ArticleAnnals of intensive care2020
Urine NGAL as a biomarker for septic AKI: a critical appraisal of clinical utility-data from the observational FINNAKI study.
Article in Annals of intensive care, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 2 of them syntheses that pooled it.
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Who cites it
33 citing papers in PubMed, 2 syntheses or guidelines pooled it, 50 citations in OpenAlex.
- Kidney Damage and Stress Biomarkers for Early Identification of Drug-Induced Kidney Injury: A Systematic Review.Drug safety · 2022Pooled it
- Neutrophil gelatinase-associated lipocalin as predictor of acute kidney injury requiring renal replacement therapy: A systematic review and meta-analysis.Frontiers in medicine · 2022Pooled it
- Optimised murine model of influenza-induced respiratory sepsis for studying acute kidney injury.Laboratory animal research · 2026Article
- Biomarker-driven risk stratification and early intervention in acute kidney injury: a comprehensive review from early warning to clinical response.Frontiers in medicine · 2026Review
- S100A8/A9 in Kidney Diseases: Mechanisms, Spatiotemporal Regulation, Biomarker Potential, and Therapeutic Implications.Journal of inflammation research · 2026Review
- Authors reply in response to a letter on "impact of aminoglycosides on survival rate and renal outcomes in patients with urosepsis: a multicenter retrospective study".Annals of intensive care · 2025Article
- Blood Biomarkers to Identify Renal Angiomyolipomas in People With Tuberous Sclerosis Complex.Neurology. Genetics · 2025Article
- Early Urine Output in the Emergency Room as a Prognostic Indicator for Critically Ill Patients Undergoing Continuous Renal Replacement.Life (Basel, Switzerland) · 2025Article
- Plasma Neutrophil Gelatinase-Associated Lipocalin as a Biomarker of Kidney Injury and Potential Predictor of Hypoxic Brain Injury in Severe Plasmodium falciparum Malaria: Insights From India.Seminars in nephrology · 2025Review
- Review
- Urinary biomarkers for diagnosing acute kidney injury in sepsis in the emergency department.Heliyon · 2025Article
- Targeted Modulation of Mitochondrial Oxidative Stress Ameliorates 5-Fluorouracil-Induced Renal Injury in BALB/c Mice.Oxidative medicine and cellular longevity · 2025Article
- Kidney point-of-care ultrasonography in the PICU: it is about time!Pediatric nephrology (Berlin, Germany) · 2024Article
- Renal resistive index by point of care ultrasound to predict sepsis associated acute kidney injury in critically ill children.Pediatric nephrology (Berlin, Germany) · 2024Observational
- Can Novel Biomarkers Effectively Predict Acute Kidney Injury in Liver or Kidney Transplant Recipients?International journal of molecular sciences · 2024Review
- Biomarkers in acute kidney injury.Annals of intensive care · 2024Review
- Plasma Biomarkers for Hypertension-Mediated Organ Damage Detection: A Narrative Review.Biomedicines · 2024Review
- A novel multiplex biomarker panel for profiling human acute and chronic kidney disease.Scientific reports · 2023Article
- Circulating extracellular vesicles in human cardiorenal syndrome promote renal injury in a kidney-on-chip system.JCI insight · 2023Article
- Subclinical and clinical acute kidney injury share similar urinary peptide signatures and prognosis.Intensive care medicine · 2023Observational
Corrections and comments
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
Abstract
backgroundNeutrophil 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.
resultsIncidences 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.
conclusionsThe 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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