Table 5.
Multivariable residual risk factor associations with eGFR after accounting for mGFR
| Model 1 | ||||
|---|---|---|---|---|
|
| ||||
| eGFRCr | eGFRCysC | |||
|
| ||||
| Risk Factor | Beta (%) | P-Value | Beta (%) | P-Value |
| Body mass index per SD | - | - | −4.3 | <.001 |
| 24-h urine albumin per SD | - | - | −0.9 | 0.17 |
| 24-h urine creatinine per SD | −4.2 | <.001 | - | - |
| Hypertension | - | - | −4.0 | 0.008 |
| Diabetes | - | - | −3.1 | 0.20 |
| High-density lipoprotein | - | - | 1.4 | 0.12 |
| cholesterol per SD | ||||
| Log Triglyceride per SD | - | - | 0.6 | 0.47 |
| Log C-reactive protein per SD | - | - | −1.9 | 0.02 |
| Uric Acid per SD | - | - | 0.9 | 0.31 |
Model 1 uses generalized estimating equations with eGFR and mGFR as a stacked dependent variables regressed on all the non-redundant and statistically significant CKD risk factors in Table 4 to compare the difference in eGFR and mGFR regression coefficients. Statistical significance determined by the statistical interaction between each CKD risk factor with eGFR relative to mGFR in the multivariable model. Age and sex were adjusted for as main effects in the model.