Table 2.
Univariate and iGFR1-adjusted (bivariate) linear regression parameter estimates for various putative predictors of log(GFR2) (n = 360) that were evaluated for inclusion in a GFR estimation model
| Predictor | Miss | Unadjusted |
iGFR1 Adjusted |
||
|---|---|---|---|---|---|
| Estimate (SE) | Explained Variability (%) | Estimate (SE) | Explained Variability (%) | ||
| log(iGFR1) | 0 | 0.95 (0.03)a | 68 | – | – |
| Δ log(ht/SCr) | 0 | 0.71 (0.08)a | 20 | 0.52 (0.04)a | 30 |
| Δ log(BUN) | 0 | −0.23 (0.07)a | 3 | −0.18 (0.04)a | 6 |
| Δ log(albumin) | 21 | −0.64 (0.29)b | 1 | −0.77 (0.16)a | 6 |
| log(age2) | 1 | −0.15 (0.05)b | 3 | −0.11 (0.03)a | 5 |
| log(ht2) | 0 | −0.27 (0.11)b | 2 | −0.29 (0.06)a | 5 |
| log(BSA2) | 0 | −0.08 (0.06) | 1 | −0.15 (0.03)a | 5 |
| log(weight2) | 0 | −0.05 (0.04) | <1 | −0.10 (0.02)a | 5 |
| Δ log(phosphate) | 29 | −0.38 (0.14)b | 2 | −0.25 (0.08)b | 3 |
| Δ log(calcium) | 21 | −0.72 (0.39) | 1 | −0.66 (0.22)b | 3 |
| Glomerular diagnosis | 3 | −0.02 (0.05) | <1 | −0.09 (0.03)b | 2 |
| Male gender | 0 | −0.01 (0.04) | <1 | −0.03 (0.03) | 1 |
| Δ log(glucose) | 21 | 0.03 (0.11) | <1 | 0.08 (0.06) | 1 |
| Δ log(proteinuria) | 42 | −0.01 (0.03) | <1 | 0.00 (0.02) | 1 |
| White race | 0 | −0.10 (0.05) | 1 | 0.03 (0.03) | <1 |
| Δ log(hemoglobin) | 32 | 0.19 (0.22) | <1 | 0.00 (0.12) | <1 |
| Δ log(potassium) | 28 | −0.01 (0.17) | <1 | −0.09 (0.10) | <1 |
| Δ log(systolic BP) | 35 | 0.22 (0.20) | <1 | −0.02 (0.12) | <1 |
| Δ log(hematocrit) | 32 | 0.11 (0.21) | <1 | 0.06 (0.12) | <1 |
| Δ log(CO2) | 23 | 0.60 (0.12) | <1 | 0.03 (0.07) | <1 |
| Δ log(sodium) | 21 | −0.83 (1.11) | <1 | 0.04 (0.63) | <1 |
Δ = log(X2) − log(X1) = log(X2/X1); GFR given in ml/min per 1.73 m2.
a
P < 0.001.
b
P ≥0.001 and < 0.05.