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Open Access 01-12-2019 | Acute Kidney Injury | Letter
Authors’ response to letter “Prediction of acute kidney injury in intensive care unit patients”
Published in: Critical Care | Issue 1/2019
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We thank Dr. Guo and coworkers for their interest and comments [1] on our article [2]. We have provided responses to their comments. First, we agree that the patient severity of illness and level of organ failure upon admission to medical cardiac intensive care units (MCICUs) may be important predictors for the development of acute kidney injury (AKI). Hence, we evaluated the predictive ability of urinary liver-type fatty acid-binding protein (L-FABP) and serum N-terminal pro-B-type natriuretic peptide (NT-proBNP) for AKI in the analytical model that included the Sequential Organ Failure Assessment (SOFA) score. In the multivariate logistic regression analysis, L-FABP, NT-proBNP, and the SOFA score were all independent predictors of AKI (Table 1). According to these findings, we speculate that a novel panel consisting of L-FABP, NT-proBNP, and the SOFA score may improve the accuracy for predicting AKI in patients treated in MCICUs. Furthermore, the addition of both L-FABP and NT-proBNP to a baseline model that included established risk factors and the SOFA score further enhanced the net reclassification and integrated discrimination improvement; this difference was greater than that obtained for either of the biomarkers and the baseline model alone (Table 2). Therefore, upon admission of patients to MCICUs, combining the measurements of the two independent predictors of AKI—L-FABP and NT-proBNP—may improve the accuracy for the early prediction of AKI beyond that achieved with either predictor alone.
Table 1
Multivariate logistic regression analyses for predictors of acute kidney injury
|
Variables
|
Multivariate model 1
|
Multivariate model 2
|
||
|---|---|---|---|---|
|
OR (95% CI)
|
P Value
|
OR (95% CI)
|
P value
|
|
|
Age (per 10 years increment)
|
1.18 (1.00–1.39)
|
0.05
|
1.21 (1.03–1.42)
|
0.02
|
|
IABP before admission
|
2.33 (1.32–4.10)
|
0.003
|
2.46 (1.42–4.27)
|
0.001
|
|
NT-proBNP (per 10-fold increment)
|
1.67 (1.22–2.29)
|
0.001
|
||
|
Tertile of NT-proBNP (pg/mL)
|
||||
|
First (< 425)
|
1.0
|
|||
|
Second (425–2730)
|
2.10 (1.27–3.47)
|
0.004
|
||
|
Third (> 2730)
|
2.16 (1.20–3.88)
|
0.01
|
||
|
Urinary L-FABP (per 10-fold increment)
|
2.69 (2.06–3.50)
|
< 0.001
|
||
|
Tertile of Urinary L-FABP (ng/mL)
|
||||
|
First (< 3.3)
|
1.0
|
|||
|
Second (3.3–11.5)
|
1.50 (0.92–2.44)
|
0.10
|
||
|
Third (> 11.5)
|
3.72 (2.34–5.93)
|
< 0.001
|
||
|
SOFA score (per 1 point increment)
|
1.12 (1.04–1.21)
|
0.004
|
||
|
Tertile of SOFA score (point)
|
||||
|
First (< 2)
|
1.0
|
|||
|
Second (2–3)
|
1.17 (0.73–1.87)
|
0.51
|
||
|
Third (> 3)
|
2.04 (1.28–3.24)
|
0.003
|
||
Table 2
Discrimination and reclassification of combination of L-FABP and NT-proBNP for acute kidney injury
|
C-index
|
P value
|
NRI
|
P value
|
IDI
|
P value
|
|
|---|---|---|---|---|---|---|
|
Baseline model
|
0.752
|
Ref.
|
Ref.
|
Ref.
|
||
|
Baseline model + NT-proBNP
|
0.772
|
0.40
|
0.350
|
< 0.001
|
0.016
|
0.002
|
|
Baseline model + L-FABP
|
0.797
|
0.06
|
0.615
|
< 0.001
|
0.085
|
< 0.001
|
|
Baseline model + NT-proBNP + L-FABP
|
0.806
|
0.02
|
0.630
|
< 0.001
|
0.093
|
< 0.001
|
|
Baseline model + NT-proBNP + L-FABP vs. Baseline model + NT-proBNP
|
0.034*
|
0.14
|
0.571
|
< 0.001
|
0.077
|
< 0.001
|
|
Baseline model + NT-proBNP + L-FABP vs. Baseline model + L-FABP
|
0.008*
|
0.73
|
0.230
|
< 0.001
|
0.008
|
0.007
|