Table 3.

D-dimer in predicting AKI with two-piecewise linear regression model in non-RM and RM patients.

	Total	Non-RM	RM
	OR (95%CI) p-value	OR (95%CI) p-value	OR (95%CI) p-value
Model I
One linear regression coefficient	1.1 (1.1, 1.2) <0.001	1.1 (1.0, 1.1) 0.114	1.3 (1.1, 1.5) <0.001
Model II
K	10	1.3	0.4
<K regression coefficient 1	1.3 (1.2, 1.5) <0.001	6.4 (1.7, 23.9) 0.005	0.0 (0.0, 50.7) 0.285
>K regression coefficient 2	1.0 (1.0, 1.1) 0.849	1.0 (1.0, 1.1) 0.591	1.3 (1.1, 1.5) <0.001
Difference between the regression coefficient 2 and 1	0.8 (0.7, 0.9) <0.001	0.2 (0.0, 0.6) 0.006	147.3 (0.0, 872159.1) 0.26
Predicted value of Y at K	1.5 (0.6, 2.4)	0.3 (−0.5, 1.1)	−1.5 (−2.5, −0.6)
Logarithmic LR test	0.002	0.004	0.267

K: Kurtosis; LR: logistic regression.