Urine NGAL as a biomarker for septic AKI: a critical appraisal of clinical utility—data from the observational FINNAKI study

Annals of Intensive Care, May 2020

Neutrophil gelatinase-associated lipocalin (NGAL) is released from kidney tubular cells under stress as well as from neutrophils during inflammation. It has been suggested as a biomarker for acute kidney injury (AKI) in critically ill patients with sepsis. To evaluate clinical usefulness of urine NGAL (uNGAL), we post-hoc applied recently introduced statistical methods to a sub-cohort of septic patients from the prospective observational Finnish Acute Kidney Injury (FINNAKI) study. Accordingly, in 484 adult intensive care unit patients with sepsis by Sepsis-3 criteria, we calculated areas under the receiver operating characteristic curves (AUCs) for the first available uNGAL to assess discrimination for four outcomes: AKI defined by Kidney Disease: Improving Global Outcomes (KDIGO) criteria, severe (KDIGO 2–3) AKI, and renal replacement therapy (RRT) during the first 3 days of intensive care, and mortality at day 90. We constructed clinical prediction models for the outcomes and used risk assessment plots and decision curve analysis with predefined threshold probabilities to test whether adding uNGAL to the models improved reclassification or decision making in clinical practice. Incidences of AKI, severe AKI, RRT, and mortality were 44.8% (217/484), 27.7% (134/484), 9.5% (46/484), and 28.1% (136/484). Corresponding AUCs for uNGAL were 0.690, 0.728, 0.769, and 0.600. Adding uNGAL to the clinical prediction models improved discrimination of AKI, severe AKI, and RRT. However, the net benefits for the new models were only 1.4% (severe AKI and RRT) to 2.5% (AKI), and the number of patients needed to be tested per one extra true-positive varied from 40 (AKI) to 74 (RRT) at the predefined threshold probabilities. The results of the recommended new statistical methods do not support the use of uNGAL in critically ill septic patients to predict AKI or clinical outcomes.

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Urine NGAL as a biomarker for septic AKI: a critical appraisal of clinical utility—data from the observational FINNAKI study

(2020) 10:51 Törnblom et al. Ann. Intensive Care https://doi.org/10.1186/s13613-020-00667-7 Open Access RESEARCH Urine NGAL as a biomarker for septic AKI: a critical appraisal of clinical utility—data from the observational FINNAKI study Sanna Törnblom1*, Sara Nisula1, Liisa Petäjä2, Suvi T. Vaara1, Mikko Haapio3, Eero Pesonen2, Ville Pettilä1 and the FINNAKI study group Abstract Background: Neutrophil gelatinase-associated lipocalin (NGAL) is released from kidney tubular cells under stress as well as from neutrophils during inflammation. It has been suggested as a biomarker for acute kidney injury (AKI) in critically ill patients with sepsis. To evaluate clinical usefulness of urine NGAL (uNGAL), we post-hoc applied recently introduced statistical methods to a sub-cohort of septic patients from the prospective observational Finnish Acute Kidney Injury (FINNAKI) study. Accordingly, in 484 adult intensive care unit patients with sepsis by Sepsis-3 criteria, we calculated areas under the receiver operating characteristic curves (AUCs) for the first available uNGAL to assess discrimination for four outcomes: AKI defined by Kidney Disease: Improving Global Outcomes (KDIGO) criteria, severe (KDIGO 2–3) AKI, and renal replacement therapy (RRT) during the first 3 days of intensive care, and mortality at day 90. We constructed clinical prediction models for the outcomes and used risk assessment plots and decision curve analysis with predefined threshold probabilities to test whether adding uNGAL to the models improved reclassification or decision making in clinical practice. Results: Incidences of AKI, severe AKI, RRT, and mortality were 44.8% (217/484), 27.7% (134/484), 9.5% (46/484), and 28.1% (136/484). Corresponding AUCs for uNGAL were 0.690, 0.728, 0.769, and 0.600. Adding uNGAL to the clinical prediction models improved discrimination of AKI, severe AKI, and RRT. However, the net benefits for the new models were only 1.4% (severe AKI and RRT) to 2.5% (AKI), and the number of patients needed to be tested per one extra true-positive varied from 40 (AKI) to 74 (RRT) at the predefined threshold probabilities. Conclusions: The results of the recommended new statistical methods do not support the use of uNGAL in critically ill septic patients to predict AKI or clinical outcomes. Keywords: Neutrophil gelatinase-associated lipocalin, Acute kidney injury, Sepsis, Critical illness, Intensive care Background Neutrophil gelatinase-associated lipocalin (NGAL) has been studied extensively as a biomarker for detection and evolution of acute kidney injury (AKI) as well as outcome [1, 2]. NGAL is a protein first found in neutrophil *Correspondence: 1 Division of Intensive Care Medicine, Department of Anaesthesiology, Intensive Care and Pain Medicine, University of Helsinki and Helsinki University Hospital, PO Box 340, 00029 HUS Helsinki, Finland Full list of author information is available at the end of the article granules [3], but synthesized in numerous human tissues in addition to kidney epithelium—e.g., respiratory tract, stomach, and colon. All in vivo functions of NGAL are not plausibly unraveled. It increases rapidly in serum and urine not only in conjunction with renal tubular injury, but also in bacterial infections, non-infectious systemic inflammatory response syndrome, and chronic and systemic diseases without bacterial infection [4]. Consequently, inflammation is considered a confounding factor hindering the routine use of NGAL as a biomarker of AKI in intensive care patients with sepsis [5–7]. © The Author(s) 2020. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativeco mmons.org/licenses/by/4.0/. Törnblom et al. Ann. Intensive Care (2020) 10:51 In a recent meta-analysis, urine NGAL (uNGAL) predicted septic AKI with an area under the receiver operating characteristic curve (AUC) of 0.90 [8], but the individual studies were rather small, the sample sizes varying between 45 and 168. Besides, generalizability of the meta-analysis may be questioned since 65% of the sepsis patients were from Asia. Furthermore, currently used statistical methods have several shortcomings: AUCs are not very suitable for evaluating the incremental value of biomarkers [9] or assessing clinical usefulness [10]. Newer reclassification methods may even make useless biomarkers appear applicable [11]. Although there is obvious need for better tools than urine output and serum creatinine for early detection and classification of AKI, the existing data on any kidney injury biomarker for AKI diagnosis, staging, prognosis, or treatment are inadequate [12]. We have previously tested the ability of uNGAL to predict AKI, renal replacement therapy (RRT), and 90-day mortality in a large non-selected cohort of 1042 adult intensive care patients [13]. Patients with sepsis comprised 46% of the study population. In comparison to the previous meta-analysis [8], this is by far the largest cohort of septic patients with uNGAL measurements. Since we did not report the septic patients separately, they could not be included in the meta-analysis [8]. We now extended our analyses to evaluate the usefulness of uNGAL in predicting AKI, RRT, and 90-day mortality in septic patients using more sophisticated statistical methods: risk assessment plot (RAP) [14] and decision curve analysis (DCA) [10]. Accordingly, we tested the hypothesis that uNGAL improves the performance of clinical risk models for AKI, RRT, and 90-day mortality in a homogeneous and clinically important group of critically ill septic patients using these new statistical methods. We are not aware of a similar detailed analysis of uNGAL or its clinical usefulness in the literature. Methods Patients We analyzed the urine of septic patients of this FINNAKI NGAL—substudy [13]. The Ethics Committee of the Department of Surgery in Helsinki University Hospital gave a nationwide approval for the FINNAKI study [15] with a deferred consent policy, confirmed by a written consent from each patient or his/her proxy. Data The patients of the original study [13] were prospectively screened for sepsis defined by the American College of Chest Physicians/Society of Critical Care Medicine (ACCP/SCCM) criteria [16]. To increas (...truncated)


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Sanna Törnblom, Sara Nisula, Liisa Petäjä, Suvi T. Vaara, Mikko Haapio, Eero Pesonen, Ville Pettilä. Urine NGAL as a biomarker for septic AKI: a critical appraisal of clinical utility—data from the observational FINNAKI study, Annals of Intensive Care, 2020, DOI: 10.1186/s13613-020-00667-7