NDT Advance Access published June 19, 2013 Nephrol Dial Transplant (2013) 0: 1–5 doi: 10.1093/ndt/gft237 Original Article Differences in prescribed Kt/V and delivered haemodialysis dose—why obesity makes a difference to survival for haemodialysis patients when using a ‘one size fits all’ Kt/V target London Medical School, London NW3 2QG, UK Keywords: anthropomorphic Watson, body composition, Kt/V, multi-frequency bioimpedance, muscle fat, obesity Correspondence and offprint requests to: Andrew Davenport; E-mail: [email protected] the Watson-based urea volume of distribution for the obese patients (BMI > 35; spKt/V 1.63 ± 0.48 versus 1.41 ± 0.35 and BMI 30–35; 1.65 ± 0.3 versus 1.46 ± 0.26, both P < 0.01). Conclusions. Prescribing dialysis or quantifying on-line clearance based on the anthropomorphically derived Watson equation leads to underestimation of the delivered dose to obese patients, due to changes in underlying body composition. As such, when using a ‘one size fits all’ target Kt/V, obese patients have an advantage over patients with normal BMI, in that they will receive a greater delivered dose of dialysis, and this may potentially explain the paradoxical survival advantage of the morbidly obese haemodialysis patient. A B S T R AC T Background. Morbid obesity is reported to be a survival factor for haemodialysis patients compared with those with a normal body mass index (BMI), yet morbid obesity (BMI >35) is a mortality risk factor for obese patients in the general population. Traditionally, haemodialysis dosing is prescribed to achieve a target Kt/V corrected for total body water (TBW). As obese patients typically have increased body fat, which contains less water than muscle, then obese patients may have lower levels of body water than their slimmer counterparts, and as such delivered Kt/V could be greater than that estimated using standard anthropomorphic equations, and so increased dialysis dose may help explain the increased survival reported for obese patients. Methods. We compared multi-frequency bioelectrical impedance analysis (MF-BIA) measurements of TBW in healthy haemodialysis outpatients, and compared TBW with that calculated from the Watson equation derived from anthropomorphic measurements. Results. Three hundred and sixty-three adult patients, mean age 58.1 ± 16.7 years, 60.9% male and 29.9% diabetic were studied. MF-BIA-measured body composition showed that as BMI increased from <20 to >35, the percentage skeletal muscle mass fell from 42.8 ± 4.9 to 29.2 ± 5.5% (P < 0.01) whereas the % fat mass increased from 24.5 ± 11.6 to 46.7 ± 6.8% (P < 0.01). As such, TBW measured by MF-BIA was significantly lower from that predicted by the Watson equation at higher BMIs (BMI > 35; 38.9 ± 6.8 versus 44.7 ± 6.9 L, P < 0.01 and BMI = 30–35; 37.2 ± 7.5 versus 41.9 ± 7.3 L, P < 0.01), and as such the delivered Kt/V using MF-BIA was much greater than that using © The Author 2013. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved. INTRODUCTION Mortality risk progressively increases with chronic kidney disease staging [1], and intuitively treatment with a greater amount of dialysis might be expected to improve patient survival. The National Cooperative Dialysis Study (NCDS) showed that those patients treated by thrice weekly haemodialysis with higher time-averaged urea concentrations were more likely to become unwell, and defined a threshold adequacy, based on urea clearance [2]. Urea clearance was expressed as Kt/V, where K is the dialyser urea clearance, t is the duration of the dialysis session and V is the volume of urea distribution [3]. Later studies showed a relationship between carbamylated haemoglobin [4] and Kt/V [5]. Subsequent observational studies reported improved patient survival rates with Kt/V > 1.0 [6, 7], and by consensus dialysis sessional Kt/V targets were increased to 1.2 [8]. The Haemodialysis study (HEMO study) 1 Downloaded from http://ndt.oxfordjournals.org/ by guest on October 1, 2014 UCL Center for Nephrology, Royal Free Hospital, University College Andrew Davenport Wilcoxon rank-sum pair test for paired values with Bonferroni correction for multiple analyses where appropriate and by ANOVA with Tukey post-hoc correction. Statistical analysis used Graph Pad Prism version 6.0 (Graph Pad, San Diego, CA, USA) and SPSS version 17 (University Chicago, USA). Statistical significance was taken at or below the 5% level. R E S U LT S We studied 363 adult patients, mean age 58.1 ± 16.7 years, 60.9% male, 28.9% diabetic and dialysis vintage 51 (20–83) months. Major racial groups were 51.5% Caucasoid, 37.8% south Saharan African or Afro-Caribbean and 34.2% Asian. Post-dialysis weight 70 ± 16.0 kg, body mass index (BMI) 25.8 ± 5.4 kg/m2, dialysis session time 3.94 ± 0.5 h with preand post-dialysis serum urea 19.8 ± 6.0 and 5.3 ± 2.3 mmol/L, respectively, with a urea reduction ratio 73.3 ± 7.1%. Pre-dialysis haemoglobin 11.4 ± 1.5 g/L, albumin 40.9 ± 3.9 g/L, median C-reactive protein 4 (2–11) mg/L and glucose 5.9 (4.8–8.4) mmol/L. TBW, measured by MF-BIA post-dialysis was 35.2 ± 7.5 L and did not differ from that estimated from Watson (36.6 ± 7.0 L), but single-pool Kt/V was statistically different for that using MF-BIA 1.65 ± 0.41 compared with that using the Watson equation, 1.56 ± 0.32, P < 0.001. MFBIA skeletal muscle mass was 26.3 ± 6.2 kg, fat mass 23.0 ± 12.0 kg, giving a percentage body skeletal muscle content of 37.6 ± 6.9% and fat content of 31.4 ± 13.0%. Patients were divided according to BMI into five groups, those with a BMI 19 or lower, 20–25, 25–30, 30–35 and >35.0. There was no difference in ethnic distribution between the groups, although there were differences in sex distribution and diabetes with BMI (Table 1). TBW was significantly greater when calculated by the Watson equation compared with that measured by MF-BIA for those patients with the greater BMIs (Figure 1). The pre-dialysis serum urea was lower in those patients with the smallest BMI compared with the highest quintile, whereas the urea reduction ratio was higher for the lowest quintile BMI compared with the highest (Table 1). Comparing single-pool Kt/V measured by the Daugirdas equation [23], and that recalculated using MF-BIA, then Kt/V was greater with the Daugirdas equation for those patients with the lowest BMIs, and lower for those with the highest BMIs (Figure 2). The percentage ultrafiltration to MF-BIA measured TBW was greater for the highest BMI groups (Table 1). Although there was a trend for patients with a lower BMI having shorter dialysis sessions, this was not significant when correcting for multiple analyses (Table 1). Body composition, in terms of muscle and fat differed between the BMI quintiles, with reducing muscle mass and increasing fat as BMI increased (Figure 3). M AT E R I A L S A N D M E T H O D S Multi-frequency bioimpedance measurements were made post dialysis in 361 healthy haemodialysis outpatients attending their mid-week dialysis session (InBody 720 Body Composition Analysis, Biospace, Seoul, South Korea) [17], using direct segmental MF-BIA with tetrapolar 8-point tactile electrodes [18], in a standardized manner [19]. Patients with cardiac pacemakers, implantable defibrillators, amputees and those unable to stand on the bioimpedance machine were excluded from study. Fresenius F4000H or 5000H dialysis machines (Fresenius Bad Homburg, Germany) were used with polysulfone high-flux dialysers (Nipro Corporation, Osaka, Japan) [20], with ultrapure quality dialysis water and low-molecular-weight heparin (Tinzaparin, Leo Laboratories, Princes Risborough, UK) [21]. Pre- and post-dialysis dialysis blood samples were taken in a standardized fashion measured with a standard laboratory auto-analyser (Roche Integra, Roche diagnostics, Lewes, UK) and haemoglobin (XE-2100 Sysmex Corporation, Kobe, Japan). Kt/V was calculated using the Daugirdas equation [22]. Body composition was derived from multi-frequency bioelectrical impedance assessments (MF-BIA) [15, 23]. Using TBW measured post dialysis by MF-BIA, Kt/V was recalculated [24] assuming the Watson formula for TBW [25]. Ethical approval was granted by the local ethical committee as part of UK National Health Service audit and clinical service development. Statistical analysis Results are expressed as mean ± standard deviation, or median and inter-quartile range, or percentage. Statistical analysis was by χ 2 analysis, corrected for small numbers by Yates’ correction, students’ t-test for parametric and the Mann–Whitney U-test for nonparametric data, Student’s pair t-test and DISCUSSION Although the NCDS study helped to define a lower limit for dialysis dosing, based on urea clearance [2, 3], subsequent 2 A. Davenport Downloaded from http://ndt.oxfordjournals.org/ by guest on October 1, 2014 ORIGINAL ARTICLE [9], the second randomized controlled trial to investigate the effect of Kt/V on patient outcomes, reported that higher doses did not improve overall patient survival. However, on subgroup analysis, women who had been established on haemodialysis for more than 3 years did benefit from higher Kt/V targets. This led to suggestions that using an estimate of body water resulted in underdosing of some patient groups on one hand and potentially delivering greater doses to others [10]. Whereas for the general population, morbid obesity is associated with increased mortality [11], several observational studies have reported that survival is increased for the morbidly obese haemodialysis patients [12, 13]. This apparent paradox may be due to changes in body composition, as fat contains less water than muscle, and the standard equations used to calculate body water may not reflect these differences. Multi-frequency bioelectrical impedance assessments (MFBIA) can be used to both measure body water [14] and also body composition in dialysis patients [15, 16]. To determine whether obese patients receive a proportionally higher dialysis dose when the same Kt/V target is used, we compared total body water (TBW) estimation by anthropomorphic equations and that measured by MF-BIA. Table 1. Patients divided according to body mass index (kg/m2) ≤20 20–25 25–30 30–35 >35.0 n 38 141 120 42 22 Male 16 90 81 28 10 Female 22 52 41 14 12 diabetic 2 38 31 20 13 Not diabetic 36 103 89 22 9 Caucasoid 12 51 50 19 10 African 10 39 36 11 8 Asian 16 49 33 9 4 Pre urea (mmol/L) 17.2 ± 5.5 20.0 ± 6.7 19.8 ± 5.0 20.4 ± 5.8 21.7 ± 5.7* URR (%) 75.2 ± 8.6 74.5 ± 6.3 73.0 ± 6.6 71.1 ± 6.5 78.7 ± 9.8* UF/TBW% 2.4 (1.4–3.2) 3.1 (1.9–4.0) 3.4 (2.3–5.0) 4.9 (2.8–6.5) 4.6 (3.5–7.7)* Session time (h) 3.8 ± 0.62 3.89 ± 0.46 4.0 ± 0.46 3.97 ± 0.55 4.12 ± 0.57 Comparison of sex, diabetes and racial origin, Sub Sahara African-AfroCaribbean (African). χ analysis. Pre-dialysis serum urea (Pre-urea). URR, urea reduction ratio. Dialysis session time in hours. Males versus females P = 0.035, diabetes versus no diabetes P < 0.001. Ultrafiltration volume (UF) to total body water (TBW). Results expressed as mean ± SD or median (inter-quartile range). *P < 0.05 BMI < 20 versus BMI > 35. 2 ORIGINAL ARTICLE Downloaded from http://ndt.oxfordjournals.org/ by guest on October 1, 2014 BMI F I G U R E 2 : Kt/V calculated by the Daugirdas equation [22] com- pared with that using total body water measured by multifrequency bioelectrical impedance analysis (MF-BIA) in patient cohort divided into body mass index (BMI) kg/m2 groups. *P < 0.05 versus MF-BIA after correction for multiple analyses. F I G U R E 1 : Total body water (TBW) calculated by Watson equation [23] compared with TBW measured by multi-frequency bioelectrical impedance analysis (MF-BIA) in patient cohort divided into body mass index (BMI) kg/m2 groups. *P < 0.05 versus MF-BIA after correction for multiple analyses. the volume of urea distribution, then V will be overestimated in the morbidly obese patient due to the relative increase in fat mass and reduction in muscle, due to the lower water content of adipose tissue. In addition, to achieve a pre-determined target, it is most likely that dialysis session time will be increased for the obese patient, so they additionally benefit both from increased clearance of time-dependent solutes, such as phosphate [28], and also control of sodium balance and overhydration. This is supported by our study with both a trend in terms of dialysis session time and an increasing proportion of ultrafiltration to TBW with increasing BMI. As such, this improved delivery of a higher dose of dialysis for the obese patient could potentially explain the apparent paradox of an apparent survival advantage for the morbidly obese (BMI > 35) haemodialysis patient compared with those with prospective studies failed to show that increasing the delivered dialysis dose based on Kt/V prescription increased patient survival [9]. This could be due to many confounders, including residual renal function, the time to accumulate uraemic toxins to cause morbidity and mortality [26], and the effects of intradialytic weight gains and extracellular volume control [27]. In addition, the mean Kt/V values in the HEMO study were not too dissimilar between the groups at 1.16 versus 1.32, so another potential confounder could have been that patients with higher BMIs had an underestimate of the actual dose delivered, and those with lower BMIs an overestimate, so that the groups were not as separated as initially thought. When dialysis is prescribed according to Kt/V, or measured by on-line clearance using the Watson equation to estimate 3 Obesity and delivered dialysis dose obesity with increased body fat content, by containing less water than muscle, paradoxically has become a survival advantage for haemodialysis patients using current treatment target paradigms. C O N F L I C T O F I N T E R E S T S TAT E M E N T The author has no conflict of interest. The data contained in this paper have not been previously published in whole or part form, or by abstract. F I G U R E 3 : Changes in body composition as percentage of muscle REFERENCES 1. Chronic Kidney Disease Prognosis ConsortiumMatsushita K, van der Velde M, Astor BC et al. Association of estimated glomerular filtration rate and albuminuria with all-cause and cardiovascular mortality in general population cohorts: a collaborative metaanalysis. Lancet 2010; 375: 2073–2081 2. Lowrie EG, Laird NM, Parker TF et al. 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