Preoperative NT-proBNP and LVEF for the prediction of acute kidney injury after noncardiac surgery: a single-centre retrospective study

Table 3 Performance metrics of postoperative AKI prediction models with and without preoperative NT-proBNP concentrations and LVEF levels

	Base model^a	Base model^a + NT-proBNP^* and LVEF
Multivariable logistic regression model ^a as the base model
AUC	0.767 (95% CI: 0.732, 0.802)	0.811 (95% CI: 0.779, 0.843)
ΔAUC	Reference	0.044, P < 0.001
Specificity, Sensitivity	0.721, 0.717	0.794, 0.700
NRI for event	Reference	0.229 (95% CI: 0.105, 0.344)
NRI for nonevent	Reference	0.363 (95% CI: 0.295, 0.439)
NRI	Reference	0.591 (95% CI: 0.437, 0.752), P < 0.000
IDI	Reference	0.100 (95% CI: 0.075, 0.125), P < 0.000

Abbreviations: AKI Acute kidney injury, ASA American Society of Anesthesiologists, AUC Area under the curve, CI Confidence interval, IDI Integral discrimination improvement, NRI Net reclassification improvement, NT-proBNP N-terminal pro-brain natriuretic peptide, LVEF Left ventricular ejection fraction
^*Natural log-transformed NT-proBNP
^aAdjusted for age (years), sex, body mass index, ASA physical status, hypertension, diabetes, coronary heart disease, stroke, congestive heart failure, ascites, the use of renin–angiotensin–aldosterone system inhibitors, emergency surgery, surgery type, surgery duration, anaesthesia type, estimated glomerular filtration rate (continuous), proteinuria, haemoglobin and serum albumin

ISSN: 1471-2253