Machine learning model for predicting acute kidney injury progression in critically ill patients

Table 2 Logistic regression model with stepwise variable selection

Variables	OR	95% CI	P value
Gender	0.91	0.87, 0.95	< 0.001
Admissions type	1.16	1.1, 1.22	< 0.001
Cardiac surgery	0.86	0.81, 0.91	< 0.001
Respiratory failure	1.47	1.41, 1.54	< 0.001
Mechanical ventilation	1.00	0.96, 1.05	0.880
MODS	1.55	1.50, 1.60	< 0.001
Spesis	1.71	1.6, 1.82	< 0.001
Vasoactive drugs	1.04	0.99, 1.09	0.101
BUN	1.01	1.01, 1.01	< 0.001
Creatinine	1.20	1.15, 1.25	< 0.001
PaO2	1.00	1.00, 1.00	0.0535
Glucose	1.00	1.00, 1.00	0.187
Lactate	1.03	1.02, 1.05	< 0.001
FST	1.00	1.00, 1.00	< 0.001

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