s u m m a r y
Purpose
Despite the high prevalence of postdialysis fatigue (PDF) in maintenance hemodialysis patients, no meta-analysis on the prevalence and risk factors of PDF has yet been published. This study aimed to identify the prevalence of PDF and explore its related factors.
Methods
PubMed, Embase, CENTRAL, Web of Science, Cumulative Index to Nursing and Allied Health Literature (CINAHL), and the four Chinese databases (National Knowledge Infrastructure [CNKI], Chinese Biomedical Literature database [SinoMed], Wanfang Digital Periodicals [WANFANG], and Chinese Science and Technology Periodicals [VIP] database) were searched from inception up to July 2022. This study was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. The articles were independently searched by two reviewers, and the relevant data were extracted. The Agency for Healthcare Research and Quality was used to assess the quality of the included studies.
Results
Thirteen articles with 2,118 participants were included. The pooled prevalence was 60.0%. The meta-analysis results revealed that the ultrafiltration volume, mean arterial pressure after dialysis, and good sleep quality were potentially associated with PDF, whereas only good sleep quality (odds ratio 0.24, 95% confidence interval 0.19–0.30) was significantly associated with PDF.
Conclusion
PDF is common in maintenance hemodialysis patients, which is related to the ultrafiltration volume, sleep quality, and mean arterial pressure after dialysis. However, the mechanism underlying the risk factors and PDF remains unknown. Further research is warranted to investigate the risk factors, intervention, treatment, and mechanism in maintenance hemodialysis patients.
Keywords
Introduction
End-stage renal disease (ESRD) refers to the inability of the kidneys to maintain fluid, electrolyte, and waste balance in the body and is a major public health challenge around the world [
1
]. More than 2 million patients with ESRD require dialysis to survive [2
], and maintenance hemodialysis (MHD) is the main method of renal replacement therapy. One of the most frequent side effects of MHD is postdialysis fatigue (PDF). PDF is defined as a feeling of exhaustion requiring rest or sleep for relief [3
]. Patients with PDF may need more than 2 hours of sleep or rest to recuperate from dialysis [4
], hindering the treatment compliance of dialysis patients. It is a pervasive and debilitating condition that adversely affects the quality of life [5
]. In addition, PDF may be associated with functional disability, cardiac ischemia occurrence, and an increased risk of mortality [6
,7
]. Chronic fatigue (not specified as PDF) may be a contributing factor to cardiovascular events and overall mortality [- Ebadi Z.
- Goërtz Y.M.J.
- Van Herck M.
- Janssen D.J.A.
- Spruit M.A.
- Burtin C.
- et al.
The prevalence and related factors of fatigue in patients with COPD: a systematic review.
Eur Respir Rev. 2021; 30200298https://doi.org/10.1183/16000617.0298-2020
8
,9
]. Although chronic fatigue is associated with a high rate of morbidity and mortality among patients with ESRD, prevalence and risk factors for PDF have not been identified yet.The prevalence of PDF ranges between 42.9% and 80.0% [
10
,11
]. Several factors may explain the variation in PDF prevalence. First of all, various scales are used to evaluate the symptoms and severity of PDF, such as the revised Piper fatigue scale (RPFS), Chalder fatigue questionnaire, postdialysis fatigue self-assessment scale (PDF scale), and self-designed questionnaires based on time, frequency, and intensity. Therefore, the sensitivity and specificity of the scales are different. Second, methodological differences, such as sampling strategy, may affect the estimates of prevalence. In addition, PDF is considered to be chronic fatigue by health care providers, which may be a key point in explaining the lack of attention in hospitals. Moreover, the lack of acknowledgment of the risk factors of PDF may be attributed to the lack of awareness of this symptom, and some risk factors for PDF remain contradictory. For example, the study by Wang et al. supported an association between PDF and C-reactive protein [12
], whereas others did not [- Wang W.P.
- He P.
- Jiang L.
- Xu R.
Post-dialysis fatigue status and influencing factors in single-center hemodialysis patients.
Chinese J Integ Trad Western Nephrol. 2021; 22 ([In Chinese]): 808-811https://doi.org/10.1016/S0272-6386(96)90256-5
13
]. Zeng et al. reported an association between PDF and mean arterial pressure after dialysis [- Zeng W.L.
- Luan Z.J.
- Wu S.
- Zhao Z.X.
- Zhou G.Y.
- Li D.T.
Influencing factors of post-dialysis fatigue in patients under maintenance hemodialysis.
J China Med Univ. 2020; 49 ([In Chinese]): 943-948https://doi.org/10.12007/j.issn.0258-4646.2020.10.016
13
], which was contradicted by another study [- Zeng W.L.
- Luan Z.J.
- Wu S.
- Zhao Z.X.
- Zhou G.Y.
- Li D.T.
Influencing factors of post-dialysis fatigue in patients under maintenance hemodialysis.
J China Med Univ. 2020; 49 ([In Chinese]): 943-948https://doi.org/10.12007/j.issn.0258-4646.2020.10.016
14
]. Meanwhile, ultrafiltration volume, serum sodium, lactic acid, and dialysis complications were also found to be associated with PDF, but the results are discrepant and inconclusive.- Zhuang B.
- Song Z.W.
- Luo J.
- Wang H.M.
- Fang L.
- Ye H.
- et al.
Analysis of post-dialysis fatigue in maintenance hemodialysis patients.
Chinese J Nephrol. 2018; 34 ([In Chinese]): 249-254https://doi.org/10.3760/cma.j.issn.1001-7097.2018.04.002
There is no worldwide consensus regarding the prevalence and risk factors of PDF. A previous summarized the estimated prevalence of PDF at 51.0–86.0% [
15
], but only included three articles without quantitative analysis. Therefore, a systematic review and meta-analysis were performed to synthesize the prevalence and risk factors of PDF to provide better guidance to health care workers.Methods
Design
The review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. The detailed study protocol can be found on the PROSPERO website under the registration number CRD42022309395.
Search methods
Nine databases were comprehensively searched from inception to July 2022, including PubMed, Embase, CENTRAL, Web of Science, Cumulative Index to Nursing and Allied Health Literature (CINAHL), and the four Chinese databases (National Knowledge Infrastructure [CNKI], Chinese Biomedical Literatures database [SinoMed], Wanfang Digital Periodicals [WANFANG] and Chinese Science and Technology Periodicals [VIP] database). Combinations of MeSH terms, Emtree synonyms, and free words were used in the literature search. The search terms comprised kidney failure, hemodialysis, renal dialysis, blood dialysis, blood purification, dialysis, maintenance hemodialysis, maintained hemodialysis, MHD, continuous renal replacement therapy, extracorporeal dialysis, fatigue, weary, exhausted, and PDF. Furthermore, no restrictions were placed on the date, country, publication status, or year of publication, but the languages were restricted to English and Chinese. The details of the search strategy are outlined in Appendix 1. In addition, grey literature and the reference lists included in the identified articles were manually searched.
Inclusion and exclusion criteria
The inclusion criteria were as follows: (1) observational studies; (2) study subjects were adult patients receiving MHD with dialysis duration of more than 3 months, as most of the symptoms of ESRD have been treated and alleviated, to rule out the influence of chronic fatigue state caused by ESRD; (3) specific diagnostic criteria for detecting PDF were available (including scales or dialysis recovery time [DRT]); (4) prevalence or risk factors of PDF were reported. The exclusion criteria were as follows: (1) the studies were not published in English or Chinese language; (2) duplicate studies; (3) no eligible data for extraction; and (4) low-quality studies.
Quality appraisal
Two reviewers (Y.Q. and W.C.X.) independently identified the relevant studies, and any discrepancy relating to the quality of studies was resolved by a third reviewer (B.D.X. or G.J.). The tool of the National Center for Biotechnology Information (US), recommended by the Agency for Healthcare Research and Quality (AHRQ), was used to evaluate the quality of the included studies. The AHRQ includes a total of 11 items with the options “Yes (1 point)," “No (0 point)," and “Unclear (0 point)." According to the score, 0–3 points are regarded as low quality, 4–7 points indicate medium quality, and 8–11 points are considered high quality [
16
].Study selection and data extraction
Strictly following the inclusion and exclusion criteria, two reviewers (Y.Q. and W.C.X.) retrieved and reviewed full-text articles after scrutinizing the titles and abstracts of all articles independently. Every article was independently evaluated by the two reviewers for inclusion in this systematic review and meta-analysis. Any discrepancies relating to article inclusion were resolved by discussion with a third reviewer (B.D.X. or G.J.) to reach a consensus. Data extraction was also performed by two independent reviewers (Y.Q. and W.C.X.). The data from the studies included in the systematic review were the name of the first author, publication year, survey time, country, sample size, age of participants, duration of dialysis, diagnostic criteria, prevalence of PDF, and risk factors.
Synthesis
Stata 15.0 software (Stata Corporation, College Station, Texas, USA) was used for data analysis. The inverse variance method was adopted to estimate the overall prevalence and 95.0% confidence intervals (CIs). The heterogeneity of the included studies was examined by Cochrane's Q statistic and I2 statistic. Pooled prevalence and 95.0% CIs for PDF were calculated using a random effects model or a fixed effects model according to the heterogeneity of results. If no statistical heterogeneity was observed among the results (p > 0.05, I2 < 50.0%), the fixed effects model was used for meta-analysis. In contrast, if statistical heterogeneity was identified, the source of heterogeneity would be further analyzed, and a random effects model was used for meta-analysis. A meta-regression analysis was performed to assess the potential effect of important covariates that may lead to heterogeneity. Significant clinical heterogeneity was evaluated by subgroup analysis or a leave-one-out method by iteratively removing the included study. A sensitivity analysis was also performed to estimate the stability of the results. In addition, the proportions of patients diagnosed with the symptoms were retrieved from all included studies to assess the pooled prevalence of PDF. The odds ratios (ORs) and associated 95% CIs were used to assess the risk factors of PDF. Meanwhile, funnel plots, Begg's test, and Egger's test were used to detect publication bias.
Results
Search outcomes
A total of 3055 articles were identified from our search strategy. After removing 872 duplicates, 2100 articles were excluded, as the titles and abstracts were not relevant to this study, and the full text of 83 articles was reviewed. Finally, 13 articles were included in the systematic review and meta-analysis.
Characteristics of the included studies
A total of 2118 participants were included in the 13 cross-sectional studies. Most articles (11/13) were published in the past 5 years, of which most (8/13) were conducted in China, with two in America, two in Italy, and one in Japan. The characteristics of the included studies are summarized in Table 1.
Table 1Characteristics of the Included Studies.
| First author (year) | Country | Survey time | Sample size, No. (M/W) | Age (mean ± SD) | Duration of dialysis | Diagnostic criteria | Prevalence (%) | Risk factors |
|---|---|---|---|---|---|---|---|---|
| Wang 2021 [ 12 ]
Post-dialysis fatigue status and influencing factors in single-center hemodialysis patients. Chinese J Integ Trad Western Nephrol. 2021; 22 ([In Chinese]): 808-811https://doi.org/10.1016/S0272-6386(96)90256-5 | China | 2018.10–2019.10 | 280 (178/102) | 46.8 ± 7.2 | ＞6 mo | CFQ | 54.4 | CRP, triacylglycerol, diastolic blood pressure after dialysis |
| Gordon 2011 [ 11 ] | America | NR | 58 (38/20) | 56.87 ± 14.54 | ≥3 mo | Questionnaire developed by Sklar | 80.8 | The average daily physical activity, dialysis vintage |
| Zhuang 2018 [ 14 ]
Analysis of post-dialysis fatigue in maintenance hemodialysis patients. Chinese J Nephrol. 2018; 34 ([In Chinese]): 249-254https://doi.org/10.3760/cma.j.issn.1001-7097.2018.04.002 | China | 2016.12–2017.6 | 109 (75/34) | 53.41 ± 10.25 | ≥3 mo | Self-designed questionnaire | 71.7 | NR |
| Mao 2021 [ 17 ]
Analysis of risk factors for post-dialysis fatigue in maintenance hemodialysis patients. Chronic Pathematol J. 2021; 22 ([In Chinese]): 1778-1780https://doi.org/10.16440/J.CNKI.1674-8166.2021.11.52 | China | 2018.7–2020.7 | 120 (73/47) | 52.75 ± 7.85 | ≥3 mo | RPFS | 55.8 | Sleep quality, ultrafiltration volume, serum calcium, mean arterial pressure after dialysis, higher interdialytic weight gain, recovery time |
| Zeng 2020 [ 13 ]
Influencing factors of post-dialysis fatigue in patients under maintenance hemodialysis. J China Med Univ. 2020; 49 ([In Chinese]): 943-948https://doi.org/10.12007/j.issn.0258-4646.2020.10.016 | China | 2018.12–2019.2 | 70 (45/25) | 54.32 ± 11.61 | ≥3 mo | RPFS | 78.6 | Ultrafiltration volume, sleep quality, mean arterial pressure after dialysis |
| Li 2018 [ 18 ]
Analysis of fatigue status and influencing factors of maintenance hemodialysis patients after dialysis. Med J Western China. 2018; 30 ([In Chinese]): 1646-1653https://doi.org/10.3969/j.issn.1672-3511.2018.11.020 | China | 2017.5–2017.6 | 148 (84/64) | NR | ≥3 mo | RPFS | 54.7 | Age, ultrafiltration volume, dialysis complications, hemoglobin, dialysis course |
| Lin 2019 [ 19 ]
Causes of fatigue status after maintenance hemodialysis in patients with coronary heart disease. Prevent Treatment Cardiovasc Dis. 2019; 8 ([In Chinese]): 39-41https://doi.org/10.3969/j.issn.1672-3015(x).2019.08.016 | China | 2017.05–2018.04 | 65 (48/17) | 49.20 ± 5.03 | ≥24 mo | FAI | 43.1 | Hemodialysis duration, ultrafiltration volume, dialysis complications |
| Bossola 2018 [ 5 ] | Italy | NR | 271 | NR | ≥12 mo | SF-36 Vitality Subscale | 60.5 | Activity daily living |
| Sklar 1996 [ 3 ] | America | 1995.06–1995.08 | 85 (50/35) | NR | ≥3 mo | Self-designed questionnaire | 50.6 | NR |
| Kodama 2020 [ 10 ] | Japan | 2016.06–2016.11 | 126 (85/41) | NR | ≥3 mo | PDF scale | 42.9 | NR |
| Zu 2020 [ 20 ] | China | 2018.03–2019.03 | 115 (59/56) | 54.50 ± 12.76 | ≥6 mo | DRT | 60.0 | IDH, postdialysis Na, lactic acid, Charlson comorbidity index, ultrafiltration rate |
| Jiang 2022 [ 21 ]
Analysis of recovery time and influencing factors of fatigue recovery after dialysis in maintenance hemodialysis patients. Chinese J Integrated Trad Western Nephrol. 2022; 23 ([In Chinese]): 145-148https://doi.org/10.3969/j.issn.1009-587X.2022.02.013 | China | 2019.12 | 626 (385/241) | 56.1 ± 12.9 | ≥3 mo | Self-designed questionnaire | 55.5 | HAMA score, HAMD score, ultrafiltration volume |
| Brys 2020 [ 22 ]
Peridialytic serum cytokine levels and their relationship with postdialysis fatigue and recovery in patients on chronic haemodialysis-A preliminary study. Cytokine. 2020; 135155223https://doi.org/10.1016/j.cyto.2020.155223 | Italy | 2017.01–2017.12 | 45 (29/16) | NR | ≥12 mo | Questionnaire developed by Sklar | 74.0 | IL-10 levels before dialysis |
Note. CFQ = Chalder Fatigue Questionnaire; CRP = C-reactive protein; FAI = Fatigue Assessment Instrument; HAMA = Hamilton Anxiety Scale; HAMD = Hamilton Depression Scale; IDH = intradialytic hypotension; IL = interleukin; M/W = men/women; NR = not reported; PDF = postdialysis fatigue; RPFS = Revised Piper Fatigue Scale; SD = standard deviation; Y = year.
Risk of bias within studies
Thirteen studies were evaluated by AHRQ. There were eight high-quality studies with a score ranging between 8 and 9 points and five middle-quality studies with scores of 6–7 points. The details of the quality assessment are presented in Table 2.
Table 2AHRQ Critical Appraisal Checklist Applied for Included Studies in the Systematic Review.
| Author (year) | Q1 | Q2 | Q3 | Q4 | Q5 | Q6 | Q7 | Q8 | Q9 | Q10 | Q11 | Score | Quality of study |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Wang (2021) | Y | Y | Y | Y | U | Y | Y | Y | N | Y | N | 8 | High |
| Gordon (2011) | Y | Y | Y | Y | U | Y | Y | Y | Y | Y | N | 9 | High |
| Zhuang (2018) | Y | Y | Y | Y | U | N | N | Y | N | Y | N | 6 | Middle |
| Mao (2021) | Y | Y | Y | Y | U | Y | N | Y | N | Y | N | 7 | Middle |
| Zeng (2020) | Y | Y | Y | Y | U | Y | N | Y | N | Y | N | 7 | Middle |
| Li (2018) | Y | Y | Y | Y | U | Y | N | Y | Y | Y | N | 8 | High |
| Lin (2019) | Y | Y | Y | Y | U | Y | N | Y | N | Y | N | 7 | Middle |
| Bossola (2018) | Y | Y | Y | Y | U | Y | Y | Y | N | Y | N | 8 | High |
| Sklar (1996) | Y | Y | Y | Y | U | Y | Y | N | N | Y | Y | 8 | High |
| Kodama (2020) | Y | Y | Y | Y | U | Y | Y | Y | Y | Y | N | 9 | High |
| Zu (2020) | Y | Y | Y | Y | U | Y | Y | Y | N | Y | N | 8 | High |
| Jiang (2022) | Y | Y | Y | Y | U | Y | N | Y | Y | Y | N | 7 | Middle |
| Brys (2020) | Y | Y | Y | Y | U | Y | N | Y | Y | Y | N | 8 | High |
Note. Q1 = Define the source of information (survey, record review); Q2 = List inclusion and exclusion criteria for exposed and unexposed subjects (cases and controls) or refer to previous publications; Q3 = Indicate period used for identifying patients.; Q4 = Indicate whether or not subjects were consecutive if not population-based; Q5 = Indicate if evaluators of subjective components of study were masked to other aspects of the status of the participants; Q6 = Describe any assessments undertaken for quality assurance purposes (e.g., test/retest of primary outcome measurements); Q7 = Explain any patient exclusions from analysis; Q8 = Describe how confounding was assessed and/or controlled; Q9 = If applicable, explain how missing data were handled in the analysis; Q10 = Summarize patient response rates and completeness of data collection; Q11 = Clarify what follow-up, if any, was expected and the percentage of patients for which incomplete data or follow-up was obtained.
N = No; U = Unclear; Y = Yes.
Prevalence of PDF
In total, 13 of the included studies reported the prevalence of PDF. The prevalence of PDF ranged from 42.9% to 80.8%, irrespective of the PDF assessment method. The pooled prevalence of PDF was estimated to be 60.0% (95% CI: 53.0%, 66.0%, I2 = 89.3%, p < 0.0001).
Meta-regression analyses
The sample size, publication year, survey time, gender ratio, literature quality score, scale, country, and duration of dialysis were chosen as covariates. However, the regression coefficients of the above covariates showed no statistically significant difference between the intervention effect of each subgroup and the designated reference subgroup (p > 0.05; Table 3).
Table 3Meta-Regression Analyses Results.
| Covariate | β | 95% CI | p |
|---|---|---|---|
| Sample size | −0.000 | −0.001 to 0.000 | 0.363 |
| Publication year | −0.025 | −0.248 to 0.198 | 0.863 |
| Survey time | −0.020 | −0.052 to 0.012 | 0.193 |
| Men to women ratio | −0.000 | −0.001 to 0.000 | 0.808 |
| Score | −0.018 | −0.160 to 0.197 | 0.824 |
| Scale | −0.014 | −0.048 to 0.021 | 0.397 |
| Country | |||
| America | 0.025 | 0.751 to 1.400 | 0.861 |
| China | 0.918 | 0.718 to 1.173 | 0.449 |
| Italy | 0.791 | 0.542 to 1.154 | 0.194 |
| Duration of dialysis | 0.026 | −0.070 to 0.768 | 0.560 |
Note. CI = confidence interval.
Subgroup analyses
Subgroup analyses were performed according to the PDF degree (mild, moderate, or severe) as determined by the scale score or DRT. The RPFS classification is based on the total score of each item added together: 0 = no fatigue, 1∼3 = mild fatigue, 4∼6 = moderate fatigue, and 7∼10 = severe fatigue. The Chalder fatigue questionnaire classification is based on the interquartile range score: ＜13 = no fatigue, 13∼16 = mild fatigue, 17∼22 = moderate fatigue, and ≥23 = severe fatigue. For DRT, PDF lasting >2 h after dialysis was defined as severe PDF, and <2 h was defined as mild PDF. The estimated pooled prevalence of mild, moderate, and severe PDF was 28.0%, 32.2%, and 20.2%, respectively. Sensitivity analysis was conducted due to the statistical heterogeneity of moderate and severe PDF (I2 = 84.1%, I2 = 92.8%). As for severe PDF, the study by Li et al. [
16
] might be a source of heterogeneity because the heterogeneity was reduced after excluding the study, with I2 decreasing from 92.8% to 76.9%. The disparity in dialysis frequency may be attributed to the heterogeneity of severe PD.The estimates of pooled prevalence of RPFS, based on the questionnaire developed by Sklar and other PDF scales, were 60.3%, 70.1%, and 53.1%, respectively. Due to the high statistical heterogeneity (I2 = 87.8%, I2 = 92.1%, I2 = 86.7%), sensitivity analysis was adopted. Heterogeneity in the scale of RPFS was significantly reduced from 87.8% to 0.0% when Zeng's study [
11
] was eliminated, possibly because patients with severe trauma within 1 month were excluded in Zeng's study, resulting in a lower total score on the behavioral/severity dimension of the scale. As for the questionnaire developed by Sklar [3
], the heterogeneity was decreased from 92.1% to 61.4% after excluding the study by Sklar et al [10
]. The heterogeneity may result from different dialysis methods (conventional dialysis with hollow fiber dialyzers vs. central venous catheterization).Subgroup analyses were conducted based on the survey time before and after 2016, as fatigue was identified as a core prognostic outcome in 2016. The estimated pooled prevalence of PDF was 59.1% before 2016 and 45.9% after 2016, with a statistical heterogeneity of 86.1% and 18.3%, respectively. Subgroup analyses of the PDF are displayed in Table 4.
Table 4Subgroup Analyses of the PDF.
| Subgroup | Number of studies | Results of heterogeneity | Effect model | Prevalence (%, 95% CI) | |
|---|---|---|---|---|---|
| (I2, %) | p | ||||
| PDF degree | |||||
| Mild | 4 | 0 | 0.526 | Fixed | 28.0 (23.9–32.1) |
| Moderate | 3 | 84.1 | <0.001 | Random | 32.2 (19.8–44.5) |
| Severe | 4 | 92.8 | <0.001 | Random | 20.2 (7.4–33.1) |
| Scales for PDF | |||||
| RPFS | 3 | 87.8 | <0.001 | Random | 60.3 (55.1–65.4) |
| Questionnaire developed by Sklar | 3 | 92.1 | <0.001 | Random | 70.1 (48.1–92.2) |
| Other PDF scale | 6 | 86.7 | <0.001 | Random | 53.1 (45.6–60.6) |
| Survey time | |||||
| The years before 2016 | 2 | 86.1 | <0.001 | Random | 59.1 (52.2–66.1) |
| The years after 2016 | 9 | 18.3 | 0.269 | Fixed | 45.9 (39.2–52.6) |
| Region | |||||
| Asia | 9 | 86.5 | <0.001 | Random | 56.1 (49.2–62.9) |
| Non-Asia | 4 | 90.8 | <0.001 | Random | 67.6 (52.6–82.6) |
Note. CI = confidence interval; PDF = postdialysis fatigue.
Risk factors
In total, 26 potential risk factors related to PDF were identified, including C-reactive protein, triacylglycerol, diastolic blood pressure after dialysis, the average daily physical activity, dialysis vintage, sleep quality, ultrafiltration volume, serum calcium, mean arterial pressure after dialysis, higher interdialytic weight gain, DRT, sleep quality, age, dialysis complications, hemoglobin, dialysis course, hemodialysis duration, activity daily living, intradialytic hypotension, postdialysis Na, lactic acid, Charlson comorbidity index, ultrafiltration rate, Hamilton Anxiety Scale score, Hamilton depression scale score, and interleukin-10 levels before dialysis. However, among them, only ultrafiltration volume, sleep quality, and mean arterial pressure after dialysis have sufficient data and could be synthesized. In the analysis of sleep quality and mean arterial pressure after dialysis, a fixed effects model was used, as no statistically significant heterogeneity was observed. While the statistical heterogeneity of ultrafiltration volume was observed, thus a random effects model was used. Sensitivity analysis was performed to explore the source of heterogeneity. After excluding the study by Lin et al,
19
the heterogeneity was reduced from 99.0% to 72.0%, which may be attributed to the inclusion of patients with MHD with coronary heart disease (Table 5).- Lin H.Y.
Causes of fatigue status after maintenance hemodialysis in patients with coronary heart disease.
Prevent Treatment Cardiovasc Dis. 2019; 8 ([In Chinese]): 39-41https://doi.org/10.3969/j.issn.1672-3015(x).2019.08.016
Table 5Pooled Risk Factors of PDF.
| Risk factors | Number of included studies | Results of heterogeneity | Effect model | Results of meta-analysis | ||
|---|---|---|---|---|---|---|
| p | I2 (%） | OR （95% CI） | p | |||
| Ultrafiltration volume | 5 | <0.001 | 99.0 | Random | 2.93 (0.83–10.40) | = 0.10 |
| Sleep quality | 2 | = 0.99 | 0.0 | Fixed | 0.24 (0.19–0.30) | <0.001 |
| Mean arterial pressure after dialysis | 2 | = 0.55 | 0.0 | Fixed | 0.96 (0.93–1.00) | = 0.03 |
Note. CI = confidence interval; OR = odds ratio; PDF = postdialysis fatigue.
Sensitivity analysis/publication bias
Sensitivity analysis suggested that the meta-analysis results were relatively stable. Funnel plots and Egger’s test were used to evaluate publication bias. The funnel plot showed no publication bias, whereas the results of Begg's test (Z = 0.583) and Egger's test (p = 0.378) indicated a low risk of publication bias in this analysis.
Discussion
This study included 13 studies with 2,118 patients. Regarding the quality of the included studies, the AHRQ scores ranged from 5 to 6, indicating a moderate or higher level of quality. Meta-regression analyses showed no statistically significant difference among the covariates of sample size, publication year, survey time, gender ratio, the literature quality score, scale, country, and duration of dialysis. However, the heterogeneity was significantly reduced in the subgroup analysis by PDF degree, scales for PDF assessment, and survey time, suggesting that the above factors may introduce heterogeneity. The pooled prevalence of PDF was 60.0%, which is lower than the systematic review published in 2018 [
23
]. This discrepancy might be attributed to our strict inclusion and exclusion criteria, whereas the other's subjects included a wider range of chronic fatigue participants. Furthermore, PDF is largely ignored in the clinical setting, and there are few effective therapies for PDF. The symptom has not been explored in other regions than China, Japan, America, and Italy. Future research should be conducted in countries that lack data on the prevalence of PDF.- Cheng L.H.
- Zhang H.M.
- Liu S.
The prevalence of fatigue in maintenance hemodialysis in China: a Meta- analysis.
Chinese J Pract Nurs. 2018; 34 ([In Chinese]): 1749-1755https://doi.org/10.3760/cma.j.issn.1672-7088.2018.22.015
This study demonstrated a difference between the pooled prevalence of PDF and the degree of fatigue. Moderate PDF was more prevalent than mild or severe PDF, which is consistent with other research results [
24
]. This finding may be related to the following two factors. On the one hand, the lack of recognition of PDF may result in overlooking PDF. Mild PDF could be ignored, whereas severe PDF could be mistaken for chronic fatigue by health care workers. On the other hand, some of the fatigue scales are not specific for PDF, and the limited sensitivity reduces the detection of mild PDF. Therefore, health care workers should pay more attention to PDF and their treatment. Future studies should lead to the development of different therapies for PDF.- Ma Y.X.
- He B.
- Jiang M.Y.
- Yang Y.L.
- Wang C.X.
- Huang C.
- et al.
Prevalence and risk factors of cancer-related fatigue: a systematic review and meta-analysis.
Int J Nurs Stud. 2020; 111103707https://doi.org/10.1016/j.ijnurstu.2020.103707
Among the included studies, nine different scales were used to measure PDF, and the distinct instruments may limit the internal validity of this study [
25
]. Among the nine scales, only the PDF scale was designed for PDF in hemodialysis patients, showing good reliability and validity [10
]. However, the new assessment scale was first applied in 2020 and needs further verification. RPFS was the most frequently used tool, but it was designed for cancer-related fatigue, yielding a lower prevalence of PDF (60.3%). The first used tool was the questionnaire developed by Sklar. The fatigue index considers the duration, frequency, and intensity of PDF, but its sensitivity and specificity have not been evaluated [3
]. Fatigue Assessment Instrument has high internal consistency and good concurrent and discriminant validity and can distinguish the fatigue of healthy people from the fatigue from hemodialysis and different diseases [26
]. Currently, there is no international consensus to measure PDF, so a multidisciplinary collaboration is recommended. Health care workers and researchers should work together to agree on the use of a dedicated scale to assess PDF to improve clinical treatment.The prevalence of PDF has varied over time. In November 2016, the standardized outcomes in nephrology-hemodialysis Fatigue Consensus Workshop identified fatigue as a core prognostic outcome [
27
]. Although the number of studies on chronic fatigue has increased year by year, few studies focused on PDF. Patients suffering from PDF received prompt treatment although the symptom was mistaken for chronic fatigue. In the last 5 years, a growing number of studies have investigated PDF, increasing its awareness among health care workers. Furthermore, the symptom of PDF in some patients is prevented before occurring, which may explain the higher prevalence of PDF after 2016 compared with before 2016. ERSD is a global public health problem, and this study suggests a higher estimated pooled prevalence of PDF in non-Asian countries than in Asia. This difference in prevalence may be attributed to the particularly high prevalence of kidney disease in Asia. With the increased awareness of the symptom of PDF among health care staff, effective measures were taken as soon as possible. An international survey indicated that 68.0% of patients reported taking longer than 2 hours to recover from a dialysis session, with 27.0% taking more than 6 hours [28
]. Therefore, it is important to improve the awareness and knowledge of PDF in non-Asian countries.Sleep quality was significantly associated with PDF. Among MHD patients, the majority (68.1%) were poor sleepers [
29
], which might be because MHD patients generally need lifelong treatment, and the relatively high treatment cost brings a considerable economic burden to the patients and their families. Therefore, MHD patients are likely to experience negative emotions, resulting in sleep disorders and poor sleep quality. Thus, health care workers should provide patients with a quiet and comfortable treatment environment during dialysis, fully assess the patient's psychological state, and carry out a personalized psychological intervention.This study identified the mean arterial pressure after dialysis as a risk factor for PDF. Previous studies reported that low blood pressure was significantly associated with longer recovery time [
30
]. Lower mean arterial pressure after dialysis leads to hypoperfusion of vital organs and affects the recovery time of the brain and heart, prolonging the recovery time of fatigue after dialysis. In addition, cold dialysis was found to relieve the symptom of fatigue [31
], as it possibly improves hemodynamic stability and systolic blood pressure [32
]. Therefore, monitoring the blood pressure of patients during dialysis and actively preventing and treating severe hypotension may alleviate fatigue after dialysis.Some studies have demonstrated the relationship between ultrafiltration volume and PDF. First, ultrafiltration volume overload is usually caused by an excessive increase in body weight during dialysis, which increases extracellular water, impairing cardiac and respiratory function, and providing a physiological basis for PDF [
33
]. Moreover, excessive ultrafiltration increases the changes in plasma and intracellular fluid movement during dialysis and increases the risk of dialysis-related hypotension [34
]. Therefore, the water intake should be appropriately reduced during dialysis treatment to effectively reduce the impact of PDF on life.To our knowledge, this study was the first systematic review and meta-analysis to analyze the pooled prevalence and risk factors of PDF. This study may enhance health care workers' understanding of PDF, promoting its prevention, assessment, diagnosis, treatment, and monitoring. Overall, one of this study's strengths is the thorough literature search across nine electronic databases to limit the risk of missing research. Moreover, the quality of included studies was high or moderate. Meta-regression, subgroup analyses, and sensitivity analyses were performed to explore the possible reasons for heterogeneity. However, the limitations of this study should also be acknowledged. First, the included studies adopted different scales for PDF, which affected the internal validity of this study. Second, the risk factors available from each study were inconsistent, so some risk factors for PDF could not be analyzed in depth. Meanwhile, the association between PDF and cardiovascular events, stroke, and mortality, and the potential possible effect of racial disparities could not be explored due to the limited number of studies. Our team aims to carry out relevant original studies in the future. Third, the included studies were conducted mainly in China, possibly raising bias. Finally, relatively high heterogeneity was observed, and the results require cautious interpretation.
Clinical implications
This study has demonstrated the prevalence of PDF and its related factors. Exploring the prevalence and risk factors of PDF can provide an up-to-date theoretical basis for the management of maintenance hemodialysis patients. Most significantly, this study emphasizes the importance of PDF.
Conclusion
We found a pooled prevalence of PDF of 60.0%. With such a high prevalence, health care workers should pay more attention to PDF. Ultrafiltration volume, sleep quality, and mean arterial pressure after dialysis are related to PDF. These findings suggest that future research with a large overall sample should be conducted to determine which risk factors most strongly affect the symptom of PDF, its underlying mechanism, and the most effective treatments.
Conflict of interest
None.
Ethics approval statement
This is not a clinical trial; this study did not require the approval of an Ethics Committee because it is based entirely on previously published studies.
Patient consent statement
As it is based entirely on previously published studies, this study did not require the approval of patients. In addition, we have asked the authors of including studies for permission to cite data.
Clinical trial registration
As it is based entirely on previously published studies, this study protocol has registered on the PROSPERO website (CRD42022309395).
Acknowledgments
None.
Appendix A. Supplementary data
The following are the Supplementary data to this article:
- Multimedia component 1
References
- Causes of death in end-Stage kidney disease: comparison between the United States renal data system and a large integrated health care system.Am J Nephrol. 2022; : 1-9https://doi.org/10.1159/000520466
- Status of care for end stage kidney disease in countries and regions worldwide: international cross-sectional survey.Br Med J. 2019; 367: l5873https://doi.org/10.1136/bmj.l5873
- Post-dialysis fatigue.Am J Kidney Dis. 1996; 367: l5873
- Investigation and analysis of post-dialysis fatigue in maintenance hemodialysis patients.J Am Soc Nephrol. 2020; 31: 365
- Prevalence and severity of post-dialysis fatigue are higher in patients on chronic hemodialysis with functional disability.Ther Apher Dial. 2018; 22: 635-640https://doi.org/10.1111/1744-9987.12705
- Prevalence of fatigue after stroke: a systematic review and meta-analysis.Eur Stroke J. 2021; 6: 319-332https://doi.org/10.1177/23969873211047681
- The prevalence and related factors of fatigue in patients with COPD: a systematic review.Eur Respir Rev. 2021; 30200298https://doi.org/10.1183/16000617.0298-2020
- Fatigue is a predictor for cardiovascular outcomes in patients undergoing hemodialysis.Clin J Am Soc Nephrol. 2010; 5: 659-666https://doi.org/10.2215/CJN.08151109
- Impact of fatigue on outcomes in the hemodialysis (HEMO) study.Am J Nephrol. 2011; 33: 515-523https://doi.org/10.1159/000328004
- A new assessment scale for post-dialysis fatigue in hemodialysis patients.Renal Replacement Therapy. 2020; 6: 1-8https://doi.org/10.1186/s41100-019-0252-5
- Post-dialysis fatigue is associated with sedentary behavior.Clin Nephrol. 2011; 75: 432-433
- Post-dialysis fatigue status and influencing factors in single-center hemodialysis patients.Chinese J Integ Trad Western Nephrol. 2021; 22 ([In Chinese]): 808-811https://doi.org/10.1016/S0272-6386(96)90256-5
- Influencing factors of post-dialysis fatigue in patients under maintenance hemodialysis.J China Med Univ. 2020; 49 ([In Chinese]): 943-948https://doi.org/10.12007/j.issn.0258-4646.2020.10.016
- Analysis of post-dialysis fatigue in maintenance hemodialysis patients.Chinese J Nephrol. 2018; 34 ([In Chinese]): 249-254https://doi.org/10.3760/cma.j.issn.1001-7097.2018.04.002
- Post-dialysis Fatigue: a frequent and debilitating symptom.Semin Dial. 2016; 9: 222-227https://doi.org/10.1111/sdi.12468
- Evidence report/technology assessment.Celiac Disease. 2004; (Summary) (104) 1–6. Available from:
- Analysis of risk factors for post-dialysis fatigue in maintenance hemodialysis patients.Chronic Pathematol J. 2021; 22 ([In Chinese]): 1778-1780https://doi.org/10.16440/J.CNKI.1674-8166.2021.11.52
- Analysis of fatigue status and influencing factors of maintenance hemodialysis patients after dialysis.Med J Western China. 2018; 30 ([In Chinese]): 1646-1653https://doi.org/10.3969/j.issn.1672-3511.2018.11.020
- Causes of fatigue status after maintenance hemodialysis in patients with coronary heart disease.Prevent Treatment Cardiovasc Dis. 2019; 8 ([In Chinese]): 39-41https://doi.org/10.3969/j.issn.1672-3015(x).2019.08.016
- Higher postdialysis lactic acid is associated with post-dialysis fatigue in maintenance of hemodialysis patients.Blood Purif. 2020; 49: 535-541https://doi.org/10.1159/000505612
- Analysis of recovery time and influencing factors of fatigue recovery after dialysis in maintenance hemodialysis patients.Chinese J Integrated Trad Western Nephrol. 2022; 23 ([In Chinese]): 145-148https://doi.org/10.3969/j.issn.1009-587X.2022.02.013
- Peridialytic serum cytokine levels and their relationship with postdialysis fatigue and recovery in patients on chronic haemodialysis-A preliminary study.Cytokine. 2020; 135155223https://doi.org/10.1016/j.cyto.2020.155223
- The prevalence of fatigue in maintenance hemodialysis in China: a Meta- analysis.Chinese J Pract Nurs. 2018; 34 ([In Chinese]): 1749-1755https://doi.org/10.3760/cma.j.issn.1672-7088.2018.22.015
- Prevalence and risk factors of cancer-related fatigue: a systematic review and meta-analysis.Int J Nurs Stud. 2020; 111103707https://doi.org/10.1016/j.ijnurstu.2020.103707
- Internal, external, and ecological validity in research design, conduct, and evaluation.Indian J Psychol Med. 2018; 40: 498-499https://doi.org/10.4103/ijpsym.Ijpsym_334_18
- The assessment of fatigue: a practical guide for clinicians and researchers.J Psychosom Res. 2004; 56: 157-170https://doi.org/10.1016/s0022-3999(03)00371-4
- Establishing core outcome domains in hemodialysis: report of the standardized outcomes in nephrology; hemodialysis (SONGHD) Consensus Workshop.Am J Kidney Dis. 2017; 69: 97-107https://doi.org/10.1053/j.ajkd.2016.05.022
- Recovery time, quality of life, and mortality in hemodialysis patients: the Dialysis Outcomes and Practice Patterns Study (DOPPS).Am J Kidney Dis. 2014; 64: 86-94https://doi.org/10.1053/j.ajkd.2014.01.014
- Fatigue and depression and sleep problems among hemodialysis patients in a tertiary care center.Saudi J Kidney Dis Transpl. 2012; 23: 729-735https://doi.org/10.4103/1319-2442.98149
- Post-dialysis recovery time is extended in patients with greater self-reported depression screening questionnaire scores.Hemodial Int. 2018; 22: 369-376https://doi.org/10.1111/hdi.12642
- Cold dialysis solution for hemodialysis patients with fatigue: a cross-over study.Iran J Kidney Dis. 2016; 10 (PMID: 27721231): 319-324
- Effect of dialysate temperature on hemodynamic stability among hemodialysis patients.Saudi J Kidney Dis Transpl. 2009; 20 (PMID: 19587499): 596-603
- Extracellular water excess and increased self-reported fatigue in chronic hemodialysis patients.Ther Apher Dial. 2018; 22: 152-159https://doi.org/10.1111/1744-9987.12648
- Efficacy of hemo-control biofeedback system in intradialytic hypotension-prone hemodialysis patients.J Kor Med Sci. 2014; 29: 805-810https://doi.org/10.3346/jkms.2014.29.6.805
Article info
Publication history
Published online: November 28, 2022
Accepted:
November 21,
2022
Received in revised form:
November 20,
2022
Received:
June 8,
2022
Identification
Copyright
© 2022 Korean Society of Nursing Science. Published by Elsevier B.V.
User license
Creative Commons Attribution (CC BY 4.0) | How you can reuse 
Elsevier's open access license policy
Creative Commons Attribution (CC BY 4.0)
Permitted
- Read, print & download
- Redistribute or republish the final article
- Text & data mine
- Translate the article
- Reuse portions or extracts from the article in other works
- Sell or re-use for commercial purposes
Elsevier's open access license policy
