Association between hemoglobin and chronic kidney disease progression: a secondary analysis of a prospective cohort study in Japanese patients

Table 4 Relationship between HB and the renal composite endpoint in different models

Exposure	Crude model (HR,95%CI, P)	Model I(HR,95%CI, P)	Model II (HR,95%CI, P)	Model III (HR,95%CI, P)
HB	0.691 (0.651, 0.733) < 0.00001	0.681 (0.640, 0.725) < 0.00001	0.836 (0.770, 0.907) 0.00002	0.863 (0.790, 0.944) 0.00123
HB Quartile
Q1	Ref	Ref	Ref	Ref
Q2	0.569 (0.427, 0.758) 0.00012	0.572 (0.426, 0.769) 0.00022	0.713 (0.518, 0.981) 0.03764	0.978 (0.697, 1.373) 0.89912
Q3	0.237 (0.166, 0.338) < 0.00001	0.241 (0.167, 0.349) < 0.00001	0.522 (0.348, 0.783) 0.00168	0.743 (0.483, 1.142) 0.17528
Q4	0.093 (0.056, 0.154) < 0.00001	0.082 (0.048, 0.139) < 0.00001	0.332 (0.181, 0.610) 0.00038	0.382 (0.203, 0.719) 0.00286
P for trend	< 0.00001	< 0.00001	0.00005	0.00669

Crude model: we did not adjust other covariants
Model I: we adjust age, gender, BMI, SBP, hypertension, diabetes, and history of CVD
Model II: we adjust age, gender, BMI, SBP, hypertension, diabetes, history of CVD, UPCR, eGFR, ALB, urinary occult blood, use of RAAS inhibitor, use of calcium channel blocker, use of diuretics
CI Confidence, Ref Reference
Model III: we adjust age(smooth), gender, BMI(smooth), SBP(smooth), hypertension, diabetes, history of CVD, UPCR(smooth), eGFR(smooth), ALB(smooth), urinary occult blood, use of RAAS inhibitor, use of calcium channel blocker, use of diuretics
HR Hazard ratios, CI Confidence, Ref Reference

ISSN: 1471-2369