Objective: To investigate the factors associated with sleep quality in maintenance hemodialysis patients and to investigate the factors associated with sleep quality in maintenance hemodialysis patients and to make risk predictions based on this.Methods: Using a convenience sampling method, 268 ESRD patients from a tertiary hospital hemodialysis unit in Beijing were selected as the study population. Combining patients' general information and laboratory data, the sleep status and related information of hemodialysis patients were investigated according to the Pittsburgh Sleep Quality Index Inventory (PSQI) and a self-administered questionnaire to scientifically assess the sleep quality of patients. SPSS20.0 statistical software was used to conduct frequency analysis of the collected data to count the composition ratio of each factor, correlation analysis, and binary logistic regression analysis methods to screen and analyze the influencing factors related to patients' sleep quality.Results: 268 hemodialysis patients had a PSQI score of (9.63±5.05), of which 113 (42.16%) patients had a PSQI score ≥11. The correlation analysis revealed that age on dialysis, work status, and the presence of emergency/hospitalization in the last month were associated with sleep quality in hemodialysis patients (P < 0.05); the binary logistic regression analysis revealed that age on dialysis (OR = 1.27, 95% CI (1.11, 1.46)) was a risk factor for sleep quality in MHD patients; being employed (OR = 0.56, 95% CI (0.35, 0.89)) and no emergency/inpatient experience in the last month (OR=0.41, 95% CI (0.27, 0.70)) were protective factors for sleep quality in MHD patients. The Pittsburgh Sleep Quality Index showed that patients' corresponding sleep problems were, in order, difficulty falling asleep, need for sleeping medication, inefficient sleep, sleep duration not meeting their needs, poor daytime functioning, and poor self-perceived sleep quality, but the sleep disorder component was relatively low in severity in this study. Conclusion: The longer the age of dialysis, non-employment and recent emergency/hospitalization experience have an impact on the sleep quality of hemodialysis patients, and targeted psychological care and comfort care should be taken to encourage them to take appropriate exercise and exercise according to their physical condition, adjust their psychological status, avoid risk factors in advance, and strengthen protective factors to help improve patients' negative emotions and sleep quality, thus improving hemodialysis patients' quality of life The quality of life of hemodialysis patients can be improved.
Research Article
Investigating influencing factors and risk prediction of sleep quality in maintenance hemodialysis patients
https://doi.org/10.21203/rs.3.rs-1995724/v1
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Hemodialysis
sleep quality
influencing factors
risk prediction
Maintenance Hemodialysis (MHD) is one of the alternative treatment methods to maintain the life of patients with End-stage renal disease (ESRD). According to statistics, there are about 120 million patients living with Chronic Kidney Disease (CKD) in China, and the Chinese National Registry of Hemodialysis Pathology (CNRD) in 2016 showed that there were 447,435 registered hemodialysis patients and 75,831 new patients in China, and the number of ESRD patients will be even larger in the future [1].
MHD prolongs the survival of patients while also interfering with their lifestyle and daily routine, leading to the development of sleep disorders [2] . Xie Likhan et al [3-4] showed that age, dialysis duration, functional metabolic abnormalities, and underlying diseases are the main factors that lead to sleep disorders in patients. Reduced sleep quality affects the quality of life of MHD patients and increases the incidence of cardiovascular risk events and all-cause mortality in patients. However, as society and people's economic levels continue to develop and change, the factors affecting the sleep quality of MHD patients are also changing. Therefore, to reduce the risk of sleep disorders in patients with MHD, it is necessary to screen for the influencing factors and to predict the risk in order to avoid them in advance. The risk prediction of the occurrence of sleep disorder influencing factors in MHD patients has not been performed in existing studies. In this study, we investigated the general conditions of MHD patients and hemodialysis-related data, and finally developed a risk prediction model, which is reported below.
1.1 Study Subjects
Using a convenient sampling method, 268 patients with MHD who were treated at a tertiary hospital hemodialysis center in Beijing from March 2021 to October 2021 were selected for the study. Inclusion criteria were as follows: (1) Receiving maintenance hemodialysis treatment with ≥3 months of dialysis cycle and in stable condition; (2) Age ≥18 years; (3) Frequency of hemodialysis of 3 times/week, 4 hours/time; (4) Consciousness and no communication impairment; (5) Voluntary participants in this study. Exclusion criteria were as follows: (1) Complications of severe diseases, such as severe cerebrovascular sequelae, acute heart failure AHF, etc.; (2) Patients with mental illness or cognitive dysfunctions; (3) Patients with speech disorders, patients with severe hearing impairment, unable to successfully cooperate with the completion of the survey.
1.2 Method
1.2.1 Survey Tools
(1) General information questionnaire: A self-administered general questionnaire, including demographic information such as age, gender, work status, and living accommodation, as well as disease information such as age on dialysis (years), primary disease, type of vascular access, serum phosphorus, serum calcium, and hemoglobin, and whether the patient had been hospitalized in the last month.
(2) Sleep quality assessment: The Pittsburgh sleep quality index (PSQI) was introduced in 1989 by Buysse et al [5]. Each component is scored on a scale of 0-3, and the cumulative score of each component is the total PSQI score, which ranges from 0-21, and the higher the score, the worse the sleep quality. Liu Xianchen [8] et al. translated the PSQI into Chinese in 1996 and conducted a reliability test, which showed that the scale had retest reliability of 0.83, and concluded that local patients could use the scale.
1.2.2 Data collection methods
Questionnaires were administered by the investigator to patients who met the inclusion/exclusion criteria and were distributed at the hemodialysis center. After obtaining informed consent from the patients, the investigator instructed the patients to fill out the questionnaire using a uniform guideline. For those who were unable to write the questionnaire independently, the investigator asked the patient for options and filled it out for them. The questionnaires were checked for omissions and were collected in time for completion.
1.2.3 Statistical Methods
Data were analyzed and processed using SPSS 20.0 statistical software. Quantitative information was described by mean ± standard deviation, and qualitative information was described using frequency and percentage parameters. Pearson's correlation analysis was used for continuous variables, binary logistic regression analysis was used for influencing factors related to sleep disorders, OR values and 95% confidence intervals were calculated for the formed regression equation models, and P < 0.05 was considered statistically significant.
2.1 Analytical results of general demographic information
In this study, 270 questionnaires were distributed and 268 valid questionnaires were returned, with a valid return rate of 99.26%. 268 MHD patients were aged between 27-90 (61.91±13.67) years, with a median dialysis duration of 7 years and a median dialysis age of 0.3-28 years. See Table 1 for specific details.
Table 1 General information of MHD patients (n=268)
2.2 Analytical results of clinical data (see Table 2)
Table 2 Clinical data of MHD patients (n=268)
|
Criteria |
Classification |
No. of cases (%) |
|
Primary Disease |
Glomerulonephritis |
66（24.6） |
|
|
Hypertension |
71（26.5） |
|
|
Diabetes |
60（22.4） |
|
|
Others |
71（26.5） |
|
Age of dialysis |
0-5 years |
57（21.3） |
|
|
6-10 years |
101（37.7） |
|
|
11-15 years |
46（17，2） |
|
|
16-20 years |
42（15.7） |
|
|
＞20 years |
22（8.2） |
|
Vascular Access |
Autologous Arteriovenous Fistula |
219（81.7） |
|
|
Artificial Arteriovenous Fistula |
35（13.1） |
|
|
Central Venous Catheter |
14（5.2） |
|
Any emergency/inpatient experience in the last 1 month |
yes |
29（10.8） |
|
|
none |
239（89.2） |
2.3 Patients' Pittsburgh Sleep Quality Index scores.See Table 3 for specific details.
Table 3 PSQI scores of MHD patients (n=268)
|
Criteria |
Min |
Max |
No. of full scores for each component |
Percentage of full marks for each component (%) |
|
Delayed sleep (Component 2) |
0 |
3 |
82 |
30.6 |
|
Hypnotic drugs (Component 6) |
0 |
3 |
48 |
18.0 |
|
Sleep efficiency (Component 4) |
0 |
3 |
40 |
14.9 |
|
Sleep duration (Component 3) |
0 |
3 |
31 |
11.6 |
|
Daytime function (Component 7) |
0 |
3 |
30 |
11.2 |
|
Conscious sleep quality (Component 1) |
0 |
3 |
21 |
7.8 |
|
Sleep disorders (Component 5) |
0 |
2 |
16 |
6.0 |
|
Total |
0 |
20 |
- |
- |
** - Indicates no data available.
2.4 Correlation analysis of general information and sleep quality of MHD patients
The total PSQI score of MHD patients was (9.63±5.05), of which 113 patients (42.16%) had PSQI ≥ 11 cases (42.16%). the work status of MHD patients was assigned: 1: working; 2 non-working. the correlation analysis between general information and sleep quality of MHD patients is detailed in Table 4.
Table 4 Correlation analysis between general information and sleep quality of MHD patients (r value)
** Significantly correlated at the .01 level (bilaterally).
* Significantly correlated at the .05 level (bilaterally).
2.5 Construction of binary logistic regression equation for sleep quality related influencing factors
A binary logistic regression analysis was performed to analyze the factors influencing sleep quality related to MHD patients (P < 0.05): the dichotomous variables were the presence or absence of emergency/hospitalization experience (no emergency/hospitalization experience assigned a value of 0, emergency/hospitalization experience assigned a value of 1) and work status (employed assigned a value of 1, non-employed assigned a value of 2); the multicategorical variables were age on dialysis (0-5 years assigned a value of 1, 6- (0-5 years assigned as 1, 6-10 years assigned as 2, 11-15 years assigned as 3, 16-20 years assigned as 4, >20 years assigned as 5). For the convenience of the following statement, this paper uses y to denote the risk of sleep disorders in MHD patients, x1 to denote the patient's dialysis age, x2 to denote work status, and x3 to denote the presence of emergency/hospitalization.
The binary regression equation between the dependent variable y (sleep disorder assigned as 0 and normal sleep assigned as 1) and the independent variables x1, x2, and x3 was established by means of binary logistic regression, and the results are shown in Table 5: From Table 5, the binary logistic regression equation is y=2.439-0.254x1-0.75x2-0.98x3.
Table 5 Binary logistic regression analysis of the influencing factors related to sleep quality
|
|
B |
Wals |
P |
Exp (B) |
95% C.I. of EXP(B) |
|
|
Lower limit |
Upper limit |
|||||
|
Job Status |
-0.75 |
4.529 |
0.033* |
0.472 |
0.237 |
0.942 |
|
Dialysis age |
-0.254 |
5.775 |
0.016* |
0.776 |
0.631 |
0.954 |
|
Emergency/inpatient experience |
-0.98 |
5.418 |
0.02* |
0.375 |
0.164 |
0.857 |
|
Constant |
2.439 |
11.644 |
0.001** |
11.46 |
|
|
*P＜0.05
**P＜0.001
2.6 Testing of the constituted binary regression equation model
The prediction model's discriminative ability was evaluated by plotting the ROC curve and calculating the area under the ROC curve. Generally, AUC < 0.6 was considered a poor discriminative ability, 0.6-0.75 as the model had some discriminative ability, and > 0.75 as good discriminative ability. As shown in Figure 1 and Table 6, the area under the curve AUC was 0.634>0.60 with a 95% CI of 0.567-0.701, suggesting that the prediction model has some discriminatory ability.
The calibration of the prediction model was evaluated using the goodness of fit test (Hosmer-Lemeshow good of fit test). The results showed that the Hosmer-Lemeshow χ2 =6.487, p=0.371>0.05, suggesting that the difference between the model predictions and the actual observations was not statistically significant and the prediction model had good calibration ability. Also, the predicted probabilities for each study subject were sorted from smallest to largest and divided into eight groups, listing the actual observed and model predicted values for each group, thus allowing for a visual comparison under each grouping to help determine the calibration ability of the model, as detailed in Table 7.
Table 6 Area under the curve Test outcome variable: Predicted probability
|
Test outcome variable: Predicted probability |
||||
|
Area
|
Standard error a |
P |
95%CI |
|
|
Lower limit |
Upper limit |
|||
|
.634 |
.034 |
.000** |
.567 |
.701 |
|
**P＜0.001 |
||||
Table 7 Prediction model calibration capabilities
|
Group |
Sleep disorders |
Normal sleep |
Total |
||
|
Observed values |
Expected Value |
Observed values |
Expected Value |
||
|
1 |
24 |
21.404 |
9 |
11.596 |
33 |
|
2 |
15 |
18.897 |
21 |
17.103 |
36 |
|
3 |
13 |
15.093 |
20 |
17.907 |
33 |
|
4 |
4 |
2.538 |
2 |
3.462 |
6 |
|
5 |
35 |
30.713 |
43 |
47.287 |
78 |
|
6 |
2 |
3.189 |
7 |
5.811 |
9 |
|
7 |
12 |
13.405 |
28 |
26.595 |
40 |
|
8 |
8 |
7.760 |
25 |
25.240 |
33 |
3.1 Elderly patients are prone to sleep disorders
In the present study, the male to female ratio was 1.3:1 and the mean age of the patients was 61.91±13.67 years, similar to previous studies. It was confirmed that older patients are prone to sleep disorders, which may be influenced by the higher accumulation of toxins in one patient, while most patients suffer from other co-morbidities that can directly affect their sleep quality. Middle-aged and elderly patients accounted for 84% of the patients, indicating an overall older age in this group. The number of secondary schools and above was 237, accounting for 89.5%, indicating that the study group had a high level of education. The percentage of non-working people was 81.7%, which shows that most of the patients were over retirement age, and of course, some young and middle-aged patients with poor health conditions were included. Those with a household income of more than 4000 yuan accounted for 55.6% and had a high standard of living. Those with low hemoglobin accounted for 31.7%, indicating that patients had some degree of anemia.
Among 268 patients, 66 patients had glomerulonephritis, 71 patients had hypertension, 60 patients had diabetes mellitus, and 71 patients had other types of diseases, and most of the ESRD patients in this study belonged to the three high groups and were in poor physical condition. Patients with dialysis age of more than 6 years accounted for 78.7%, indicating that patients suffered from a long-term illness. There were 219 patients with autologous arteriovenous endovascular fistula, and 29 patients had emergency or hospitalization experience within the hospital. Taken together, the etiology of the patients is complex and may be related to family genetics or to long-term drug use that damages the kidney.
3.2 Age of dialysis as a risk factor for patient sleep quality
The individual components of the Pittsburgh Sleep Quality Index questionnaire, in order of the percentage of those with perfect scores, were delayed sleep onset (30.6%), hypnotic medication (18.0%), sleep efficiency (14.9%), sleep duration (11.6%), daytime dysfunction (11.2%), perceived sleep quality (7.8%), and sleep disorders (6.0%). Their corresponding sleep problems were, in order, difficulty falling asleep, need for sleeping pills, low sleep efficiency, sleep duration not meeting their needs, poor daytime functioning, and poor conscious sleep quality, but the sleep disorder component was relatively low in severity in this study.
Chinese literature reported that more than 89% of ESRD patients were treated with hemodialysis and sleep disturbance was very common in maintenance hemodialysis patients [9] . In the present study, the author found that 42.16% of MHD patients had poor sleep quality, which was lower than the findings of KRAUS and Wu Y et al [10-11] . Wu MJ et al [12] showed that female patients had poorer sleep quality than male patients. However, in the present study, gender did not correlate with sleep quality (P > 0.05). This may be related to the fact that male patients, as the breadwinners of their families, have increased life stress, complex interpersonal relationships, and need to bear more social responsibilities and family burdens.
The results of this study showed no correlation between the age of MHD patients and their sleep quality (P > 0.05), which is not consistent with the study of Lu Meisu and Zhang Min et al [13-14]. However, the results of the study showed that the longer the age of dialysis, the worse the sleep quality of the patients. This may be due to the fact that as the number of dialysis years increases, patients experience signs and symptoms of secondary diseases in addition to the primary disease as well as hemodialysis treatment, such as renal bone disease, secondary hyperparathyroidism, malnutrition, and pain and discomfort can have a negative physiological and psychological impact on patients, which can lead to a decrease in sleep quality. At the same time, with the increasing number of dialysis sessions, some patients may feel heavy due to the financial burden, and this great psychological pressure is also one of the important factors leading to sleep disorders in patients [15] . Terzi [16] et al. showed that adequate dialysis can improve the sleep quality of patients; GU [17] showed that hemodialysis combined with hemoperfusion can improve sleep disorders in patients and also can promote melatonin secretion in patients and improve sleep quality. Therefore, patients' sleep quality can be improved by giving them different hemodialysis treatment plans.
3.3 Effect of employment status on patients' sleep quality
Different levels of education reflect, to some extent, the occupations in which they are employed, and the occupations differ in terms of their economic capacity, social activities and lifestyles [18].. The results of this study showed that MHD patients who were employed had higher sleep quality than those who were not employed ((OR=0.56, 95% CI (0.35, 0.89)), i.e., being employed was a protective factor for sleep quality in MHD patients. This result suggests that MHD patients may have a high workload and require more mental activities because of their jobs, and may not have time for lunch break during the day; also, the patients are more educated and can cope better with the adverse factors affecting sleep quality through the knowledge about hemodialysis and sleep. The results of this study suggest that health education on psychological care as well as knowledge of sleep etc. should be strengthened for non-working MHD patients, and patients should be encouraged to perform appropriate mental activities and reduce daytime sleep time in order to improve their sleep quality.
3.4 No emergency/inpatient experience in the last month as a protective factor for patient sleep quality
Patients with MHD may require hospitalization for treatment of hyperkalemia, heart failure, and complications or unexpected injuries, such as fractures. The results of this study showed that no emergency/hospitalization experience in the last month (OR=0.41, 95% CI (0.27, 0.70)) was a protective factor for sleep quality in MHD patients. This may be because patients are prone to a strong sense of isolation due to the unfamiliarity of the hospitalization environment and the lack of family companionship and care; one study [19] pointed out that most maintenance hemodialysis patients have difficulty falling asleep, shallow sleep, easy awakening, difficulty in falling back asleep after waking, and the poor mental status during the day. The need to perform some therapeutic care operations on time during hospitalization and the different working hours of patients in the same ward can seriously affect sleep quality and psychological mood. This result suggests that medical staff should strengthen the assessment of patients' conditions and instruct patients to seek medical consultation and treatment promptly if they have discomfort, to reduce the chance of hospitalization and emergency treatment for patients.
In conclusion, the overall sleep quality of MHD patients remains poor, which is related to the patient's dialysis age, work status, and the last 1-month emergency/hospitalization experience. The occurrence of sleep disorders in dialysis patients is the result of multiple factors, including the progression of the patient's primary disease, lifestyle habits, psychological factors, comorbidities, ion metabolism disorders, and toxin accumulation. In contrast to the above factors, hemodialysis treatment itself can have an impact on the quality of patients' sleep. Therefore, medical workers should develop a reasonable dialysis plan in conjunction with the patient's condition to ensure the adequacy of dialysis, so that dialysis patients can obtain the maximum benefit from dialysis treatment, reduce the occurrence of complications, and reduce the impact of sleep disorders induced by hemodialysis treatment. The psychological status of patients should also be closely monitored and early intervention should be made after abnormalities are detected. Strengthening protective factors for sleep quality in MHD patients and taking measures in advance to minimize the risk of sleep disorders as much as possible can help reduce the occurrence of sleep disorders in patients. A study [20] confirmed that by enhancing patients' understanding of their situation and mastering relevant health knowledge, patients' psychological stress can be relieved, thus improving sleep quality. Therefore, health care professionals can provide targeted psychological care and health education to MHD patients, can provide comfort care for them, encourage patients to reduce daytime sleep time, perform appropriate physical exercise according to their physical strength, reduce loneliness, discomfort, and other pessimistic emotions can take hemodialysis treatment combined with conventional hemodialysis to reduce large molecule toxins in patients' bodies, reduce skin itching, improve bone pain, etc. Adjust the dialysis mode to improve the quality of sleep and improve the quality of life of patients.
Ethics approval and consent to participate
This was an observational study, according to the ethical guidelines of the Helsinki Declaration and was approved by the Human Ethics Committee of China-Japan Friendship Hospital. We have received informed consent from the participants. Ethics review number is 2017-51.
Consent for publication
Not applicable.
Availability of data and materials
All data generated or analysed during this study are included in this published article.
Competing interests
The authors declare that they have no competing interests.
Funding
Not applicable.
Authors' contributions
Wanning Jia: Conceptualization, Methodology, Software, Data curation, Writing- Original draft preparation.
Liu Yang: Supervision, Software, Validation.
Wenwen He: Visualization, Investigation.
Lu Zhang: Writing- Reviewing and Editing.
Acknowledgements
The authors would like to thank the reviewers for their constructive feedback and all the users who participated in this study.
Authors' information (optional)
the name by which each author is known, with his or her highest academic degree(s) and institutional affiliation:
Wanning Jia:bachelor,China-Japan Friendship Hospital.
Liu Yang:master,China-Japan Friendship Hospital.
Wenwen He:bachelor,China-Japan Friendship Hospital.
Lu Zhang:bachelor,China-Japan Friendship Hospital.
the name and address of the author responsible for correspondence and proof about the manuscript:
Liu Yang:, China-Japan Friendship Hospital, No. 2, Yinghua East Street, Chaoyang District, Beijing, China.
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No competing interests reported.