Subclinical AKI: ready for primetime in clinical practice?
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There has been considerable progress over the last decade in the standardization of the acute kidney injury (AKI) definition with the publication of the RIFLE, AKIN, KDIGO and ERBP classification criteria. However, these classification criteria still rely on imperfect parameters such as serum creatinine and urinary output. The use of timed urine collections, kinetic eGFR (estimated glomerular filtration rate), real time measurement of GFR and direct measures of tubular damage can theoretically aid in a more timely diagnosis of AKI and improve patients’ outcome. There has been an extensive search for new biomarkers indicative of structural tubular damage but it remains controversial whether these new markers should be included in the current classification criteria. The use of these markers has also led to the creation of a new concept called subclinical AKI, a condition where there is an increase in biomarkers but without clinical AKI, defined as an increase in serum creatinine and/or a decrease in urinary output. In this review we provide a framework on how to critical appraise biomarker research and on how to position the concept of subclinical AKI. The evaluation of biomarker performance and the usefulness of the concept ‘subclinical AKI’ requires careful consideration of the context these biomarkers are used in (clinical versus research setting) and the goal we want to achieve (risk assessment versus prediction versus early diagnosis versus prognostication). It remains currently unknown whether an increase in biomarkers levels without functional repercussion is clinically relevant and whether including biomarkers in classification criteria will improve patients’ outcome.
KeywordsAKI Subclinical AKI Biomarkers Renal functional reserve Real time GFR Serum creatinine kinetics
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Conflict of interest
No conflicts of interests to declare.
This article does not contain any studies with human participants performed by any of the authors.
For this type of study formal consent is not required.
- 1.Bellomo R, Ronco C, Kellum JA, Mehta RL, Palevsky P (2004) Acute renal failure—definition, outcome measures, animal models, fluid therapy and information technology needs: the Second International Consensus Conference of the Acute Dialysis Quality Initiative (ADQI) Group. Crit Care 8(4):R204–R212CrossRefGoogle Scholar
- 4.Fliser D, Laville M, Covic A, Fouque D, Vanholder R, Juillard L et al (2012) A European Renal Best Practice (ERBP) position statement on the Kidney Disease Improving Global Outcomes (KDIGO) clinical practice guidelines on acute kidney injury: part 1: definitions, conservative management and contrast-induced nephropathy. Nephrol Dial Transplant 27(12):4263–4272CrossRefGoogle Scholar
- 16.Di Somma S, Magrini L, De Berardinis B, Marino R, Ferri E, Moscatelli P et al (2013) Additive value of blood neutrophil gelatinase-associated lipocalin to clinical judgement in acute kidney injury diagnosis and mortality prediction in patients hospitalized from the emergency department. Crit Care (London England) 17(1):R29CrossRefGoogle Scholar
- 21.McWilliam SJ, Antoine DJ, Jorgensen AL, Smyth RL, Pirmohamed M (2018) Urinary biomarkers of aminoglycoside-induced nephrotoxicity in cystic fibrosis: kidney injury molecule-1 and neutrophil gelatinase-associated lipocalin. Science 8(1):5094Google Scholar
- 24.Bachorzewska-Gajewska H, Malyszko J, Sitniewska E, Malyszko JS, Dobrzycki S (2007) Neutrophil gelatinase-associated lipocalin (NGAL) correlations with cystatin C, serum creatinine and eGFR in patients with normal serum creatinine undergoing coronary angiography. Nephrol Dial Transplant 22(1):295–296CrossRefGoogle Scholar
- 26.Bellomo R, Bagshaw S, Langenberg C, Ronco C (2007) Pre-renal azotemia: a flawed paradigm in critically ill septic patients? Contrib Nephrol 156:1–9Google Scholar
- 43.Vanmassenhove J, Glorieux G, Lameire N, Hoste E, Dhondt A, Vanholder R et al (2015) Influence of severity of illness on neutrophil gelatinase-associated lipocalin performance as a marker of acute kidney injury: a prospective cohort study of patients with sepsis. BMC Nephrol 16:18CrossRefGoogle Scholar
- 54.Bell M, Larsson A, Venge P, Bellomo R, Martensson J (2015) Assessment of cell-cycle arrest biomarkers to predict early and delayed acute kidney injury. Dis Mark 2015:158658Google Scholar
- 57.Meersch M, Schmidt C, Hoffmeier A, Van Aken H, Wempe C, Gerss J et al (2017) Prevention of cardiac surgery-associated AKI by implementing the KDIGO guidelines in high risk patients identified by biomarkers: the PrevAKI randomized controlled trial. Intensive Care Med 43(11):1551–1561CrossRefGoogle Scholar
- 66.O’Sullivan ED, Doyle A (2017) The clinical utility of kinetic glomerular filtration rate. Clin Kidney J 10(2):202–208Google Scholar