Table 3 Multiple regression analysis (objective value: Log ACR)

From: Gut microbiome-derived phenyl sulfate contributes to albuminuria in diabetic kidney disease

  Model 1 Model 2 Model 3
  Regression coefficient 95% CI p Regression coefficient 95% CI p Regression coefficient 95% CI p
Log(PS + 1)* 0.270 0.108 0.431 0.001 0.176 0.020 0.332 0.028 0.176 0.017 0.335 0.031
Age      −0.003 −0.017 0.011 0.652 −0.0004 −0.015 0.014 0.961
Gender*      0.333 0.056 0.611 0.019 0.396 0.097 0.695 0.010
BMI      0.020 −0.013 0.054 0.233 0.017 −0.022 0.055 0.397
SBP*      0.014 0.005 0.023 0.002 0.011 −0.0002 0.022 0.054
HbA1c      0.019 −0.115 0.152 0.786 0.035 −0.107 0.176 0.630
Log eGFR*      −1.919 −2.502 −1.335 <0.001 −1.883 −2.516 −1.250 <0.001
Duration          −0.003 −0.021 0.015 0.716
DBP*          0.010 −0.007 0.027 0.243
ALT          −0.004 −0.016 0.009 0.579
TC          −0.001 −0.006 0.005 0.761
TG          0.0004 −0.002 0.002 0.692
HDL          0.002 −0.010 0.013 0.795
UA          0.040 −0.054 0.134 0.403
  1. Multiple regression analysis based on clinical factors as an independent examined by variance inflation factor (VIF) <10. ACR was used as an independent variable factor. Model 1 (crude model), model 2 (adjusted by known factors: age, gender, BMI, SBP, HbA1c, log (eGFR))23, and model 3 (full model, adjusted by model 2 plus fundamental clinical data in Supplementary Table 4 (DBP, ALT, TC, TG, HDL, and UA) were used
  2. *p < 0.05 was regarded as statistically significant. Remaining variables after the stepwise method based on Akaike’s information criterion (AIC) in model 3 are depicted as *