC 20037. Phone: 202-741-2283; Fax: 202-741-2285; E-mail: pkimmel{at}mfa.gwu.edu


    Abstract
 Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Conclusions
 Disclosures
 References
 
Background and Objectives: Few studies have assessed sleep disturbances or perception of pain in patients with early-stage chronic kidney disease. It was hypothesized that perception of pain and sleep disturbance would increase with chronic kidney disease stage, that pain and sleep disturbance would correlate with psychosocial variables, and that there would be a higher prevalence of pain and sleep disturbances in patients with chronic kidney disease compared with general medical patients.

Design, Setting, Participants, & Measurements: A total of 92 predialysis patients with chronic kidney disease and 61 general medical outpatients were evaluated using the Beck Depression Inventory, Illness Effects Questionnaire, Multidimensional Scale of Perceived Social Support, Satisfaction with Life Scale, Karnofsky Scale, Pittsburgh Sleep Questionnaire, and McGill Pain questionnaire.

Results: With the exception of expected differences in serum creatinine, estimated GFR, Karnofsky score, albumin, and hemoglobin, there were no significant differences between groups. A total of 69% of patients with chronic kidney disease experienced pain; 55.2% had disordered sleep. Pain was associated with quality-of-life indicators, including depression, burden of illness, and life satisfaction. Disordered sleep correlated with depression, illness burden, social support, and pain frequency. There were no differences in perception of pain or sleep disturbance between patients with chronic kidney disease and control patients.

Conclusions: Pain is common in patients with early-stage chronic kidney disease and is associated with patients’ perception of lower quality of life. The prevalence of pain, sleep disturbance, and abnormal psychologic status of patients with chronic kidney disease may be similar to outpatients with other chronic medical illnesses.


    Introduction
 Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Conclusions
 Disclosures
 References
 
Sleep disorders are prevalent in patients with ESRD (15). They are not necessarily improved by dialysis but may be ameliorated by transplantation (6,7). Perception of pain was recently identified as an important symptom in patients with ESRD (810). Both perception of pain and sleep disturbance may have a large impact on quality of life (QOL) for patients with ESRD (10,11).

Many studies have shown the QOL of dialysis patients to be lower than that in the general population (1115). QOL may affect mortality in a variety of conditions, including ESRD (1321). McClellan et al. (20) demonstrated that functional status and QOL predict early mortality among patients who enter treatment for ESRD. DeOreo (21) showed that functional status was associated with mortality and frequency of hospitalizations. The Dialysis Outcomes and Practice Patterns Study (DOPPS), a large, international, observational study, demonstrated that QOL indicators from the SF-36 were associated with differential survival and morbidity (18).

Pain and sleep disturbances have been shown to affect QOL in a variety of medical conditions (22,23). Perception of sleep disturbances and depression have been correlated in several general population studies (2430). Kaneita et al. (24) recently studied this relationship in Japan and collected data on depression and sleep disturbances from 24,686 individuals. They found an inverse relationship between depression and perception of sleep disturbance (24). Furthermore, sleep disturbances have been associated with common medical illnesses, including cerebrovascular and coronary artery disease (31). Perception of pain is believed to have a significant effect on sleep disturbance in patients with arthritis and other general medical conditions (32).

Few studies have assessed sleep disturbances or perception of pain in patients with early-stage chronic kidney disease (CKD). Studies have been hampered by lack of non–kidney disease control populations. Associations between psychologic status, perception of QOL, disturbed sleep, and pain have not been evaluated in patients with early stages of CKD.

The purpose of this study was to evaluate the association of perception of sleep disturbance and pain with QOL indicators such as depression and perception of burden of illness in outpatients with CKD. Our hypothesis was that perception of pain and sleep disturbance would worsen on the basis of stage of CKD and that perception of pain and sleep disturbance would correlate with psychosocial variables, including depressive affect and burden of illness scores.


    Materials and Methods
 Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Conclusions
 Disclosures
 References
 
The site of the study was the George Washington University Medical Center (GWUMC) Outpatient Clinic. All patients with CKD in the GWUMC outpatient clinic were eligible to participate. The control group consisted of general medicine outpatients without CKD. A serum creatinine of <1.5 mg/dl was used to enroll patients in the control arm of the study. The study was approved by the Committee on Human Research of the GWUMC. Data were collected by research assistants who administered questions in an interview format. Informed consent was obtained. Eligible patients were not selected consecutively. Clinics and patients were targeted for recruitment on the basis of research assistant availability and diagnostic screening from clinic schedules. We used the Beck Depression Inventory (BDI), Illness Effects Questionnaire (IEQ), Single Question QOL Scale (SQQOL), Multidimensional Scale of Perceived Social Support (MSP), Satisfaction with Life Scale (SWLS), Karnofsky scores, Pittsburgh Sleep Questionnaire (PSQ), and a modified McGill Pain Questionnaire to evaluate participants. We also measured treatment and nutrition parameters, including albumin, hemoglobin, and estimated GFR (eGFR) using the Modification of Diet in Renal Disease (MDRD) Equation (33). Ethnicity was determined by patient self-report.

Measures
BDI.  The BDI is a screening tool for depression that has been used in both the general and CKD populations. It consists of 21 items that examine somatic and cognitive effects of depression, using a rating scale to quantify the level of depression as none, mild, moderate, or severe (34,35). Each question is scored from 0 to 3. In the general population, a BDI score of ≥11 is used as a cutoff for depression (34). Scores of ≥11 are indicative of depression in the general population, whereas scores >14 are used as cutoff values in patients with ESRD (35,36). BDI scores have been linked with mortality in patients with ESRD (13,37).

IEQ.  The IEQ is used to quantify the patient's perception of burden of illness. It contains 20 items scored on a seven-point Likert scale. The IEQ has been validated in ESRD and CKD patient populations and has also been associated with mortality (11,15,16,3740).

SQQOL.  The SQQOL has been used in several recent studies of dialysis patients (10,11). We showed that this single-question global QOL measure correlated with depression, number of symptoms, life satisfaction scores, perception of burden of illness, social support, and satisfaction with nephrologist scores but not with age, level of albumin, hemoglobin, Kt/V, or Karnofsky scores, demonstrating its validity as a QOL measure (10,11).

MSP.  The MSP consists of 12 questions on a seven-point scale designed to measure overall perceived social support from family, friends, or significant others (41,42). The scale has previously been used in patients with CKD (13,16,3840). Higher scores are associated with improved survival in patients who have ESRD and are treated with hemodialysis (16).

SWLS.  The SWLS contains five items, rated on a scale from 1 to 7, that are designed to measure overall perception of QOL (43,44). The SWLS has been shown to correlate with a number of subjective QOL measures (43). The SWLS has also been validated in ESRD and CKD populations (11,15,16,37,38).

The Karnofsky Performance Status Scale (45).  The Karnofsky Performance Status Scale measures a patient's functional status using a scale that ranges from 0 to 100. A score of 100 signifies full capacity to carry out normal activities of daily living, and a score of 0 indicates death. Scores <70 indicate that some level of assistance is needed to carry out daily activities. The Karnofsky scale has been used in previous QOL studies in patients with ESRD and CKD (11,13,15,16,38).

PSQ.  The PSQ screens for sleep disturbances during a 1-mo period (46). There are 19 questions with seven "component" scores including "subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleeping medication, and daytime dysfunction" (46). The seven component scores are summed to give one global score (46). A global Pittsburgh Sleep Quality Index (PSQI) score >5 has an 89.6% sensitivity and 86.5% specificity for determining disturbance in sleep (46). The PSQ has previously been used in both patients with ESRD and CKD (47,48).

McGill Pain Questionnaire.  A modified McGill Pain Questionnaire was used to measure perception of pain. This survey includes questions regarding the nature, location, frequency, intensity, and duration of pain (49). It has previously been used in patients with ESRD (9,10,50). Pain frequency was measured by asking patients how often they experience pain on a scale from 1 to 10, with 1 defining rarely experiencing pain and 10 defining always experiencing pain. Pain duration was measured by asking patients how long their pain lasts in minutes. The intensity of pain was rated on an intensity scale of 1 to 10 (49). The percentage of patients with pain was calculated on the basis of how many patients reported experiencing pain in the past month.

Statistical Analyses
All statistical analyses were performed using SAS version 9.1 (SAS Institute, Cary, NC). Correlation analysis with Pearson or Spearman coefficients was used to assess relationships among the demographic, pain, and sleep variables as appropriate. The Mantel-Haenszel {chi}2 test was used for comparisons between nominal variables. Duncan multiple range test was used to calculate statistical differences between means of variables. P < 0.05 was considered significant for all tests. Results are expressed as means ± SD.


    Results
 Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Conclusions
 Disclosures
 References
 
A total of 120 patients with CKD were approached, and 28 declined, for a total of 92 patients with CKD, or a recruitment rate of 76.7%. A total of 98 general medical patients were approached, and 37 declined, for a total of 61 general medical patients, or a recruitment rate of 62.2%. Table 1 shows the demographic and clinical characteristics of the patients in the CKD and general medical outpatient groups. With the exception of eGFR, serum creatinine, albumin, hemoglobin, and Karnofsky scores, there were no statistically significant differences in mean parameters assessed between the two groups. In the CKD group, 73.9% were black and 48.3% of patients were female. The mean age was 62.4 ± 12.5 yr; 46.1% had diabetes. The mean Karnofsky score was 82.5 ± 13.6. Mean serum creatinine concentration was 2.8 ± 1.9 mg/dl, with a mean eGFR of 33.4 ± 23.7 ml/min per 1.73 m2. The mean serum albumin concentration was 4.0 ± 0.5 g/dl, and mean hemoglobin concentration was 11.9 ± 1.7 g/dl. The mean IEQ score was 41.6 ± 29.8, and mean BDI score was 7.4 ± 6.9. Mean total MSP score was 69.0 ± 15.8, with a mean SWLS score of 23.0 ± 8.5. The MSP and SWLS scores are similar to that of normative populations (16). The mean SQQOL score was 7.4 ± 2.3. There were no statistically significant differences in the psychologic, pain, or sleep variables between the two groups, as shown in Table 2.


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Table 1. Comparison of demographic and clinical characteristics of the CKD and general medical groupsa

 

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Table 2. Psychological, pain, and sleep variables in general medical patients and patients with CKDa

 
Sixty-nine percent of patients with CKD experienced pain, with a mean pain intensity score of 4.5 ± 3.7. Fifty-five percent of patients with CKD had disordered sleep, with a mean PSQ score of 6.8 ± 3.9. The proportion of patients who experienced pain or disordered sleep was not different in the CKD or the general medical patient groups. There was no correlation of pain and sleep parameters with GFR or stage of CKD (Figures 1 and 2, Tables 3 and 4). There was also no significant difference in the mean psychologic, pain, and sleep variables across the various stages of CKD (Table 5).


Figure 1
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Figure 1. Percentage of patients who reported pain in the past month. CKD, chronic kidney disease.

 

Figure 2
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Figure 2. Percentage of patients with a sleep disturbance (Pittsburgh Sleep Questionnaire score >5).

 

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Table 3. Correlation matrix of psychosocial, pain, sleep, medical and demographic variables in the CKD groupa

 

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Table 4. Correlation matrix of psychosocial, pain, and sleep variables in CKDa

 

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Table 5. Mean demographic, psychosocial, pain, and sleep variables in CKD

 
Table 3 displays a correlation matrix of demographic; medical and treatment variables; and psychosocial, pain, and sleep variables in patients with CKD. Table 3 is notable for the lack of statistically significant correlations between these variables. Hemoglobin level correlated with BDI and MSP scores, whereas Karnofsky scores correlated with IEQ, SQQOL, SWLS, and pain frequency measures. In contrast, Table 4 is notable for the numerous significant intercorrelations between the psychosocial, pain, and sleep variables. Pain intensity correlated with depressive affect (BDI; r = 0.278, P = 0.010), perceived burden of illness (IEQ; r = 0.297, P = 0.006), social support (MSP; r = –0.241, P = 0.026), and satisfaction with life (SWLS; r = –0.221, P = 0.046) measures. Pain frequency was associated with all QOL indicators: Depressive affect (BDI; (r = 0.295, P = 0.006), perceived burden of illness (IEQ; r = 0.326, P = 0.002), social support (MSP; r = –0.217, P = 0.045), and satisfaction with life (SWLS; r = –0.254, P = 0.020) measures, as well as the SQQOL (r = –0.271, P = 0.011). Total PSQ scores correlated with depressive affect (BDI; r = 0.220, P = 0.047), perceived burden of illness (IEQ; r = 0.324, P = 0.003), social support (MSP; r = –0.286, P = 0.009), SQQOL (r = –0.217, P = 0.045), and pain frequency (r = 0.247, P = 0.023).


    Discussion
 Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Conclusions
 Disclosures
 References
 
Patients with CKD frequently perceive pain and sleep disturbances. In this study, perception of pain and sleep disturbances of patients with CKD was not associated with demographic or treatment variables; neither was perception of pain and sleep disturbances associated with creatinine, CKD stage, or eGFR. Perception of poor sleep of patients with CKD is tightly linked to poorer QOL, defined by many measures, as well as their perception of pain (as in hemodialysis patients) (5,8,9,11,14,15). Counterintuitively, there were no significant differences in mean perception of pain or sleep disturbance between the patients with CKD and a comparison population of 61 general medical outpatients without renal disease.

Few studies have evaluated perception of pain and sleep disturbance in patients with early-stage CKD. Ilieuscu et al. (47) studied the prevalence of sleep disturbance in patients who had CKD and did not yet require renal replacement therapy. Using the PSQI as a measure of perception of disturbed sleep, they reported that 63 of 120 patients (57.5%) had poor sleep, as defined by a global PSQI score of >5 (47). There was no association between the global PSQI score and blood urea nitrogen, serum creatinine, or calculated creatinine clearance, similar to our findings (47). De Santo et al. (51) evaluated the prevalence of sleep disorders in 52 patients with early stages of CKD using a 26-item self-administered questionnaire. They found an 80.7% prevalence of sleep disturbance in patients with early stages of CKD (51). However, there was no control population in these studies (47,51).

Kurella et al. (52) found a high prevalence of sleep disturbances in patients with CKD and ESRD using the Kidney Disease Quality of Life (KDQOL) sleep scale. However, in contrast to our study, they found a direct association between eGFR and scores on the KDQOL sleep scale in nonblack patients. Potential reasons for the disparities in results would include the use of different instruments, size of studies, sample population, and study design used (52).

The prevalence of pain, sleep disturbance, and abnormal psychosocial status of patients with CKD may be similar to that of outpatients with diabetes and other chronic medical illnesses. It is unclear why these results are similar between the two groups. One possibility is that the average GFR, 33.4 ± 23.7 ml/min per 1.73 m2 in the CKD group, was not decreased to the level where uremic symptoms would be expected. In addition, it is possible that although the patients with CKD have more severe disease burden, they may be more likely to deny the severity of their illness as a coping mechanism.

Shidler et al. (38) discussed this possibility in a study of 50 patients with chronic renal insufficiency in which the relationship between QOL and psychosocial parameters was explored. A dissociation between stage of disease and social support was noted in this study, suggesting the possibility of denial. Similar to the results of our study that showed comparable results between patients with CKD and general medical patients, Shidler et al. (38) did not find a correlation between decreased renal function and psychologic measures, including the IEQ, BDI, and SWLS.

It is also possible that the general medical population had a high degree of chronic medical illness, including diabetes and osteoarthritis, which could have led to the similarity in these results. There were, however, no differences between the proportion of patients with diabetes in the CKD and general medical groups. There is likely a high prevalence of psychologic illness in the general medicine clinic patients, which may be similar to the prevalence of psychologic illness in the CKD group (53). Psychologic illness may be associated with perception of pain and sleep disturbance (48). A potential limitation of the study, in addition to the difference between groups in the Karnofsky score, is the absence of assessment of Charlson comorbidity scores, which may have differed between the groups. Previous studies have shown a high prevalence of sleep disturbance in the general population, further supporting these similar results between the CKD and general medical groups. Morin et al. (54) evaluated the prevalence of insomnia in 2001 adults from Quebec, Canada. Approximately one quarter of the patients surveyed reported disordered sleep (54), similar to the CKD population in this study, supporting our results that show a high prevalence of sleep disturbance in both groups. The reasons for these similarities are not entirely clear, but delineation of differences between these populations will require larger and multicenter sampling strategies.

Other potential limitations of this study include its cross-sectional nature. Therefore, direction and causality cannot be inferred. In addition, the patient selection cannot be viewed as a random process. However, we do not know of a particular bias that could be introduced into the study because of our approach, because we surveyed the renal and the general medical patients in a similar manner. Consideration must be given to the fact that in correlational analyses, multiple comparisons may render associations with P values between 0.01 and 0.05 potentially relatively less meaningful. Correlations with r values of <0.3 suggest relationships in which <10% of the variation in a parameter is explained by the change in the magnitude of the other factor. Nevertheless, this study provides potentially important information. This is the only controlled data on QOL and symptoms in early-stage CKD to our knowledge. In addition, the CKD and control groups that were recruited were well matched for all variables, with the expected exception of serum creatinine, eGFR, hemoglobin, and Karnofsky score.


    Conclusions
 Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Conclusions
 Disclosures
 References
 
Our data showing strong relationships between pain, sleep disturbances, and psychologic variables suggest that interventions directed at the symptoms of pain and disordered sleep may improve the psychological status of patients with CKD. Alternatively, psychosocial interventions such as treatment of depression or interventions designed to increase social support may improve perception of pain and sleep disorders in patients with CKD. Nephrologists should be aware of the prevalence of pain and perception of disturbed sleep in patients and should consider screening patients for these symptoms.


    Disclosures
 Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Conclusions
 Disclosures
 References
 
None.


    Acknowledgments
 
S.D.C. was supported by a research fellowship from the National Kidney Foundation. We thank the patients for participating in this study. We also thank the faculty members of the Divisions of Renal Diseases and Hypertension and General Internal Medicine for their help in patient recruitment.


    Footnotes
 
Published online ahead of print. Publication date available at www.cjasn.org.

Received February 14, 2007. Accepted May 25, 2007.


    References
 Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Conclusions
 Disclosures
 References
 

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