Skip to main content
Download PDF

Impact of variables on recovery time in patients undergoing hemodialysis: an international survey

BMC Nephrology volume 26, Article number: 13 (2025) Cite this article

Abstract

Background

Dialysis recovery time (DRT) refers to the period during which fatigue and weakness subside following hemodialysis treatment, allowing patients to resume their daily routines. This study aimed to identify the factors influencing DRT in hemodialysis patients in Turkey and Portugal, where the prevalence of chronic kidney disease is notably high.

Methods

A cross-sectional observational study was conducted in a private dialysis center in Turkey and three dialysis centers in Portugal. The study included hemodialysis patients aged 18 years or older who had been undergoing four-hour hemodialysis sessions three times a week for at least six months. Participants had no communication barriers and voluntarily agreed to take part in the study. Data were collected using a semi-structured questionnaire to gather descriptive characteristics and the Hospital Anxiety and Depression Scale. Logistic regression analysis was employed to identify independent variables influencing DRT.

Results

A total of 294 patients participated in the study, including 187 from Turkey and 107 from Portugal. In Turkey, increased interdialytic weight gain (P = 0.043) was associated with prolonged recovery time, while the use of high-flux dialyzers (P = 0.026) was linked to shorter recovery times. In Portugal, older age (P = 0.020) was found to extend recovery time.

Conclusion

Recovery time after dialysis is influenced by varying factors across different countries. Further research with larger sample sizes is needed to deepen understanding of these factors and their implications.

Clinical trial number

NCT04667741.

Peer Review reports

Introduction

Hemodialysis induces significant changes in the concentrations of small and medium-weight molecules, acid-base balance, and serum electrolyte levels. Additionally, rapid ultrafiltration (UF), an increase in ultrafiltration volume per unit of time, and a high rate of vascular refill are commonly observed during treatment [1]. These physiological changes and biochemical events can lead to symptoms during and for hours after dialysis treatment, significantly impacting patients’ quality of life [2, 3].

Dialysis recovery time (DRT) refers to the period required for patients to recover from feelings of fatigue and weakness following hemodialysis and resume their daily routines. Most patients experience challenges in performing activities of daily living during this recovery period [4,5,6]. DRT is assessed by asking patients the question, “How long does it take you to recover from a dialysis session?” and recording their response in minutes. Studies have shown a statistically significant negative correlation between DRT and sub-dimensions of the Quality of Life Scale [6].

Research indicates that DRT varies among patients. For instance, one study reported that 52.1% of patients had a DRT of less than 2 h [7], while another found that 40% of patients recovered in under 4 h [2]. Conversely, a study revealed that 10% of patients had a DRT exceeding 12 h [8]. Furthermore, studies have demonstrated a relationship between prolonged DRT and increased mortality risk. For example, mortality was found to be 1.6 times higher in patients whose DRT exceeded 12 h [8]. DRT is influenced by both non-modifiable and modifiable risk factors. Non-modifiable factors include age, gender, serum albumin levels, diabetes, and psychiatric conditions [8]. Modifiable factors, on the other hand, include the sodium concentration in the dialysate, intradialytic weight loss, and the frequency of acute complications [9]. However, the precise pathophysiological mechanisms and risk factors contributing to prolonged DRT remain unclear [10]. Given the impact of prolonged recovery time on patients, healthcare professionals, and caregivers, there has been growing interest in identifying modifiable treatment-related factors in recent international studies [4, 7, 8, 10,11,12,13,14,15].

The prevalence of chronic kidney disease (CKD), a global public health concern, is increasing rapidly worldwide. In 2015, Portugal had the highest incidence of CKD in Europe [16], and by 2017, it ranked sixth among Western European countries [17]. In the same period, Turkey ranked first in CKD prevalence in the North African and Middle Eastern regions [17]. Hemodialysis is the initial renal replacement therapy for 89.54% of CKD patients in Portugal [16] and 76.93% in Turkey [18]. However, while only one study on DRT has been conducted in Turkey [19], no studies on this topic have been identified in Portugal.

Study objectives

This study aimed to identify the factors affecting DRT in hemodialysis patients in Turkey and Portugal, two countries with high prevalence rates of CKD. These factors included socio-demographic characteristics, clinical and biochemical variables, hemodialysis session features, and levels of depression and anxiety.

Research question

  • What are the socio-demographic variables affecting recovery time in patients undergoing hemodialysis in Turkey?

  • What are the clinical, biochemical variables, and hemodialysis sessions’ features affecting recovery time in patients undergoing hemodialysis in Turkey?

  • What are the socio-demographic variables affecting recovery time in patients undergoing hemodialysis in Portugal?

  • What are the clinical, biochemical variables, and hemodialysis sessions’ affecting recovery time in patients undergoing hemodialysis in Portugal?

Methods

Study design and participants

This cross-sectional observational study was conducted with patients who were treated with hemodialysis between October 2020 and May 2022.

The study population consisted of hemodialysis patients receiving treatment at a private dialysis center in Turkey and three dialysis centers in Portugal. Conducting the research in two different countries allowed for a comparison of similarities and differences in practices. The study sample included patients aged 18 years or older who had been undergoing hemodialysis for four hours per session, three times a week, for at least six months, with no communication barriers, and who voluntarily agreed to participate. Patients with psychiatric or cognitive disorders that impaired communication, or those unable to hear or comprehend the questions, were classified as having communication problems and were excluded from the study. Data were collected from the patients’ medical records.

The dialysis center in Turkey treated a total of 221 patients. However, 11 patients were excluded as they had just begun treatment at the center in mid-October 2020, when the study was conducted. This left 210 patients in the study population. Among them, 19 patients were excluded due to inability to communicate in Turkish (3 patients), communication issues caused by physical disabilities (2 patients), and hearing or perception problems (14 patients). After applying the inclusion criteria, the sample comprised 191 patients. During the data collection, an additional 5 patients were excluded due to hospitalization (2 patients), death (1 patient), and incomplete questionnaire responses (2 patients). Ultimately, the study was completed with 187 patients (89.04%. In Portugal, 160 patients across three dialysis centers formed the study population. However, 53 patients were excluded due to cognitive impairments, leaving a final sample of 107 patients, which constituted 66.87% of the original population. This study was registered on ClinicalTrials.gov and reported following the STROBE checklist.

Outcomes

Dialysis recovery time

Dialysis Recovery Time was assessed using the method described by Lindsay et al. [6]. This measure is straightforward to interpret and respond to and has shown statistically significant negative correlations with all but one subscale of the Short Form 36 Health Survey [6]. Participants were asked about their recovery time following the first dialysis session of the month. Specifically, researchers posed the question: “Over the last month, how long, on average, did it take for you to recover from your dialysis sessions and resume your normal, usual activities?” Responses were recorded in minutes.

Patients were monitored for 12 dialysis sessions (one month). At the end of the month, patients were asked about their recovery time for the monitored month. There is no specific cut-off value to categorize patients with hemodialysis treatments according to their recovery time. However, patients were categorized into two groups in which the ones with the closest numbers were put together in accordance with the studies that were reported previously [11, 19].

Ultrafiltration rate

Ultrafiltration rate (UFR) was calculated in milliliters per hour per kilogram (ml/h/kg) by dividing the UF volume by the dialysis session duration and the target body weight. Based on the available literature [10, 21, 22], UFR was categorized into three groups: ≤10 ml/h/kg, 10–13 ml/h/kg, and > 13 ml/h/kg. A single UFR value for each patient was determined by averaging the UFR values from 12 hemodialysis sessions.

Interdialytic weight gain

Interdialytic Weight Gain (IDWG) was defined as the difference between the predialysis weight of the current dialysis session and the postdialysis weight from the previous session. The average IDWG over 12 hemodialysis sessions was also calculated [23]. This measurement was assessed over the one-month duration of the study.

Cannulation methods

The cannulation method was defined by the researchers and documented in the data collection form. The area puncture method involves cannulating within the same general area for each session. The rope-ladder technique requires rotating the needle placement sites along the entire length of the cannulation segment with each dialysis session. In the buttonhole method, needles are inserted at the same site, angle, and depth for consecutive dialysis sessions [20].

Hemodialysis sessions’ features

Data from the patients’ 12 hemodialysis sessions were recorded, and the values for each variable were averaged. These variables included: travel time to the dialysis unit (minutes), time spent waiting before dialysis began upon arrival (minutes), dialysate bicarbonate concentration (mmol/L), dialysate sodium level (mEq/L), blood flow rate (ml/min), UF volume (ml), UFR (ml/h/kg), pre-dialysis weight, and post-dialysis weight. The researchers collected this information by asking patients specific questions before the start of their dialysis sessions.

Depression and anxiety

Depression and anxiety were evaluated with the Hospital Anxiety and Depression Scale (HADS) by the researchers [24, 25].

Data collection and measurements

Data were collected using a semi-structured questionnaire developed by the researchers after reviewing the relevant literature. The questionnaire was developed specifically for use in this study (Supplement I). This form captured the subjects’ socio-demographic and medical characteristics. Researchers completed the questionnaire through face-to-face interviews with patients during the second hour of their hemodialysis treatment. Completing the form, which consisted of 17 questions, took approximately 10 min. The questions covered topics such as age, weight, height, hemodialysis treatment details, transportation to dialysis, alcohol and smoking habits, comorbidities, vascular access type, and dialysis shift. After 12 hemodialysis sessions, researchers recorded the results of biochemical parameters obtained from routine monthly blood samples into the data form. These parameters included Kt/V, urea reduction ratio (URR), phosphorus, C-reactive protein (CRP), sodium, hematocrit (HCT), hemoglobin (HGB), parathormone (PTH), white blood cell count (WBC), albumin, predialysis creatinine, postdialysis creatinine, bicarbonate, calcium, predialysis urea, and postdialysis urea.

Hospital anxiety and depression scale (HADS)

This scale was developed by Zigmond and Snaith [24] to identify the patient’s risk of anxiety and depression and to measure their level and change in severity. The scale’s validity and reliability in Turkey and in Portugal was assessed by Aydemir et al. [25] and Pais-Ribeiro et al. [26] respectively. It is used to detect anxiety and depression in a short time and to identify the risk group but not to diagnose these conditions in patients with a physical illness. Seven of the 14 questions of the scale measure anxiety and seven measure depression. The answers are scored in 4-point Likert form between 0 and 3. The score range is 0 to 21. The cutoff points of the Turkish version of the HADS were 10 and 7 for the anxiety and depression subscales, respectively [25]. The scale was completed by the researchers before treatment was started at the 1st hemodialysis sessions. Completing the form took about 5 min.

Statistical analysis

Comparisons of normally distributed variables were performed using Student’s t-test, while the Mann-Whitney U test was applied for non-normally distributed variables. Categorical variables were analyzed using the chi-square test. Logistic regression analysis was conducted to identify independent variables influencing post-dialysis recovery time. Variables identified in the previous analyses were included as predictors in the model. A P-value of < 0.05 was considered statistically significant.

Results

The study included a total of 294 patients, with 187 participants from Turkey and 107 from Portugal. The median age [IQR] of patients was 64 years [56–70] in Turkey and 69 years [62–76] in Portugal. Descriptive statistics for participants from both countries are presented in Table 1.

Table 1 Patients’ descriptive statistics (n = 294)
Full size table

Details about the dialysis sessions and patients’ biochemical parameters are provided in Table 2. In Turkey, 80.2% of patients were transported by the dialysis center’s service vehicle, whereas in Portugal, 97.2% of patients were transported by ambulance. The median commute time from home to the dialysis center was 21.5 min [14.5–29.5] in Turkey and 17.77 min [10.33–25.83] in Portugal. The mean Kt/V values (± standard deviation) were 1.73 ± 0.25 in Turkey and 1.74 ± 0.33 in Portugal.

Table 2 Hemodialysis sessions’ features and biochemical variables – country results (n = 294)
Full size table

Results in Turkey

Recovery time was significantly longer for patients with comorbidities (P = 0.016), heart failure (P = 0.010), higher IDWG (P = 0.049), longer commuting times to the dialysis center (P = 0.049), and longer waiting times after arriving at the dialysis center (P = 0.028), in addition to those with end-stage renal disease. Additionally, patients who did not use a high-flux dialyzer experienced longer recovery times (P = 0.013) (Table 3). There is no statistically significant relationship between the other variables and DRT (Supplement II).

Table 3 Relationship of descriptive features with post-dialysis recovery time – country results (n = 294)
Full size table

Results in Portugal

In the sample collected from Portugal, longer recovery times were observed for older patients (P = 0.035) and those with higher CRP levels (P = 0.013) and predialysis creatinine (P = 0.045). Conversely, recovery time was shorter for patients with higher Kt/V (P = 0.023), serum sodium (P = 0.012), and bicarbonate levels (P < 0.001). Additionally, longer recovery times were associated with longer commutes to the dialysis center (P = 0.010) and unemployment (P = 0.022) (Table 3). There is no statistically significant relationship between the other variables and DRT (Supplement II).

Logistic regression analysis results

A logistic regression analysis was performed to identify factors influencing post-dialysis recovery time, with the results presented in Table 4. In Turkey, patients with larger IDWG had longer recovery time (OR = 1.452, CI: 1.011–2.084; P = 0.043), whereas those using a high-flux dialyzer experienced shorter recovery time (OR = 0.418, CI: 0.194–0.889; P = 0.026). In Portugal, older age was associated with longer recovery times (OR = 1.070, CI: 1.010–1.132; P = 0.020). No other variables showed significant effects on post-dialysis recovery time (P > 0.05).

Table 4 Effect of variables on high post-dialysis recovery time – logistic regression model
Full size table

Discussion

We concluded that increased IDWG prolonged recovery time in patients undergoing hemodialysis in Turkey, while the use of a high-flux dialyzer shortened recovery time. In contrast, older age was associated with longer recovery time in Portugal.

Discussion of the results in Turkey

The presence of comorbidities in patients undergoing hemodialysis may affect their recovery time [27]. Previous studies have shown that patients with comorbidities experience longer recovery times [9, 28,29,30], while Harford et al. [7] have found no significant relationship between chronic diseases and recovery time. Rayner et al. [8] specifically noted longer recovery times for patients with diabetes, psychiatric diseases [8], and Davenport et al. [11] concluded that that patients with cancer, heart disease and diabetes had longer time. Patients with heart failure comorbidity tend to have longer recovery time compared to those without [9]. In our study, we also observed longer recovery times in patients with heart failure, consistent with existing literature [13, 29]. UF during hemodialysis can lead to reduced organ perfusion, potentially causing issues such as [31] reduced blood flow to the heart, cognitive decline, and postdialysis hypotension, which can impact patient survival [32, 33]. Patients with heart failure may experience exacerbated symptoms post-hemodialysis due to the systemic effects of the condition on the dialysis process.

Consistent with previous research [8, 9, 14, 34, 35], our study observed that recovery time lengthens with increasing IDWG, in contrast to the findings of Bossola et al. [10] who reported no significant correlation between the two. It is widely recognized that patients with excessive IDWG typically receive a higher UFR [36]. Hemodialysis induces a rapid redistribution of electrolytes and fluids across cell membranes, potentially contributing to delayed recovery time [8, 34]. It is plausible that UFR levels may impact cytokine production or clearance, thereby influencing recovery time [10]. Müller-Steinhardt et al. [37] demonstrated that a gradual reduction in UFR from 40 to 46 to 7–10 mL/min led to a notable increase in IL-10 concentrations (P = 0.012) and a decrease in Interleukin-1 beta (IL-1ß) concentrations. However, limited research exists on the relationship between UFR and cytokine modulation compared to studies on cytokine removal and hemodialysis filter types. Our study revealed that patients with high IDWG experienced prolonged recovery times.

We also discovered that patients who used a high-flux dialyzer had a shorter recovery time. A few studies in the literature examined the impact of high-flux dialyzer treatment on recovery time [38, 39]. There was no significant difference in recovery time between patients treated with high-flux hemodialysis and hemodiafiltration. Canseven [39] noted a decrease in post-dialysis fatigue in patients using a high-flux dialyzer. Low-flux dialyzers effectively eliminate small solutes through diffusion but have limited ability to remove middle-sized solutes, which are considered more toxic and challenging to eliminate through diffusion [40]. This limitation prompted the development of high-flux membrane dialyzers [41], which reduce beta-2 microglobulin levels more than low-flux dialyzers. Beta-2 microglobulin levels serve as an indicator of uremic toxins and other intermediate molecules with similar systemic or extracorporeal kinetics in dialysis patients. Therefore, it is possible that the shortened recovery time is due to the removal of toxic substances from the body through the use of a high-flux dialyzer [42].

The duration of the wait for patients to begin dialysis treatment after arriving at the unit is significant. This study found that a longer wait for treatment after arrival at the dialysis center also prolonged the overall treatment time. According to a national audit by the Scottish government, this accounted for nearly a quarter of the wasted time and affected patients regardless of whether they arrived by hospital transport or their own means [43]. Research has shown that transportation and waiting times in dialysis units not only impact the patient experience but also contribute to higher mortality rates and lower quality of life with longer wait and travel times [44]. The waiting time varies greatly among units, indicating that there is potential for dialysis units to reduce this time through improved organization.

Discussion of the results in Portugal

Some studies have shown that older patients tend to experience higher levels of fatigue after dialysis [5, 45], while in other cases, there is no clear relationship between age and recovery time [10, 13, 14]. Post-dialysis recovery time is more common among the elderly population [46,47,48]. According to Fitzpatrick et al. [30], individuals under 65 years of age have a shorter recovery time compared to those over 65. Rayner et al. [8] and Elsayed et al. [49] observed an increase in recovery time with age, while Kumar et al. [34] did not find a significant relationship between age and recovery time. One possible explanation is that older individuals may have more chronic health issues, slower recovery of bodily functions, and lower tolerance levels compared to younger individuals.

In individuals undergoing chronic hemodialysis, fatigue seems to be linked to the serum level of interleukin 6, indicating a role of inflammation [5]. Increased oxidative stress, a common feature in hemodialysis [50], has also been suggested as a significant factor in uremic myopathy and fatigue in renal failure [51]. The relationship between Kt/V level and recovery time has yielded varied results in the literature. While some studies found no correlation [8, 9, 34, 49], Canseven [39] reported that patients with high Kt/V had a longer recovery time. Our study showed that recovery time decreases as Kt/V increases, consistent with the findings of Guedes et al. [28]. Uremic toxins associated with uremia-related inflammation are typically large middle molecules that may be better cleared by high-flux membranes [52], potentially leading to improved inflammatory and oxidative stress status. As all patients in our study used high-flux dialyzers, the higher Kt/V levels suggest that the duration of dialysis recovery time may have been reduced. Jayanti et al. [13] found that unemployed patients had longer recovery time, while Rayner et al. [8] reported shorter recovery times for employed patients. In contrast, Kumar et al. [34] found no significant relationship between recovery time and working status. Our study revealed that employed patients had longer recovery times, possibly due to their higher activity levels compared to the unemployed. Returning to work and resuming daily activities after dialysis treatment could also contribute to extended recovery time.

Similar results for both countries

The travel burden for chronic dialysis patients living in rural areas can be particularly challenging, impacting their outcomes and quality of life. Studies have shown that longer travel distances are associated with increased mortality risk and higher rates of anemia among hemodialysis patients [53,54,55]. Living in rural areas and facing greater travel distances can also hinder access to necessary nutritional supplements, affecting protein balance. While existing research has not specifically examined the relationship between commuting time to dialysis centers and recovery time, our study suggests that longer commutes are linked to lengthier recovery periods. The time spent traveling to and from dialysis centers can be draining and time-consuming [44], contributing to a decline in patients’ quality of life [44, 56, 57].

Strengths and limitations

The main strengths of our study include the novelty of being the first work on this subject in both Turkey and Portugal, as well as the international comparative analysis conducted on recovery time, which is a significant factor impacting patients’ quality of life. However, there are limitations to our study. Like any observational study, there may be unmeasured confounding or other sources of bias affecting the observed associations. Some variables that could influence recovery time, such as intradialytic hypotension, medication use, and changes in glucose levels, were not assessed in this study. Additionally, the subjective nature of responses to the recovery time question, the assessment of recovery time at a single point in time rather than as a mean of repeated measures, and the potential difficulty in generalizing our results to all patients in the dialysis centers where the study was conducted are important considerations.

Conclusion

In summary, the recovery time following dialysis may vary depending on various factors in different countries. Our study revealed that factors such as chronic illness, high IDWG, and the use of high-flux dialyzers impact recovery time in Turkey, while working status, travel time to the dialysis center, and high Kt/V levels influence recovery time in Portugal. Additional research with larger sample sizes is needed to further explore this topic.

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

References

  1. Nissenson AR. Improving outcomes for ESRD patients: shifting the quality paradigm. Clin J Am Soc Nephrol. 2014;9(2):430–4.

    Article  PubMed  Google Scholar 

  2. Alvarez L, Brown D, Hu D, et al. Intradialytic symptoms and Recovery Time in patients on thrice-weekly In-Center hemodialysis: a cross-sectional online survey. Kidney Med. 2019;2(2):125–30.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Flythe JE, Assimon MM, Wenger JB, et al. Ultrafiltration Rates and the quality incentive program: proposed measure definitions and their potential Dialysis Facility implications. Clin J Am Soc Nephrol. 2016;11(8):1422–33.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Awuah KT, Afolalu BA, Hussein UT, et al. Time to recovery after a hemodialysis session: impact of selected variables. Clin Kidney J. 2013;6(6):595–8.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Bossola M, Di Stasio E, Giungi S, et al. Fatigue is associated with serum interleukin-6 levels and symptoms of depression in patients on chronic hemodialysis. J Pain Symptom Manage. 2015;49(3):578–85.

    Article  PubMed  Google Scholar 

  6. Lindsay RM, Heidenheim PA, Nesrallah G, et al. Minutes to recovery after a hemodialysis session: a simple health-related quality of life question that is reliable, valid, and sensitive to change. Clin J Am Soc Nephrol. 2006;1(5):952–9.

    Article  PubMed  Google Scholar 

  7. Harford A, Gul A, Cumber S, et al. Low dialysate potassium concentration is associated with prolonged recovery time. Hemodial Int. 2017;21(Suppl2):S27–32.

    PubMed  Google Scholar 

  8. Rayner HC, Zepel L, Fuller DS, et al. Recovery time, quality of life, and mortality in hemodialysis patients: the Dialysis outcomes and practice patterns study (DOPPS). Am J Kidney Dis. 2014;64(1):86–94. PMID.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Antari GAA, Sukmarini L, Adam M. Associated factors of post-hemodialysis recovery time in kidney failure patients. Enfermeria Clin. 2019;29:247–51.

    Article  Google Scholar 

  10. Bossola M, Di Stasio E, Monteburini T, et al. Recovery Time after Hemodialysis is inversely Associated with the Ultrafiltration Rate. Blood Purif. 2019;47(1–3):45–51.

    Article  CAS  PubMed  Google Scholar 

  11. Davenport A, Guirguis A, Almond M, et al. Comparison of characteristics of centers practicing incremental vs. conventional approaches to hemodialysis delivery - postdialysis recovery time and patient survival. Hemodial Int. 2019;23(3):288–96.

    Article  PubMed  Google Scholar 

  12. Duggal V, Hussein WF, Reiterman M, et al. The effect of blood flow rate on dialysis recovery time in patients undergoing maintenance hemodialysis: a prospective, parallel-group, randomized controlled trial. Hemodial Int. 2019;23(2):223–9.

    Article  PubMed  Google Scholar 

  13. Jayanti A, Foden P, Morris J, et al. Time to recovery from haemodialysis: location, intensity and beyond. Nephrol (Carlton). 2016;21(12):1017–26.

    Article  CAS  Google Scholar 

  14. Lopes GB, Silva LF, Pinto GB, et al. Patient’s response to a simple question on recovery after hemodialysis session strongly associated with scores of comprehensive tools for quality of life and depression symptoms. Qual Life Res. 2014;23(8):2247–56.

    Article  PubMed  Google Scholar 

  15. Yoowannakul S, Tangvoraphonkchai K, Davenport A. Patient-reported intra-dialytic symptoms and post-dialysis recovery times are influenced by psychological distress rather than dialysis prescription. Ren Replace Ther. 2019;5:14.

    Article  Google Scholar 

  16. Macário F. Relatório gabinete de registo da SPN tratamento substitutivo renal da doença renal crónica estadio V em Portugal. 2016. Lisboa. Available from http://www.bbg01.com/cdn/clientes/spnefro/noticias/130/REGISTO_DRCV2016.pdf. Accessed in January 2024.

  17. GBD Chronic Kidney Disease Collaboration. Global, regional, and national burden of chronic kidney disease, 1990–2017: a systematic analysis for the global burden of Disease Study 2017. Lancet. 2020;395(10225):709–33.

    Article  Google Scholar 

  18. Türkiye. 2019 Yılı Ulusal Nefroloji, Diyaliz ve Transplantasyon Kayıt Sistemi Raporu. Türk Nefroloji Derneği Yayınları. Available from: http://www.nefroloji.org.tr/folders/file/registry_2019.pdf. Accessed in January 2024.

  19. Ozen N, Cepken T, Tosun B. Do biochemical parameters and intradialytic symptoms affect post-dialysis recovery time? A prospective, descriptive study. Ther Apher Dial. 2021;25(6):899–907.

    Article  CAS  PubMed  Google Scholar 

  20. Parisotto MT, Schoder VU, Miriunis C, et al. Cannulation technique influences arteriovenous fistula and graft survival. Kidney Int. 2014;86(4):790–7.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Flythe JE, Kimmel SE, Brunelli SM. Rapid fluid removal during dialysis is associated with cardiovascular morbidity and mortality. Kidney Int. 2011;79(2):250–7.

    Article  PubMed  Google Scholar 

  22. Saran R, Bragg-Gresham JL, Levin NW, et al. Longer treatment time and slower ultrafiltration in hemodialysis: associations with reduced mortality in the DOPPS. Kidney Int. 2006;69(7):1222–8.

    Article  CAS  PubMed  Google Scholar 

  23. Ozen N, Cinar FI, Askin D, et al. Nonadherence in Hemodialysis patients and related factors: a Multicenter Study. J Nurs Res. 2019;27(4):e36.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Zigmond AS, Snaith RP. The hospital anxiety and depression scale. Acta Psychiatr Scand. 1983;67(6):361–70.

    Article  CAS  PubMed  Google Scholar 

  25. Aydemir Ö, Güvenir T, Küey L, et al. Validity and reliability of Turkish version of hospital anxiety and depression scale. Turkish J Psychiatry. 1997;8:280–7. (Original work published in Turkish).

    Google Scholar 

  26. Pais-Ribeiro J, Silva I, Ferreira T, et al. Validation study of a Portuguese version of the hospital anxiety and Depression Scale. Psychol Health Med. 2007;12(2):225–. – 35;quiz235-7.

    Article  CAS  PubMed  Google Scholar 

  27. Bossola M, Tazza L. Appetite is associated with the time of recovery after the dialytic session in patients on chronic hemodialysis. Nephron Clin Pract. 2013;123(1–2):129–33.

    Article  PubMed  Google Scholar 

  28. Guedes M, Pecoits-Filho R, Leme JEG, et al. Impacts of dialysis adequacy and intradialytic hypotension on changes in dialysis recovery time. BMC Nephrol. 2020;21(1):529.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Hussein WF, Arramreddy R, Sun SJ, et al. Higher Ultrafiltration Rate is Associated with longer Dialysis Recovery Time in patients undergoing conventional hemodialysis. Am J Nephrol. 2017;46(1):3–10.

    Article  PubMed  Google Scholar 

  30. Fitzpatrick J, Sozio SM, Jaar BG, et al. Frailty, Age, and Postdialysis Recovery Time in a Population New to Hemodialysis. Kidney360. 2021;2(9):1455–62.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Assa S, Kuipers J, Ettema E, et al. Effect of isolated ultrafiltration and isovolemic dialysis on myocardial perfusion and left ventricular function assessed with 13 N-NH3 positron emission tomography and echocardiography. Am J Physiol Ren Physiol. 2018;314(3):F445–52.

    Article  Google Scholar 

  32. Polinder-Bos HA, García DV, Kuipers J, et al. Hemodialysis induces an Acute decline in cerebral blood Flow in Elderly patients. J Am Soc Nephrol. 2018;29(4):1317–25.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Assimon MM, Flythe JE. Definitions of intradialytic hypotension. Semin Dial. 2017;30(6):464–72.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Bipin Kumar S, Karthikeyan B, Nair SV, et al. A study of factors affecting Dialysis Recovery Time in Haemodialysis patients in India. Indian J Nephrol. 2021;31(5):460–6.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Smokovska N, Grozdanovski R, Spasovski G. Impact of different variables on recovery time in patients receiving hemodialysis. Bantao J. 2015;13(1):20–4.

    Article  Google Scholar 

  36. Lindberg M, Prütz KG, Lindberg P, et al. Interdialytic weight gain and ultrafiltration rate in hemodialysis: lessons about fluid adherence from a national registry of clinical practice. Hemodial Int. 2019;13(2):181–8.

    Article  Google Scholar 

  37. Müller-Steinhardt M, Kock N, Härtel C, et al. Production of monokines in patients under polysulphone haemodiafiltration is influenced by the ultrafiltration flow rate. Nephrol Dial Transpl. 2001;16(9):1830–7.

    Article  Google Scholar 

  38. Smith JR, Zimmer N, Bell E, et al. A Randomized, Single-Blind, crossover trial of Recovery Time in High-Flux Hemodialysis and Hemodiafiltration. Am J Kidney Dis. 2017;69(6):762–70.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Canseven M. Hemodiyaliz Hastalarinda Diyaliz Sonu Yorgunluk Nedenleri. Uzmanlık Tezi. Necmettin Erbakan Üniversitesi. Konya. 2021. Türkiye [Published in Turkey].

  40. Abe M, Hamano T, Wada A, et al. High-performance membrane dialyzers and mortality in Hemodialysis patients: a 2-Year Cohort Study from the Annual Survey of the Japanese Renal Data Registry. Am J Nephrol. 2017;46(1):82–92.

    Article  CAS  PubMed  Google Scholar 

  41. Eknoyan G, Beck GJ, Cheung AK, et al. Effect of dialysis dose and membrane flux in maintenance hemodialysis. N Engl J Med. 2002;347(25):2010–9.

    Article  PubMed  Google Scholar 

  42. Lonnemann G, Koch KM. Beta(2)-microglobulin amyloidosis: effects of ultrapure dialysate and type of dialyzer membrane. J Am Soc Nephrol. 2002;13(Suppl1):S72–7.

    Article  CAS  PubMed  Google Scholar 

  43. Transporting Patients to and from the Dialysis Unit – A National Audit. Available from: https://www.srr.scot.nhs.uk/projects/PDF/SRR_Transporting_Patients_to_and_from_the_Dialysis_Unit_Extended%20website%20version.pdf. Accessed in January 2024.

  44. Moist LM, Bragg-Gresham JL, Pisoni RL, et al. Travel time to dialysis as a predictor of health-related quality of life, adherence, and mortality: the Dialysis outcomes and practice patterns study (DOPPS). Am J Kidney Dis. 2008;51(4):641–50.

    Article  PubMed  Google Scholar 

  45. Bossola M, Marzetti E, Di Stasio E, et al. Prevalence and associated variables of post-dialysis fatigue: results of a prospective multicentre study. Nephrology. 2018;23(6):552–8.

    Article  PubMed  Google Scholar 

  46. Lerdal A, Wahl A, Rustøen T, et al. Fatigue in the general population: a translation and test of the psychometric properties of the Norwegian version of the fatigue severity scale. Scand J Public Health. 2005;33(2):123–30.

    Article  PubMed  Google Scholar 

  47. Vestergaard S, Nayfield SG, Patel KV, et al. Fatigue in a representative population of older persons and its association with functional impairment, functional limitation, and disability. J Gerontol Biol Sci Med Sci. 2009;64(1):76–82.

    Article  Google Scholar 

  48. Bossola M, Di Stasio E, Antocicco M, et al. Variables associated with time of recovery after hemodialysis. J Nephrol. 2013;26(4):787–92.

    Article  CAS  PubMed  Google Scholar 

  49. Elsayed MM, Zeid MM, Hamza OMR, et al. Dialysis recovery time: associated factors and its association with quality of life of hemodialysis patients. BMC Nephrol. 2022;23(1):298.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Liakopoulos V, Roumeliotis S, Gorny X, et al. Oxidative stress in Hemodialysis patients: a review of the literature. Oxid Med Cell Longev. 2017;2017:3081856.

    Article  PubMed  PubMed Central  Google Scholar 

  51. Kaltsatou A, Sakkas GK, Poulianiti KP, et al. Uremic myopathy: is oxidative stress implicated in muscle dysfunction in uremia? Front Physiol. 2015;6:102.

    Article  PubMed  PubMed Central  Google Scholar 

  52. Mitra S, Kharbanda K. Effects of expanded hemodialysis therapy on clinical outcomes. Contrib Nephrol. 2017;191:188–99.

    Article  CAS  PubMed  Google Scholar 

  53. Stephens JM, Brotherton S, Dunning SC. Geographic disparities in patient travel for dialysis in the United States. J Rural Health. 2013;29(4):339–48.

    Article  PubMed  Google Scholar 

  54. Tonelli M, Manns B, Culleton B. Association between proximity to the attending nephrologist and mortality among patients receiving hemodialysis. CMAJ. 2007;177(9):1039–44.

    Article  PubMed  PubMed Central  Google Scholar 

  55. Chao CT, Lai CF, Huang JW, et al. Association of increased travel distance to dialysis units with the risk of anemia in rural chronic hemodialysis elderly. Hemodial Int. 2015;19(1):44–53.

    Article  PubMed  Google Scholar 

  56. van der Borg WE, Verdonk P, de Jong-Camerik JG, et al. A continuous juggle of invisible forces: how fatigued dialysis patients manage daily life. J Health Psychol. 2021;6(6):917–34.

    Article  Google Scholar 

  57. Anees M, Malik MR, Abbasi T, et al. Demographic factors affecting quality of life of hemodialysis patients - Lahore, Pakistan. Pak J Med Sci. 2014;30(5):1123–7.

    PubMed  PubMed Central  Google Scholar 

Download references

Funding

No.

Author information

Authors and Affiliations

  1. Department of Internal Medicine Nursing, Faculty of Nursing, Istanbul University, Istanbul, Turkey

    Nurten Ozen

  2. Department of Nephrology, Guven Hospital, Ankara, Turkey

    Tayfun Eyileten

  3. Department of Mathematics and Information Systems, School of Economics of the University of Porto and LIAAD- INESC Porto LA, Porto, Portugal

    Paulo Teles

  4. Department of Dialysis, Private RFM Dialysis Center, Ankara, Turkey

    Baris Seloglu & Aysegul Ocuk

  5. Department of Infirmary, Ankara Sınav College Central Campus, Ankara, Turkey

    Ayse Gurel

  6. Department of Anesthesiology and Reanimation, Prof. Dr. Cemil Tascioglu City Hospital, University of Health Sciences, Istanbul, Turkey

    Volkan Ozen

  7. S Francisco Dialysis Unit, Porto, Portugal

    Filipa Fernandes, Luís Campos, Sara Coutinho & Joana Teixeira

  8. NefroDouro Dialysis Unit, Vila da Feira, Porto, Portugal

    Filipa Fernandes

  9. Unidade Local de Saúde do Nordeste, Mogadouro Dialysis Unit, Bragança, Portugal

    Sandra Cristina Mendo Moura

  10. Department of Nursing, Nursing School of Porto, Porto, Portugal

    Olga Ribeiro

  11. CINTESIS - Center for Health Technology and Services Research, University of Porto, Porto, Portugal

    Olga Ribeiro

  12. Nursing School of Porto, Porto, Portugal

    Clemente Neves Sousa

  13. Faculty of Medicine, CINTESIS - Center for Health Technology and Services Research, University of Porto, Porto, Portugal

    Clemente Neves Sousa

  14. Vascular Access Center (Grupo Estudos Vasculares), Porto, Portugal

    Clemente Neves Sousa

Authors
  1. Nurten Ozen
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Tayfun Eyileten
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Paulo Teles
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Baris Seloglu
    View author publications

    You can also search for this author inPubMed Google Scholar

  5. Ayse Gurel
    View author publications

    You can also search for this author inPubMed Google Scholar

  6. Aysegul Ocuk
    View author publications

    You can also search for this author inPubMed Google Scholar

  7. Volkan Ozen
    View author publications

    You can also search for this author inPubMed Google Scholar

  8. Filipa Fernandes
    View author publications

    You can also search for this author inPubMed Google Scholar

  9. Luís Campos
    View author publications

    You can also search for this author inPubMed Google Scholar

  10. Sara Coutinho
    View author publications

    You can also search for this author inPubMed Google Scholar

  11. Joana Teixeira
    View author publications

    You can also search for this author inPubMed Google Scholar

  12. Sandra Cristina Mendo Moura
    View author publications

    You can also search for this author inPubMed Google Scholar

  13. Olga Ribeiro
    View author publications

    You can also search for this author inPubMed Google Scholar

  14. Clemente Neves Sousa
    View author publications

    You can also search for this author inPubMed Google Scholar

Contributions

Concept – NO, CNS; Design – NO, CNS, TE; Supervision – NO, BS, AG, AO, FF, LC, SC, JT, SCMM, OR; Resources – NO, CNS, TE; Materials - NO, CNS; Data Collection and/or Processing - BS, AG, AO, FF, LC, SC, JT, SCMM, OR; Analysis and/or Interpretation – NO, PT; Literature Search - NO; Writing Manuscript - NO, CNS, PT; Critical Review - NO, CNS, PT, TE.

Corresponding author

Correspondence to Nurten Ozen.

Ethics declarations

Ethics approval and consent to participate

The study was conducted in accordance with the Declaration of Helsinki and was approved by the local ethics committees in Turkey (Kapadokya University Scientific Research and Publication Ethics Committee, permission no: 2020.19, date: July 14, 2020) and Portugal (Escola Superior de Enfermagem do Porto, permission no: 8/2020, date: September 7, 2020). Informed consent was obtained from all subjects and the written permission was obtained from the institutions.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Supplementary Material 2

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ozen, N., Eyileten, T., Teles, P. et al. Impact of variables on recovery time in patients undergoing hemodialysis: an international survey. BMC Nephrol 26, 13 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12882-024-03937-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12882-024-03937-9

Keywords

BMC Nephrology

ISSN: 1471-2369

Contact us