Is there a necessity for individual blood water corrections when conductivity-based access blood flow measurements are made?

BACKGROUND/AIMS: Access blood water flow rate (Qaw) can be measured during hemodialysis using an online effective ionic dialysance (EID) methodology. Fresenius employ this methodology in their 2008K dialysis machine. The machine computer converts Qaw to an access blood flow rate (Fresenius Qa) using a generic blood water constant (BWC). We wished to validate this BWC. METHODS: 18 patients had Fresenius Qa measurements using the EID and these were compared with a 'gold standard' ultrasound dilution methodology (Transonic Qa). Qa values were also obtained by removing the BWC from Fresenius Qa values to obtain the Qaw and recorrecting it with individualized patient factors using hematocrit and total protein values (HctTp Qa). The measurements were repeated after 1 h. RESULTS: There were no significant differences between Fresenius and Transonic, nor between HctTp and Transonic Qa values (p > 0.17). There were strong correlations between both sets of values (r > 0.856; p < 0.001). There was a significant correlation between the pairs of Transonic Qa values (r = 0.823; p < 0.007), but not for Fresenius Qa pairs (r = 0.573; p > 0.07). It was surmised that the BWC was not valid post-dialysis. CONCLUSION: The generic BWC is comparable to individualized blood water correction factors when Qa measures are made early in dialysis and prior to ultrafiltration treatment.

Lowering postdialysis plasma sodium (conductivity) to increase sodium removal in volume-expanded hemodialysis patients: a pilot study using a biofeedback software system.

BACKGROUND: Extracellular fluid expansion is common in hemodialysis patients. Aggressive fluid removal may lead to intradialytic complications. High dialysate sodium concentrations may lessen complications, but may increase extracellular volume. We hypothesized that decreasing plasma sodium concentration during dialysis will increase sodium removal and decrease extracellular volume. STUDY DESIGN: Pilot clinical trial. SETTING & PARTICIPANTS: 16 patients with end-stage kidney disease treated using thrice-weekly hemodialysis at a university teaching hospital hemodialysis unit. INTERVENTION: Stepwise decrease in postdialysis plasma sodium level (calculated as end-of-session plasma conductivity) over 4 phases effected by dialysate conductivity measurement cells and a biofeedback software system (Diacontrol; Hospal, www.hospal.it) that allowed alteration of dialysate inlet conductivity and calculation of plasma conductivity. OUTCOMES: Decrease in postdialysis plasma sodium (conductivity) levels, sodium removal, redistribution of body water, and effect of these on interdialytic weight gain and blood pressure. MEASUREMENTS: Plasma sodium and conductivity values (the latter measured in millisiemens per centimeter); ionic mass balance (sodium removal); bioelectrical impedance analysis measurements of body-water compartments and phase angle; interdialytic weight gain; and blood pressure. RESULTS: Plasma sodium concentrations at the end of dialysis were decreased from 137.8 (phase 1) to 135.6 mmol/L (phase 4) and end-of-session plasma conductivity values were decreased from 14.0 (phase 1) to 13.5 mS/cm (phase 4; all mean values). Ionic mass balance increased from 383 to 480 mmol. Extracellular water was significantly decreased, phase angle was increased, and blood pressure and interdialytic weight gain were decreased. Plasma sodium levels correlated significantly with plasma conductivity; thus, changes in postdialysis plasma sodium levels can be inferred from changes in end-of-session plasma conductivity values. LIMITATIONS: Small number of patients. No information for dietary sodium intake. CONCLUSION: To decrease extracellular volume, it may be necessary to add diffusive to convective sodium losses.

Cystatin C levels in functionally anephric patients undergoing dialysis: the effect of different methods and intensities.

BACKGROUND AND OBJECTIVES: Cystatin C, a low molecular weight protein, is produced by nucleated cells, filtered by glomeruli, and degraded by tubules at a constant rate. Its serum concentration has been proposed as a marker of GFR. Its size should make it dialyzable. It is hypothesized that serum cystatin C levels are influenced by the method and intensity of dialysis received. DESIGN: This is a cross-sectional pilot study of cystatin C in functionally anephric dialysis patients. It was measured predialysis in 14 patients on conventional (3 to 5 h, 3 x wk) hemodialysis; eight on nocturnal hemodialysis (three to seven nights, 6 to 8 h); three on daily hemodialysis (6 d, 1(1/2) to 2(1/2) h); and 10 on automated peritoneal dialysis. All had urea kinetic studies and values for single pool Kt/V (Sp Kt/V), standard weekly Kt/V (Std Kt/V), and protein equivalent of nitrogen appearance (nPNA; g/kg/d). C reactive protein (CRP; mg/L) and thyroid stimulating hormone (TSH; mIU/L) were measured as factors known to influence cystatin C. RESULTS: There was no correlation between cystatin C and Sp Kt/V, but there was a significant inverse linear correlation with Std Kt/V and there were significant differences between treatment modalities in cystatin C levels and in Std Kt/V. The estimation of cystatin C was reliable and stable over 3 to 6 wk and its levels uninfluenced by nPNA, CRP, or TSH. CONCLUSION: Serum cystatin C levels are influenced by the method and intensity of dialysis and may have a role in treatment adequacy monitoring.

Minutes to recovery after a hemodialysis session: a simple health-related quality of life question that is reliable, valid, and sensitive to change.

Patients who have end-stage renal failure and are treated by hemodialysis (HD) face a stressful chronic illness with a demanding treatment regimen that affects quality of life. Quality-of-life domains can be measured by assessment questionnaires that are easy to complete, reliable, valid, and sensitive to change. There is current interest in HD regimens that provide more frequent treatments (e.g., daily) than the conventional thrice weekly. Improvement in quality of life by these regimens has been reported. A published prospective, cohort, controlled study (London Daily/Nocturnal Hemodialysis Study) included the results of a number of quality-of-life indicators that were applied to the study patients. In general, the indicators used were well established and of proven validity. Included was one single question that was added intuitively and had not received previous validation: "How long does it take you to recover from a dialysis session?" The responses to this question allow the validation of this simple question as a tool to be used in HD clinical research. Twenty-three patients who were treated by frequent HD (5 to 7 d or nights) and 22 control subjects who were treated by thrice-weekly dialysis were studied during an 18-mo period. The "time to recovery" question was administered along with a battery of renal disease-specific questionnaires and the Generic Medical Outcomes Survey 36 Item-Short Form (SF-36) plus the global Health Utilities Index. Missing data rates, reliability over time, construct validity, and sensitivity to change were assessed from the "time to recovery" responses by standard methods. The question was administered on a total of 314 occasions and answered successfully on 313. The test-retest correlation over 3-mo intervals was highly significant (r = 0.962, P = 0.000; n = 100). Convergent construct validity was established by significant correlations between time to recovery and fatigue (r = 0.38, P = 0.000; n = 313), dialysis stress (r = 0.348, P = 0.000), disease stress (r = 0.374, P = 0.000), SF-36 subscales especially vitality (r = -0.356 P = 0.000), and the Health Utilities Index (r = -0.232, P = 0.000). These scales captured mainly physical or physiologic domains. Divergent construct validity was established by lack of correlations between "time to recovery" and a number of subscales that captured mainly emotional or psychosocial domains, e.g., SF-36 subscale for "role emotional" (r = -0.102, NS) and dialysis stressors such as access problems (r = -0.015, NS) or equipment malfunction (r = 0.032, NS). Test sensitivity was established when the conventionally dialyzed group showed no significant difference in time to recovery between baseline and other time periods, whereas the daily/nocturnal group had a significant reduction between baseline (while on conventional dialysis) and the result at each other time period (minimum P = 0.05). There also was a significant difference between the control and experimental groups over time (ANOVA P = 0.000). The response to the question, "How long does it take you to recover from a dialysis session?" is interpreted easily, is easy to which to respond, shows stability over time by test-retest, shows both convergent and divergent validity, and is sensitive to change. As such, it should be considered as a standard question in HD-related studies in which a health-related quality-of-life outcome is examined.