
==== Front
Ann Intensive Care
Ann Intensive Care
Annals of Intensive Care
2110-5820
Springer International Publishing Cham

39279017
1360
10.1186/s13613-024-01360-9
Review
Biomarkers in acute kidney injury
http://orcid.org/0000-0001-9500-9080
Ostermann Marlies marlies.ostermann@gstt.nhs.uk

1
Legrand Matthieu 2
Meersch Melanie 3
Srisawat Nattachai 4
Zarbock Alexander 23
Kellum John A. 5
1 https://ror.org/00j161312 grid.420545.2 Department of Critical Care, Guy’s & St Thomas’ NHS Foundation Hospital, London, SE1 7EH UK
2 https://ror.org/043mz5j54 grid.266102.1 0000 0001 2297 6811 Department of Anesthesia and Perioperative Care, Division of Critical Care Medicine, University of California San Francisco, San Francisco, USA
3 https://ror.org/01856cw59 grid.16149.3b 0000 0004 0551 4246 Department of Anesthesiology, Intensive Care and Pain Medicine, University Hospital Münster, Münster, Germany
4 https://ror.org/028wp3y58 grid.7922.e 0000 0001 0244 7875 Division of Nephrology, Department of Medicine, Faculty of Medicine, and Center of Excellence in Critical Care Nephrology, Chulalongkorn University, Bangkok, Thailand
5 https://ror.org/01an3r305 grid.21925.3d 0000 0004 1936 9000 Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA USA
15 9 2024
15 9 2024
2024
14 14514 6 2024
7 8 2024
© The Author(s) 2024
2024
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Acute kidney injury (AKI) is a multifactorial syndrome with a high risk of short- and long-term complications as well as increased health care costs. The traditional biomarkers of AKI, serum creatinine and urine output, have important limitations. The discovery of new functional and damage/stress biomarkers has enabled a more precise delineation of the aetiology, pathophysiology, site, mechanisms, and severity of injury. This has allowed earlier diagnosis, better prognostication, and the identification of AKI sub-phenotypes. In this review, we summarize the roles and challenges of these new biomarkers in clinical practice and research.

issue-copyright-statement© La Société de Réanimation de Langue Francaise = The French Society of Intensive Care (SRLF) 2024
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pmcIntroduction

Acute kidney injury (AKI) is a multifactorial syndrome characterised by a rapid (hours to days) deterioration of kidney function and a high risk of short- and long-term complications, effects on quality of life and increased health care costs [1–8]. Despite its frequent occurrence, there are no specific therapies and only limited diagnostic tools used in routine clinical care. Traditionally, AKI is diagnosed by a rise in serum creatinine (sCr) and/or fall in urine output, independent of underlying aetiology, pathophysiology and anatomical site of injury [9]. Both, sCr and urine output are markers of kidney function with important limitations. (Table 1) Further, in most forms of AKI, renal tubular epithelial cells are the primary locus of injury and a reduction in glomerular filtration is a late and insensitive development. In some cases, injury to renal epithelial cells may not even manifest in a functional change and AKI remains undetected (‘subclinical AKI’). Thus, reliance solely on changes in sCr and/or urine output ignores sub-clinical AKI, may delay the recognition and management of AKI and potentially contribute to unfavourable outcomes.Table 1 Limitations of serum creatinine and urine output for assessment of kidney function

Parameter	Limitations	
Serum creatinine	• Insensitive to kidney damage especially for health kidneys—nearly 50% of function must be lost before serum creatinine increases

• Slow to increase (as long as 24-48 h) following an insult

• Affected by exogenous creatine intake

• Dependent on muscle mass and metabolism and liver function

• May be affected by physiological and analytic variability

• Can increase without true change in renal function, for instance in the setting of drug-induced inhibition of tubular secretion (e.g. cimetidine, trimethoprim) or hemoconcentration (e.g. diuresis)

• May be altered during pregnancy

	
Urine output	• Transient oliguria may be physiological

• Can be manipulated with diuretics*

• Prone to measurement error even with a urinary catheter

	
*Importantly, intact tubular function is necessary for loop diuretics to increase urine output

AKI acute kidney injury

Importantly, the serum half-life of creatinine increases from about 4 h to as much as 24–72 h as glomerular filtration rate (GFR) decreases. Thus, the sCr concentration may take 24–36 h to rise after a kidney injury [10]. Further, in patients with sepsis, liver disease, fluid overload and/or muscle wasting, reductions in GFR may not be accurately reflected by sCr and there may be additional delays. A post hoc analysis of the ‘Fluid and Catheter Treatment Trial’ showed that AKI was revealed or classified differently in up to 18% of patients after sCr results were adjusted for net fluid balance and estimated total body water [11]. Affected patients had mortality rates similar to those with AKI that was apparent before adjustment. In addition to the risk of delayed diagnosis, AKI may also be erroneously over-diagnosed, for instance in patients taking drugs that increase creatine availability or compete with tubular secretion, ie, cimetidine or trimethoprim [12].

Lastly, urine production does not correlate with glomerular filtration and may persist until renal function almost ceases. Further, oliguria may be an appropriate physiological response during periods of hypovolaemia, prolonged fasting, after surgery and following stress, pain or trauma [13]. On the other hand, the use of diuretics can increase urine output in patients with AKI without affecting survival [14].

Adjunctive AKI biomarkers

Additional kidney biomarkers have been discovered and validated in different patient cohorts. They vary in the cells they originate from, their physiological function, their kinetics and distribution. (Table 2) There are 3 broad categories of urinary biomarkers. The first group includes biomarkers which have a low molecular weight and are freely filtered at the glomerulus, e.g. β2-microglobulin, lysozyme, α1-microglobulin, light chains and cystatin C. Under normal circumstances, these molecules are reabsorbed completely by proximal tubular epithelial cells so that they are only detectable in the urine following tubular epithelial cell dysfunction. A second group of biomarkers is upregulated in renal cells in response to kidney injury. These molecules include monomeric neutrophil gelatinase associated lipocalin (NGAL), Dickkopf-3 (DKK3) and kidney injury molecule-1 (KIM-1) which are expressed mainly in distal and proximal tubular epithelial cells [15]. Hepatocyte growth factor (HGF) is a biomarker that is upregulated in interstitial cells in response to kidney injury. A related group of biomarkers are constitutively expressed by tubular epithelial cells and then released into the urine in response to AKI. Examples of this group include the lysosomal enzyme N-acetyl-β-D-glucosaminidase (NAG), the cytosolic protein lactate dehydrogenase or the brush border protein gp130. Cell cycle arrest markers like insulin like growth factor binding protein 7 (IGFBP7) and tissue inhibitor of metalloproteinases 2 (TIMP-2) appear to also be constitutively produced and are released rapidly (i.e. within hours) in response to injurious stimuli causing tubular cell stress [16]. Prolonged and increased expression of TIMP-2 and IGFBP7 may be synonymous with cell damage [17]. C–C motif chemokine ligand 14 (CCL14) is a member of the chemokine family that is implicated in tissue injury and repair processes. It is primarily produced by macrophages and monocytes and is thought to play an important role in recruiting and activating monocytes and other leukocyte subtypes to sites of injury or infection in various organ systems, including the kidney [18, 19]. Lastly, biomarkers may be emitted by inflammatory cells residing or entering the kidneys during AKI. Examples include interleukin-18 (IL-18) which is released by macrophages and neutrophils passing through the kidney and IL-9 which is produced by CD4 + T cells and released into the urine in patients with acute interstitial nephritis [20].Table 2 Description and characteristics of selected AKI biomarkers

AKI biomarker	Biological role	Biological sample	Roles in clinical practice	Populations / settings studied	Limitations / confounders	Regulatory approval	
Functional biomarkers	
 Cystatin C	13 kDa Cysteine protease inhibitor produced by nucleated human cells; freely filtered	Plasma	Diagnosis of AKI and measurement of severity	ICU

Liver transplantation

Hospitalized patients

	Elevated in CKD

Confounded by age, sex, inflammatory state, diabetes, low albumin, glucocorticosteroids

	FDA approved and CE marked for GFR estimation in clinical practice	
 Proenkephalin A	Endogenous polypeptide hormone in adrenal medulla, immune system and renal tissue; freely filtered and measured in plasma	Plasma	Diagnosis and assessment of AKI severityI and renal recovery	Hospitalized patients	Elevated in CKD

may be less sensitive than creatinine or cystatin C

	CE marked for clinical use	
Stress biomarkers	
 Dickkopf-3 (DKK3)	38 kDa Renal tubular cell–derived glycoprotein; secreted into urine under tubular stress conditions	Urine	Risk assessment and prediction of AKI	Cardiac surgery	Elevated in CKD		
 Tissue inhibitor of metalloproteinases-2 (TIMP-2); Insulin-like growth factor binding protein 7 (IGFB7)	Proteins released by tubular epithelial cells (TIMP-2 distal, IGFBP7 proximal) that can induce cell cycle arrest	Urine	Prediction and diagnosis of AKI and assessment of severity	ICU		US FDA and EC marked for predicting stage 2 or 3 AKI in adults	
Damage biomarkers	
 Alanine aminopeptidase (AAP); γ-glutamyl transpeptidase (γ-GT); Alkaline phosphatase (ALP)	Enzymes located in several organs, including the brush border of proximal tubular cells	Urine	Diagnosis and severity of AKI	ICU	Elevated in UTI, cardiovascular disease, stroke		
 C–C motif chemokine ligand 14 (CCL 14)	Pro-inflammatory chemokine implicated in tissue injury and repair processes; primarily produced by macrophages and monocytes; has a role in activating monocytes, recruiting immune cells to sites of injury or infection and in regulating inflammation in various organ systems	Urine	Persistence of severe AKI	ICU			
 Chitinase 3-like protein 1	39 kDa Intracellular protein of glycoside hydrolase family; expressed by endothelial cells, macrophages & neutrophils and released into the urine and plasma	Urine

Plasma

	Diagnosis of AKI	ICU	Limited performance in real-world settings as a single biomarker		
 Hepatocyte growth factor (HGF)	Antifibrotic cytokine produced by mesenchymal cells; involved in tubular cell regeneration after AKI and measured in plasma	Plasma	Severity of AKI and renal recovery	Hospitalized	Limited performance		
 Hepcidin	2.78 kDa Peptide hormone predominantly produced in hepatocytes; freely filtered into urine and plasma	Urine

Plasma

	Diagnosis of AKI and assessment of severity	ICU	Decreased in anemia and increased in inflammatory state		
 Interleukin-18 (IL-18)	18 kDa Pro-inflammatory cytokine; released into urine following tubular cell damage	Urine	Prediction and diagnosis of AKI	Hospitalized patients

ED

	Elevated in inflammatory states		
 Interleukin-9 (IL‑9)	30-40 kDa Pleiotropic cytokine secreted by CD4 + helper cells	Urine	Differential diagnosis of AKI	Acute interstitial nephritis			
 Kidney Injury Molecule–1 (KIM-1)	Transmembrane glycoprotein produced by proximal tubular cell; released into urine after tubular cell damage	Urine	Prediction and diagnosis of AKI and assessment of severity	Hospitalized patients

ED

	May take 24 h to more to peak after injury	US FDA approval and EC marked for pre-clinical drug development	
 Liver-type fatty acid-binding protein (L-FABP)	14 kDa Intracellular lipid chaperone; freely filtered and reabsorbed in proximal tubule; excreted into urine after tubular cell damage and measured in the urine and plasma	Urine

Plasma

	Diagnosis of AKI	ICU

ED

	Associated with anemia in non-diabetic patients	Japan Ministry of Health, Labour, and Welfare approval for clinical use	
 N-acetyl-β-D-glucosaminidase (NAG)	 > 130 kDa Lysosomal enzyme; released into urine after tubular damage	Urine	Diagnosis of AKI	Hospitalized patients	Elevated in diabetes and albuminuria		
 Neutrophil gelatinase-associated lipocalin (NGAL)	At least 3 different types measured in the urine and plasma:

• i) Monomeric 25 kDa glycoprotein produced by neutrophils and epithelial tissues, including tubular cells

ii) Homodimeric 45 kDa protein produced by neutrophils

iii) Heterodimeric 135 kDa protein produced by tubular cells

	Urine

Plasma

	Diagnosis of AKI and measurement of severity	Hospitalized patients

ED

	Elevated in sepsis, UTI, CKD

Measurement of general inflammation

	US FDA approved for children; CE marked	
AKI acute kidney injury, CKD chronic kidney disease, ED emergency department, ICU intensive care unit, UTI urinary tract infection, TNFα tumor necrosis factor α, GFR glomerular filtration rate, FDA Food and Drug Administration, EC European Conformity, CE Conformité Européene

Another method of categorising renal biomarkers is to stratify them based on their characteristics. Thus, some biomarkers primarily reflect glomerular filtration (i.e. serum cystatin c, proenkephalin A), glomerular integrity (i.e. albuminuria and proteinuria), tubular stress (i.e. IGFBP7 and TIMP-2), tubular damage [i.e. NGAL, KIM-1, NAG, Liver fatty acid-binding protein (L-FABP)], intra-renal inflammation (i.e. IL-18, IL-9) or repair mechanisms (CCL14).

Role of AKI biomarkers in clinical practice

The discovery of these new functional and damage/stress biomarkers has enabled a more precise delineation of the aetiology, pathophysiology, site, mechanisms, and severity of injury, earlier diagnosis and better prognostication, and the identification of AKI sub-phenotypes [21–25]. (Table 2, Fig. 1) However, it is important to acknowledge that biomarkers have specific characteristics and kinetic profiles. Since no biomarker can fulfil all these tasks, they need to be matched with their respective purpose and be measured at appropriate time points.(i) Early diagnosis of AKI

Fig. 1 Different types of AKI biomarkers. AAP Alanine aminopeptidase, ALP Alkaline phosphatase, CCL14 C–C motif chemokine ligand 14, DKK3 Dickkopf-3, γ-GT γ-glutamyl transpeptidase, HGF Hepatocyte growth factor, IGFBP7 Insulin like growth factor binding protein 7, IL-9 Interleukin-9, IL-18 Interleukin-18, KIM-1 Kidney injury molecule-1, L-FABP Liver fatty acid-binding protein, NAG N-acetyl-β-D-glucosaminidase, NGAL Neutrophil gelatinase associated lipocalin, TIMP-2 Tissue inhibitor of metalloproteinases-2

Several biomarkers may indicate the early onset of AKI and enable the identification of patients with evidence of kidney injury without a change in sCr, ie. “sub-clinical AKI” [21, 22, 26–28]. A study in 178 children showed that those who had elevated urine NGAL (uNGAL) concentrations without a rise in sCr had an almost fourfold increased risk of all-stage AKI on day 3 compared to children without an uNGAL and sCr rise [29]. Two meta-analyses including 19 studies with 2,538 patients and 16 studies with 2,906 patients, respectively, found NGAL to be an useful early indicator of AKI, both overall and across a range of clinical settings [30, 31]. The Sapphire study showed that urinary [TIMP-2] × [IGFBP7] concentration was superior to all other biomarkers in critically ill patients for predicting the development of moderate / severe AKI in the following 12 h with an area under the receiver operating curve (AUC) of 0.80 [32]. The risk for major adverse kidney events (MAKE) including death, dialysis or persistent renal dysfunction within 30 days was significantly increased if urinary [TIMP-2] x [IGFBP7] > 0.3 (ng/ml)2/1,000 and doubled when values were > 2.0 (ng/ml)2/1,000. A follow-up analysis showed that combining [TIMP-2] x [IGFBP7] with serum creatinine significantly (p = 0.02) increased the AUC from 0.80 [95% confidence interval CI 0.76–0.84] to 0.85 (95% CI 0.81–0.89) [33]. A meta-analysis of 20 studies including 3625 patients concluded that urinary [TIMP-2] × [IGFBP7] was a reliable effective predictive test for all cause-AKI with an AUC of 0.81 [34].

The role of proenkephalin A as a filtration marker was confirmed in a meta-analysis of 11 observational studies with 3969 patients showing a pooled AUC of 0.77 (95% CI 0.73–0.81) [35]. However, it was acknowledged that the small sample sizes in the majority of the included studies could potentially lead to an overestimation of effects.(ii) Determining AKI aetiology

AKI is not a single disease but rather a multi-factorial syndrome characterized by a wide spectrum of pathophysiological processes. Some biomarkers have proven to be useful in identifying the main aetiology and/or excluding potential causes [33, 36, 37]. For instance, in patients with acute decompensated heart failure treated with diuretics, a rise in sCr is often observed, sometimes prompting clinicians to stop diuretics. However, there is evidence that further decongestion in this context is associated with reduced mortality, despite the apparent functional AKI [38]. In this context, observational studies have revealed that the sCr rise was often not associated with an increase in urinary NAG, KIM-1 or NGAL [36]. Thus, determining whether an increase in sCr represents kidney damage or simply reflects diuretic-induced free water removal is useful. Similarly, in patients with cirrhosis, differentiating between hepato-renal syndrome (HRS)-AKI and other types of AKI is challenging. A recent expert consensus meeting by the Acute Disease Quality Initiative (ADQI) and the International Club of Ascites (ICA) concluded that the combined use of functional (e.g., sCr, Cystatin C) and damage (e.g., albuminuria, uNGAL) biomarkers enabled more accurate differential diagnosis of the aetiology and mechanisms of AKI in patients with cirrhosis and potentially enabled the identification of AKI sub-phenotypes suitable for specific therapeutic interventions [39, 40]. For instance, in 162 patients with cirrhosis and AKI, the response rate to terlipressin was 70% in patients with uNGAL < 220 μg/g of creatinine compared to only 33% in those with uNGAL > 220 μg/g of creatinine [41]. Subanalyses of the Sapphire study showed the kinetics of cell cycle arrest biomarkers after exposure to nephrotoxic insults and allowed the identification of patients with nephrotoxin induced AKI [37, 42].

Urinary IL‑9 has emerged as a biomarker suggestive of the diagnosis of acute interstitial nephritis (AIN) versus acute tubular injury, glomerular diseases, and diabetic kidney disease [20, 43]. Moreover, among patients with AIN, those with high urinary IL-9 levels benefited most from therapy with corticosteroids.(iii) Prediction of persistent AKI

The distinction between transient (< 48 h) and persistent (> 48 h) AKI is clinically important as a persistent AKI is associated with worse outcomes [44, 45]. Further, the duration of AKI impacts clinical management. For instance, the use of renal replacement therapy (RRT) is typically reserved for patients with persistent AKI. In 331 critically ill patients with AKI stage 2 or 3, the urinary biomarker CCL14 was found to identify those with a high risk of delayed recovery [19]. A meta-analysis of 6 studies including 952 patients with AKI concluded that urinary CCL14 was an effective marker for predicting persistent AKI with a pooled diagnostic accuracy of 0.84 [46]. This offers opportunities to improve patient outcomes by enabling individualised and targeted interventions appropriately [47].

Similarly, a study evaluating the role of proenkephalin A in sepsis / septic shock showed that the proenkephalin levels within 24 h of ICU admission were significantly higher in those patients who subsequently developed MAKE or persistent or worsening AKI [48]. Finally, in 733 patients undergoing cardiac surgery, preoperative ratio of urinary DKK3 to creatinine concentrations greater than 471 pg/mg was associated with a significantly higher risk of persistent kidney dysfunction (OR 6.67; 95% CI 1.67–26.61, p = 0.0072) and dialysis dependency (OR 13.57; 95% CI 1.50–122.77, p = 0.020) after 90 days compared with a ratio of 471 pg/mg or less [49].(iv) Prediction of RRT

Receipt of RRT is a common endpoint of biomarker analysis. Several biomarkers, including NGAL, IL-18, cystatin C, cell cycle arrest markers and CCL14 associate with RRT initiation. For instance, analysis of data from the Protocolized Care for Early Septic Shock (ProCESS) trial showed that patients who still had an urinary [TIMP-2] x [IGFBP7] concentration > 0.3 (ng/ml)2/1,000 after receiving fluid resuscitation were at higher risk for a composite endpoint of progression to AKI stage 2/3, receipt of RRT or mortality [50]. A previous systematic review and meta-analysis including 63 studies comprising 15,928 critically ill patients published until September 2017 concluded that several biomarkers showed reasonable prediction of RRT use for critically ill patients with AKI but the strength of evidence precluded their routine use to guide decision-making on when to initiate RRT [51]. Studies using CCL14 were not included.

It is important to point out that timing of RRT remains heterogenous in clinical practice and advice regarding indications and timing has changed over time [52–54]. Further, most studies evaluated biomarker performance by their ability to predict “receipt of RRT” rather than “meeting specific indications for RRT”, independent of whether RRT was initiated or not.

Finally, there may be a role for biomarkers in combination with other tests. For instance, an observational study in 208 critically ill patients showed that the combination of the furosemide stress test with urinary CCL14 results had better predictive ability than the CCL14 result in isolation [55]. The combination of a negative furosemide stress test and high urinary CCL14 levels had a predictive value for the development of an indication for RRT with an AUC of 0.87 (95% CI 0.82–0.92).(v) Prediction of long-term outcomes after AKI

Patients surviving an episode of AKI are at high risk of chronic kidney disease (CKD), cardiovascular morbidity and reduced long-term survival [3, 56, 57]. Serum creatinine has a limited role in indicating kidney health in the acute setting, in particular in patients with muscle wasting and persistent morbidities.

In a prospective study of 164 critically ill patients with AKI, urinary CCL14, [TIMP-2] x [IGFBP7] and NGAL, sampled at the time of AKI onset, were studied to assess their predictive ability for renal non-recovery within 7 days [58]. While NGAL was not predictive, CCL14 (assayed with an ELISA rather than the clinical test) had fair prediction ability (AUC 0.71 [95% CI 0.63–0.77]) and [TIMP-2] x [IGFBP7] had the best predictive ability for renal non-recovery (AUC 0.78 [95% CI 0.71–0.84]). A secondary analysis of the Sapphire study showed a higher risk of death and RRT over 9 months of follow-up in critically ill patients with AKI and [TIMP-2] x [IGFBP7] concentrations > 0.3 (ng/ml)2/1000 at the time of study enrolment, compared to those with levels ≤ 0.3 (HR 1.44 [95% CI 1.00—2.06]) [59].

Similarly, an elevated Proenkephalin A level at ICU admission in patients not meeting the sCr and urine output criteria for AKI was associated with an increased risk of death close to patients with AKI [60]. A secondary analysis of a multicentre, prospective cohort study of critically ill patients explored the association between renal biomarkers at time of ICU discharge and 1-year mortality and showed that elevated plasma cystatin C, plasma NGAL, uNGAL, and Proenkephalin A levels at ICU discharge were associated with a higher risk of 1-year all-cause mortality, including in patients with low sCr results at discharge [61]. Coca et al. studied the association between 5 urinary kidney injury biomarkers including NGAL, IL-18, KIM-1, Liver-type Fatty Acid Binding Protein (L-FABP), and albumin and all-cause mortality in a multicenter, prospective 3 years follow-up study in six clinical centers in the United States and Canada including 1199 adults who underwent cardiac surgery [62]. The highest tertile of biomarkers was associated with a 2 to 3.2 fold increased risk of mortality when compared with the lowest tertile. Together, these findings suggest that several biomarkers have potential to identify high risk patients, though they have not yet been studied to guide follow-up care.(vi) Identification of AKI sub-phenotypes

It is now clear that the syndrome (i.e., phenotype) of AKI is comprised of numerous sub-phenotypes, which can be identified and discriminated through shared features such as etiology/cause, risk factors, diagnostic features and prognosis [63–65]. Importantly, identified sub-phenotypes may behave differently in response to selected interventions. Existing and emerging biomarkers are likely to have a prominent role in discriminating sub-phenotypes of AKI directly, if they are specific for a particular sub-phenotype, or indirectly, if the absence of a detectable biomarker excludes that sub-phenotype [43, 66].

Progress in precision medicine has been furthered through advances in AKI sub-phenotyping, facilitated by novel biomarkers of AKI combined with leveraging electronic health records and advanced analytical methods. For instance, in 2 cohorts of septic patients, latent class analysis (LCA) identified 2 distinct AKI sub-phenotypes defined by different levels of biomarkers [66]. One type had a greater risk of renal non-recovery and 28-day mortality compared to the other. Using data from the VASST trial (vasopressin versus norepinephrine infusion in patients with septic shock), the authors observed that these sub-phenotypes had heterogeneity of treatment effect for the early addition of vasopressin.

Expanding the diagnostic criteria of AKI by integrating biomarkers of kidney stress/damage will not only embrace the concept of sub-clinical AKI but can also enable further differentiation of sub-phenotypes of AKI [67].

Biomarker-guided management

Several studies have shown benefit associated with the use of functional and damage/stress biomarkers, in particular after surgery and in the context of nephrotoxin exposure [22]. The ‘Prevention of cardiac surgery associated AKI by implementing the KDIGO guidelines in high-risk patients identified by biomarkers’ (PrevAKI) trial was the first which used biomarkers to identify high risk patients [26]. In this single-center randomized controlled trial, patients were analyzed for risk of AKI by measuring urinary [TIMP-2] x [IGFBP7] 4 h after cardiopulmonary bypass surgery. Patients with an urinary [TIMP-2] x [IGFBP7] concentration ≥ 0.3 (ng/ml)2/1000 were randomized to receive a care bundle which was based on the recommendations by the Kidney Diseases Improving Global Outcomes (KDIGO) expert panel with focus on haemodynamic and fluid optimisation and avoidance of nephrotoxic exposures. The proportion of patients with any stage AKI was significantly lower in the intervention group compared to the control arm [55.1 versus 71.7%; adjusted risk ratio (ARR) 16.6% (95 CI 5.5–27.9%]); p = 0.004). Rates of moderate to severe AKI were also significantly reduced by the intervention compared to controls (29.7% versus 44.9%; p = 0.009). There were no differences in rates of RRT, mortality or persistent renal dysfunction at 30, 60 or 90 days. A follow-up study in 12 international sites confirmed these findings [28]. The occurrence of moderate and severe AKI was significantly lower in the intervention group compared to the control group [14.0% vs 23.9%; ARR 10.0% (95% CI 0.9–19.1); p = 0.034]. Again, there were no significant differences in other specified secondary outcomes.

In the ‘Biomarker-guided intervention to prevent AKI after major surgery (BigPAK)’ trial, a similar care bundle including early optimization of fluids and maintenance of perfusion pressure, was applied to patients after non-cardiac major surgery who were testing positive for the urinary [TIMP-2] × [IGFBP7] biomarker [27]. Although there was no statistically significant difference in total AKI incidence between the groups (31.7% in the intervention group versus 47.5% in the standard care group, p = 0.076), the rates of AKI stage II/III were reduced in the intervention group (6.7% versus 19.7%, p = 0.04), as were length of stay in ICU (median difference 1 day, p = 0.03) and in hospital (median difference 5 days, p = 0.04).

The role of measuring urinary [TIMP-2] × [IGFBP7] in high risk patients attending the emergency department was evaluated in a single center study [68]. One hundred patients with a urinary [TIMP-2] × [IGFBP7] concentration > 0.3 were randomized to immediate one-time nephrological consultation and implementation of the KDIGO AKI recommendations versus usual care. There was no significant difference in the primary outcome (incidence of moderate to severe AKI within the first day after admission) but patients in the intervention arm had significantly lower sCr results on day 2, lower maximum sCr results and a higher urine output on day 3. Adequately powered trials are needed to confirm these results [69].

Biomarker guided management in sepsis was evaluated in the LAPIS trial [70]. This study compared a three-level kidney-sparing sepsis bundle based on the KDIGO recommendations and guided by risk stratification using serial measurement of urinary [TIMP-2] x [IGFBP7] in patients with sepsis. The study was terminated prematurely and concluded that this strategy was feasible and safe.

Nephrotoxins contribute to approximately 30% of AKI cases in critically ill patients. The measurement of biomarkers has been shown to support drug stewardship, informing medication prescription, drug dosing as well as the application of supportive measures. In a real-world evaluation, the use of urinary [TIMP-2] x [IGFBP7] as an AKI risk screening tool resulted in differential application of various components of the AKI management bundle to those with a positive test result [71]. 51% of patients had at least one medication change in response to a [TIMP-2] x [IGFBP7] result. NGAL has been evaluated for cisplatin-associated AKI and demonstrated that NGAL facilitated the recognition of AKI 4.5 days sooner than sCr for cisplatin associated AKI [72]. In patients with amphotericin-induced AKI, NGAL detected the event about 3 days sooner than sCr [73].

Biomarkers can also be used to classify potentially nephrotoxic drugs and determine their direct effect on the kidneys. [74] Further, panels of tubular damage markers have been approved for assessment of tubular injury in non-clinical and clinical drug studies to help guide safety assessments of new potential therapies [75].

Biomarker adoption into clinical practice

The increasing ability to measure new AKI biomarkers and the observation that they likely identify an earlier phase of AKI and allow sub-phenotyping has opened the door to personalised medicine for AKI [76]. In the opinion of many experts, this approach is ready for daily use in conjunction with traditional tests [47, 77, 78]. However, the adoption into routine clinical practice has been slow. The reasons vary between institutions but include several factors. First, there is heterogeneity in the performance of various biomarkers in different clinical studies, depending on the patient cohort, timing of measurement, chosen cut-off values, laboratory technique (including use of research assays rather than approved clinical tests) and confounding factors. Second, specific cut-offs have not been determined for all biomarkers. Third, standardized assays and point-of-care testing devices are not available for all biomarkers, and not all biomarker tests are approved by regulatory bodies for clinical use. Fourth, financial costs are often mentioned as barriers. However, a recent cost-utility analysis of biomarkers predicting persistent AKI concluded that biomarker-directed care led to lower total costs and more quality adjusted life years and was cost-effective as the $50,000/QALY threshold [79].

The 23rd ADQI panel concluded that a combination of damage and functional biomarkers, along with clinical information, improved the diagnostic accuracy of AKI, allowed the recognition of different pathophysiological processes, could discriminate AKI aetiology and served to assess AKI severity [67]. Further, the expert panel proposed that clinical information enriched by damage and functional biomarkers could lead to more sensitive AKI definitions and assist the prevention and management of AKI. However, the expert panel was not able to issue specific recommendations for all potential clinical scenarios [67].

Conclusions

Kidney biomarkers have a role in diagnosing AKI earlier, differentiating between different sub-phenotypes of AKI, identifying high-risk patients and informing clinical management in specific clinical scenarios. The role of individual biomarkers depends on their specific characteristics. To achieve personalised AKI management, integration of appropriate AKI biomarkers into routine clinical practice is essential.

Abbreviations

AAP Alanine aminopeptidase

ADQI Acute disease quality initiative acute disease quality initiative (ADQI)

AIN Acute interstitial nephritis

AKI Acute kidney injury

ALP Alkaline phosphatase

ARR Adjusted risk ratio

AUC Area under the receiver operating curve

BigPAK Biomarker-guided intervention to prevent AKI after major surgery

CCL14 C–C motif chemokine ligand 14

CI Confidence interval

CKD Chronic kidney disease

DKK3 Dickkopf-3

ED Emergency department

GFR Glomerular filtration rate

γ-GT γ-Glutamyl transpeptidase

HGF Hepatocyte growth factor

HRS Hepato-renal syndrome

ICA International club of ascites

ICU Intensive care unit

IGFBP7 Insulin like growth factor binding protein 7

IQR Interquartile range

IL-9 Interleukin-9

IL-18 Interleukin-18

KDIGO Kidney diseases improving global outcomes

KIM-1 Kidney injury molecule-1

LCA Latent class analysis

L-FABP Liver fatty acid-binding protein

MAKE Major adverse kidney events

NAG N-acetyl-β-D-glucosaminidase

NGAL Neutrophil gelatinase associated lipocalin

OR Odds ratio

PrevAKI Prevention of cardiac surgery associated AKI by implementing the KDIGO guidelines in high-risk patients identified by biomarkers

ProCESS Protocolized care for early septic shock

RRT Renal replacement therapy

SCr Serum creatinine

TIMP-2 Tissue inhibitor metalloproteinase 2

TNFα Tumor necrosis factor α

uNGAL Urine NGAL

UTI Urinary tract infection

VASST Vasopressin versus norepinephrine infusion in septic shock

Author contributions

MO is the guarantor of the content of the manuscript. MO wrote the first draft. ML, MM, NS and JAK reviewed the first draft and subsequent drafts, made edits and jointly created the tables. The final draft was approved by all authors.

Funding

This study received no external funding.

Availability of data and materials

Not applicable.

Declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

All other authors declare no competing of interests.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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References

1. Ronco C Bellomo R Kellum JA Acute kidney injury Lancet 2019 394 10212 1949 1964 10.1016/S0140-6736(19)32563-2 31777389
Ronco C, Bellomo R, Kellum JA. Acute kidney injury. Lancet. 2019;394(10212):1949–64.31777389 10.1016/S0140-6736(19)32563-2
2. Pickkers P Darmon M Hoste E Joannidis M Legrand M Ostermann M Acute kidney injury in the critically ill: an updated review on pathophysiology and management Intensive Care Med 2021 47 8 835 850 10.1007/s00134-021-06454-7 34213593
Pickkers P, Darmon M, Hoste E, Joannidis M, Legrand M, Ostermann M, et al. Acute kidney injury in the critically ill: an updated review on pathophysiology and management. Intensive Care Med. 2021;47(8):835–50.34213593 10.1007/s00134-021-06454-7
3. Haines RW Powell-Tuck J Leonard H Crichton S Ostermann M Long-term kidney function of patients discharged from hospital after an intensive care admission: observational cohort study Sci Rep 2021 11 1 9928 10.1038/s41598-021-89454-3 33976354
Haines RW, Powell-Tuck J, Leonard H, Crichton S, Ostermann M. Long-term kidney function of patients discharged from hospital after an intensive care admission: observational cohort study. Sci Rep. 2021;11(1):9928.33976354 10.1038/s41598-021-89454-3
4. Ostermann M Lumlertgul N James MT Dialysis-Dependent acute kidney injury-a risk factor for adverse outcomes Jama Netw Open 2024 7 3 e240346 10.1001/jamanetworkopen.2024.0346 38457185
Ostermann M, Lumlertgul N, James MT. Dialysis-Dependent acute kidney injury-a risk factor for adverse outcomes. Jama Netw Open. 2024;7(3): e240346.38457185 10.1001/jamanetworkopen.2024.0346
5. McNicholas BA Haines R Ostermann M Survive or thrive after ICU: what's the score? Ann Intensive Care 2023 13 1 43 10.1186/s13613-023-01140-x 37202549
McNicholas BA, Haines R, Ostermann M. Survive or thrive after ICU: what’s the score? Ann Intensive Care. 2023;13(1):43.37202549 10.1186/s13613-023-01140-x
6. McNicholas B Akcan Arikan A Ostermann M Quality of life after acute kidney injury Curr Opin Crit Care 2023 29 6 566 579 10.1097/MCC.0000000000001090 37861184
McNicholas B, Akcan Arikan A, Ostermann M. Quality of life after acute kidney injury. Curr Opin Crit Care. 2023;29(6):566–79.37861184 10.1097/MCC.0000000000001090
7. Ostermann M Basu RK Mehta RL Acute kidney injury Intensive Care Med 2023 49 2 219 222 10.1007/s00134-022-06946-0 36592201
Ostermann M, Basu RK, Mehta RL. Acute kidney injury. Intensive Care Med. 2023;49(2):219–22.36592201 10.1007/s00134-022-06946-0
8. Lumlertgul N Baker E Pearson E Dalrymple KV Pan J Jheeta A Changing epidemiology of acute kidney injury in critically ill patients with COVID-19: a prospective cohort Ann Intensive Care 2022 12 1 118 10.1186/s13613-022-01094-6 36575315
Lumlertgul N, Baker E, Pearson E, Dalrymple KV, Pan J, Jheeta A, et al. Changing epidemiology of acute kidney injury in critically ill patients with COVID-19: a prospective cohort. Ann Intensive Care. 2022;12(1):118.36575315 10.1186/s13613-022-01094-6
9. Kellum JA Lameire N Diagnosis, evaluation, and management of acute kidney injury: a KDIGO summary (Part 1) Crit Care 2013 17 1 204 10.1186/cc11454 23394211
Kellum JA, Lameire N. Diagnosis, evaluation, and management of acute kidney injury: a KDIGO summary (Part 1). Crit Care. 2013;17(1):204.23394211 10.1186/cc11454
10. Kashani K Rosner MH Ostermann M Creatinine: from physiology to clinical application Eur J Intern Med 2020 72 9 14 10.1016/j.ejim.2019.10.025 31708357
Kashani K, Rosner MH, Ostermann M. Creatinine: from physiology to clinical application. Eur J Intern Med. 2020;72:9–14.31708357 10.1016/j.ejim.2019.10.025
11. Liu KD Thompson BT Ancukiewicz M Steingrub JS Douglas IS Matthay MA Acute kidney injury in patients with acute lung injury: impact of fluid accumulation on classification of acute kidney injury and associated outcomes Crit Care Med 2011 39 12 2665 2671 10.1097/CCM.0b013e318228234b 21785346
Liu KD, Thompson BT, Ancukiewicz M, Steingrub JS, Douglas IS, Matthay MA, et al. Acute kidney injury in patients with acute lung injury: impact of fluid accumulation on classification of acute kidney injury and associated outcomes. Crit Care Med. 2011;39(12):2665–71.21785346 10.1097/CCM.0b013e318228234b
12. Ostermann M Joannidis M Acute kidney injury 2016: diagnosis and diagnostic workup Crit Care 2016 20 1 299 10.1186/s13054-016-1478-z 27670788
Ostermann M, Joannidis M. Acute kidney injury 2016: diagnosis and diagnostic workup. Crit Care. 2016;20(1):299.27670788 10.1186/s13054-016-1478-z
13. Ostermann M Shaw AD Joannidis M Management of oliguria Intensive Care Med 2023 49 1 103 106 10.1007/s00134-022-06909-5 36266588
Ostermann M, Shaw AD, Joannidis M. Management of oliguria. Intensive Care Med. 2023;49(1):103–6.36266588 10.1007/s00134-022-06909-5
14. Ostermann M Awdishu L Legrand M Using diuretic therapy in the critically ill patient Intensive Care Med 2024 10.1007/s00134-024-07441-4 39133282
Ostermann M, Awdishu L, Legrand M. Using diuretic therapy in the critically ill patient. Intensive Care Med. 2024. 10.1007/s00134-024-07441-4.39133282 10.1007/s00134-024-07441-4
15. Törnblom S Nisula S Petäjä L Vaara ST Haapio M Pesonen E Urine NGAL as a biomarker for septic AKI: a critical appraisal of clinical utility—data from the observational FINNAKI study Ann Intensive Care 2020 10 1 51 10.1186/s13613-020-00667-7 32347418
Törnblom S, Nisula S, Petäjä L, Vaara ST, Haapio M, Pesonen E, et al. Urine NGAL as a biomarker for septic AKI: a critical appraisal of clinical utility—data from the observational FINNAKI study. Ann Intensive Care. 2020;10(1):51.32347418 10.1186/s13613-020-00667-7
16. Emlet DR Pastor-Soler N Marciszyn A Wen X Gomez H Humphries W Insulin-like growth factor binding protein 7 and tissue inhibitor of metalloproteinases-2: differential expression and secretion in human kidney tubule cells Am J Physiol Renal Physiol 2017 312 2 F284 F296 10.1152/ajprenal.00271.2016 28003188
Emlet DR, Pastor-Soler N, Marciszyn A, Wen X, Gomez H, Humphries W, et al. Insulin-like growth factor binding protein 7 and tissue inhibitor of metalloproteinases-2: differential expression and secretion in human kidney tubule cells. Am J Physiol Renal Physiol. 2017;312(2):F284–96.28003188 10.1152/ajprenal.00271.2016
17. McCullough PA Ostermann M Forni LG Bihorac A Koyner JL Chawla LS Serial urinary tissue inhibitor of metalloproteinase-2 and insulin-like growth factor-binding protein 7 and the prognosis for acute kidney injury over the course of critical illness Cardiorenal Med 2019 9 6 358 369 10.1159/000502837 31618746
McCullough PA, Ostermann M, Forni LG, Bihorac A, Koyner JL, Chawla LS, et al. Serial urinary tissue inhibitor of metalloproteinase-2 and insulin-like growth factor-binding protein 7 and the prognosis for acute kidney injury over the course of critical illness. Cardiorenal Med. 2019;9(6):358–69.31618746 10.1159/000502837
18. Laing KJ Secombes CJ Chemokines Dev Comp Immunol 2004 28 5 443 460 10.1016/j.dci.2003.09.006 15062643
Laing KJ, Secombes CJ. Chemokines. Dev Comp Immunol. 2004;28(5):443–60.15062643 10.1016/j.dci.2003.09.006
19. Hoste E Bihorac A Al-Khafaji A Ortega LM Ostermann M Haase M Identification and validation of biomarkers of persistent acute kidney injury: the RUBY study Intensive Care Med 2020 46 5 943 953 10.1007/s00134-019-05919-0 32025755
Hoste E, Bihorac A, Al-Khafaji A, Ortega LM, Ostermann M, Haase M, et al. Identification and validation of biomarkers of persistent acute kidney injury: the RUBY study. Intensive Care Med. 2020;46(5):943–53.32025755 10.1007/s00134-019-05919-0
20. Moledina DG Wilson FP Pober JS Perazella MA Singh N Luciano RL Urine TNF-α and IL-9 for clinical diagnosis of acute interstitial nephritis JCI Insight 2019 10.1172/jci.insight.127456 31092735
Moledina DG, Wilson FP, Pober JS, Perazella MA, Singh N, Luciano RL, et al. Urine TNF-α and IL-9 for clinical diagnosis of acute interstitial nephritis. JCI Insight. 2019. 10.1172/jci.insight.127456.31092735 10.1172/jci.insight.127456
21. Ostermann M Karsten E Lumlertgul N Biomarker-based management of AKI: fact or fantasy? Nephron 2022 146 3 295 301 10.1159/000518365 34515152
Ostermann M, Karsten E, Lumlertgul N. Biomarker-based management of AKI: fact or fantasy? Nephron. 2022;146(3):295–301.34515152 10.1159/000518365
22. Kane-Gill SL Meersch M Bell M Biomarker-guided management of acute kidney injury Curr Opin Crit Care 2020 26 6 556 562 10.1097/MCC.0000000000000777 33027146
Kane-Gill SL, Meersch M, Bell M. Biomarker-guided management of acute kidney injury. Curr Opin Crit Care. 2020;26(6):556–62.33027146 10.1097/MCC.0000000000000777
23. Honore PM Jacobs R Joannes-Boyau O Verfaillie L De Regt J Van Gorp V Biomarkers for early diagnosis of AKI in the ICU: ready for prime time use at the bedside? Ann Intensive Care 2012 2 1 24 10.1186/2110-5820-2-24 22747706
Honore PM, Jacobs R, Joannes-Boyau O, Verfaillie L, De Regt J, Van Gorp V, et al. Biomarkers for early diagnosis of AKI in the ICU: ready for prime time use at the bedside? Ann Intensive Care. 2012;2(1):24.22747706 10.1186/2110-5820-2-24
24. Jia H-M Cheng L Weng Y-B Wang J-Y Zheng X Jiang Y-J Cell cycle arrest biomarkers for predicting renal recovery from acute kidney injury: a prospective validation study Ann Intensive Care 2022 12 1 14 10.1186/s13613-022-00989-8 35150348
Jia H-M, Cheng L, Weng Y-B, Wang J-Y, Zheng X, Jiang Y-J, et al. Cell cycle arrest biomarkers for predicting renal recovery from acute kidney injury: a prospective validation study. Ann Intensive Care. 2022;12(1):14.35150348 10.1186/s13613-022-00989-8
25. Fuhrman DY Stanski NL Krawczeski CD Greenberg JH Arikan AAA Basu RK A proposed framework for advancing acute kidney injury risk stratification and diagnosis in children: a report from the 26th acute disease quality initiative (ADQI) conference Pediatr Nephrol 2024 39 3 929 939 10.1007/s00467-023-06133-3 37670082
Fuhrman DY, Stanski NL, Krawczeski CD, Greenberg JH, Arikan AAA, Basu RK, et al. A proposed framework for advancing acute kidney injury risk stratification and diagnosis in children: a report from the 26th acute disease quality initiative (ADQI) conference. Pediatr Nephrol. 2024;39(3):929–39.37670082 10.1007/s00467-023-06133-3
26. Meersch M Schmidt C Hoffmeier A Van Aken H Wempe C Gerss J 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 2017 43 11 1551 1561 10.1007/s00134-016-4670-3 28110412
Meersch M, Schmidt C, Hoffmeier A, Van Aken H, Wempe C, Gerss J, et al. 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. 2017;43(11):1551–61.28110412 10.1007/s00134-016-4670-3
27. Göcze I Jauch D Götz M Kennedy P Jung B Zeman F Biomarker-guided intervention to prevent acute kidney injury after major surgery: the prospective randomized BigpAK study Ann Surg 2018 267 6 1013 1020 10.1097/SLA.0000000000002485 28857811
Göcze I, Jauch D, Götz M, Kennedy P, Jung B, Zeman F, et al. Biomarker-guided intervention to prevent acute kidney injury after major surgery: the prospective randomized BigpAK study. Ann Surg. 2018;267(6):1013–20.28857811 10.1097/SLA.0000000000002485
28. Zarbock A Küllmar M Ostermann M Lucchese G Baig K Cennamo A Prevention of cardiac surgery-associated acute kidney injury by Implementing the KDIGO guidelines in High-risk patients identified by biomarkers: the prevAKI-Multicenter randomized controlled trial Anesth Analg 2021 133 2 292 302 10.1213/ANE.0000000000005458 33684086
Zarbock A, Küllmar M, Ostermann M, Lucchese G, Baig K, Cennamo A, et al. Prevention of cardiac surgery-associated acute kidney injury by Implementing the KDIGO guidelines in High-risk patients identified by biomarkers: the prevAKI-Multicenter randomized controlled trial. Anesth Analg. 2021;133(2):292–302.33684086 10.1213/ANE.0000000000005458
29. Stanski N Menon S Goldstein SL Basu RK Integration of urinary neutrophil gelatinase-associated lipocalin with serum creatinine delineates acute kidney injury phenotypes in critically ill children J Crit Care 2019 53 1 7 10.1016/j.jcrc.2019.05.017 31174170
Stanski N, Menon S, Goldstein SL, Basu RK. Integration of urinary neutrophil gelatinase-associated lipocalin with serum creatinine delineates acute kidney injury phenotypes in critically ill children. J Crit Care. 2019;53:1–7.31174170 10.1016/j.jcrc.2019.05.017
30. Haase M Bellomo R Devarajan P Schlattmann P Haase-Fielitz A Accuracy of neutrophil gelatinase-associated lipocalin (NGAL) in diagnosis and prognosis in acute kidney injury: a systematic review and meta-analysis Am J Kidney Dis 2009 54 6 1012 1024 10.1053/j.ajkd.2009.07.020 19850388
Haase M, Bellomo R, Devarajan P, Schlattmann P, Haase-Fielitz A. Accuracy of neutrophil gelatinase-associated lipocalin (NGAL) in diagnosis and prognosis in acute kidney injury: a systematic review and meta-analysis. Am J Kidney Dis. 2009;54(6):1012–24.19850388 10.1053/j.ajkd.2009.07.020
31. Ho J Tangri N Komenda P Kaushal A Sood M Brar R Urinary, plasma, and serum biomarkers' utility for predicting acute kidney injury associated with cardiac surgery in adults: a meta-analysis Am J Kidney Dis 2015 66 6 993 1005 10.1053/j.ajkd.2015.06.018 26253993
Ho J, Tangri N, Komenda P, Kaushal A, Sood M, Brar R, et al. Urinary, plasma, and serum biomarkers’ utility for predicting acute kidney injury associated with cardiac surgery in adults: a meta-analysis. Am J Kidney Dis. 2015;66(6):993–1005.26253993 10.1053/j.ajkd.2015.06.018
32. Kashani K Al-Khafaji A Ardiles T Artigas A Bagshaw SM Bell M Discovery and validation of cell cycle arrest biomarkers in human acute kidney injury Crit Care 2013 17 1 R25 10.1186/cc12503 23388612
Kashani K, Al-Khafaji A, Ardiles T, Artigas A, Bagshaw SM, Bell M, et al. Discovery and validation of cell cycle arrest biomarkers in human acute kidney injury. Crit Care. 2013;17(1):R25.23388612 10.1186/cc12503
33. Forni LG Joannidis M Artigas A Bell M Hoste E Joannes-Boyau O Characterising acute kidney injury: the complementary roles of biomarkers of renal stress and renal function J Crit Care 2022 71 154066 10.1016/j.jcrc.2022.154066 35696851
Forni LG, Joannidis M, Artigas A, Bell M, Hoste E, Joannes-Boyau O, et al. Characterising acute kidney injury: the complementary roles of biomarkers of renal stress and renal function. J Crit Care. 2022;71: 154066.35696851 10.1016/j.jcrc.2022.154066
34. Huang F Zeng Y Lv L Chen Y Yan Y Luo L Predictive value of urinary cell cycle arrest biomarkers for all cause-acute kidney injury: a meta-analysis Sci Rep 2023 13 1 6037 10.1038/s41598-023-33233-9 37055509
Huang F, Zeng Y, Lv L, Chen Y, Yan Y, Luo L, et al. Predictive value of urinary cell cycle arrest biomarkers for all cause-acute kidney injury: a meta-analysis. Sci Rep. 2023;13(1):6037.37055509 10.1038/s41598-023-33233-9
35. Lin LC Chuan MH Liu JH Liao HW Ng LL Magnusson M Proenkephalin as a biomarker correlates with acute kidney injury: a systematic review with meta-analysis and trial sequential analysis Crit Care 2023 27 1 481 10.1186/s13054-023-04747-5 38057904
Lin LC, Chuan MH, Liu JH, Liao HW, Ng LL, Magnusson M, et al. Proenkephalin as a biomarker correlates with acute kidney injury: a systematic review with meta-analysis and trial sequential analysis. Crit Care. 2023;27(1):481.38057904 10.1186/s13054-023-04747-5
36. Ahmad T Jackson K Rao VS Tang WHW Brisco-Bacik MA Chen HH Worsening renal function in patients with acute heart failure undergoing aggressive diuresis is not associated with tubular injury Circulation 2018 137 19 2016 2028 10.1161/CIRCULATIONAHA.117.030112 29352071
Ahmad T, Jackson K, Rao VS, Tang WHW, Brisco-Bacik MA, Chen HH, et al. Worsening renal function in patients with acute heart failure undergoing aggressive diuresis is not associated with tubular injury. Circulation. 2018;137(19):2016–28.29352071 10.1161/CIRCULATIONAHA.117.030112
37. Ostermann M McCullough PA Forni LG Bagshaw SM Joannidis M Shi J Kinetics of urinary cell cycle arrest markers for acute kidney injury following exposure to potential renal insults Crit Care Med 2018 46 3 375 383 10.1097/CCM.0000000000002847 29189343
Ostermann M, McCullough PA, Forni LG, Bagshaw SM, Joannidis M, Shi J, et al. Kinetics of urinary cell cycle arrest markers for acute kidney injury following exposure to potential renal insults. Crit Care Med. 2018;46(3):375–83.29189343 10.1097/CCM.0000000000002847
38. Fudim M Loungani R Doerfler SM Coles A Greene SJ Cooper LB Worsening renal function during decongestion among patients hospitalized for heart failure: findings from the evaluation study of congestive heart failure and pulmonary artery catheterization effectiveness (ESCAPE) trial Am Heart J 2018 204 163 173 10.1016/j.ahj.2018.07.019 30121018
Fudim M, Loungani R, Doerfler SM, Coles A, Greene SJ, Cooper LB, et al. Worsening renal function during decongestion among patients hospitalized for heart failure: findings from the evaluation study of congestive heart failure and pulmonary artery catheterization effectiveness (ESCAPE) trial. Am Heart J. 2018;204:163–73.30121018 10.1016/j.ahj.2018.07.019
39. Nadim MK Kellum JA Forni L Francoz C Asrani SK Ostermann M Acute kidney injury in patients with cirrhosis: acute disease quality initiative (ADQI) and international club of ascites (ICA) joint multidisciplinary consensus meeting J Hepatol 2024 10.1016/j.jhep.2024.03.031 38527522
Nadim MK, Kellum JA, Forni L, Francoz C, Asrani SK, Ostermann M, et al. Acute kidney injury in patients with cirrhosis: acute disease quality initiative (ADQI) and international club of ascites (ICA) joint multidisciplinary consensus meeting. J Hepatol. 2024. 10.1016/j.jhep.2024.03.031.38527522 10.1016/j.jhep.2024.03.031
40. Nadim MK Forni LG Ostermann M Hepatorenal syndrome in the intensive care unit Intensive Care Med 2024 50 6 978 981 10.1007/s00134-024-07438-z 38695933
Nadim MK, Forni LG, Ostermann M. Hepatorenal syndrome in the intensive care unit. Intensive Care Med. 2024;50(6):978–81.38695933 10.1007/s00134-024-07438-z
41. Gambino C Piano S Stenico M Tonon M Brocca A Calvino V Diagnostic and prognostic performance of urinary neutrophil gelatinase-associated lipocalin in patients with cirrhosis and acute kidney injury Hepatology 2023 77 5 1630 1638 36125403
Gambino C, Piano S, Stenico M, Tonon M, Brocca A, Calvino V, et al. Diagnostic and prognostic performance of urinary neutrophil gelatinase-associated lipocalin in patients with cirrhosis and acute kidney injury. Hepatology. 2023;77(5):1630–8.36125403
42. Kane-Gill SL Ostermann M Shi J Joyce EL Kellum JA Evaluating renal stress using pharmacokinetic urinary biomarker data in critically ill patients receiving vancomycin and/or piperacillin-Tazobactam: a secondary analysis of the multicenter sapphire study Drug Saf 2019 42 10 1149 1155 10.1007/s40264-019-00846-x 31240688
Kane-Gill SL, Ostermann M, Shi J, Joyce EL, Kellum JA. Evaluating renal stress using pharmacokinetic urinary biomarker data in critically ill patients receiving vancomycin and/or piperacillin-Tazobactam: a secondary analysis of the multicenter sapphire study. Drug Saf. 2019;42(10):1149–55.31240688 10.1007/s40264-019-00846-x
43. Moledina DG Wilson FP Kukova L Obeid W Luciano R Kuperman M Urine interleukin-9 and tumor necrosis factor-α for prognosis of human acute interstitial nephritis Nephrol Dial Transplant 2021 36 10 1851 1858 10.1093/ndt/gfaa169 33125471
Moledina DG, Wilson FP, Kukova L, Obeid W, Luciano R, Kuperman M, et al. Urine interleukin-9 and tumor necrosis factor-α for prognosis of human acute interstitial nephritis. Nephrol Dial Transplant. 2021;36(10):1851–8.33125471 10.1093/ndt/gfaa169
44. Chawla LS Bellomo R Bihorac A Goldstein SL Siew ED Bagshaw SM Acute kidney disease and renal recovery: consensus report of the acute disease quality initiative (ADQI) 16 workgroup Nat Rev Nephrol 2017 13 4 241 257 10.1038/nrneph.2017.2 28239173
Chawla LS, Bellomo R, Bihorac A, Goldstein SL, Siew ED, Bagshaw SM, et al. Acute kidney disease and renal recovery: consensus report of the acute disease quality initiative (ADQI) 16 workgroup. Nat Rev Nephrol. 2017;13(4):241–57.28239173 10.1038/nrneph.2017.2
45. Forni LG Darmon M Ostermann M Oudemans-van Straaten HM Pettilä V Prowle JR Renal recovery after acute kidney injury Intensive Care Med 2017 43 6 855 866 10.1007/s00134-017-4809-x 28466146
Forni LG, Darmon M, Ostermann M, Oudemans-van Straaten HM, Pettilä V, Prowle JR, et al. Renal recovery after acute kidney injury. Intensive Care Med. 2017;43(6):855–66.28466146 10.1007/s00134-017-4809-x
46. Chen YT Pan HC Hsu CK Sun CY Chen CY Chen YH Performance of urinary C-C motif chemokine ligand 14 for the prediction of persistent acute kidney injury: a systematic review and meta-analysis Crit Care 2023 27 1 318 10.1186/s13054-023-04610-7 37596698
Chen YT, Pan HC, Hsu CK, Sun CY, Chen CY, Chen YH, et al. Performance of urinary C-C motif chemokine ligand 14 for the prediction of persistent acute kidney injury: a systematic review and meta-analysis. Crit Care. 2023;27(1):318.37596698 10.1186/s13054-023-04610-7
47. Kellum JA Bagshaw SM Demirjian S Forni L Joannidis M Kampf JP CCL14 testing to guide clinical practice in patients with AKI: results from an international expert panel J Crit Care 2024 82 154816 10.1016/j.jcrc.2024.154816 38678981
Kellum JA, Bagshaw SM, Demirjian S, Forni L, Joannidis M, Kampf JP, et al. CCL14 testing to guide clinical practice in patients with AKI: results from an international expert panel. J Crit Care. 2024;82: 154816.38678981 10.1016/j.jcrc.2024.154816
48. Hollinger A Wittebole X François B Pickkers P Antonelli M Gayat E Proenkephalin A 119–159 (Penkid) is an early biomarker of septic acute kidney injury: the kidney in sepsis and septic shock (Kid-SSS) study Kidney Int Rep 2018 3 6 1424 1433 10.1016/j.ekir.2018.08.006 30450469
Hollinger A, Wittebole X, François B, Pickkers P, Antonelli M, Gayat E, et al. Proenkephalin A 119–159 (Penkid) is an early biomarker of septic acute kidney injury: the kidney in sepsis and septic shock (Kid-SSS) study. Kidney Int Rep. 2018;3(6):1424–33.30450469 10.1016/j.ekir.2018.08.006
49. Schunk SJ Zarbock A Meersch M Küllmar M Kellum JA Schmit D Association between urinary dickkopf-3, acute kidney injury, and subsequent loss of kidney function in patients undergoing cardiac surgery: an observational cohort study Lancet 2019 394 10197 488 496 10.1016/S0140-6736(19)30769-X 31202596
Schunk SJ, Zarbock A, Meersch M, Küllmar M, Kellum JA, Schmit D, et al. Association between urinary dickkopf-3, acute kidney injury, and subsequent loss of kidney function in patients undergoing cardiac surgery: an observational cohort study. Lancet. 2019;394(10197):488–96.31202596 10.1016/S0140-6736(19)30769-X
50. Molinari L Del Rio-Pertuz G Smith A Landsittel DP Singbartl K Palevsky PM Utility of biomarkers for sepsis-associated acute kidney injury staging JAMA Netw Open 2022 5 5 e2212709 10.1001/jamanetworkopen.2022.12709 35583867
Molinari L, Del Rio-Pertuz G, Smith A, Landsittel DP, Singbartl K, Palevsky PM, et al. Utility of biomarkers for sepsis-associated acute kidney injury staging. JAMA Netw Open. 2022;5(5): e2212709.35583867 10.1001/jamanetworkopen.2022.12709
51. Klein SJ Brandtner AK Lehner GF Ulmer H Bagshaw SM Wiedermann CJ Biomarkers for prediction of renal replacement therapy in acute kidney injury: a systematic review and meta-analysis Intensive Care Med 2018 44 3 323 336 10.1007/s00134-018-5126-8 29541790
Klein SJ, Brandtner AK, Lehner GF, Ulmer H, Bagshaw SM, Wiedermann CJ, et al. Biomarkers for prediction of renal replacement therapy in acute kidney injury: a systematic review and meta-analysis. Intensive Care Med. 2018;44(3):323–36.29541790 10.1007/s00134-018-5126-8
52. Ostermann M Dickie H Barrett NA Renal replacement therapy in critically ill patients with acute kidney injury–when to start Nephrol Dial Transplant 2012 27 6 2242 2248 10.1093/ndt/gfr707 22231034
Ostermann M, Dickie H, Barrett NA. Renal replacement therapy in critically ill patients with acute kidney injury–when to start. Nephrol Dial Transplant. 2012;27(6):2242–8.22231034 10.1093/ndt/gfr707
53. Ostermann M Bagshaw SM Lumlertgul N Wald R Indications for and timing of initiation of KRT Clin J Am Soc Nephrol 2023 18 1 113 120 36100262
Ostermann M, Bagshaw SM, Lumlertgul N, Wald R. Indications for and timing of initiation of KRT. Clin J Am Soc Nephrol. 2023;18(1):113–20.36100262
54. Ostermann M Joannidis M Pani A Floris M De Rosa S Kellum JA Patient selection and timing of continuous renal replacement therapy Blood Purif 2016 42 3 224 237 10.1159/000448506 27561956
Ostermann M, Joannidis M, Pani A, Floris M, De Rosa S, Kellum JA, et al. Patient selection and timing of continuous renal replacement therapy. Blood Purif. 2016;42(3):224–37.27561956 10.1159/000448506
55. Meersch M Weiss R Gerss J Albert F Gruber J Kellum JA Predicting the development of renal replacement therapy indications by combining the furosemide stress test and chemokine (C-C Motif) ligand 14 in a cohort of postsurgical patients Crit Care Med 2023 51 8 1033 1042 10.1097/CCM.0000000000005849 36988335
Meersch M, Weiss R, Gerss J, Albert F, Gruber J, Kellum JA, et al. Predicting the development of renal replacement therapy indications by combining the furosemide stress test and chemokine (C-C Motif) ligand 14 in a cohort of postsurgical patients. Crit Care Med. 2023;51(8):1033–42.36988335 10.1097/CCM.0000000000005849
56. Hoste EAJ Kellum JA Selby NM Zarbock A Palevsky PM Bagshaw SM Global epidemiology and outcomes of acute kidney injury Nat Rev Nephrol 2018 14 10 607 625 10.1038/s41581-018-0052-0 30135570
Hoste EAJ, Kellum JA, Selby NM, Zarbock A, Palevsky PM, Bagshaw SM, et al. Global epidemiology and outcomes of acute kidney injury. Nat Rev Nephrol. 2018;14(10):607–25.30135570 10.1038/s41581-018-0052-0
57. Peerapornratana S Fiorentino M Priyanka P Murugan R Kellum JA Recovery after AKI: effects on outcomes over 15 years J Crit Care 2023 76 154280 10.1016/j.jcrc.2023.154280 36848723
Peerapornratana S, Fiorentino M, Priyanka P, Murugan R, Kellum JA. Recovery after AKI: effects on outcomes over 15 years. J Crit Care. 2023;76: 154280.36848723 10.1016/j.jcrc.2023.154280
58. Qian BS Jia HM Weng YB Li XC Chen CD Guo FX Analysis of urinary C-C motif chemokine ligand 14 (CCL14) and first-generation urinary biomarkers for predicting renal recovery from acute kidney injury: a prospective exploratory study J Intensive Care 2023 11 1 11 10.1186/s40560-023-00659-2 36941674
Qian BS, Jia HM, Weng YB, Li XC, Chen CD, Guo FX, et al. Analysis of urinary C-C motif chemokine ligand 14 (CCL14) and first-generation urinary biomarkers for predicting renal recovery from acute kidney injury: a prospective exploratory study. J Intensive Care. 2023;11(1):11.36941674 10.1186/s40560-023-00659-2
59. Koyner JL Shaw AD Chawla LS Hoste EA Bihorac A Kashani K Tissue inhibitor metalloproteinase-2 (TIMP-2)⋅IGF-binding protein-7 (IGFBP7) levels are associated with adverse long-term outcomes in patients with AKI J Am Soc Nephrol 2015 26 7 1747 1754 10.1681/ASN.2014060556 25535301
Koyner JL, Shaw AD, Chawla LS, Hoste EA, Bihorac A, Kashani K, et al. Tissue inhibitor metalloproteinase-2 (TIMP-2)⋅IGF-binding protein-7 (IGFBP7) levels are associated with adverse long-term outcomes in patients with AKI. J Am Soc Nephrol. 2015;26(7):1747–54.25535301 10.1681/ASN.2014060556
60. Dépret F Hollinger A Cariou A Deye N Vieillard-Baron A Fournier MC Incidence and outcome of subclinical acute kidney injury using penkid in critically ill patients Am J Respir Crit Care Med 2020 202 6 822 829 10.1164/rccm.201910-1950OC 32516543
Dépret F, Hollinger A, Cariou A, Deye N, Vieillard-Baron A, Fournier MC, et al. Incidence and outcome of subclinical acute kidney injury using penkid in critically ill patients. Am J Respir Crit Care Med. 2020;202(6):822–9.32516543 10.1164/rccm.201910-1950OC
61. Legrand M Hollinger A Vieillard-Baron A Dépret F Cariou A Deye N One-year prognosis of kidney injury at discharge from the ICU: a multicenter observational study Crit Care Med 2019 47 12 e953 e961 10.1097/CCM.0000000000004010 31567524
Legrand M, Hollinger A, Vieillard-Baron A, Dépret F, Cariou A, Deye N, et al. One-year prognosis of kidney injury at discharge from the ICU: a multicenter observational study. Crit Care Med. 2019;47(12):e953–61.31567524 10.1097/CCM.0000000000004010
62. Coca SG Garg AX Thiessen-Philbrook H Koyner JL Patel UD Krumholz HM Urinary biomarkers of AKI and mortality 3 years after cardiac surgery J Am Soc Nephrol 2014 25 5 1063 1071 10.1681/ASN.2013070742 24357673
Coca SG, Garg AX, Thiessen-Philbrook H, Koyner JL, Patel UD, Krumholz HM, et al. Urinary biomarkers of AKI and mortality 3 years after cardiac surgery. J Am Soc Nephrol. 2014;25(5):1063–71.24357673 10.1681/ASN.2013070742
63. Stanski NL Rodrigues CE Strader M Murray PT Endre ZH Bagshaw SM Precision management of acute kidney injury in the intensive care unit: current state of the art Intensive Care Med 2023 49 9 1049 1061 10.1007/s00134-023-07171-z 37552332
Stanski NL, Rodrigues CE, Strader M, Murray PT, Endre ZH, Bagshaw SM. Precision management of acute kidney injury in the intensive care unit: current state of the art. Intensive Care Med. 2023;49(9):1049–61.37552332 10.1007/s00134-023-07171-z
64. Gordon AC Alipanah-Lechner N Bos LD Dianti J Diaz JV Finfer S From ICU syndromes to ICU subphenotypes: consensus report and recommendations for developing precision medicine in ICU Am J Respir Crit Care Med 2024 10.1164/rccm.202311-2086SO 38687499
Gordon AC, Alipanah-Lechner N, Bos LD, Dianti J, Diaz JV, Finfer S, et al. From ICU syndromes to ICU subphenotypes: consensus report and recommendations for developing precision medicine in ICU. Am J Respir Crit Care Med. 2024. 10.1164/rccm.202311-2086SO.38687499 10.1164/rccm.202311-2086SO
65. Legrand M Bagshaw SM Bhatraju PK Bihorac A Caniglia E Khanna AK Sepsis-associated acute kidney injury: recent advances in enrichment strategies, sub-phenotyping and clinical trials Crit Care 2024 28 1 92 10.1186/s13054-024-04877-4 38515121
Legrand M, Bagshaw SM, Bhatraju PK, Bihorac A, Caniglia E, Khanna AK, et al. Sepsis-associated acute kidney injury: recent advances in enrichment strategies, sub-phenotyping and clinical trials. Crit Care. 2024;28(1):92.38515121 10.1186/s13054-024-04877-4
66. Bhatraju PK Zelnick LR Herting J Katz R Mikacenic C Kosamo S Identification of acute kidney injury subphenotypes with differing molecular signatures and responses to vasopressin therapy Am J Respir Crit Care Med 2019 199 7 863 872 10.1164/rccm.201807-1346OC 30334632
Bhatraju PK, Zelnick LR, Herting J, Katz R, Mikacenic C, Kosamo S, et al. Identification of acute kidney injury subphenotypes with differing molecular signatures and responses to vasopressin therapy. Am J Respir Crit Care Med. 2019;199(7):863–72.30334632 10.1164/rccm.201807-1346OC
67. Ostermann M Zarbock A Goldstein S Kashani K Macedo E Murugan R Recommendations on acute kidney injury biomarkers from the acute disease quality initiative consensus conference: a consensus statement JAMA Netw Open 2020 3 10 e2019209 10.1001/jamanetworkopen.2020.19209 33021646
Ostermann M, Zarbock A, Goldstein S, Kashani K, Macedo E, Murugan R, et al. Recommendations on acute kidney injury biomarkers from the acute disease quality initiative consensus conference: a consensus statement. JAMA Netw Open. 2020;3(10): e2019209.33021646 10.1001/jamanetworkopen.2020.19209
68. Schanz M Wasser C Allgaeuer S Schricker S Dippon J Alscher MD Urinary [TIMP-2]·[IGFBP7]-guided randomized controlled intervention trial to prevent acute kidney injury in the emergency department Nephrol Dial Transplant 2019 34 11 1902 1909 10.1093/ndt/gfy186 29961888
Schanz M, Wasser C, Allgaeuer S, Schricker S, Dippon J, Alscher MD, et al. Urinary [TIMP-2]·[IGFBP7]-guided randomized controlled intervention trial to prevent acute kidney injury in the emergency department. Nephrol Dial Transplant. 2019;34(11):1902–9.29961888 10.1093/ndt/gfy186
69. von Groote T Meersch M Romagnoli S Ostermann M Ripollés-Melchor J Schneider AG Biomarker-guided intervention to prevent acute kidney injury after major surgery (BigpAK-2 trial): study protocol for an international, prospective, randomised controlled multicentre trial BMJ Open 2023 13 3 e070240 10.1136/bmjopen-2022-070240
von Groote T, Meersch M, Romagnoli S, Ostermann M, Ripollés-Melchor J, Schneider AG, et al. Biomarker-guided intervention to prevent acute kidney injury after major surgery (BigpAK-2 trial): study protocol for an international, prospective, randomised controlled multicentre trial. BMJ Open. 2023;13(3): e070240.10.1136/bmjopen-2022-070240
70. Gómez H Zarbock A Pastores SM Frendl G Bercker S Asfar P Feasibility assessment of a biomarker-guided kidney-sparing sepsis bundle: the limiting acute kidney injury progression in sepsis trial Crit Care Explor 2023 5 8 e0961 10.1097/CCE.0000000000000961 37614799
Gómez H, Zarbock A, Pastores SM, Frendl G, Bercker S, Asfar P, et al. Feasibility assessment of a biomarker-guided kidney-sparing sepsis bundle: the limiting acute kidney injury progression in sepsis trial. Crit Care Explor. 2023;5(8): e0961.37614799 10.1097/CCE.0000000000000961
71. Kane-Gill SL Peerapornratana S Wong A Murugan R Groetzinger LM Kim C Use of tissue inhibitor of metalloproteinase 2 and insulin-like growth factor binding protein 7 [TIMP2]•[IGFBP7] as an AKI risk screening tool to manage patients in the real-world setting J Crit Care 2020 57 97 101 10.1016/j.jcrc.2020.02.002 32086072
Kane-Gill SL, Peerapornratana S, Wong A, Murugan R, Groetzinger LM, Kim C, et al. Use of tissue inhibitor of metalloproteinase 2 and insulin-like growth factor binding protein 7 [TIMP2]•[IGFBP7] as an AKI risk screening tool to manage patients in the real-world setting. J Crit Care. 2020;57:97–101.32086072 10.1016/j.jcrc.2020.02.002
72. Gaspari F Cravedi P Mandalà M Perico N de Leon FR Stucchi N Predicting cisplatin-induced acute kidney injury by urinary neutrophil gelatinase-associated lipocalin excretion: a pilot prospective case-control study Nephron Clin Pract 2010 115 2 c154 c160 10.1159/000312879 20407275
Gaspari F, Cravedi P, Mandalà M, Perico N, de Leon FR, Stucchi N, et al. Predicting cisplatin-induced acute kidney injury by urinary neutrophil gelatinase-associated lipocalin excretion: a pilot prospective case-control study. Nephron Clin Pract. 2010;115(2):c154–60.20407275 10.1159/000312879
73. Rocha PN Macedo MN Kobayashi CD Moreno L Guimarães LH Machado PR Role of urine neutrophil gelatinase-associated lipocalin in the early diagnosis of amphotericin B-induced acute kidney injury Antimicrob Agents Chemother 2015 59 11 6913 6921 10.1128/AAC.01079-15 26303800
Rocha PN, Macedo MN, Kobayashi CD, Moreno L, Guimarães LH, Machado PR, et al. Role of urine neutrophil gelatinase-associated lipocalin in the early diagnosis of amphotericin B-induced acute kidney injury. Antimicrob Agents Chemother. 2015;59(11):6913–21.26303800 10.1128/AAC.01079-15
74. Karimzadeh I Barreto EF Kellum JA Awdishu L Murray PT Ostermann M Moving toward a contemporary classification of drug-induced kidney disease Crit Care 2023 27 1 435 10.1186/s13054-023-04720-2 37946280
Karimzadeh I, Barreto EF, Kellum JA, Awdishu L, Murray PT, Ostermann M, et al. Moving toward a contemporary classification of drug-induced kidney disease. Crit Care. 2023;27(1):435.37946280 10.1186/s13054-023-04720-2
75. Dieterle F Sistare F Goodsaid F Papaluca M Ozer JS Webb CP Renal biomarker qualification submission: a dialog between the FDA-EMEA and predictive safety testing consortium Nat Biotechnol 2010 28 5 455 462 10.1038/nbt.1625 20458315
Dieterle F, Sistare F, Goodsaid F, Papaluca M, Ozer JS, Webb CP, et al. Renal biomarker qualification submission: a dialog between the FDA-EMEA and predictive safety testing consortium. Nat Biotechnol. 2010;28(5):455–62.20458315 10.1038/nbt.1625
76. Birkelo BC Koyner JL Ostermann M Bhatraju PK The road to precision medicine for acute kidney injury Crit Care Med 2024 52 7 1127 1137 10.1097/CCM.0000000000006328 38869385
Birkelo BC, Koyner JL, Ostermann M, Bhatraju PK. The road to precision medicine for acute kidney injury. Crit Care Med. 2024;52(7):1127–37.38869385 10.1097/CCM.0000000000006328
77. Koyner JL Arndt C Martinez B de Irujo J Coelho S Garcia-Montesinos de la Peña M di Girolamo L Assessing the role of Chemokine (C-C motif) ligand 14 in AKI: a European consensus meeting Ren Fail 2024 46 1 2345747 10.1080/0886022X.2024.2345747 38666354
Koyner JL, Arndt C, Martinez B, de Irujo J, Coelho S, Garcia-Montesinos de la Peña M, di Girolamo L, et al. Assessing the role of Chemokine (C-C motif) ligand 14 in AKI: a European consensus meeting. Ren Fail. 2024;46(1):2345747.38666354 10.1080/0886022X.2024.2345747
78. Ostermann M Wu V Sokolov D Lumlertgul N Definitions of acute renal dysfunction: an evolving clinical and biomarker paradigm Curr Opin Crit Care 2021 27 6 553 559 10.1097/MCC.0000000000000886 34535002
Ostermann M, Wu V, Sokolov D, Lumlertgul N. Definitions of acute renal dysfunction: an evolving clinical and biomarker paradigm. Curr Opin Crit Care. 2021;27(6):553–9.34535002 10.1097/MCC.0000000000000886
79. Echeverri J Martins R Harenski K Kampf JP McPherson P Textoris J Exploring the cost-utility of a biomarker predicting persistent severe acute kidney injury: the case of c-c motif chemokine ligand 14 (CCL14) Clinicoecon Outcomes Res 2024 16 1 12 10.2147/CEOR.S434971 38235419
Echeverri J, Martins R, Harenski K, Kampf JP, McPherson P, Textoris J, et al. Exploring the cost-utility of a biomarker predicting persistent severe acute kidney injury: the case of c-c motif chemokine ligand 14 (CCL14). Clinicoecon Outcomes Res. 2024;16:1–12.38235419 10.2147/CEOR.S434971
