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. 2018 Apr 1;9(2):182-191.
doi: 10.14336/AD.2017.0307. eCollection 2018 Apr.

Urinary Neutrophil Gelatinase-Associated Lipocalin Is Excellent Predictor of Acute Kidney Injury in Septic Elderly Patients

Affiliations

Urinary Neutrophil Gelatinase-Associated Lipocalin Is Excellent Predictor of Acute Kidney Injury in Septic Elderly Patients

Erica Pires da Rocha et al. Aging Dis. .

Abstract

Elderly is the main age group affected by acute kidney injury (AKI). There are no studies that investigated the predictive properties of urinary (u) NGAL as an AKI marker in septic elderly population. This study aimed to evaluate the efficacy of uNGAL as predictor of AKI diagnosis and prognosis in elderly septic patients admitted to ICUs. We prospectively studied elderly patients with sepsis admitted to ICUs from October 2014 to November 2015. Assessment of renal function was performed daily by serum creatinine and urine output. The level of uNGAL was performed within the first 48 hours of the diagnosis of sepsis (NGAL1) and between 48 and 96 hours (NGAL2). The results were presented using descriptive statistics and area under the receiver operating characteristic curve (AUC-ROC) and p value was 5%. Seventy-five patients were included, 47 (62.7%) developed AKI. At logistic regression, chronic kidney disease and low mean blood pressure at admission were identified as factors associated with AKI (OR=0.05, CI=0.01-0.60, p=0.045 and OR=0.81, CI=0,13-0.47; p=0.047). The uNGAL was excellent predictor of AKI diagnosis (AUC-ROC >0.95, and sensitivity and specificity>0.89), anticipating the AKI diagnosis in 2.1±0.3 days. Factors associated with mortality in the logistic regression were presence of AKI (OR=2.14, CI=1.42-3.98, p=0.04), chronic obstructive pulmonary disease (OR = 9.37, CI =1.79-49.1, p=0.008) and vasoactive drugs (OR=2.06, CI=0.98-1.02, p=0.04). The accuracy of NGALu 1 and 2 as predictors of death was intermediate, with AUC-ROC of 0.61 and 0.62; sensitivity between 0.65 and 0.77 and specificity lower than 0.6. The uNGAL was excellent predictor of AKI in septic elderly patients in ICUs and can anticipate the diagnosis of AKI in 2.1 days.

Keywords: NGAL; acute kidney injury; biomarker; elderly.

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Figures

Figure 1.
Figure 1.
Screening and enrollment.
Figure 2.
Figure 2.
ROC analysis of uNGAL in septic elderly patients with AKI vs non-AKI. A) ROC analysis of uNGAL measured on first 48 hours of admission to ICU in septic elderly patients with AKI vs non-AKI. B) ROC analysis of uNGAL measured between 48-96 hours of admission to ICU in septic elderly patients with AKI vs non-AKI. C) ROC analysis of uNGAL/uCr measured on first 48 hours of admission to ICU in septic elderly patients with AKI vs non-AKI. D) ROC analysis of uNGAL/uCr measured between 48-96 hours of admission to ICU in septic elderly patients with AKI vs non-AKI.
Figure 3.
Figure 3.
ROC analysis of uNGAL in survivors versus non-survivor’s septic elderly patients. A) ROC analysis of uNGAL measured on first 48 hours of admission to ICU in survivors versus non-survivor’s septic elderly patients. B) ROC analysis of uNGAL measured between 48-96 hours of admission to ICU in survivors versus non-survivor’s septic elderly patients. C) ROC analysis of uNGAL/uCr measured on first 48 hours of admission to ICU in survivors versus non-survivor’s septic elderly patients. D) ROC analysis of uNGAL/uCr measured between 48-96 hours of admission to ICU in survivors versus non-survivor’s septic elderly patients

References

    1. Mayr VD, Dünser MW, Greil V, Jochberger S, Luckner G, Ulmer H, et al. (2006). Causes of death and determinants of outcome in critically ill patients. Crit Care, 10: R154. - PMC - PubMed
    1. Angus DC, Linde-Zwirble WT, Lidicker J, Clermont G, Carcillo J, Pinsky MR (2001). Epidemiology of severe sepsis in the United States: analysis of incidence, outcome, and associated costs of care. Crit Care Med, 9: 1303-10. - PubMed
    1. Silva E, Pedro M de A, Sogayar ACB, Mohovic T, Silva CL de O, Janiszewski M, et al. (2004). Brazilian Sepsis Epidemiological Study (BASES study). Crit Care, 8(4): R251-60. - PMC - PubMed
    1. Lentini P, de Cal M, Clementi A, D’Angelo A, Ronco C (2012). Sepsis and AKI in ICU Patients: The Role of Plasma Biomarkers. Crit Care Res Pract, 856401. - PMC - PubMed
    1. Zarjou A, Agarwal A (2011). Sepsis and acute kidney injury. J Am Soc Nephrol JASN, 22(6): 999-1006. - PubMed

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