본문 바로가기
KERD
논문KCI 등재

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

Albert Annemarie|Haase Michael|Haase-Fielitz Anja|Albert Christian|Zapf Antonia|Braun-Dullaeus Rüdiger Christian
대한진단검사의학회 (Korean Society For Laboratory Medicine)|2021.01|Annals of Laboratory Medicine|제41권 제1호|pp. 1-15|DOI 10.3343/alm.2021.41.1.1

2

조회

0

다운로드

4

인용

0

참고문헌

키워드

Acute kidney injuryNeutrophil gelatinase-associated lipocalinSerum creatinineSubclinical AKIAKI phenotypesPreclinical AKIKidney biomarkerKidney risk predictionCell cycle arrest biomarker
주제분류병리학

초록

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.

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.

참고문헌 (128)

  1. Chertow GM, "Acute kidney injury, mortality, length of stay, and costs in hospitalized patients", J Am Soc Nephrol, 16, pp.3365~3370 (2005)
  2. Ronco C, "Acute kidney injury", Lancet, 394, pp.1949~1964 (2019)
  3. Haase-Fielitz A, "Treatment, clinical course, and cross-sectoral information transmission in patients with acute-on-chronic kidney injury", Bundesgesundheitsblatt- Gesundheitsforschung- Gesundheitsschutz, 62, pp.773~781 (2019)
  4. Kellum JA, "Kidney disease: improving global outcomes (KDIGO)Acute Kidney Injury Work Group. KDIGO clinical practice guideline for acute kidney", Kidney Int Suppl, 2, pp.1~138 (2012)
  5. Kashani K, "Quality improvement goals for acute kidney injury", Clin J Am Soc Nephrol, 14, pp.941~953 (2019)
  6. Haase M, "Electronic alerts for acute kidney injury", Dtsch Arztebl Int, 114, pp.1~8 (2017)
  7. Haase-Fielitz A, "The effects of intensive versus routine treatment in patients with acute kidney injury", Dtsch Arztebl Int, 117, pp.289~296 (2020)
  8. McCullough PA, "Diagnosis of acute kidney injury using functional and injury biomarkers: workgroup statements from the tenth Acute Dialysis Quality Initiative Consensus Conference", Contrib Nephrol, 182, pp.13~29 (2013)
  9. Huen SC, "Molecular phenotyping of clinical AKI with novel urinary biomarkers", Am J Physiol Renal Physiol, 309, pp.F406~F413 (2015)
  10. Haase M, "The outcome of neutrophil gelatinase-associated lipocalin-positive subclinical acute kidney injury: a multicenter pooled analysis of prospective studies", J Am Coll Cardiol, 57, pp.1752~1761 (2011)
  11. Waikar SS, "Creatinine kinetics and the definition of acute kidney injury", J Am Soc Nephrol, 20, pp.672~679 (2009)
  12. Thongprayoon C, "Serum creatinine level, a surrogate of muscle mass, predicts mortality in critically ill patients", J Thorac Dis, 8, pp.E305~E311 (2016)
  13. Waikar SS, "Imperfect gold standards for kidney injury biomarker evaluation", J Am Soc Nephrol, 23, pp.13~21 (2012)
  14. 김한아, "Proenkephalin, Neutrophil Gelatinase-Associated Lipocalin, and Estimated Glomerular Filtration Rates in Patients With Sepsis", Annals of Laboratory Medicine, 37(5), pp.388~397 (2017), 대한진단검사의학회
  15. Zeng X, "Incidence, outcomes, and comparisons across definitions of AKI in hospitalized individuals", Clin J Am Soc Nephrol, 9, pp.12~20 (2014)
  16. Misuk Ji, "Comparing Results of Five Glomerular Filtration Rate-Estimating Equations in the Korean General Population: MDRD Study, Revised Lund-Malmӧ, and Three CKD-EPI Equations", Annals of Laboratory Medicine, 36(6), pp.521~528 (2016), 대한진단검사의학회
  17. Wang X, "Early serum cystatin C-enhanced risk prediction for acute kidney injury post cardiac surgery: a prospective, observational, cohort study", Biomarkers, 25, pp.20~26 (2020)
  18. Basu RK, "Combining functional and tubular damage biomarkers improves diagnostic precision for acute kidney injury after cardiac surgery", J Am Coll Cardiol, 64, pp.2753~2762 (2014)
  19. Stevens LA, "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, 51, pp.395~406 (2008)
  20. Haase M, "Novel biomarkers early predict the severity of acute kidney injury after cardiac surgery in adults", Ann Thorac Surg, 88, pp.124~130 (2009)
  21. Correa S, "Cystatin C for risk stratification in patients after an acute coronary syndrome", J Am Heart Assoc, 7, pp.e009077~ (2018)
  22. Flores-Blanco PJ, "Cystatin C-based CKDEPI equations and N-terminal pro-B-type natriuretic peptide for predicting outcomes in acutely decompensated heart failure", Clin Cardiol, 38, pp.106~113 (2015)
  23. Denning GM, "Proenkephalin expression and enkephalin release are widely observed in non-neuronal tissues", Peptides, 29, pp.83~92 (2008)
  24. Beunders R, "Proenkephalin (PENK) as a novel biomarker for kidney function", J App Lab Med, 2, pp.400~412 (2017)
  25. Ng LL, "Proenkephalin, renal dysfunction, and prognosis in patients with acute heart failure: a GREAT network study", J Am Coll Cardiol, 69, pp.56~69 (2017)
  26. Caironi P, "Circulating proenkephalin, acute kidney injury, and its improvement in patients with severe sepsis or shock", Clin Chem, 64, pp.1361~1369 (2018)
  27. Rosenqvist M, "Proenkephalin a 119–159 (penKid)–a novel biomarker for acute kidney injury in sepsis: an observational study", BMC Emerg Med, 19, pp.75~ (2019)
  28. Mossanen JC, "Elevated soluble urokinase plasminogen activator receptor and proenkephalin serum levels predict the development of acute kidney injury after cardiac surgery", Int J Mol Sci, 18, pp.1662~ (2017)
  29. Haase M, "The identification of three novel biomarkers of major adverse kidney events", Biomark Med, 8, pp.1207~1217 (2014)
  30. Ostermann M, "Pathophysiology of AKI", Best Pract Res Clin Anaesthesiol, 31, pp.305~314 (2017)
  31. Chertow GM, "Preoperative renal risk stratification", Circulation, 95, pp.878~884 (1997)
  32. Conlon PJ, "Acute renal failure following cardiac surgery", Nephrol Dial Transplant, 14, pp.1158~1162 (1999)
  33. Haase-Fielitz A, "Perioperative hemodynamic instability and fluid overload are associated with increasing acute kidney injury severity and worse outcome after cardiac surgery", Blood Purif, 43, pp.298~308 (2017)
  34. Haase M, "Novel biomarkers, oxidative stress, and the role of labile iron toxicity in cardiopulmonary bypassassociated acute kidney injury", J Am Coll Cardiol, 55, pp.2024~2033 (2010)
  35. Christian Albert, "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", American Journal of Kidney Diseases, 76(6), pp.826~841.e1 (2020), Elsevier BV[DOI]
  36. Haase M, "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, 54, pp.1012~1024 (2009)
  37. Haase-Fielitz A, "The predictive performance of plasma neutrophil gelatinase-associated lipocalin (NGAL) increases with grade of acute kidney injury", Nephrol Dial Transplant, 24, pp.3349~3354 (2009)
  38. Mishra J, "Neutrophil gelatinase-associated lipocalin (NGAL) as a biomarker for acute renal injury after cardiac surgery", Lancet, 365, pp.1231~1238 (2005)
  39. 김소영, "Plasma Neutrophil Gelatinase-Associated Lipocalin as a Marker of Tubular Damage in Diabetic Nephropathy", Annals of Laboratory Medicine, 38(6), pp.524~529 (2018), 대한진단검사의학회
  40. de Geus HRH, "Plasma NGAL similarly predicts acute kidney injury in sepsis and nonsepsis", Biomark Med, 7, pp.415~421 (2013)
  41. Pickering JW, "The clinical utility of plasma neutrophil gelatinase-associated lipocalin in acute kidney injury", Blood Purif, 35, pp.295~302 (2013)
  42. Zhou F, "Diagnostic value of neutrophil gelatinase-associated lipocalin for early diagnosis of cardiac surgery-associated acute kidney injury: a meta-analysis", Eur J Cardiothorac Surg, 49, pp.746~755 (2016)
  43. Ho J, "Urinary, plasma, and serum biomarkers’ utility for predicting acute kidney injury associated with cardiac surgery in adults: a meta-analysis", Am J Kidney Dis, 66, pp.993~1005 (2015)
  44. Nemeth E, "The role of hepcidin in iron metabolism", Acta Haematol, 122, pp.78~86 (2009)
  45. Mori K, "Endocytic delivery of lipocalin-siderophore-iron complex rescues the kidney from ischemia-reperfusion injury", J Clin Invest, 115, pp.610~621 (2005)
  46. Ho J, "Urinary hepcidin-25 and risk of acute kidney injury following cardiopulmonary bypass", Clin J Am Soc Nephrol, 6, pp.2340~2346 (2011)
  47. Prowle JR, "Greater increase in urinary hepcidin predicts protection from acute kidney injury after cardiopulmonary bypass", Nephrol Dial Transplant, 27, pp.595~602 (2012)
  48. van Swelm RPL, "Renal handling of circulating and renalsynthesized hepcidin and its protective effects against hemoglobin-mediated kidney injury", J Am Soc Nephrol, 27, pp.2720~2732 (2016)
  49. Yang QH, "Acute renal failure during sepsis: potential role of cell cycle regulation", J Infect, 58, pp.459~464 (2009)
  50. Kashani K, "Discovery and validation of cell cycle arrest biomarkers in human acute kidney injury", Crit Care, 17, pp.R25~ (2013)
  51. for acute kidney injury: a meta-analysis exploring detection time and cutoff levels, "Oncotarget", 2017, 100631~100639
  52. "Food and Drug Administration Letter to Astute Medical 2014"[URL]
  53. Heung M, "Common chronic conditions do not affect performance of cell cycle arrest biomarkers for risk stratification of acute kidney injury", Nephrol Dial Transplant, 31, pp.1633~1640 (2016)
  54. Emlet DR, "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, 312, pp.F284~F296 (2017)
  55. Hoste E, "Identification and validation of biomarkers of persistent acute kidney injury: the RUBY study", Intensive Care Med, 46, pp.943~953 (2020)
  56. Codorniu A, "Methods used to assess the performance of biomarkers for the diagnosis of acute kidney injury: a systematic review and meta-analysis", Biomarkers, 23, pp.766~772 (2018)
  57. Hoste EAJ, "Derivation and validation of cutoffs for clinical use of cell cycle arrest biomarkers", Nephrol Dial Transplant, 29, pp.2054~2061 (2014)
  58. Bihorac A, "Validation of cell-cycle arrest biomarkers for acute kidney injury using clinical adjudication", Am J Respir Crit Care Med, 189, pp.932~939 (2014)
  59. Kashani K, "Biomarkers of acute kidney injury: the pathway from discovery to clinical adoption", Clin Chem Lab Med, 55, pp.1074~1089 (2017)
  60. Parikh CR, "Postoperative biomarkers predict acute kidney injury and poor outcomes after adult cardiac surgery", J Am Soc Nephrol, 22, pp.1748~1757 (2011)
  61. Parikh CR, "Postoperative biomarkers predict acute kidney injury and poor outcomes after pediatric cardiac surgery", J Am Soc Nephrol, 22, pp.1737~1747 (2011)
  62. Di Somma S, "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, 17, pp.R29~ (2013)
  63. Nickolas TL, "Diagnostic and prognostic stratification in the Emergency Department using urinary biomarkers of nephron damage: a multicenter prospective cohort study", J Am Coll Cardiol, 59, pp.246~255 (2012)
  64. Hjortrup PB, "Predictive value of NGAL for use of renal replacement therapy in patients with severe sepsis", Acta Anaesthesiol Scand, 59, pp.25~34 (2015)
  65. Mårtensson J, "Urinary neutrophil gelatinase-associated lipocalin to hepcidin ratio as a biomarker of acute kidney injury in intensive care unit patients", Minerva Anestesiol, 81, pp.1192~1200 (2015)
  66. Ralib AM, "The clinical utility window for acute kidney injury biomarkers in the critically ill", Crit Care, 18, pp.601~ (2014)
  67. Endre ZH, "Improved performance of urinary biomarkers of acute kidney injury in the critically ill by stratification for injury duration and baseline renal function", Kidney Int, 79, pp.1119~1130 (2011)
  68. Haase-Fielitz A, "Neutrophil gelatinase-associated lipocalin as a biomarker of acute kidney injury: a critical evaluation of current status", Ann Clin Biochem, 51, pp.335~351 (2014)
  69. Haase M, "Subclinical AKI–an emerging syndrome with important consequences", Nat Rev Nephrol, 8, pp.735~739 (2012)
  70. Bellomo R, "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, 8, pp.R204~R212 (2004)
  71. Twerenbold R, "0", 1-hour triage algorithm for myocardial infarction in patients with renal dysfunction, 2018, pp.137, 436~451
  72. Kellum JA, "What can we expect from biomarkers for acute kidney injury?", Biomark Med, 8, pp.1239~1245 (2014)
  73. Albert C, "Urinary biomarkers may provide prognostic information for subclinical acute kidney injury after cardiac surgery", J Thorac Cardiovasc Surg, 155, pp.2441~2452 (2018)
  74. Joannidis M, "Use of cell cycle arrest biomarkers in conjunction with classical markers of acute kidney injury", Crit Care Med, 47, pp.e820~e826 (2019)
  75. Moledina DG, "Phenotyping of acute kidney injury: beyond serum creatinine", Semin Nephrol, 38, pp.3~11 (2018)
  76. Sharma A, "Renal functional reserve and renal recovery after acute kidney injury", Nephron Clin Pract, 127, pp.94~100 (2014)
  77. Kangasniemi OP, "Preoperative C-reactive protein is predictive of long-term outcome after coronary artery bypass surgery", Eur J Cardiothorac Surg, 29, pp.983~985 (2006)
  78. Xie Y, "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, 95, pp.1486~1493 (2019)
  79. Christian Albert, "Urinary Biomarkers may Complement the Cleveland Score for Prediction of Adverse Kidney Events After Cardiac Surgery: A Pilot Study", Annals of Laboratory Medicine, 40(2), pp.131~141 (2020), 대한진단검사의학회[DOI]
  80. Herget-Rosenthal S, "Prognostic value of tubular proteinuria and enzymuria in nonoliguric acute tubular necrosis", Clin Chem, 50, pp.552~558 (2004)
  81. Katz N, "Acute kidney stress–a useful term based on evolution in the understanding of acute kidney injury", Crit Care, 20, pp.23~ (2016)
  82. de Geus HRH, "The cardiac surgery-associated neutrophil gelatinase-associated lipocalin (CSA-NGAL) score: a potential tool to monitor acute tubular damage", J Thorac Cardiovasc Surg, 151, pp.1476~1481 (2016)
  83. Vanmassenhove J, "Subclinical AKI: ready for primetime in clinical practice?", J Nephrol, 32, pp.9~16 (2019)
  84. Au V, "Urinary neutrophil gelatinase-associated lipocalin (NGAL) distinguishes sustained from transient acute kidney injury after general surgery", Kidney Int Rep, 1, pp.3~9 (2016)
  85. Damman K, "Renal impairment, worsening renal function, and outcome in patients with heart failure: an updated meta-analysis", Eur Heart J, 35, pp.455~469 (2014)
  86. Heywood JT, "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, 13, pp.422~430 (2007)
  87. Maisel AS, "Neutrophil gelatinase-associated lipocalin for acute kidney injury during acute heart failure hospitalizations: the AKINESIS study", J Am Coll Cardiol, 68, pp.1420~1431 (2016)
  88. Wettersten N, "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, 22, pp.251~263 (2020)
  89. Dupont M, "Lack of significant renal tubular injury despite acute kidney injury in acute decompensated heart failure", Eur J Heart Fail, 14, pp.597~604 (2012)
  90. Singer E, "Urinary neutrophil gelatinase-associated lipocalin distinguishes pre-renal from intrinsic renal failure and predicts outcomes", Kidney Int, 80, pp.405~414 (2011)
  91. Bellomo R, "Pre-renal azotemia:a flawed paradigm in critically ill septic patients?", Contrib Nephrol, 156, pp.1~9 (2007)
  92. for acute kidney injury risk assessment, "Am J Kidney Dis", 2016, 19~28
  93. Bell M, "Assessment of cell-cycle arrest biomarkers to predict early and delayed acute kidney injury", Dis Markers, 2015, pp.158658~ (2015)
  94. Delcroix G, "NGAL usefulness in the Intensive Care Unit three hours after cardiac surgery", ISRN Nephrol, 2013, pp.865164~ (2012)
  95. Coca SG, "Urinary biomarkers of AKI and mortality 3 years after cardiac surgery", J Am Soc Nephrol, 25, pp.1063~1071 (2014)
  96. Singer E, "Urinary NGAL-positive acute kidney injury and poor long-term outcomes in hospitalized patients", Kidney Int Rep, 1, pp.114~124 (2016)
  97. Koyner JL, "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, 26, pp.1747~1754 (2015)
  98. Hsu CY, "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, 180, pp.402~410 (2020)
  99. Klein SJ, "Biomarkers for prediction of renal replacement therapy in acute kidney injury: a systematic review and meta-analysis", Intensive Care Med, 44, pp.323~336 (2018)
  100. Pickering JW, "Linking injury to outcome in acute kidney injury: a matter of sensitivity", PLoS One, 8, pp.e62691~ (2013)
  101. Hanah Kim, "Proenkephalin Predicts Organ Failure, Renal Replacement Therapy, and Mortality in Patients With Sepsis", Annals of Laboratory Medicine, 40(6), pp.466~473 (2020), 대한진단검사의학회[DOI]
  102. Pickering JW, "New metrics for assessing diagnostic potential of candidate biomarkers", Clin J Am Soc Nephrol, 7, pp.1355~1364 (2012)
  103. Pencina MJ, "Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond", Stat Med, 27, pp.157~172 (2008)
  104. Choi N, "Urinary Hepcidin-25 is elevated in patients that avoid acute kidney injury following cardiac surgery", Can J Kidney Health Dis, 5, pp.2054358117~ (2018)
  105. Levante C, "Routine adoption of TIMP2 and IGFBP-7 biomarkers in cardiac surgery for early identification of acute kidney injury", Int J Artif Organs, 40, pp.714~718 (2017)
  106. Leaf DE, "Iron, hepcidin, and death in human AKI", J Am Soc Nephrol, 30, pp.493~504 (2019)
  107. Rizo-Topete LM, "Acute kidney injury risk assessment and the Nephrology Rapid Response Team", Blood Purif, 43, pp.82~88 (2017)
  108. Haase-Fielitz A, "Early warning systems in acute kidney insufficiency", Nephrologe, 12, pp.318~322 (2017)
  109. Albert C, "Urinary neutrophil gelatinase-associated lipocalin-guided risk assessment for major adverse kidney events after open-heart surgery", Biomark Med, 12, pp.975~985 (2018)
  110. Meersch M, "Prevention of cardiac surgery-associated AKI by implementing the KDIGO guidelines in high risk patients identified by biomarkers:the PrevAKI randomized controlled trial", Intensive Care Med, 43, pp.1551~1561 (2017)
  111. Göcze I, "Biomarker-guided intervention to prevent acute kidney injury after major surgery: the prospective randomized BigpAK study", Ann Surg, 267, pp.1013~1020 (2018)
  112. Parikh A, "Does NGAL reduce costs? A cost analysis of urine NGAL (uNGAL) & serum creatinine (sCr) for acute kidney injury (AKI) diagnosis", PLoS One, 12, pp.e0178091~ (2017)
  113. Meeusen JW, "Performance of cystatin C– and creatinine-based estimated glomerular filtration rate equations depends on patient characteristics", Clin Chem, 61, pp.1265~1272 (2015)
  114. Ferguson TW, "Cystatin C as a biomarker for estimating glomerular filtration rate", Curr Opin Nephrol Hypertens, 24, pp.295~300 (2015)
  115. Luis-Lima S, "Chronic kidney disease staging with cystatin C or creatinine-based formulas: flipping the coin", Nephrol Dial Transplant, 34, pp.287~294 (2019)
  116. Bongiovanni C, "Serum cystatin C for the diagnosis of acute kidney injury in patients admitted in the emergency department", Dis Markers, 2015, pp.416059~ (2015)
  117. Marino R, "Diagnostic and short-term prognostic utility of plasma pro-enkeph-alin (pro-ENK) for acute kidney injury in patients admitted with sepsis in the emergency department", J Nephrol, 28, pp.717~724 (2015)
  118. Hollinger A, "Proenkephalin A 119-159 (Penkid) is an early biomarker of septic acute kidney injury: the Kidney in Sepsis and Septic Shock (KidSSS) study", Kidney Int Rep, 3, pp.1424~1433 (2018)
  119. Doemming S, "Pro-enkephalin in plasma of surgical icu-patients with sepsis - a pilot study", Intensive Care Med Exp, 3(S1), pp.A256~ (2015)
  120. Nadim MK, "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, 7, pp.e008834~ (2018)
  121. Boeddinghaus J, "Direct comparison of 4 very early rule-out strategies for acute myocardial infarction using high-sensitivity cardiac troponin I", Circulation, 135, pp.1597~1611 (2017)
  122. Maisel AS, "Rapid measurement of B-type natriuretic peptide in the emergency diagnosis of heart failure", N Engl J Med, 347, pp.161~167 (2002)
  123. Pufulete M, "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, 7, pp.112~ (2018)
  124. de Grooth HJ, "AKI biomarkers are poor discriminants for subsequent need for renal replacement therapy, but do not disqualify them yet", Intensive Care Med, 44, pp.1156~1158 (2018)
  125. Devarajan P, "NGAL for the detection of acute kidney injury in the emergency room", Biomark Med, 8, pp.217~219 (2014)
  126. Devarajan P, "Biomarkers in acute kidney injury: are we ready for prime time?", Nephron Clin Pract, 127, pp.176~179 (2014)
  127. Doi K, "Reduced production of creatinine limits its use as marker of kidney injury in sepsis", J Am Soc Nephrol, 20, pp.1217~1221 (2009)
  128. Liangos O, "Comparative analysis of urinary biomarkers for early detection of acute kidney injury following cardiopulmonary bypass", Biomarkers, 14, pp.423~431 (2009)

관련 논문AI추천

Urinary tissue inhibitor of metalloproteinase-2 and insulin-like growth factor-binding protein 7 as biomarkers of patients with established acute kidney injuryJi Hyun Yang, Myung-Gyu Kim, Sang-Kyung Jo, Se Won Oh, Sung Yoon Lim, Won Yong Cho대한내과학회 · The Korean Journal of Internal Medicine2020 · 제35권 제3호Neutrophil Gelatinase-Associated Lipocalin Cutoff Value Selection and Acute Kidney Injury Classification System Determine Phenotype Allocation and Associated OutcomesAlbert Annemarie, Albert Christian, Bellomo Rinaldo, Blume Louisa, Braun-Dullaeus Rüdiger C., Haase Michael, Hinkel Ulrich Paul, Radtke Sebastian, Stieger Philipp대한진단검사의학회 · Annals of Laboratory Medicine2023 · 제43권 제6호Neutrophil Gelatinase-Associated Lipocalin as a Promising Novel Biomarker for Early Detection of Kidney Injury조선영, 허미나대한진단검사의학회 · Annals of Laboratory Medicine2018 · 제38권 제5호New Biomarkers of Acute Kidney Injury and the Cardio-renal SyndromeRobert Hawkins대한진단검사의학회 · Annals of Laboratory Medicine2011 · 제31권 제2호Effectiveness of Plasma and Urine Neutrophil Gelatinase-Associated Lipocalin for Predicting Acute Kidney Injury in High-Risk PatientsHur Mina, Kim Hanah, Lee Chang-Hoon, Moon Hee-Won, Yi Ahram, Yun Yeo-Min대한진단검사의학회 · Annals of Laboratory Medicine2021 · 제41권 제1호Recent Update on Acute Kidney Injury-to-Chronic Kidney Disease Transition고은실, 정성진연세대학교의과대학 · Yonsei Medical Journal2024 · 제65권 제5호

이 간행물의 다른 논문 (16건)

Clinical Utility of Mac-2 Binding Protein Glycosylation Isomer in Chronic Liver DiseasesLoomba Rohit, Izumi Namiki, Tamaki Nobuharu, Kurosaki Masayukipp. 16-24Application of Next Generation Sequencing in Laboratory MedicineWu Jinhua, Schubert Jeffrey, Li Marilyn M., Zhong Yiming, Xu Fengpp. 25-43Evaluation of the CellaVision Advanced RBC Application for Detecting Red Blood Cell Morphological AbnormalitiesPark Seong Jun, Yoon Jung, Yoon Soo-Young, 권정아pp. 44-50Moving Rate of Positive Patient Results as a Quality Control Tool for High-Sensitivity Cardiac Troponin T AssaysHe Yuting, Wang Yi, Li Tingting, Cao Shunwang, Xiong Yujuan, Ke Peifeng, Huang Xianzhangpp. 51-59Effectiveness of Plasma and Urine Neutrophil Gelatinase-Associated Lipocalin for Predicting Acute Kidney Injury in High-Risk PatientsLee Chang-Hoon, Yi Ahram, Yun Yeo-Min, Hur Mina, Moon Hee-Won, Kim Hanahpp. 60-67
원문 보기