Table 4 Factors predicting vascular access created timely with renal function expressed by Cr, MDRD-eGFR and CG-eGFR.

Variable	Adjusted OR (95% CI)	P value	Adjusted OR (95% CI)	P value	Adjusted OR (95% CI)	P value
Sex
Female	1.00 (reference)
Male	2.02 (1.23, 3.31)	0.005
Age at VA creation	0.97 (0.95, 0.99)	0.008
Renal function at VA creation
By Cr (mg/dL)	0.81 (0.74, 0.89)	< 0.001
By eGFR (MDRD) (ml/min/1.73 m²)			1.27 (1.11, 1.46)	0.001
By eGFR (CG) (ml/min/1.73 m²)					1.24 (1.11, 1.39)	< 0.001
eGFR slope (ml/min/1.73 m² per year)*		0.001^#		0.008^#		0.001^#
Q1 (< − 7.79)	0.37 (0.19, 0.73)	0.004	0.46 (0.24, 0.86)	0.015	0.38 (0.20, 0.72)	0.003
Q2 (− 7.79 ~ < − 4.30)	1.28 (0.61, 2.72)	0.5	1.30 (0.62, 2.72)	0.5	1.22 (0.58, 2.54)	0.6
Q3 (− 4.30 ~ < − 2.44)	1.00 (reference)	–	1.00 (reference)	–	1.00 (reference)	–
Q4 (≥ − 2.44)	0.97 (0.49, 1.93)	0.9	0.95 (0.48, 1.87)	0.9	1.02 (0.52, 2.03)	0.9

MDRD eGFR equation: 186 × serum creatinine^−1.154 × age^−0.203 × 0.742 (if female)^21,22. Cockcroft–Gault eGFR equation: [(140 − age)] × weight × 0.85 (if female)/(72 × serum creatinine), adjusted for BSA/1.73 m². \(BSA = weight~_{{{\text{kg}}}}^{{0.425}} \times height~_{{{\text{cm}}}}^{{0.725}} \times 0.007184\)^22,23.
Multiple logistic regression included the variables of sex, age at shunt creation, marital status, year of education, occupation, smoking, diabetes mellitus, renal function at chronic kidney disease (CKD) program enrollment, renal function at shunt creation, eGFR slope, CKD care program duration, and time period when VA was created. Here are only shown the significant variables by backward selection in this multivariable logistic regression model. A two-tailed value of P < 0.05 was considered to be statistically significant.
VA vascular access, OR odds ratio, CI confidence interval, Cr creatinine, eGFR estimated glomerular filtration rate, MDRD modification of diet in renal disease, CG Cockcroft–Gault, BSA body surface area.
*Quartile of eGFR slope, using eligible eGFRs calculated by MDRD equation.
^#P value for linear trend.

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