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The effect of BCM guided dry weight assessment on short-term survival in Chinese hemodialysis patients

Primary results of a randomized trial – BOdy COmposition MOnitor (BOCOMO) study

BMC Nephrology volume 21, Article number: 135 (2020) Cite this article

Abstract

Background

Lack of accurate and effective assessment tools of fluid status is one of the major challenges to reach proper dry weight (DW) in chronic hemodialysis (HD) population. The aim of this randomized study was to evaluate the effect of bioimpedance guided DW assessment on long-term outcomes in Chinese HD patients. Eligible patients were randomly assigned (1:1) to two groups in each center, the control group and body composition monitor (BCM) group. In the BCM group, DW has been evaluated by bioimpedance technic every 2 months during follow-up. The primary composite endpoint consisted of death, acute myocardial infarction, cerebral infarction, cerebral hemorrhage, and peripheral vascular disease.

Methods

A total of 445 patients were recruited from 11 hemodialysis centers from Beijing, Tianjin and Shijiazhuang cities from Jan 1, 2013 to Dec 31, 2014. They were randomized into either BCM group or control group. All patients have been followed up for 1 year or until Dec 31, 2014 or censoring.

Results

At baseline, there were no significant differences between two groups in terms of demographic parameters, dialysis vintage, percentage of vascular access, and comorbid conditions. At the end of the study, 18 (4.04%) patients had died (11 in control group and 7 in BCM group). Kaplan-Meier survival analysis showed no significant difference in survival rates between two groups (log-rank test P = 0.07). However, there was an increasing trend of survival rates in BCM group compared to the control group. In the multivariable Cox analysis, there was a nonsignificant trend toward less primary composite end points in the BCM group in the adjusted analysis, the hazard ratio was impressive (0.487, 95% CI 0.217–1.091, P = 0.08).

Conclusion

Bioimpedance technic has been applied to assess fluid status for decades and has been proved to be a promising tool for clinical practice. Although short-term outcomes were not improved in the randomized, controlled trial, the ascending trend in survival has been observed. Further studies are needed to investigate the survival benefit of bioimpedance method in DW assessment in a larger sample with longer follow-up period.

Trial registration

ClinicalTrials.org, NCT01509937. Registered 13 January 2012,

Peer Review reports

Background

Knowledge of optimal fluid status is essential in delivering care to maintenance hemodialysis (MHD) patients. Persistent overhydration (OH) causes hypertension, left ventricular hypertrophy, pulmonary edema, congestive heart failure, and leads to higher mortality [1,2,3,4,5,6,7,8]. Compared with normorhydrated patients, patients with recurrent episodes of intra-dialytic hypovolemia are at a higher risk of acute ischemic events, potentially leading to functional impairment and organ damage, including accelerated loss of residual renal function [9], blood access function loss [10], brain atrophy [11], mesenteric infarction [12], and hence, higher morbidity and mortality [13, 14].

Optimal fluid management is critical to ensure high quality of care in patients –receiving MHD. Dry weight (DW) assessment/adjustment and control of intradialytic weight gain are main components of fluid management. However, DW assessment remains a challenge in MHD patients. Gold standard measurements of fluid status, such as isotope dilution methods, are not clinically feasible due to their complexity and great expense. Inferior vena cava diameter measurements, estimations of N-terminal-pro-BNP (N-terminal-pro-brain natriuretic peptide) and other cardiac peptides have not been proved to be practical or reliable in the detection of fluid status in individual patients [15,16,17]. As a result, probing for DW based on trial and error has been common in clinical practice [18]. However, self-reported symptoms cannot be always reliable without knowing the medical history. Hypertension alone was found to be unreliable to define hypervolemia in part of some patients [17, 19].

Bioimpedance spectroscopy (BIS) has long been used to assess human body composition and has been extensively validated by isotope dilution methods [20, 21] and reference body composition methods [21,22,23]. It appears to be a promising and a valuable tool in aiding DW estimation for MHD patients. In addition, several observational studies showed the potential benefits of BIS on control of blood pressure and fluid status [1, 24]. Wizemann et al [1] found that patients who had 15% or more expansion of extra-cellular fluid (ECF) suffered higher mortality risk compared with those who had less than 15% ECF expansion estimated by BIS method in MHD patients. Recently, Onofriescu et al. found significant improvement of survival in the bioimpedance group (aiding DW by applying BIS method) compared to the clinical methods (control) group with a follow-up of 2.5 year (HR = 0.112, 95% CI, 0.014–0.918; P = 0.04) in a population from Turkey [25].

This multicenter, open label, single blinded, randomized controlled trial (RCT) was designed to explore the effect of BIS guided DW assessment on long-term outcomes in Chinese patients receiving MHD.

Methods

This study design has been described previously [26]. It was approved by the Ethics Committee of Clinical Research, Peking University First Hospital and each participating center (clinical trial number: NCT01509937).

Patients

Patients were recruited from 11 clinical sites in Beijing, Tianjin and Shijiazhuang (eight centers in Beijing, two in Tianjin and 1 in Shijiazhuang) from Jan 1, 2013 to Dec 31, 2014 [26]. Beijing, Tianjin and Shijiazhuang are three main big cities located in the middle-north part of China. Patients who were older than 18 and younger than 80 years old are eligible. Patients who initiated HD less than 3 months, been dialyzed less than five times per 2 weeks, produced urine more than 800 ml per 24 h the day before dialysis session, or a Kt/V less than 1.2 were excluded. Furthermore, we excluded patients with unstable clinical conditions (i.e. acute infection, heart failure), with pace-maker or metallic prosthesis (contraceptive device, artificial joint et al). Written informed consent was obtained from all patients.

Study treatment

Patients were randomized to control group and Body-Composition-Monitor (BCM) group equally in each center according to the method of random number table.

Body composition and hydration state had been assessed by a portable whole body BIS device (BCM; Fresenius Medical Care, Bad Homburg, Germany). Patient measurements were obtained before the first HD session of the week. The extracellular and intracellular fluid volumes and total body water were calculated from a fluid model [20]. These fluid volumes were then used to determine the fluid overload, expressed as OH value [27]. DWBCM was calculated by pre-weight minus OH (kg).

Patients in the control group received BCM measurements at the beginning and end of the study, but the results were kept blinded to the investigators. In the control group, DW was adjusted according to the dialysis center’s standard clinical practice. In the BCM group, BCM was performed at 2-monthly intervals during follow-up. In addition to routine practice, patients’ DWs were adjusted according to BCM output data following the DW adjustment strategy.

All of baseline demographics, clinical data, laboratory data, BCM measurements, ultrasonic cardiograph data and any adverse events were monitored regularly and recorded on study case report forms according to the protocol published [26].

Study outcomes

The primary objective of the study is to compare incidence rate of the composite endpoint between BCM group and control group, composed of death, acute myocardial infarction, cerebral infarction, cerebral hemorrhage, and peripheral vascular disease. That had been judged by the committee of BOCOMO study comprised of all directors from every clinical site.

Statistical analysis

Normally distributed variables were expressed as mean ± SD. Non-normally distributed variables were presented as median (25th, 75th percentiles). Categorical variables are presented as frequencies (percentages). Continuous variables were compared with the use of Student’s t-test or the Mann-Whitney test (for non-normally distributed data), and categorical data with the use of chi-square tests. Survival estimates and curves were generated according to the Kaplan–Meier method. Cox regression survival analysis also was performed using a backward stepwise model adjusting for demographic data (age and gender), comorbid conditions (cardiac infarction, cerebral hemorrhage, cerebral infarction and peripheral vascular disease), and other predictors (causes of end stage renal disease (ESRD), dialysis vintage, vascular access). Both Kaplan–Meier curves and Cox model used the same end point (time to event) and patients were censored when they were transferred to another dialysis center, underwent transplantation, inserted of metallic device or were still on treatment until the end of the study. All analyses were done with SAS V9.3 (SAS Institute inc, Cary, North Carolina). A P value of less than 0.05 was considered as statistically significant.

According to the data from Beijing Hemodialysis Quality Control and Improvement Center, the annual mortality rate of Beijing MHD patients is around 10%, it is estimated that 3 year mortality to be 30%. It is also estimated that the rate of composite endpoint within 3 year period of time is 40%. We made an assumption that BCM guided DW assessment would reduce the 3-year composite endpoint rate from 40 to 32% (20% relative risk reduction). To reach statistical significance with α < 0.05 and power > 80%, the sample size required is 1128. Allowing for a 20% loss-to-follow-up, the total sample size planned is 1354. After 1 year follow-up, 6.19% (14) of all enrolled patients (226) from 5 centers reached the composite endpoint, which was much lower than the expected rate (13.3%). Accordingly, the sample size of the study had been recalculated and 6464 patients was required to reach the statistical significance. Given the changeable difficulty to reach that number, the follow-up period of the protocol was corrected to 1 year and the study had been prematurely terminated after all patients had been followed at least 1 year.

Results

A total of 445 patients were included in the final analysis (Fig. 1): 53.93% males, mean age 54.8 ± 12.7 years, median dialysis vintage of 4.13 years, 91.69% of them were dialyzed through an arterial venous fistula; approximately half of them had ESRD due to chronic glomerulonephritis (51.16%) (Table 1).

Fig. 1
figure 1

Flow diagram of the trial

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Table 1 Demographic characteristics and baseline laboratory parameters of the entire study subjects
Full size table

Baseline characteristics of the randomly assigned patients were listed in Table 1. At baseline, there were no significant differences between two groups in terms of demographic parameters, dialysis vintage, percentage of blood access, and comorbid conditions (myocardial infarction, cerebral hemorrhage, cerebral infarction and peripheral vascular disease).

During a median follow-up of 13.7 months, 18 (4.0%) patients died, 8 (1.8%) from cerebral hemorrhage (4 in control group and 4 in BCM group, respectively), 4 (0.9%) from infection (all in control group), 3 (0.7%) from sudden death (2 in control group and 1 in BCM group), 1 (0.2%) from heart failure (in control group), 1 (0.2%) from respiratory failure (in BCM group) and 1 (0.2%) from upper gastrointestinal bleeding (in BCM group) (Table 2). A total of 22 (4.9%) patients dropped out before the study end. The reasons for censoring included transferring to other dialysis centers (n = 8, 1.8%), patient refusal (n = 3, 0.7%), renal transplantation (n = 3, 0.7%), insertion of metallic joint (n = 3, 0.7%) and others (n = 5, 1.1%).

Table 2 list of composite primary end point by group
Full size table

As mentioned in the protocol, BCM measurement had been done every 2 months in the BCM group. The average of OH values at each visit in the one-year follow-up had been shown in Fig. 2 ranged from 2.11 L to 2.13 L with a standard deviation between 1.45 L and 1.49 L.

Fig. 2
figure 2

The OH values at each visit. OH: overhydration

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Kaplan-Meier survival analysis showed no significant difference in survival between two groups (HR = 0.51, 95% confidence interval: 0.24–1.08, log-rank test p-value = 0.07; Fig. 3) after 1 year follow-up. However, there was an increasing trend of survival improvement in the BCM group compared to the control group overtime.

Fig. 3
figure 3

Kaplan-Meier curve comparing the survival between the BCM group and Conventional group over. BCM: body-composition-monitor. (HR = 0.51, 95% confidence interval: 0.24–1.08, log-rank test p-value = 0.07)

Full size image

In the multivariable Cox analysis, after adjustment for age, gender, dialysis vintage, vascular access, comorbidities and laboratory data, there was a nonsignifcant trend toward less primary composite end points in BCM group (Table 3). (HR = 0.487, 95% CI 0.217–1.091, P = 0.08).

Table 3 Results of the multivariate Cox adjusted model
Full size table

Discussion

The present study was the first randomized control trial to investigate the survival benefit of BIS-based DW adjustment in the field of DW assessment in Chinese hemodialysis population. In this RCT study, although applying BCM to assess hydration status and adjust DW failed to improve the patients’ outcome compared to the clinical standard practice in 1 year follow-up, the increasing trend of survival had been observed in the BCM group.

Bioimpedance has been applied to evaluate body composition and hydration status in both hemodialysis and peritoneal dialysis patients for decades. It is not only noninvasive and easily applicable, but also well-validated [20]. It is notable that hydration status defined by BCM was associated with survival benefits had been proved by Wizemann et al. In this study, the relation between baseline hydration status and survival in 269 hemodialysis patients [1]. It showed that overhydration defined as 15% relative to the extracellular water above the normohydration target (presented an excess of ECW of 2.5 L) was linked to a more than 2-fold increased mortality risk in median follow-up of 3.5-year secondary only to the presence of diabetes.

Previous studies had demonstrated that strict BCM guided fluid management led to better blood pressure control, a decrease in arterial stiffness, a reduction of intradialytic symptoms and most importantly, a better survival [25, 28,29,30,31,32,33,34]. The first randomized prospective study evaluated the effect of adjustment of DW guided by BCM measurement every 3 months on survival was published by Onofriescu et al. from Turkey [25]. Normal hydration range was defined as OH value between -1 L to 1 L in this study. It was found that all-cause mortality (both unadjusted and multivariate adjusted) was significantly lower in the bioimpedance group compared to the clinical-methods group (HR = 0.1 and 0.112, respectively). Although only 131 patients were enrolled, they were followed up for a long enough period (3.5 years). On the other hand, − 2 L to 1 L after dialysis was defined as the normal target of OH value by Chen Huan-sheng from Taiwan [33]. The incidence of acute fluid overload or cardiovascular-related events decreased significantly in non-diabetes mellitus patients via monthly BCM measurement. Compared to the above target ranges of normal hydration, we used − 1.6 L to 1.6 L in our study. After 1 year follow-up with the BCM measurement in a two-month interval, although no significant results were demonstrated, the reduction trend of overall events was observed in the BCM group. In a recent systematic review and meta-analysis which included five randomized controlled trials in HD patients [35], bioimpedance-based DW assessment was proven to be associated with improvement of systolic blood pressure and of pre-dialysis fluid overload. Unfortunately, no significant improvement in survival rate was observed. Evidence for the survival benefits of BCM-guided intervention is still limited due to lack of prospective trials.

The major limitations of this trial are the insufficient number of participants and the limited follow-up period. In the previous statistical analysis, 1354 patients and 3 years follow-up were necessary to reach the statistical significance. At the end of the study, the actual rate of composite endpoint was 11.7%, lower than the predicted rate (13.3%). On the other hand, the rate of recruitment of each center is lower than expected, which induced the huge difficulties to recruit a total of 6464 patients into the study. The study was considered to be terminated earlier. Eventually, this study enrolled a total of 445 patients and had been closed after 1-year follow-up. The above factors might contribute to the insignificant result of our study. Meanwhile, the baseline characteristics demonstrated that our patients had relatively physical well-being which contributed to the better survival, for instance, lower OH value before dialysis (less than 2.5 L), both hemoglobin and albumin levels in the target range (111.5 g/L and 40.8 g/L), more arteriovenous fistula (91.7%) and shorter dialysis vintage (4.1 years). We are fully aware of the failure during the recruitment and follow-up of patients. Based on the survival trend shown in our pilot study, longer intervention time and enough sicker participants were both necessary to reach a positive result in the further study. Secondly, as an additional operation, both doctors and patients could not be kept blinded to BCM measurement in this study. Thirdly, although there were fewer patients dropped out than we assumed, more patients lost follow up in the BCM group than in the control group (14 vs. 8). The latter two both may cause bias of the results. Finally, the present study has been completed 5 years ago. We made great effort to recruit more units and patients during the following years. Unfortunately, short of finances and manpower were the main barriers.

Conclusion

In conclusion, failure to assess hydration status is an important barrier to achieve and maintain DW in clinical practice in hemodialysis patients. Bioimpedence method has been proved to be an accurate, simple and inexpensive tool to define the DW. Given limited evidence for the survival benefits of BCM-guided intervention, it might become the basis of appropriate fluid management and reduce cardiovascular events and death, especially in sicker patients. Further well-designed studies with enough recruitment and follow-up period are necessary.

Availability of data and materials

The individual participant data that underlie the results reported in this article (including data dictionaries), after deidentification (text, tables, figures, and appendices) are available from the corresponding author on reasonable request.

Abbreviations

MHD:

Maintenance hemodialysis

DW:

Dry weight

BIS:

Bioimpedance spectroscopy

ECF:

Extra-cellular fluid

BCM:

Body Composition Monitor

OH:

Overhydration

ESRD:

End stage renal disease

iPTH:

Intact parathyroid hormone

CVC:

Central venous catheter

References

  1. Wizemann V, Wabel P, Chamney P, et al. The mortality risk of overhydration in haemodialysis patients. Nephrol Dial Transplant. 2009;24(5):1574–9.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Zoccali C, Moissl U, Chazot C, et al. Chronic fluid overload and mortality in ESRD. J Am Soc Nephrol. 2017;28(8):2491–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Hecking M, Moissl U, Genser B, et al. Greater fluid overload and lower interdialytic weight gain are independently associated with mortality in a large international hemodialysis population. Nephrol Dial Transplant. 2018;33(10):1832–42.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Dekker MJ, Marcelli D, Canaud BJ, et al. Impact of fluid status and inflammation and their interaction on survival: a study in an international hemodialysis patient cohort. Kidney Int. 2017;91(5):1214–23.

    Article  PubMed  Google Scholar 

  5. Onofriescu M, Siriopol D, Voroneanu L, et al. Overhydration, cardiac function and survival in hemodialysis patients. PLoS One. 2015;10(8):e0135691.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Tabinor M, Elphick E, Dudson M, Kwok CS, Lambie M, Davies SJ. Bioimpedance-defined overhydration predicts survival in end stage kidney failure (ESKF): systematic review and subgroup meta-analysis. Sci Rep. 2018;8(1):4441.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Dekker M, Konings C, Canaud B, et al. Pre-dialysis fluid status, pre-dialysis systolic blood pressure and outcome in prevalent haemodialysis patients: results of an international cohort study on behalf of the MONDO initiative. Nephrol Dial Transplant. 2018;33(11):2027–34.

    Article  CAS  PubMed  Google Scholar 

  8. Siriopol D, Siriopol M, Stuard S, et al. An analysis of the impact of fluid overload and fluid depletion for all-cause and cardiovascular mortality. Nephrol Dial Transplant. 2019;34(8):1385–93.

    Article  PubMed  Google Scholar 

  9. Jansen MA, Hart AA, Korevaar JC, et al. Predictors of the rate of decline of residual renal function in incident dialysis patients. Kidney Int. 2002;62(3):1046–53.

    Article  PubMed  Google Scholar 

  10. Puskar D, Pasini J. Savić, Bedalov G, Sonicki Z. survival of primary arteriovenous fistula in 463 patients on chronic hemodialysis. Croat Med J. 2002;43(3):306–11.

    PubMed  Google Scholar 

  11. Mizumasa T, Hirakata H, Yoshimitsu T, et al. Dialysis-related hypotension as a cause of progressive frontal lobe atrophy in chronic hemodialysis patients: a 3-year prospective study. Nephron Clin Pract. 2004;97(1):c23–30.

    Article  PubMed  Google Scholar 

  12. John AS, Tuerff SD, Kerstein MD. Nonocclusive mesenteric infarction in hemodialysis patients. J Am Coll Surg. 2000;190(1):84–8.

    Article  CAS  PubMed  Google Scholar 

  13. Shoji T, Tsubakihara Y, Fujii M, Imai E. Hemodialysis-associated hypotension as an independent risk factor for two-year mortality in hemodialysis patients. Kidney Int. 2004;66(3):1212–20.

    Article  PubMed  Google Scholar 

  14. Tislér A, Akócsi K, Hárshegyi I, et al. Comparison of dialysis and clinical characteristics of patients with frequent and occasional hemodialysis-associated hypotension. Kidney Blood Press Res. 2002;25(2):97–102.

    Article  PubMed  Google Scholar 

  15. Cheriex EC, Leunissen KM, Janssen JH, Mooy JM, van Hooff JP. Echography of the inferior vena cava is a simple and reliable tool for estimation of 'dry weight' in haemodialysis patients. Nephrol Dial Transplant. 1989;4(6):563–8.

    CAS  PubMed  Google Scholar 

  16. Lee SW, Song JH, Kim GA, Lim HJ, Kim MJ. Plasma brain natriuretic peptide concentration on assessment of hydration status in hemodialysis patient. Am J Kidney Dis. 2003;41(6):1257–66.

    Article  CAS  PubMed  Google Scholar 

  17. Vasko R, Müller GA, Ratliff BB, Jung K, Gauczinski S, Koziolek MJ. Clinical judgment is the most important element in overhydration assessment of chronic hemodialysis patients. Clin Exp Nephrol. 2013;17(4):563–8.

    Article  PubMed  Google Scholar 

  18. Canaud B, Lertdumrongluk P. Probing 'dry weight' in haemodialysis patients: 'back to the future'. Nephrol Dial Transplant. 2012;27(6):2140–3.

    Article  PubMed  Google Scholar 

  19. Wabel P, Moissl U, Chamney P, et al. Towards improved cardiovascular management: the necessity of combining blood pressure and fluid overload. Nephrol Dial Transplant. 2008;23(9):2965–71.

    Article  PubMed  Google Scholar 

  20. Moissl UM, Wabel P, Chamney PW, et al. Body fluid volume determination via body composition spectroscopy in health and disease. Physiol Meas. 2006;27(9):921–33.

    Article  PubMed  Google Scholar 

  21. van den Ham EC, Kooman JP, Christiaans MH, et al. Body composition in renal transplant patients: bioimpedance analysis compared to isotope dilution, dual energy X-ray absorptiometry, and anthropometry. J Am Soc Nephrol. 1999;10(5):1067–79.

    PubMed  Google Scholar 

  22. McClanahan BS, Stockton MB, Lanctot JQ, et al. Measurement of body composition in 8-10-year-old African-American girls: a comparison of dual-energy X-ray absorptiometry and foot-to-foot bioimpedance methods. Int J Pediatr Obes. 2009;4(4):389–96.

    Article  PubMed  Google Scholar 

  23. Lintsi M, Kaarma H, Kull I. Comparison of hand-to-hand bioimpedance and anthropometry equations versus dual-energy X-ray absorptiometry for the assessment of body fat percentage in 17-18-year-old conscripts. Clin Physiol Funct Imaging. 2004;24(2):85–90.

    Article  PubMed  Google Scholar 

  24. Pillon L, Piccoli A, Lowrie EG, Lazarus JM, Chertow GM. Vector length as a proxy for the adequacy of ultrafiltration in hemodialysis. Kidney Int. 2004;66(3):1266–71.

    Article  PubMed  Google Scholar 

  25. Onofriescu M, Hogas S, Voroneanu L, et al. Bioimpedance-guided fluid management in maintenance hemodialysis: a pilot randomized controlled trial. Am J Kidney Dis. 2014;64(1):111–8.

    Article  PubMed  Google Scholar 

  26. Liu L, Long G, Ren J, et al. A randomized controlled trial of long term effect of BCM guided fluid management in MHD patients (BOCOMO study): rationales and study design. BMC Nephrol. 2012;13:120.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Chamney PW, Wabel P, Moissl UM, et al. A whole-body model to distinguish excess fluid from the hydration of major body tissues. Am J Clin Nutr. 2007;85(1):80–9.

    Article  CAS  PubMed  Google Scholar 

  28. Machek P, Jirka T, Moissl U, Chamney P, Wabel P. Guided optimization of fluid status in haemodialysis patients. Nephrol Dial Transplant. 2010;25(2):538–44.

    Article  PubMed  Google Scholar 

  29. Moissl U, Arias-Guillen M, Wabel P, et al. Bioimpedance-guided fluid management in hemodialysis patients. Clin J Am Soc Nephrol. 2013;8(9):1575–82.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Hur E, Usta M, Toz H, et al. Effect of fluid management guided by bioimpedance spectroscopy on cardiovascular parameters in hemodialysis patients: a randomized controlled trial. Am J Kidney Dis. 2013;61(6):957–65.

    Article  PubMed  Google Scholar 

  31. Vujicic B, Mikolasevic I, Racki S, Orlic L, Ljutic D, Bubic I. BCM--body composition monitor: a new tool for the assessment of volume-dependent hypertension in patients on maintenance haemodialysis. Coll Antropol. 2013;37(3):815–9.

    PubMed  Google Scholar 

  32. Onofriescu M, Mardare NG, Segall L, et al. Randomized trial of bioelectrical impedance analysis versus clinical criteria for guiding ultrafiltration in hemodialysis patients: effects on blood pressure, hydration status, and arterial stiffness. Int Urol Nephrol. 2012;44(2):583–91.

    Article  PubMed  Google Scholar 

  33. Huan-Sheng C, Yeong-Chang C, Ming-Hsing H, et al. Application of bioimpedance spectroscopy in Asian dialysis patients (ABISAD-III): a randomized controlled trial for clinical outcomes. Int Urol Nephrol. 2016;48(11):1897–909.

    Article  PubMed  Google Scholar 

  34. Patel HV, Annigeri RA, Kowdle PC, et al. Bioimpedance spectroscopy-guided ultrafiltration normalizes hydration and reduces Intradialytic adverse events in hemodialysis patients. Indian J Nephrol. 2019;29(1):1–7.

    CAS  PubMed  PubMed Central  Google Scholar 

  35. Covic A, Ciumanghel AI, Siriopol D, et al. Value of bioimpedance analysis estimated "dry weight" in maintenance dialysis patients: a systematic review and meta-analysis. Int Urol Nephrol. 2017;49(12):2231–45.

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

This study was supported by the Fresenius Medical Care Company. We thank all the patients who participated in this trial; Jin-Wei Wang, PhD. for help with the statistical analysis.

Funding

The study was supported by the Fresenius Medical Care Company. Neither Fresenius Medical Care (which markets the Body Composition Monitor) nor the sponsor had a role in study design and conduct; data management, collection, and analysis; or preparation and submission of the manuscript.

Author information

Authors and Affiliations

  1. Renal Division, Department of Medicine, Peking University First Hospital, Beijing, China

    Li Liu & Yuqing Chen

  2. Institute of Nephrology, Peking University, Beijing, China

    Li Liu & Yuqing Chen

  3. Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China

    Li Liu & Yuqing Chen

  4. Key Laboratory of Chronic Kidney Disease Prevention and Treatment, Ministry of Education, Beijing, China

    Li Liu & Yuqing Chen

  5. Department of Nephrology, Capital Medical University Fuxing Hospital, Beijing, China

    Yi Sun

  6. Department of Nephrology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China

    Jinsheng Xu

  7. Nephrotic Blood Purification Center, Tianjin Third Central Hospital, Tianjin, China

    Ping Yuan

  8. Department of Nephrology, Beijing Miyun County Hospital, Beijing, China

    Yulan Shen

  9. Department of Nephrology, General Hospital of Tianjin Medical University, Tianjin, China

    Shan Lin

  10. Department of Nephrology, Beijing Shijitan Hospital, Beijing, China

    Weiming Sun

  11. Department of Nephrology, Beijing Boai Hospital, China Rehabilitation Research Center, Captain Medical University, Rehabilitation Medical College, Beijing, China

    Yingchun Ma

  12. Department of Nephrology, Aviation General Hospital, Beijing, China

    Jianwei Ren

  13. Department of Nephrology, China Academy of Chinese Medical Sciences Guang’anmen Hospital, Beijing, China

    Wenjun Liu

  14. Department of Nephrology, Beijing Aerospace General Hospital, Beijing, China

    Jinghong Lei

  15. Department of Nephrology, Peking University People’s Hospital, Beijing, China

    Li Zuo

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  1. Li Liu
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Contributions

Research idea, study design: LZ; participants enrollment, participants follow-up, database management: LL, YS, YC, JX, PY, YS, SL, WS, YM, JR, WL, JL; ethics and regulatory documents preparation: LL; data analysis/interpretation and statistical analysis: LZ; supervision and mentorship: YS, YC, JX, PY, YS, SL, WS, YM, JR, WL, JL, LZ. Each author contributed important intellectual content during manuscript drafting or revision and accepts accountability for the overall work by ensuring that questions pertaining to the accuracy or integrity of any portion of the work are appropriately investigated and resolved. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Li Zuo.

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Liu, L., Sun, Y., Chen, Y. et al. The effect of BCM guided dry weight assessment on short-term survival in Chinese hemodialysis patients. BMC Nephrol 21, 135 (2020). https://doi.org/10.1186/s12882-020-01793-x

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BMC Nephrology

ISSN: 1471-2369

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