Table 6.
Linear Regression analysis of confounding variables considering estimated glomerular filtration rate (eGFR) as dependent variable in the baseline stage and 1st follow up.
| Variables | Beta Coefficient (β) | p-value | 95% confidence interval for β |
|
|---|---|---|---|---|
| Lower Bound | Upper Bound | |||
| Baseline Data | ||||
| (Constant) | 0.000 | 117.699 | 239.844 | |
| Gender | -.223 | 0.026* | −20.221 | −1.291 |
| Age | -.417 | 0.000*** | −1.326 | -.479 |
| BMI | .055 | 0.569 | −0.952 | 1.722 |
| SBP | -.257 | 0.023* | −0.585 | −0.044 |
| DBP | -.070 | 0.514 | −0.653 | 0.329 |
| S. uric acid | -.050 | 0.597 | −0.046 | 0.027 |
| FBS | .010 | 0.913 | −2.338 | 2.612 |
| 1stFollow up | ||||
| (Constant) | 0.000 | 50.294 | 131.088 | |
| Gender | -.252 | 0.010** | −23.880 | −3.389 |
| Age | -.375 | 0.000*** | −1.358 | -.463 |
| BMI | .264 | 0.089 | −0.181 | 2.529 |
| SBP | .151 | 0.438 | −0.230 | 0.526 |
| DBP | .069 | 0.710 | −0.460 | 0.673 |
| S. uric acid | -.092 | 0.354 | −0.065 | 0.024 |
| FBS | -.046 | 0.635 | −2.615 | 1.603 |
Dependent Variable was eGFR in ml/min/1.73m2 in Baseline and 1st Follow up data. Here, (*p < 0.05) = significant, (**p < 0.01) = highly significant, (***p < 0.001) = very highly significant. Linear regression analysis was performed. Here, BMI= Body mass index, SBP= Systolic blood pressure, DBP = Diastolic blood pressure, FBS= Fasting blood sugar, S. uric acid = Serum uric Acid, eGFR = estimated glomerular filtration rate.