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Erschienen in: Critical Care 1/2019

Open Access 01.12.2019 | Letter

Authors’ response to letter “Prediction of acute kidney injury in intensive care unit patients”

verfasst von: Hiroyuki Naruse, Hiroshi Takahashi, Junnichi Ishii

Erschienen in: Critical Care | Ausgabe 1/2019

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
Multivariate model adjusted for all baseline variables with P < 0.05 by univariate analysis. NT-proBNP, L-FABP, and the SOFA score were assessed as either continuous variables (model 1) or variables categorized into tertiles (model 2)
CI confidence interval, IABP intraaortic balloon pump, L-FABP liver-type fatty acid-binding protein, NT-proBNP N-terminal pro-B-type natriuretic peptide, OR odds ratio, SOFA Sequential Organ Failure Assessment
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
Baseline model included age, sex, hypertension, dyslipidemia, diabetes, smoking status, atrial fibrillation, acute decompensated heart failure, previous myocardial infarction, previous coronary revascularization, heart rate, emergent coronary angiography or percutaneous coronary intervention before admission, intraaortic balloon pump before admission, and the SOFA score
IDI integrated discrimination improvement, L-FABP liver-type fatty acid-binding protein, NT-proBNP N-terminal pro-B-type natriuretic peptide, NRI net reclassification improvement, Ref. reference
*Estimated differences between two groups
Second, unfortunately, the serum creatinine (SCr) concentration used for the diagnosis of AKI in our study had not been corrected according to fluid balance because of the inconsistent data recorded. Adjustment of the SCr concentration was proposed according to the assumption that the SCr concentration may be diluted by positive fluid balance [3]. However, Shen et al. have suggested that a large proportion of the infused fluid eventually leaks into the third space instead of contributing to blood volume [4]. Therefore, the use of adjusted SCr might have overestimated the AKI incidence [4]. Further studies are needed to clarify this issue.
Finally, the C-index observed following the addition of both L-FABP and NT-proBNP showed the improvement beyond that of the baseline model alone (Table 2). On performing the calibration using the Hosmer–Lemeshow test, the model involving the addition of both L-FABP and NT-proBNP to the baseline model showed a good fit, whereas the model involving the addition of a single biomarker or the baseline model alone showed a poor fit.

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Literatur
1.
Zurück zum Zitat Guo RJ, Xue FS, Shao LJ. Prediction of acute kidney injury in intensive care unit patients. Crit Care. 2018;22:304.CrossRef Guo RJ, Xue FS, Shao LJ. Prediction of acute kidney injury in intensive care unit patients. Crit Care. 2018;22:304.CrossRef
2.
Zurück zum Zitat Naruse H, Ishii J, Takahashi H, Kitagawa F, Nishimura H, Kawai H, et al. Predicting acute kidney injury using urinary liver-type fatty-acid binding protein and serum N-terminal pro-B-type natriuretic peptide levels in patients treated at medical cardiac intensive care units. Crit Care. 2018;22:197.CrossRef Naruse H, Ishii J, Takahashi H, Kitagawa F, Nishimura H, Kawai H, et al. Predicting acute kidney injury using urinary liver-type fatty-acid binding protein and serum N-terminal pro-B-type natriuretic peptide levels in patients treated at medical cardiac intensive care units. Crit Care. 2018;22:197.CrossRef
3.
Zurück zum Zitat Macedo E, Bouchard J, Soroko SH, Chertow GM, Himmelfarb J, Ikizler TA, et al. Program to Improve Care in Acute Renal Disease Study. Fluid accumulation, recognition and staging of acute kidney injury in critically-ill patients. Crit Care. 2010;14:R82.CrossRef Macedo E, Bouchard J, Soroko SH, Chertow GM, Himmelfarb J, Ikizler TA, et al. Program to Improve Care in Acute Renal Disease Study. Fluid accumulation, recognition and staging of acute kidney injury in critically-ill patients. Crit Care. 2010;14:R82.CrossRef
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Zurück zum Zitat Shen Y, Zhang W. Assessing association between fluid balance and acute kidney injury after cardiac surgery. Reply J Crit Care. 2018;45:249–50.CrossRef Shen Y, Zhang W. Assessing association between fluid balance and acute kidney injury after cardiac surgery. Reply J Crit Care. 2018;45:249–50.CrossRef
Metadaten
Titel
Authors’ response to letter “Prediction of acute kidney injury in intensive care unit patients”
verfasst von
Hiroyuki Naruse
Hiroshi Takahashi
Junnichi Ishii
Publikationsdatum
01.12.2019
Verlag
BioMed Central
Erschienen in
Critical Care / Ausgabe 1/2019
Elektronische ISSN: 1364-8535
DOI
https://doi.org/10.1186/s13054-019-2340-x

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