Neutrophil Gelatinase-associated Lipocalin as a Predictor of Acute Kidney Injury in Patients during Treatment with Colistimethate Sodium

Background: The emergence of multidrug-resistant, Gram-negative bacteria has resulted in reconsideration of colistimethate sodium (CMS) as a last resort for treatment of such infections. However, acute kidney injury (AKI) may represent a major limiting adverse effect of use of CMS. Early AKI detection in CMS-treated patients can help prevent progression to acute failure and reduce the need of renal replacement therapy. We hypothesized that plasma neutrophil gelatinase-associated lipocalin (NGAL) may be an early biomarker of AKI in CMS-treated patients. Materials and Methods: This prospective cohort study included patients aged >= 20 years who received intravenous CMS between March 2014 and November 2015. AKI was defined according to Kidney Disease: Improving Global Outcomes criteria. The primary endpoint was the difference between the average time to AKI onset based on serum creatinine and empirically derived plasma NGAL levels. Results: Among 109 CMS-treated patients, 23 patients (mean age, 61.3 +/- 16.1 years; men, 65.2%) were evaluated. Thirteen (56.5%) patients fulfilled the AKI criteria. The mean time to AKI onset based on serum creatinine after CMS initiation was 78.15 +/- 30.49 hours. AKI was detected approximately 22 hours earlier using plasma NGAL than when using serum creatinine as an indicator of AKI (P = 0.035). The baseline plasma NGAL level was 264.0 +/- 167.3 ng/mL and 192.7 +/- 65.3 ng/mL in patients with and without AKI, respectively (P = 0.218). The area under the curve for plasma NGAL level at 56 hours was 0.796 (95% confidence interval, 0.609-0.983; P = 0.017), with a sensitivity and specificity of 69.2% and 90.0%, respectively (cutoff value, 285 ng/mL). Conclusion: NGAL level was found to be a strong predictor of AKI. This study provides additional evidence of the utility of NGAL for AKI in patients with treated CMS. Plasma NGAL represent sensitive and specific predictive early biomarkers for AKI in patient treated CMS.