Table 2.
Patient characteristics and change in proteinuriaa
| Percent difference in Up/c
|
||||
|---|---|---|---|---|
| Unadjusted, n = 419
|
Adjustedb, n = 402
|
|||
| Estimate [95% CI] | P value | Estimate [95% CI] | P value | |
| iGFR, per 10% Decrease | 14% [10%, 18%] | <0.01 | 17% [13%, 21%] | <0.01 |
| Age, per 2-yr Increase | 8% [1%, 14%] | 0.01 | 6% [0%, 12%] | 0.07 |
| Male versus female Sex | −2% [−24%, 27%] | 0.88 | 12% [−12%, 41%] | 0.36 |
| Non-Caucasian versus Caucasian race * | 39% [6%, 81%] | 0.02 | 40% [9%, 80%] | 0.01 |
| BMI SDS, z-score, per 1 unit increasec | 3% [−8%, 15%] | 0.60 | 3% [−6%, 14%] | 0.52 |
| Glomerular versus non-glomerular CKD diagnosis | 140% [79%, 221%] | <0.01 | 134% [73%, 219%] | <0.01 |
| ACE and/or ARB use | 8% [−16%, 38%] | 0.57 | −16% [−34%, 7%] | 0.16 |
SDS, standard deviation score.
a
Linear regression of log Up/c as a continuous variable.
b
Controlling for iGFR, age, gender, race, BMI percentile, cause of CKD, and ACEI or ARB use.
c
Missing data: race, n = 1; BMI SDS, n = 16.