Ann Lab Med.  2021 Jan;41(1):1-15. 10.3343/alm.2021.41.1.1.

Biomarker-Guided Risk Assessment for Acute Kidney Injury: Time for Clinical Implementation?

Affiliations
  • 1Medical Faculty, University Clinic for Cardiology and Angiology, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany
  • 2Diaverum Renal Services, MVZ Potsdam, Potsdam, Germany
  • 3Medical Faculty, Otto-von-Guericke University Magdeburg, Magdeburg, Germany
  • 4Department of Nephrology and Endocrinology, Klinikum Ernst von Bergmann, Potsdam, Germany
  • 5Department of Medical Biometry and Epidemiology, University Medical Center HamburgEppendorf, Germany
  • 6Department of Cardiology, Immanuel Diakonie Bernau, Heart Center Brandenburg, Brandenburg Medical School Theodor Fontane (MHB), Germany
  • 7Institute of Social Medicine and Health Systems Research, Otto-von-Guericke University Magdeburg, Magdeburg, Germany
  • 8Faculty of Health Sciences Brandenburg, Potsdam, Germany

Abstract

Acute kidney injury (AKI) is a common and serious complication in hospitalized patients, which continues to pose a clinical challenge for treating physicians. The most recent Kidney Disease Improving Global Outcomes practice guidelines for AKI have restated the importance of earliest possible detection of AKI and adjusting treatment accordingly. Since the emergence of initial studies examining the use of neutrophil gelatinase-associated lipocalin (NGAL) and cycle arrest biomarkers, tissue inhibitor metalloproteinase-2 (TIMP-2) and insulin-like growth factor-binding protein (IGFBP7), for early diagnosis of AKI, a vast number of studies have investigated the accuracy and additional clinical benefits of these biomarkers. As proposed by the Acute Dialysis Quality Initiative, new AKI diagnostic criteria should equally utilize glomerular function and tubular injury markers for AKI diagnosis. In addition to refining our capabilities in kidney risk prediction with kidney injury biomarkers, structural disorder phenotypes referred to as “preclinical-” and “subclinical AKI” have been described and are increasingly recognized. Additionally, positive biomarker test findings were found to provide prognostic information regardless of an acute decline in renal function (positive serum creatinine criteria). We summarize and discuss the recent findings focusing on two of the most promising and clinically available kidney injury biomarkers, NGAL and cell cycle arrest markers, in the context of AKI phenotypes. Finally, we draw conclusions regarding the clinical implications for kidney risk prediction.

Keyword

Acute kidney injury; AKI phenotypes; Neutrophil gelatinase-associated lipocalin; Subclinical AKI; Preclinical AKI; Kidney biomarker; Serum creatinine; Kidney risk prediction; Cell cycle arrest biomarker

Figure

  • Fig. 1 Entities within the AKI spectrum. AKI phenotypes derived from a 2×2 table of four scenarios essentially differentiating changes in glomerular filtration function and structural tubular kidney injury. Abbreviations: AKI, acute kidney injury; BM, biomarker; SCr, serum creatinine; RFR, renal functional reserve.

  • Fig. 2 Revised conceptual model for AKI. White and light grey circles represent antecedents of AKI, i.e. patients at risk with suspected sepsis or those undergoing cardiac surgery. Acute kidney stress is defined as the preinjury phase that may transition into AKI. Sustained kidney stress will mitigate renal functional reserve and eventually transition into any variation of structural and functional kidney impairment (BM+/SCr-, BM-/SCr+, BM+/SCr+, and AKI-RRT). Structural kidney injury is indicated by a positive BM (+) finding. Arrows between the circles show potential transitions between AKI stages. AKI requiring RRT or patient death are associated adverse outcomes. Grey variations of the circles for kidney risk, kidney stress, and structural or functional kidney injury reflect increasing risk of adverse events [75, 93]. Abbreviations: AKI, acute kidney injury; SCr, serum creatinine; GFR, glomerular filtration rate; RFR, renal functional reserve; RRT, renal replacement therapy; BM, biomarker. Low risk for event Risk for event (observation zone), potential “kidney-stress”, “preclinical” or “subclinical” AKI Severe risk for event Critical risk for event

  • Fig. 3 Risk assessment chart for severe AKI. Consideration of NGAL cutoff concentrations provides the possibility of delineating a diagnostic “grey-zone” in clinical kidney risk assessment into an “Observational Zone” with the risk of kidney stress and preclinical or subclinical AKI. Severe AKI defined as RIFLE AKI stage injury or failure. Derived from data reported in [35]. Abbreviations: AKI, acute kidney injury; NGAL, neutrophil gelatinase-associated lipocalin; RIFLE, risk injury, failure, loss of kidney function, end-stage renal disease classification [70].


Cited by  4 articles

Predictive Value of Plasma NGAL:Hepcidin-25 for Major Adverse Kidney Events After Cardiac Surgery with Cardiopulmonary Bypass: A Pilot Study
Christian Albert, Michael Haase, Annemarie Albert, Martin Ernst, Siegfried Kropf, Rinaldo Bellomo, Sabine Westphal, Rüdiger C. Braun-Dullaeus, Anja Haase-Fielitz, Saban Elitok
Ann Lab Med. 2021;41(4):357-365.    doi: 10.3343/alm.2021.41.4.357.

Biomarker Rule-in or Rule-out in Patients With Acute Diseases for Validation of Acute Kidney Injury in the Emergency Department (BRAVA): A Multicenter Study Evaluating Urinary TIMP-2/IGFBP7
Hyun Suk Yang, Mina Hur, Kyeong Ryong Lee, Hanah Kim, Hahn Young Kim, Jong Won Kim, Mui Teng Chua, Win Sen Kuan, Horng Ruey Chua, Chagriya Kitiyakara, Phatthranit Phattharapornjaroen, Anchalee Chittamma, Thiyapha Werayachankul, Urmila Anandh, Sanjeeva Herath, Zoltan Endre, Andrea Rita Horvath, Paola Antonini, Salvatore Di Somma
Ann Lab Med. 2022;42(2):178-187.    doi: 10.3343/alm.2022.42.2.178.

New Issues With Neutrophil Gelatinase-associated Lipocalin in Acute Kidney Injury
Sun Young Cho, Mina Hur
Ann Lab Med. 2023;43(6):529-530.    doi: 10.3343/alm.2023.43.6.529.

Neutrophil Gelatinase-Associated Lipocalin Cutoff Value Selection and Acute Kidney Injury Classification System Determine Phenotype Allocation and Associated Outcomes
Annemarie Albert, Sebastian Radtke, Louisa Blume, Rinaldo Bellomo, Michael Haase, Philipp Stieger, Ulrich Paul Hinkel, Rüdiger C. Braun-Dullaeus, Christian Albert
Ann Lab Med. 2023;43(6):539-553.    doi: 10.3343/alm.2023.43.6.539.


Reference

1. Chertow GM, Burdick E, Honour M, Bonventre JV, Bates DW. Acute kidney injury, mortality, length of stay, and costs in hospitalized patients. J Am Soc Nephrol. 2005; 16:3365–70.
Article
2. Ronco C, Bellomo R, Kellum JA. Acute kidney injury. Lancet. 2019; 394:1949–64.
Article
3. Haase-Fielitz A, Ernst M, Lehmanski F, Gleumes J, Blödorn G, Spura A, et al. Treatment, clinical course, and cross-sectoral information transmission in patients with acute-on-chronic kidney injury. Bundesgesundheitsblatt-Gesundheitsforschung-Gesundheitsschutz. 2019; 62:773–81.
4. Kellum JA, Lameire N, Aspelin P, Barsoum RS, Burdmann EA, Goldstein SL, et al. Kidney disease: improving global outcomes (KDIGO) Acute Kidney Injury Work Group. KDIGO clinical practice guideline for acute kidney injury. Kidney Int Suppl. 2012; 2:1–138.
5. Kashani K, Rosner MH, Haase M, Lewington AJP, O’Donoghue DJ, Wilson FP, et al. Quality improvement goals for acute kidney injury. Clin J Am Soc Nephrol. 2019; 14:941–53.
Article
6. Haase M, Kribben A, Zidek W, Floege J, Albert C, Isermann B, et al. Electronic alerts for acute kidney injury. Dtsch Arztebl Int. 2017; 114:1–8.
Article
7. Haase-Fielitz A, Elitok S, Schostak M, Ernst M, Isermann B, Albert C, et al. The effects of intensive versus routine treatment in patients with acute kidney injury. Dtsch Arztebl Int. 2020; 117:289–96.
Article
8. McCullough PA, Shaw AD, Haase M, Bouchard J, Waikar SS, Siew ED, et al. Diagnosis of acute kidney injury using functional and injury biomarkers: workgroup statements from the tenth Acute Dialysis Quality Initiative Consensus Conference. Contrib Nephrol. 2013; 182:13–29.
Article
9. Huen SC, Parikh CR. Molecular phenotyping of clinical AKI with novel urinary biomarkers. Am J Physiol Renal Physiol. 2015; 309:F406–13.
Article
10. Haase M, Devarajan P, Haase-Fielitz A, Bellomo R, Cruz DN, Wagener G, et al. The outcome of neutrophil gelatinase-associated lipocalin-positive subclinical acute kidney injury: a multicenter pooled analysis of prospective studies. J Am Coll Cardiol. 2011; 57:1752–61.
11. Waikar SS, Bonventre JV. Creatinine kinetics and the definition of acute kidney injury. J Am Soc Nephrol. 2009; 20:672–9.
Article
12. Thongprayoon C, Cheungpasitporn W, Kashani K. Serum creatinine level, a surrogate of muscle mass, predicts mortality in critically ill patients. J Thorac Dis. 2016; 8:E305–11.
Article
13. Waikar SS, Betensky RA, Emerson SC, Bonventre JV. Imperfect gold standards for kidney injury biomarker evaluation. J Am Soc Nephrol. 2012; 23:13–21.
Article
14. Kim H, Hur M, Lee S, Marino R, Magrini L, Cardelli P, et al. Proenkephalin, neutrophil gelatinase-associated lipocalin, and estimated glomerular filtration rates in patients with sepsis. Ann Lab Med. 2017; 37:388–97.
Article
15. Zeng X, McMahon GM, Brunelli SM, Bates DW, Waikar SS. Incidence, outcomes, and comparisons across definitions of AKI in hospitalized individuals. Clin J Am Soc Nephrol. 2014; 9:12–20.
Article
16. Ji M, Lee YH, Hur M, Kim H, Cho HI, Yang HS, et al. Comparing results of five glomerular filtration rate-estimating equations in the Korean general population: MDRD study, revised Lund-Malmö, and three CKD-EPI equations. Ann Lab Med. 2016; 36:521–8.
Article
17. Wang X, Lin X, Xie B, Huang R, Yan Y, Liu S, et al. Early serum cystatin C-enhanced risk prediction for acute kidney injury post cardiac surgery: a prospective, observational, cohort study. Biomarkers. 2020; 25:20–6.
Article
18. Basu RK, Wong HR, Krawczeski CD, Wheeler DS, Manning PB, Chawla LS, et al. Combining functional and tubular damage biomarkers improves diagnostic precision for acute kidney injury after cardiac surgery. J Am Coll Cardiol. 2014; 64:2753–62.
Article
19. Stevens LA, Coresh J, Schmid CH, Feldman HI, Froissart M, Kusek J, et al. Estimating GFR using serum cystatin C alone and in combination with serum creatinine: a pooled analysis of 3,418 individuals with CKD. Am J Kidney Dis. 2008; 51:395–406.
Article
20. Haase M, Bellomo R, Devarajan P, Ma Q, Bennett MR, Möckel M, et al. Novel biomarkers early predict the severity of acute kidney injury after cardiac surgery in adults. Ann Thorac Surg. 2009; 88:124–30.
Article
21. Correa S, Morrow DA, Braunwald E, Davies RY, Goodrich EL, Murphy SA, et al. Cystatin C for risk stratification in patients after an acute coronary syndrome. J Am Heart Assoc. 2018; 7:e009077.
Article
22. Flores-Blanco PJ, Manzano-Fernández S, Pérez-Calvo JI, Pastor-Pérez FJ, Ruiz-Ruiz FJ, Carrasco-Sánchez FJ, et al. Cystatin C-based CKD-EPI equations and N-terminal pro-B-type natriuretic peptide for predicting outcomes in acutely decompensated heart failure. Clin Cardiol. 2015; 38:106–13.
Article
23. Denning GM, Ackermann LW, Barna TJ, Armstrong JG, Stoll LL, Weintraub NL, et al. Proenkephalin expression and enkephalin release are widely observed in non-neuronal tissues. Peptides. 2008; 29:83–92.
Article
24. Beunders R, Struck J, Wu AHB, Zarbock A, Di Somma S, Mehta RL, et al. Proenkephalin (PENK) as a novel biomarker for kidney function. J App Lab Med. 2017; 2:400–12.
Article
25. Ng LL, Squire IB, Jones DJL, Cao TH, Chan DCS, Sandhu JK, et al. Proenkephalin, renal dysfunction, and prognosis in patients with acute heart failure: a GREAT network study. J Am Coll Cardiol. 2017; 69:56–69.
26. Caironi P, Latini R, Struck J, Hartmann O, Bergmann A, Bellato V, et al. Circulating proenkephalin, acute kidney injury, and its improvement in patients with severe sepsis or shock. Clin Chem. 2018; 64:1361–9.
Article
27. Rosenqvist M, Bronton K, Hartmann O, Bergmann A, Struck J, Melander O. Proenkephalin a 119–159 (penKid)–a novel biomarker for acute kidney injury in sepsis: an observational study. BMC Emerg Med. 2019; 19:75.
28. Mossanen JC, Pracht J, Jansen TU, Buendgens L, Stoppe C, Goetzenich A, et al. Elevated soluble urokinase plasminogen activator receptor and proenkephalin serum levels predict the development of acute kidney injury after cardiac surgery. Int J Mol Sci. 2017; 18:1662.
Article
29. Haase M, Bellomo R, Albert C, Vanpoucke G, Thomas G, Laroy W, et al. The identification of three novel biomarkers of major adverse kidney events. Biomark Med. 2014; 8:1207–17.
Article
30. Ostermann M, Liu K. Pathophysiology of AKI. Best Pract Res Clin Anaesthesiol. 2017; 31:305–14.
Article
31. Chertow GM, Lazarus JM, Christiansen CL, Cook EF, Hammermeister KE, Grover F, et al. Preoperative renal risk stratification. Circulation. 1997; 95:878–84.
Article
32. Conlon PJ, Stafford-Smith M, White WD, Newman MF, King S, Winn MP, et al. Acute renal failure following cardiac surgery. Nephrol Dial Transplant. 1999; 14:1158–62.
Article
33. Haase-Fielitz A, Haase M, Bellomo R, Calzavacca P, Spura A, Baraki H, et al. Perioperative hemodynamic instability and fluid overload are associated with increasing acute kidney injury severity and worse outcome after cardiac surgery. Blood Purif. 2017; 43:298–308.
Article
34. Haase M, Bellomo R, Haase-Fielitz A. Novel biomarkers, oxidative stress, and the role of labile iron toxicity in cardiopulmonary bypass-associated acute kidney injury. J Am Coll Cardiol. 2010; 55:2024–33.
Article
35. Albert C, Zapf A, Haase M, Röver C, Pickering JW, Albert A, et al. Neutrophil gelatinase-associated lipocalin measured on clinical laboratory platforms for the prediction of acute kidney injury and the associated need for dialysis therapy: a systematic review and meta-analysis. Am J Kidney Dis. 2020; https://doi.org/10.1053/j.ajkd.2020.05.015.
Article
36. Haase M, Bellomo R, Devarajan P, Schlattmann P, Haase-Fielitz A. NGAL Meta-Analysis Investigator Group. 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; 54:1012–24.
Article
37. Haase-Fielitz A, Bellomo R, Devarajan P, Bennett M, Story D, Matalanis G, et al. The predictive performance of plasma neutrophil gelatinase-associated lipocalin (NGAL) increases with grade of acute kidney injury. Nephrol Dial Transplant. 2009; 24:3349–54.
Article
38. Mishra J, Dent C, Tarabishi R, Mitsnefes MM, Ma Q, Kelly C, et al. Neutrophil gelatinase-associated lipocalin (NGAL) as a biomarker for acute renal injury after cardiac surgery. Lancet. 2005; 365:1231–8.
Article
39. Kim SY, Jeong TD, Lee W, Chun S, Sunwoo S, Kim SB, et al. Plasma neutrophil gelatinase-associated lipocalin as a marker of tubular damage in diabetic nephropathy. Ann Lab Med. 2018; 38:524–9.
Article
40. de Geus HRH, Betjes MG, Schaick Rv, Groeneveld JABJ. Plasma NGAL similarly predicts acute kidney injury in sepsis and nonsepsis. Biomark Med. 2013; 7:415–21.
Article
41. Pickering JW, Endre ZH. The clinical utility of plasma neutrophil gelatinase-associated lipocalin in acute kidney injury. Blood Purif. 2013; 35:295–302.
Article
42. Zhou F, Luo Q, Wang L, Han L. Diagnostic value of neutrophil gelatinase-associated lipocalin for early diagnosis of cardiac surgery-associated acute kidney injury: a meta-analysis. Eur J Cardiothorac Surg. 2016; 49:746–55.
Article
43. 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; 66:993–1005.
Article
44. Nemeth E, Ganz T. The role of hepcidin in iron metabolism. Acta Haematol. 2009; 122:78–86.
Article
45. Mori K, Lee HT, Rapoport D, Drexler IR, Foster K, Yang J, et al. Endocytic delivery of lipocalin-siderophore-iron complex rescues the kidney from ischemia-reperfusion injury. J Clin Invest. 2005; 115:610–21.
Article
46. Ho J, Reslerova M, Gali B, Gao A, Bestland J, Rush DN, et al. Urinary hepcidin-25 and risk of acute kidney injury following cardiopulmonary bypass. Clin J Am Soc Nephrol. 2011; 6:2340–6.
Article
47. Prowle JR, Ostland V, Calzavacca P, Licari E, Ligabo EV, Echeverri JE, et al. Greater increase in urinary hepcidin predicts protection from acute kidney injury after cardiopulmonary bypass. Nephrol Dial Transplant. 2012; 27:595–602.
Article
48. van Swelm RPL, Wetzels JFM, Verweij VGM, Laarakkers CMM, Pertijs JCLM, van der Wijst J, et al. Renal handling of circulating and renal-synthesized hepcidin and its protective effects against hemoglobin-mediated kidney injury. J Am Soc Nephrol. 2016; 27:2720–32.
Article
49. Yang QH, Liu DW, Long Y, Liu HZ, Chai WZ, Wang XT. Acute renal failure during sepsis: potential role of cell cycle regulation. J Infect. 2009; 58:459–64.
Article
50. 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:R25.
Article
51. Song Z, Ma Z, Qu K, Liu S, Niu W, Lin T. Diagnostic prediction of urinary [TIMP-2]×[IGFBP-7] for acute kidney injury: a meta-analysis exploring detection time and cutoff levels. Oncotarget. 2017; 8:100631–9.
52. Food and Drug Administration. Letter to Astute Medical. 2014. Available from: http://www.accessdata.fda.gov/cdrh_docs/pdf13/den130031.pdf. Accessed July 11, 2020.
53. Heung M, Ortega LM, Chawla LS, Wunderink RG, Self WH, Koyner JL, et al. Common chronic conditions do not affect performance of cell cycle arrest biomarkers for risk stratification of acute kidney injury. Nephrol Dial Transplant. 2016; 31:1633–40.
Article
54. Emlet DR, Pastor-Soler N, Marciszyn A, Wen X, Gomez H, Humphries WH 4th, 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:F284–96.
Article
55. Hoste E, Bihorac A, Al-Khafaji A, Ortega LM, Ostermann M, Hasse M, et al. Identification and validation of biomarkers of persistent acute kidney injury: the RUBY study. Intensive Care Med. 2020; 46:943–53.
Article
56. Codorniu A, Lemasle L, Legrand M, Blet A, Mebazaa A, Gayat E. Methods used to assess the performance of biomarkers for the diagnosis of acute kidney injury: a systematic review and meta-analysis. Biomarkers. 2018; 23:766–72.
Article
57. Hoste EAJ, McCullough PA, Kashani K, Chawla LS, Joannidis M, Shaw AD, et al. Derivation and validation of cutoffs for clinical use of cell cycle arrest biomarkers. Nephrol Dial Transplant. 2014; 29:2054–61.
Article
58. Bihorac A, Chawla LS, Shaw AD, Al-Khafaji A, Davison DL, DeMuth GE, et al. Validation of cell-cycle arrest biomarkers for acute kidney injury using clinical adjudication. Am J Respir Crit Care Med. 2014; 189:932–9.
Article
59. Kashani K, Cheungpasitporn W, Ronco C. Biomarkers of acute kidney injury: the pathway from discovery to clinical adoption. Clin Chem Lab Med. 2017; 55:1074–89.
Article
60. Parikh CR, Coca SG, Thiessen-Philbrook H, Shlipak MG, Koyner JL, Wang Z, et al. Postoperative biomarkers predict acute kidney injury and poor outcomes after adult cardiac surgery. J Am Soc Nephrol. 2011; 22:1748–57.
Article
61. Parikh CR, Devarajan P, Zappitelli M, Sint K, Thiessen-Philbrook H, Li S, et al. Postoperative biomarkers predict acute kidney injury and poor outcomes after pediatric cardiac surgery. J Am Soc Nephrol. 2011; 22:1737–47.
Article
62. Di Somma S, Magrini L, De Berardinis B, Marino R, Ferri E, Moscatelli P, et al. 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. 2013; 17:R29.
Article
63. Nickolas TL, Schmidt-Ott KM, Canetta P, Forster C, Singer E, Sise M, et al. Diagnostic and prognostic stratification in the Emergency Department using urinary biomarkers of nephron damage: a multicenter prospective cohort study. J Am Coll Cardiol. 2012; 59:246–55.
64. Hjortrup PB, Haase N, Treschow F, M⊘ller MH, Perner A. Predictive value of NGAL for use of renal replacement therapy in patients with severe sepsis. Acta Anaesthesiol Scand. 2015; 59:25–34.
Article
65. Mårtensson J, Glassford NJ, Jones S, Eastwood GM, Young H, Peck L, et al. Urinary neutrophil gelatinase-associated lipocalin to hepcidin ratio as a biomarker of acute kidney injury in intensive care unit patients. Minerva Anestesiol. 2015; 81:1192–200.
66. Ralib AM, Pickering JW, Shaw GM, Than MP, George PM, Endre ZH. The clinical utility window for acute kidney injury biomarkers in the critically ill. Crit Care. 2014; 18:601.
Article
67. Endre ZH, Pickering JW, Walker RJ, Devarajan P, Edelstein CL, Bonventre JV, et al. Improved performance of urinary biomarkers of acute kidney injury in the critically ill by stratification for injury duration and baseline renal function. Kidney Int. 2011; 79:1119–30.
Article
68. Haase-Fielitz A, Haase M, Devarajan P. Neutrophil gelatinase-associated lipocalin as a biomarker of acute kidney injury: a critical evaluation of current status. Ann Clin Biochem. 2014; 51:335–51.
Article
69. Haase M, Kellum JA, Ronco C. Subclinical AKI–an emerging syndrome with important consequences. Nat Rev Nephrol. 2012; 8:735–9.
Article
70. Bellomo R, Ronco C, Kellum JA, Mehta RL, Palevsky P. Acute Dialysis Quality Initiative workgroup. 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. 2004; 8:R204–12.
71. Twerenbold R, Badertscher P, Boeddinghaus J, Nestelberger T, Wildi K, Puelacher C, et al. 0/1-hour triage algorithm for myocardial infarction in patients with renal dysfunction. Circulation. 2018; 137:436–51.
72. Kellum JA, Devarajan P. What can we expect from biomarkers for acute kidney injury? Biomark Med. 2014; 8:1239–45.
Article
73. Albert C, Albert A, Kube J, Bellomo R, Wettersten N, Kuppe H, et al. Urinary biomarkers may provide prognostic information for subclinical acute kidney injury after cardiac surgery. J Thorac Cardiovasc Surg. 2018; 155:2441–52.
Article
74. Joannidis M, Forni LG, Haase M, Koyner J, Shi J, Kashani K, et al. Use of cell cycle arrest biomarkers in conjunction with classical markers of acute kidney injury. Crit Care Med. 2019; 47:e820–6.
Article
75. Moledina DG, Parikh CR. Phenotyping of acute kidney injury: beyond serum creatinine. Semin Nephrol. 2018; 38:3–11.
Article
76. Sharma A, Mucino MJ, Ronco C. Renal functional reserve and renal recovery after acute kidney injury. Nephron Clin Pract. 2014; 127:94–100.
Article
77. Kangasniemi OP, Biancari F, Luukkonen J, Vuorisalo S, Satta J, Pokela R, et al. Preoperative C-reactive protein is predictive of long-term outcome after coronary artery bypass surgery. Eur J Cardiothorac Surg. 2006; 29:983–5.
Article
78. Xie Y, Ankawi G, Yang B, Garzotto F, Passannante A, Breglia A, et al. Tissue inhibitor metalloproteinase-2 (TIMP-2)•IGF-binding protein-7 (IGFBP-7) levels are associated with adverse outcomes in patients in the intensive care unit with acute kidney injury. Kidney Int. 2019; 95:1486–93.
79. Albert C, Haase M, Albert A, Kropf S, Bellomo R, Westphal S, et al. Urinary biomarkers may complement the Cleveland score for prediction of adverse kidney events after cardiac surgery: a pilot study. Ann Lab Med. 2020; 40:131–41.
Article
80. Herget-Rosenthal S, Poppen D, Hüsing J, Marggraf G, Pietruck F, Jakob HG, et al. Prognostic value of tubular proteinuria and enzymuria in nonoliguric acute tubular necrosis. Clin Chem. 2004; 50:552–8.
Article
81. Katz N, Ronco C. Acute kidney stress–a useful term based on evolution in the understanding of acute kidney injury. Crit Care. 2016; 20:23.
Article
82. de Geus HRH, Ronco C, Haase M, Jacob L, Lewington A, Vincent JL. The cardiac surgery-associated neutrophil gelatinase-associated lipocalin (CSA-NGAL) score: a potential tool to monitor acute tubular damage. J Thorac Cardiovasc Surg. 2016; 151:1476–81.
Article
83. Vanmassenhove J, Van Biesen W, Vanholder R, Lameire N. Subclinical AKI: ready for primetime in clinical practice? J Nephrol. 2019; 32:9–16.
Article
84. Au V, Feit J, Barasch J, Sladen RN, Wagener G. Urinary neutrophil gelatinase-associated lipocalin (NGAL) distinguishes sustained from transient acute kidney injury after general surgery. Kidney Int Rep. 2016; 1:3–9.
Article
85. Damman K, Valente MAE, Voors AA, O’Connor CM, van Veldhuisen DJ, Hillege HL. Renal impairment, worsening renal function, and outcome in patients with heart failure: an updated meta-analysis. Eur Heart J. 2014; 35:455–69.
Article
86. Heywood JT, Fonarow GC, Costanzo MR, Mathur VS, Wigneswaran JR, Wynne J, et al. High prevalence of renal dysfunction and its impact on outcome in 118,465 patients hospitalized with acute decompensated heart failure: a report from the ADHERE database. J Card Fail. 2007; 13:422–30.
Article
87. Maisel AS, Wettersten N, van Veldhuisen DJ, Mueller C, Filippatos G, Nowak R, et al. Neutrophil gelatinase-associated lipocalin for acute kidney injury during acute heart failure hospitalizations: the AKINESIS study. J Am Coll Cardiol. 2016; 68:1420–31.
88. Wettersten N, Horiuchi Y, van Veldhuisen DJ, Mueller C, Filippatos G, Nowak R, et al. Short-term prognostic implications of serum and urine neutrophil gelatinase-associated lipocalin in acute heart failure: findings from the AKINESIS study. Eur J Heart Fail. 2020; 22:251–63.
Article
89. Dupont M, Shrestha K, Singh D, Awad A, Kovach C, Scarcipino M, et al. Lack of significant renal tubular injury despite acute kidney injury in acute decompensated heart failure. Eur J Heart Fail. 2012; 14:597–604.
Article
90. Singer E, Elger A, Elitok S, Kettritz R, Nickolas TL, Barasch J, et al. Urinary neutrophil gelatinase-associated lipocalin distinguishes pre-renal from intrinsic renal failure and predicts outcomes. Kidney Int. 2011; 80:405–14.
Article
91. Bellomo R, Bagshaw S, Langenberg C, Ronco C. Pre-renal azotemia: a flawed paradigm in critically ill septic patients? Contrib Nephrol. 2007; 156:1–9.
Article
92. Vijayan A, Faubel S, Askenazi DJ, Cerda J, Fissell WH, Heung M, et al. Clinical use of the urine biomarker [TIMP-2]×[IGFBP-7] for acute kidney injury risk assessment. Am J Kidney Dis. 2016; 68:19–28.
93. Bell M, Larsson A, Venge P, Bellomo R, Mårtensson J. Assessment of cell-cycle arrest biomarkers to predict early and delayed acute kidney injury. Dis Markers. 2015; 2015:158658.
Article
94. Delcroix G, Gillain N, Moonen M, Radermacher L, Damas F, Minon JM, et al. NGAL usefulness in the Intensive Care Unit three hours after cardiac surgery. ISRN Nephrol. 2012; 2013:865164.
Article
95. 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; 25:1063–71.
Article
96. Singer E, Schrezenmeier EV, Elger A, Seelow ER, Krannich A, Luft FC, et al. Urinary NGAL-positive acute kidney injury and poor long-term outcomes in hospitalized patients. Kidney Int Rep. 2016; 1:114–24.
Article
97. Koyner JL, Shaw AD, Chawla LS, Hoste EAJ, Bihorac A, Kashani K, et al. Tissue Inhibitor Metalloproteinase-2 (TIMP-2)•IGF-Binding Protein-7 (IGFBP-7) levels are associated with adverse long-term outcomes in patients with AKI. J Am Soc Nephrol. 2015; 26:1747–54.
Article
98. Hsu CY, Chinchilli VM, Coca S, Devarajan P, Ghahramani N, Go AS, et al. Post–acute kidney injury proteinuria and subsequent kidney disease progression: the Assessment, Serial Evaluation, and Subsequent Sequelae in Acute Kidney Injury (ASSESS-AKI) study. JAMA Intern Med. 2020; 180:402–10.
99. 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; 44:323–36.
Article
100. Pickering JW, Endre ZH. Linking injury to outcome in acute kidney injury: a matter of sensitivity. PLoS One. 2013; 8:e62691.
Article
101. Kim H, Hur M, Struck J, Bergmann A, Di Somma S. Proenkephalin predicts organ failure, renal replacement therapy, and mortality in patients with sepsis. Ann Lab Med. 2020; 40:466–73.
Article
102. Pickering JW, Endre ZH. New metrics for assessing diagnostic potential of candidate biomarkers. Clin J Am Soc Nephrol. 2012; 7:1355–64.
Article
103. Pencina MJ, D’Agostino RB Sr, D’Agostino RB Jr, Vasan RS. Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond. Stat Med. 2008; 27:157–72.
Article
104. Choi N, Rigatto C, Zappitelli M, Gao A, Christie S, Hiebert B, et al. Urinary Hepcidin-25 is elevated in patients that avoid acute kidney injury following cardiac surgery. Can J Kidney Health Dis. 2018; 5:20543581 17744224.
Article
105. Levante C, Ferrari F, Manenti C, Husain-Syed F, Scarpa M, Hinna Danesi T, et al. Routine adoption of TIMP2 and IGFBP-7 biomarkers in cardiac surgery for early identification of acute kidney injury. Int J Artif Organs. 2017; 40:714–8.
Article
106. Leaf DE, Rajapurkar M, Lele SS, Mukhopadhyay B, Boerger EAS, Mc Causland FR, et al. Iron, hepcidin, and death in human AKI. J Am Soc Nephrol. 2019; 30:493–504.
Article
107. Rizo-Topete LM, Rosner MH, Ronco C. Acute kidney injury risk assessment and the Nephrology Rapid Response Team. Blood Purif. 2017; 43:82–8.
Article
108. Haase-Fielitz A, Albert C, Haase M. Early warning systems in acute kidney insufficiency. Nephrologe. 2017; 12:318–22.
109. Albert C, Albert A, Bellomo R, Kropf S, Devarajan P, Westphal S, et al. Urinary neutrophil gelatinase-associated lipocalin-guided risk assessment for major adverse kidney events after open-heart surgery. Biomark Med. 2018; 12:975–85.
Article
110. 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; 43:1551–61.
Article
111. 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; 267:1013–20.
112. Parikh A, Rizzo JA, Canetta P, Forster C, Sise M, Maarouf O, et al. Does NGAL reduce costs? A cost analysis of urine NGAL (uNGAL) & serum creatinine (sCr) for acute kidney injury (AKI) diagnosis. PLoS One. 2017; 12:e0178091.
113. Meeusen JW, Rule AD, Voskoboev N, Baumann NA, Lieske JC. Performance of cystatin C– and creatinine-based estimated glomerular filtration rate equations depends on patient characteristics. Clin Chem. 2015; 61:1265–72.
Article
114. Ferguson TW, Komenda P, Tangri N. Cystatin C as a biomarker for estimating glomerular filtration rate. Curr Opin Nephrol Hypertens. 2015; 24:295–300.
Article
115. Luis-Lima S, Escamilla-Cabrera B, Negrín-Mena N, Estupiñán S, Delgado-Mallén P, Marrero-Miranda D, et al. Chronic kidney disease staging with cystatin C or creatinine-based formulas: flipping the coin. Nephrol Dial Transplant. 2019; 34:287–94.
Article
116. Bongiovanni C, Magrini L, Salerno G, Gori CS, Cardelli P, Hur M, et al. Serum cystatin C for the diagnosis of acute kidney injury in patients admitted in the emergency department. Dis Markers. 2015; 2015:416059.
Article
117. Marino R, Struck J, Hartmann O, Maisel AS, Rehfeldt M, Magrini L, et al. Diagnostic and short-term prognostic utility of plasma pro-enkephalin (pro-ENK) for acute kidney injury in patients admitted with sepsis in the emergency department. J Nephrol. 2015; 28:717–24.
Article
118. 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; 3:1424–33.
Article
119. Doemming S, Simon TP, Humbs A, Martin L, Bruells C, Hartmann O, et al. Pro-enkephalin in plasma of surgical icu-patients with sepsis - a pilot study. Intensive Care Med Exp. 2015; 3(S1):A256.
Article
120. Nadim MK, Forni LG, Bihorac A, Hobson C, Koyner JL, Shaw A, et al. Cardiac and vascular surgery–associated acute kidney injury: the 20th International Consensus Conference of the ADQI (Acute Disease Quality Initiative) Group. J Am Heart Assoc. 2018; 7:e008834.
Article
121. Boeddinghaus J, Nestelberger T, Twerenbold R, Wildi K, Badertscher P, Cupa J, et al. Direct comparison of 4 very early rule-out strategies for acute myocardial infarction using high-sensitivity cardiac troponin I. Circulation. 2017; 135:1597–611.
122. Maisel AS, Krishnaswamy P, Nowak RM, McCord J, Hollander JE, Duc P, et al. Rapid measurement of B-type natriuretic peptide in the emergency diagnosis of heart failure. N Engl J Med. 2002; 347:161–7.
Article
123. Pufulete M, Maishman R, Dabner L, Higgins JPT, Rogers CA, Dayer M, et al. B-type natriuretic peptide-guided therapy for heart failure (HF): a systematic review and meta-analysis of individual participant data (IPD) and aggregate data. Syst Rev. 2018; 7:112.
Article
124. de Grooth HJ, Parienti JJ, Schetz M. AKI biomarkers are poor discriminants for subsequent need for renal replacement therapy, but do not disqualify them yet. Intensive Care Med. 2018; 44:1156–8.
Article
125. Devarajan P. NGAL for the detection of acute kidney injury in the emergency room. Biomark Med. 2014; 8:217–9.
Article
126. Devarajan P, Murray P. Biomarkers in acute kidney injury: are we ready for prime time? Nephron Clin Pract. 2014; 127:176–9.
Article
127. Doi K, Yuen PST, Eisner C, Hu X, Leelahavanichkul A, Schnermann J, et al. Reduced production of creatinine limits its use as marker of kidney injury in sepsis. J Am Soc Nephrol. 2009; 20:1217–21.
Article
128. Liangos O, Tighiouart H, Perianayagam MC, Kolyada A, Han WK, Wald R, et al. Comparative analysis of urinary biomarkers for early detection of acute kidney injury following cardiopulmonary bypass. Biomarkers. 2009; 14:423–31.
Article
Full Text Links
  • ALM
Actions
Cited
CITED
export Copy
Close
Share
  • Twitter
  • Facebook
Similar articles
Copyright © 2024 by Korean Association of Medical Journal Editors. All rights reserved.     E-mail: koreamed@kamje.or.kr