ArticleBlood purification2019
Plasma Biomarkers in Predicting Renal Recovery from Acute Kidney Injury in Critically Ill Patients.
Article in Blood purification, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 15 citations in OpenAlex.
- Editorial: Novel diagnostic and prognostic methods in acute kidney injury among patients in intensive care unit.Frontiers in nephrology · 2025Article
- Acute Kidney Injury Prognosis Prediction Using Machine Learning Methods: A Systematic Review.Kidney medicine · 2025Review
- Association between serum osmolality and deteriorating renal function in patients with acute myocardial infarction: analysis of the MIMIC- IV database.BMC cardiovascular disorders · 2024Article
- Predictive value of perioperative NT-proBNP levels for acute kidney injury in patients with compromised renal function undergoing cardiac surgery: a case control study.BMC anesthesiology · 2024Article
- Assessment of the renal angina index in patients hospitalized in a cardiac intensive care unit.Scientific reports · 2024Article
- Prognostic Value of Natriuretic Peptide Levels for Adverse Renal Outcomes in Patients With Moderate to Severe Acute Kidney Injury With or Without Heart Failure.Journal of the American Heart Association · 2023Review
- Application of Machine Learning to Predict Acute Kidney Disease in Patients With Sepsis Associated Acute Kidney Injury.Frontiers in medicine · 2021Article
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Authors and funding
4 authors at 1 institution in 2 countries.
Funding
Abstract
backgroundNumerous studies have suggested a possible role for acute kidney injury (AKI) biomarkers in predicting renal recovery both before and after renal replacement therapy (RRT). However, definitions for recovery and whether to include patients dying but free of RRT may influence results.
objectivesTo validate plasma neutrophil gelatinase-associated lipocalin (pNGAL) as a useful biomarker for predicting or improving the ability of clinical predictors alone to predict recovery following AKI, including in our model plasma B-type natriuretic peptide (pBNP) to account for cardiovascular events.
methodsWe analyzed 69 patients enrolled in the Acute Renal Failure Trial Network study. pNGAL and pBNP were measured on days 2, 7, and 14. We analyzed their predictive ability for subsequent recovery, defined as alive and independent from dialysis in 60 days. In sensitivity analyses, we explored changes in results with alternative definitions of recovery.
resultsTwenty-nine patients (42%) recovered from AKI. Neither pNGAL nor pBNP, alone or in combination, was accurate predictors of renal recovery-the best area under the receiver-operating characteristics curve (AUC) was for pNGAL using the largest relative change (AUC 0.59, 95% CI 0.45-0.74). The best clinical model achieved superior performance to biomarkers (AUC 0.69, 95% CI 0.56-0.81). The AUC was greatest (0.75, 95% CI 0.60-0.91) when pNGAL + pBNP on day 14 were added to the clinical model but this increase did not achieve statistical significance. However, integrated discrimination improvement analysis showed that the addition of pNGAL and pBNP on day 14 to the clinical model significantly improved the prediction of renal recovery (p = 0.008).
conclusionspNGAL and pBNP can improve the accuracy of clinical parameters in predicting AKI recovery and a full model using biomarkers together with age achieved adequate discrimination.
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