Gh. Murata et al., ESTIMATING UREA CLEARANCE IN PATIENTS ON CONTINUOUS AMBULATORY PERITONEAL-DIALYSIS - A MULTIVARIATE-ANALYSIS, International journal of artificial organs, 21(9), 1998, pp. 515-520
The purpose of this study was to determine if Kt/V urea in continuous
ambulatory peritoneal dialysis (CAPD) could be estimated by a multivar
iate model based upon simple clinical observations. The study included
439 clearance studies in 301 CARD patients followed in 8 dialysis cen
ters. Weekly urea clearance, 24 h urine volume and 24 h drain volume w
ere normalized to body water by the formulae of Watson (Kt/V UV/V, and
DV/V respectively). Adequate dialysis was defined as Kt/V greater tha
n or equal to 2.0 weekly. Subjects at 2 units were used to derive the
models, while others were used for model validation. Stepwise multiple
linear regression was performed on the derivation set (DS) to identif
y the clinical variables that correlated with Kt/V. The model was then
used to estimate Kt/V for the validation set (VS). In the DS, 110 cle
arance studies were performed in subjects with residual renal function
. Multiple linear regression showed that weekly Kt/V was defined by th
e expression: Kt/V = 1.48 + 24.1 (UV/V) + 2.92 (DV/V) - 0.049 (serum c
reatinine) (r = 0.750, p < 0.001). In 204 VS studies, the correlation
between estimated and measured Kt/V was 0.633. There were marked diffe
rences in the proportion of adequately dialyzed patients when Kt/V est
imated from the formula shown was <2.0, between 2.0 and 2.3, and >2.3
weekly (79%, 54.7% and 79.7%, respectively; p < 0.001). In the 33 stud
ies done in DS anuric patients, regression analysis showed the followi
ng: Kt/V = 0.46 + 2.59 (DV/V) + 0.009(age) (r = 0.562; p = 0.003). In
92 VS studies in anuric subjects, there was strong correlation between
estimated and measured KW (r = 0.740). Again, there were marked diffe
rences in the frequency of adequate dialysis in anuric patients with e
stimated Kt/V <2.0, between 2.0 and 2.3 and >2.3 weekly (8.1%, 68.8%,
and 100%, respectively; p < 0.001). The risk of low KW can be estimate
d by multivariate linear models requiring only simple clinical measure
ments.