Comparison of volume of blood processed on haemodialysis adequacy measurement sessions vs regular non-adequacy sessions

Kenneth Scott Brimble, Joye St Onge, Darin J. Treleaven and Euan J. Carlisle

Department of Medicine, McMaster University, Hamilton, Ontario, Canada



   Abstract
 Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 References
 
Background. Knowledge that adequacy measures such as the urea reduction ratio (URR) or Kt/Vurea are being measured on haemodialysis may influence the behaviour of patients or staff such that the treatment may be better on those days. This study therefore tested the hypothesis that mean volume of blood processed (VBP), utilized as a surrogate for adequacy, is higher on adequacy measurement days than non-measurement days.

Methods. Patients were identified who had been on haemodialysis over the preceding 8 months. Primary outcome was the difference in the mean VBP (in litres) on URR measurement compared with non-URR measurement days ({Delta}VBPU–N). Univariate and multivariate correlates of mean VBP and {Delta}VBPU–N were also determined.

Results. Eighty-nine patients were identified who met inclusion and exclusion criteria. Linear regression demonstrated a weak relationship between VBP and URR (r=0.24, P<0.02). This relationship was much stronger when VBP was adjusted for patient weight (mean VBP/weight; r=0.78, P<0.0001). The overall mean VBP was 87.4 l (±1.2 l) and the average {Delta}VBPU–N was 1.1 l (±0.3 l) (P=0.001). Twenty per cent of patients had a clinically relevant {Delta}VBPU–N of >3.6 l. Patients with a graft or fistula had a significantly higher {Delta}VBPU–N than patients with a tunnelled catheter.

Conclusions. This study demonstrates that the average VBP is less on non-URR than on URR measurement days; this difference was clinically important in >20% of patients. Univariate analysis indicated that the use of a fistula or graft correlated with a higher {Delta}VBPU–N. This implies that our current method of assessing dialysis adequacy does systematically overestimate the average delivered dose of dialysis in a subset of patients.

Keywords: blood volume; compliance; haemodialysis adequacy; urea reduction ratio



   Introduction
 Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 References
 
Delivered dose of haemodialysis is a major predictor of patient morbidity and mortality [15]. This is measured routinely, typically on a monthly basis using either the Kt/Vurea or the urea reduction ratio (URR). Minimum recommended target adequacy levels are either a Kt/Vurea of 1.2 or a URR of 65% per dialysis session, delivered three times a week [6].

A limitation of such an approach to adequacy monitoring is that the result from a single dialysis treatment is assumed to be representative of all dialysis treatments throughout the month. However, non-adherence to the dialysis prescription is a prevalent problem [711]. In addition, knowledge that the URR or Kt/Vurea is being formally measured may influence the behaviour of certain patients or members of staff such that compliance with dialysis treatment may be better on adequacy measurement days.

This study was designed to identify potential overestimation of delivered dialysis dose in patients undergoing haemodialysis at a single centre by comparing delivered dialysis dose on URR measurement and on non-URR measurement days. Volume of blood processed (VBP) per dialysis session, also known as Qt [12], was recorded on all dialysis treatment records and was chosen as a surrogate marker of dialysis adequacy. The rationale for this is based on the breakdown of factors that determine Kt/Vurea and URR. K, or clearance, is dependent on the dialysis membrane properties, dialysate flow and access blood flow. Duration of dialysis is represented by t while V, the urea volume of distribution (Vd), is proportional to the patient's weight. VBP is simply the product of access blood flow and time, the factors that are most subject to treatment-to-treatment variations. This study therefore tested the hypothesis that mean VBP is higher on adequacy measurement days than non-measurement days, and evaluated clinical variables that might influence such a difference.



   Subjects and methods
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 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 References
 
Patients were identified from a haemodialysis census database at St Joseph's Hospital in Hamilton (ON, Canada). Only patients who had been on haemodialysis over the last 8 months were considered. Patients were excluded if any of the following had been changed over the study period: access type, prescribed blood or dialysate flow, prescribed treatment duration or level of nursing care required.

Demographic and comorbidity data were abstracted from charts as well as information on the dialysis prescription, type of access, dialysis shift and level of nursing assistance. Subsequently, all dialysis treatment sheets over the preceding 8 months were reviewed for VBP, treatment duration, dialysis shift (morning, evening or afternoon), level of nursing care, target weight, URR and ultrafiltration volume. URR was measured mid-week as described previously using the blood re-infusion sampling technique [6], where pre-dialysis urea is drawn immediately prior to haemodialysis initiation and post-dialysis urea is drawn 5 min after the patient's blood has been re-infused. This procedure does not have a direct effect on the VBP for that session. All patients were dialysed with biocompatible membranes. VBP was recorded after each session from the haemodialysis machine. VBP is simply the product of the blood flow calculated from the calibrated blood pump, integrated over the total time of the dialysis session. The blood pump was recalibrated under standardized conditions according to manufacturer specifications at regularly scheduled intervals. Blood flows derived by the haemodialysis machine were also compared in vivo with the ultrasound velocity dilution method (Transonic Systems, Ithaca, NY, USA). Blood flows derived from the haemodialyser correlated highly with the corresponding ultrasound dilution determined blood flows (r=0.93, P<0.0001), overestimating the ultrasound dilution-derived blood flows by 9.1% (95% confidence interval (CI) 8.3–9.9%).

Level of nursing care was defined as follows: (i) ‘total-care’, where patients require a dialysis nurse for the entire setup and delivery of the dialysis treatment; and (ii) ‘self-care’, where patients monitor and adjust the dialysis treatment themselves but may require a dialysis nurse to insert the needles and connect them to the dialysis machine.

Confirmation of a relationship between VBP and URR was ascertained by Pearson's coefficient of linear regression on mean values for individual patients. Primary outcome was the difference in the mean VBP in litres on URR measurement vs non-measurement days ({Delta}VBPU–N), and was calculated by determining the mean VBP on URR measurement (VBPU) and non-measurement (VBPN) days for each patient. The overall mean VBPU and VBPN were then calculated for the entire cohort and compared using a two-tailed paired Student's t-test. Univariate and multivariate correlates of VBP and {Delta}VBPU–N were determined by a two-tailed Student's t-test and analysis of variance (ANOVA) for categorical variables. Data analysis was carried out using the SPSS Version 9.0 (SPSS Inc., Chicago, IL, USA) software package.



   Results
 Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 References
 
Two hundred and ninety-five haemodialysis patients were identified who had been on haemodialysis over the preceding 8 months. The dialysis charts of 125 of these patients were sampled by convenience by two of the authors (J.S. and S.B.) for further review, and 89 patients were identified who met the additional inclusion and exclusion criteria. Eighty-six patients (96.6%) were dialysed three times a week, and 8650 haemodialysis treatment sheets were reviewed overall in the final analysis (95.0% complete).

The mean patient age was 64.7 years, and 56.2% were males. Just over half of all patients (50.6%) had coronary artery disease (CAD) while 38.2% had diabetes mellitus (DM). Linear regression analysis demonstrated a significant, albeit weak, relationship between mean VBP and mean URR (r=0.24, P<0.02). This relationship was much stronger when VBP was adjusted for patient weight (mean VBP/weight; r=0.78, P<0.0001).

The overall mean VBP was 87.4 l (±1.2 l) and the average {Delta}VBPU–N was 1.1 l (±0.3 l) (Table 1Go), representing a statistically significant difference (P=0.001). This is graphically represented in Figure 1Go, which indicates that overall 70% of the patients had a positive {Delta}VBPU–N. To ensure that the difference observed was not simply an effect of the weekday on which URRs were determined, two further analyses were performed. The URR values in our centre are measured monthly, typically on a Wednesday or Thursday. When the analysis was restricted to values from these days, the {Delta}VBPU–N was still significant (1.3±0.4 l, P<0.002). In the second analysis, VBPU values were discarded and VBPN values were compared for Wednesdays and Thursdays with the other days of the week. The difference in VBP was no longer significant (-0.2±0.2 l, P=0.43).


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Table 1.  Haemodialysis treatment variables

 


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Fig. 1.  Distribution of {Delta}VBPU–N by access type. The y-axis represents an assigned patient number, with patients grouped by access type.

 
The mean URR was 72.0% (±0.65) and the average prescribed time per treatment session was 3.92 h (±0.02); 88% of patients were prescribed 4 h (Table 1Go). The {Delta}tU–N (difference between treatment time on URR measurement and non-measurement days) could be determined in 81 patients and was 0.6 min (±0.01), which was not statistically significant (P=0.22). The average blood flow determined in the same 81 patients was 372.1 ml/min (±4.7), and the difference between average blood flow on URR measurement and non-measurement days ({Delta}QU–N) was 4.7 ml/min (±1.5), which was statistically significant (P=0.005). When this was evaluated in the patients in the upper quintile, the impact of the difference in blood flow was more pronounced. In these patients, {Delta}QU–N was four-fold higher at 20.1 ml/min (±1.1; P<0.0001), while {Delta}tU–N was approximately two-fold higher at 1.4 min (±0.6; P=0.03).

A summary of the findings from the univariate analysis is shown in Table 2Go. Patients who were male, non-diabetic, used either a fistula or graft or required less intensive nursing care had a higher mean VBP and blood flow by univariate analysis. Other variables, including CAD, peripheral vascular disease and dialysis shift did not correlate with VBP or blood flow. In a multivariate linear regression analysis (not shown), gender, access type and level of nursing care remained predictive of VBP. Only access type in a univariate analysis was predictive of {Delta}VBPU–N; patients with a graft or fistula had a significantly higher {Delta}VBPU–N than patients with a tunnelled catheter.


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Table 2.  Comparison of VBP, {Delta}VBP and blood flow stratified by baseline demographics

 



   Discussion
 Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 References
 
This study demonstrates that the average VBP is less on non-URR than URR measurement days; both patient- and dialysis centre-factors may account for this difference. In either case these factors may result in either an increase in dialysis duration or blood flow on URR measurement days.

Patients may be more likely to arrive late or request early discontinuation on days they know URR is not being measured, resulting in a decrease in delivered dialysis duration. Alternatively, when patients are able to adjust the haemodialysis machine settings, they may choose to increase dialysis blood flows on the days the URR is being measured in an attempt to improve results. It has been shown previously [13] that serum potassium, urea and inter-dialytic weight gain are higher when measured at unanticipated times than on regularly scheduled measurement days. This suggests that patients change their behaviour in anticipation of a measurement day to improve results. Numerous studies have evaluated the influence of non-compliance on haemodialysis adequacy and patient outcomes [711]. These studies indicate that skipped treatments and shortened dialysis times are associated with increased mortality, stressing the importance of patient compliance with the dialysis prescription on all treatment days.

This study demonstrated that differences in access blood flow explained much of the difference in VBP rather than dialysis duration. This is perhaps not surprising; it would be easier to simply increase access blood flow, if the access permits, rather than increase the time the patient remains on dialysis. Longer stays on URR measurement days would potentially lead to delays in the start-up time for the next patient, and would be less desirable for both the patients and the dialysis centre.

Use of a fistula or graft correlated with a higher {Delta}VBPU–N. This may reflect the fact that tunnelled catheters perform less consistently than fistulae and grafts, and therefore are subject to greater variability, overwhelming any minor influences that may arise on URR measurement compared with non-measurement days. Alternatively, access blood flow may already be maximized and may not be amenable to favourable manipulation on URR measurement days. This was borne out by the fact that the average blood flow was significantly lower in patients with catheters, whereas dialysis duration was not (data not shown).

Which factors are important with respect to the difference in {Delta}VBPU–N observed in this study? One might anticipate that if patient factors are more important then self-care patients, who have greater control over dialysis duration and access blood flow, would have higher {Delta}VBPU–N values than total-care patients. This, however, was not the case. This would suggest that nursing behaviours may be more important determinants of the increase in VBP on URR measurement vs non-measurement days.

Mortality risk increases by 11% with each 5% decrease in URR <70% [1]. Regression analysis from this study would suggest that a decrease in URR from 70% to 65% corresponds, on average, to a decrease in VBP of 8.0 l. The {Delta}VBPU–N of 1.1 l detected in this study reflects an estimated URR decrease of <1%, and a corresponding increase in mortality of 1.5%; thus, this statistically significant result is unlikely to be clinically significant overall. However, 20% of patients had a {Delta}VBPU–N >3.6, corresponding to a 5% increased risk of mortality, which may be clinically relevant. Interestingly, this value was only 3.4% when the analysis was repeated on non-URR days using the equivalent weekday VBP values for VBPU, suggesting that this observation is not simply due to chance.

It should be noted that this study is not without limitations. It is a retrospective study and data collection was not complete. Nonetheless, it would be difficult to carry out such a study prospectively without increasing patient and nurse awareness, and potentially influencing their behaviours to negate any true effect. VBP and weight-adjusted VBP have not been shown to correlate with clinical outcomes and are not a substitute for more appropriate adequacy measures such as URR or Kt/Vurea. VBP (and VBP/weight) does correlate with URR, however, and this observed relationship is physiologically sound.

In summary, there was a small but statistically significant difference in {Delta}VBPU–N; this was primarily due to a difference in {Delta}QU–N. More than 20% of patients demonstrated a clinically relevant difference in {Delta}VBPU–N. This implies that our current method of assessing dialysis adequacy systematically overestimates the average delivered dose of dialysis in a subset of patients. Excessive reliance on a single measure of dialysis adequacy is therefore discouraged, particularly in those patients with borderline URR values. Attention to individual dialysis treatments, including the VBP and/or the use of online monitoring of urea clearance measures, rather than simply testing adequacy monthly will lead to more consistent achievement of adequate haemodialysis and may ultimately improve patient outcomes.



   Notes
 
Correspondence and offprint requests to: Scott Brimble, Suite 708, 25 Charlton Avenue East, Hamilton, ON, L8N 1Y2 Canada. Email: brimbles{at}mcmaster.ca Back



   References
 Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 References
 

  1. Owen WF, Lew NL, Liu Y, Lowrie EG, Lazarus JM. The urea reduction ratio and serum albumin concentration as predictors of mortality in patients undergoing hemodialysis. N Engl J Med1993; 329: 1001–1006[Abstract/Free Full Text]
  2. Collins AJ, Ma JZ, Umen A, Keshaviah P. Urea index and other predictors of hemodialysis patient survival. Am J Kidney Dis1994; 23: 272–282[ISI][Medline]
  3. Hakim RM, Breyer J, Ismail N, Schulman G. Effects of dose of dialysis on morbidity and mortality. Am J Kidney Dis1994; 23: 663–669
  4. Held PJ, Port FK, Wolfe RA et al. The dose of hemodialysis and patient mortality. Kidney Int1996; 50: 550–556[ISI][Medline]
  5. Parker T, Husni L, Huang W, Lew N, Lowrie EG, Dallas Nephrology Associates. Survival of hemodialysis patients in the United States is improved with a greater quantity of dialysis. Am J Kidney Dis1994; 23: 670–680[ISI][Medline]
  6. NKF-K/DOQI Clinical Practice Guidelines for Hemodialysis Adequacy: update 2000. Am J Kidney Dis2001; 37 [1 Suppl 1]: S7–S64[Medline]
  7. Latham CE. Obstacles to achieving adequate dialysis dose: compliance, education, transportation, and reimbursement. Am J Kidney Dis1998; 32 [6 Suppl 4]: S93–S95[Medline]
  8. Sherman RA, Cody RP, Matera JJ, Rogers ME, Solanchick JC. Deficiencies in delivered hemodialysis therapy due to missed and shortened treatments. Am J Kidney Dis1994; 24: 921–923[ISI][Medline]
  9. Rocco MJ, Burkart JM. Prevalence of missed treatments and early sign-offs in hemodialysis patients. J Am Soc Nephrol1993; 4: 1178–1183[Abstract]
  10. Leggat JE, Orzol SM, Hulbert-Shearon TE et al. Noncompliance in hemodialysis: predictors and survival analysis. Am J Kidney Dis1998; 32: 139–145[ISI][Medline]
  11. Bleyer AJ, Hylander B, Sudo H et al. An international study of patient compliance with hemodialysis. JAMA1999; 281: 1211–1213[Abstract/Free Full Text]
  12. Santoro A. Confounding factors in the assessment of delivered hemodialysis dose. Kidney Int2000; 58 [Suppl 76]: S19–S27[ISI]
  13. Arici M, Altun B, Usalan C et al. Compliance in hemodialysis patients: unanticipated monitoring of biochemical indices. Blood Purif1998; 16: 275–280[ISI][Medline]
  14. Fink JC, Blahut SA, Briglia AE, Gardner JF, Light PD. Effect of center- versus patient-specific factors on variation in dialysis adequacy. J Am Soc Nephrol2001; 12: 164–169[Abstract/Free Full Text]
Received for publication: 18.12.02
Accepted in revised form: 22. 3.02