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Stuart L. Goldstein, MD Professor of Pediatrics Baylor College of Medicine Pediatric Acute Kidney Injury and Biomarkers 6th PCRRT Conference, Rome 2010.

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Presentation on theme: "Stuart L. Goldstein, MD Professor of Pediatrics Baylor College of Medicine Pediatric Acute Kidney Injury and Biomarkers 6th PCRRT Conference, Rome 2010."— Presentation transcript:

1 Stuart L. Goldstein, MD Professor of Pediatrics Baylor College of Medicine Pediatric Acute Kidney Injury and Biomarkers 6th PCRRT Conference, Rome 2010

2 Acknowledgements Baylor College of Medicine/Texas Children’s AKI Study Group Laura Loftis, MD Annabelle Chua, MD Ayse Arikan, MD Michael Zappitelli, MD Alyssa Riley-Kothari, MD Yue Du, PhD Leticia Castillo, MD Jack Price, MD David Nelson, MD John Lynn Jeffries, MD Joshua Blinder, MD Jeffrey Towbin, MD Anjan Shah, MD Brady Moffett, RPh

3 Outline AKI Epidemiology – Old Definitions Risk Factor Assessment New AKI Definitions Treatment Prognosis New Advancements - Biomarkers

4 AKI Definitions to 2002 Over 30 definitions in published literature Nearly all based on absolute or change in serum creatinine concentration Pediatric AKI definitions – All AKI is created equal 100% rise in SCr eCCL < 75 ml/min/1.73m 2 SCr twice normal for patient age Few prospective pediatric studies Retrospective studies assess AKI causes Control group without AKI not assessed to determine risk factors for AKI

5 Pediatric AKI Epidemiology until 2002: What was Out There? Most original data all single center Predate current ICU technology and practice Predate recent disease therapies Bone marrow transplantation Cardiac transplantation Congenital heart surgery Cite Hemolytic-Uremic Syndrome/primary renal disease as most common causes Most articles after 1995 are literature review

6 Patient Selection  Reviewed all admissions to Texas Children’s Hospital from January 1998 through June 2001  Selected patients <20 years of age with ARF listed as diagnosis on discharge or death summary  Reviewed list and defined ARF as GFR by Schwartz < 75 ml/min/1.73m 2 (n=254)

7 Most Common ARF Causes  ATN-Dehydration (21%)  Nephrotoxic drugs (16%)  Sepsis (11%)  Unknown (14%)  Primary Renal Disease (7%) Patient Survival  176/254 patients (70%)  110/185 patients with ICU care (60%)  43/77 patients receiving renal replacement therapy (56%)

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9 Pediatric AKI Epidemiology AuthorYear Time span CohortAKI Cause Williams2002 1978- 1998 All hospital 1978-88: HUS 38%, Oncology 8% 1988-98: HUS 22% Oncology 17% Hui-Stickle2005 1999- 2001 All hospital Ischemic 21% Nephrotoxins 16% Primary Renal 7% Akcan-Arikan2007 2005- 2006 PICU Pneumonia (33%) SIRS/sepsis(27%) Cardiogenic (10%)

10 Pediatric AKI Risk Factors Few comparative data of populations with versus without AKI to determine who is truly at risk Most data examine only patients with AKI and report causes (previous slides)

11 AKI Risk Factors – Assessment Issues Retrospective aminoglycoside study AKI defined as 50% decrease Heme/Onc and Pulm with highest AKI Surgery with lowest AKI Heme/Onc and Pulm assessed SCr significantly more often than Surgery Zappitelli and Goldstein, submitted

12 Pediatric AKI Risk Factors: The Critically Ill Patient Highest risk for AKI development AKI now results from other systemic illness or its treatment and not from primary kidney disease Most pediatric AKI studies focus on patients who receive RRT More recent studies compare patients with AKI versus without AKI

13 Single-center, prospective observational study over one year (2000-2001) Pediatric ICU population 3 days to 18 years of age AKI defined as doubling SCr Doubling of upper limit of normal Doubling of PICU admission SCr True “baseline” pre-PICU SCr not assessed CKD patients: AKI defined as 25% increase in SCr

14 1047 admissions Exclusions for patient age, prematurity, decision to withhold care, pregnancy 4.5% AKI rate

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16 Risk factors Thrombocytopenia Older age Hypoxemia Hypotension Coagulopathy Increased PRISM and PELOD scores also AKI risk factors

17 Is All AKI Created Equal? Recent adult patient data demonstrate Small SCr rises associated with mortality AKI associated with mortality and length of hospitalization AKI is now recognized as risk factor for poor outcome, independent of severity of illness

18 AKI Severity and Outcome Chertow GM et al: J Am Soc Nephrol, 2005

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20 All AKI is NOT Equal Multidimensional classification system is needed to Grade AKI severity Follow changes in kidney function Standardize AKI as a hard outcome measure

21 AKI RIFLE Criteria: ADQI II

22 Prospective single center observational study PICU patients receiving mechanical ventilation and vasoactive medications AKI defined by a pediatric modified RIFLE criteria (pRIFLE) pRIFLEmax defined as highest pRIFLE stratum achieved at 14 days of PICU admission or patient discharge, whichever came first

23 eCCl determined by Schwartz formula Baseline eCCl from three months before PICU 100 ml/min/1.73m 2 if no data available pRIFLE differs from RIFLE in Oliguria duration RIFLE-F limit eCCl

24 AKI occurred early in PICU admission 82% of AKI patients attained their initial RIFLE stratum in the first 7 days. Initial RIFLE R N=76 Initial RIFLE I N=31 3/76 (4%) RIFLEmax F 12/31 (39%) pRIFLEmax F

25 “Persistent” AKI on admission

26 Biomarkers A biologic characteristic that is measured and evaluated objectively as an indicator of normal biologic processes, pathogenic processes, or pharmacologic response to therapeutic intervention. Hewitt et al, JASN, 2004  imaging test (renal ultrasound for kidney size)  gene expression profiles for specific health or disease states  proteinuria  lipid profile  metabolomic profiles

27 Why do we need biomarkers of AKI?  Independent RF for mortality and longer LOS in critically ill children. Ackan-Arikan et al, KI, 2007; Plotz et al, Intens Care Med, 2008  Independent RF for LOS in children having cardiac surgery. Bernier et al, ASN, 2008  Independent RF for longer LOS in children treated with aminoglycosides. Zappitelli et al, CJASN, 2008; Zappitelli et al, ASN, 2007  May be a RF for long-term abnormal renal function problems. Askenazi et al, KI, 2006  Because AKI is important.

28 Why do we need biomarkers of AKI? No treatment. Diagnosis based on SCr rise: 1 to 3 days after injury – failed past clinical trials. Several issues with SCr as a marker of GFR.

29 Utilities of biomarkers in AKI Early diagnosis Define severity of injury, monitor AKI course Define AKI subtypes & etiology (pre-renal, septic, nephrotoxic) Monitor response to AKI interventions Risk stratify for poor outcomes (dialysis need, CKD, mortality) Identify location of renal tubular injury Devarajan & Williams, Seminars in Nephrol, 2007

30 What is an ideal biomarker? Qualities Accurate, reliable Relatively non-invasive/acceptable to patients Rapidly measurable, standardized assay Sensitive/specific with reproducible cutoff values Requires case definition: AKIN, pRIFLE Nguyen & Devarajan, Ped Nephrol, 2008

31 Phases of biomarker discovery: bench to bedside Phases of biomarker development Phase Terminology Action Steps Phase 1 Preclinical Discovery Discover biomarkers in tissues or body fluids Confirm and prioritize promising candidates Phase 2 Assay Development Develop and optimize clinically useful assay Test on existing samples of established disease Phase 3 Retrospective Study Test biomarker in completed clinical trial Test if biomarker detects the disease early Evaluate sensitivity, specificity, ROC Phase 4 Prospective Screening Use biomarker to screen population Identify extent and characteristics of disease Identify false referral rate Phase 5 Disease Control Determine impact of screening on reducing disease burden Devarajan & Williams, Seminars Nephrol, 2007; Coca & Parikh, CJASN, 2008 Discovery Translational Validation

32 Biomarker discovery in AKI: bench to bedside NGAL: Expressed in proximal and distal nephron Binds and transports iron-carrying molecules Role in injury and repair Rises very early (hours) after injury in animals, confirmed in children having CPB IL-18: Role in inflammation, activating macrophages and mediates ischemic renal injury IL-18 antiserum to animals protects against ischemic AKI Studied in several human models KIM-1: Epithelial transmembrane protein, ?cell-cell interaction. Appears to have strong relationship with severity of renal injury

33 Biomarker studies in different populations Cardiac surgery Critically ill patients Sepsis Nephrotoxin-treated patients Renal transplant General hospital population

34 Cardiac surgery: Known timing of AKI NGAL: Children led the way! Mishra et al, Lancet, 2005 SCr rise 48-72 hrs Wagener et al, Anesthesiology, 2006 Adults Not quite as good

35 Cardiac surgery Parikh et al,KI, 2006 Children

36 Critical Illness: unknown timing of AKI IL-18 SCr rise Parikh et al, JASN, 2005 Critically ill adults: retrospective. Landmark study.

37 Critical illness population NGALKIM-1 The day of SCr rise: Can biomarkers tell us WHO has “true AKI” versus who has volume depletion? Predict lack of SCr return to normal within 48 hrs when taken at time of SCr rise

38 Texas Children’s AKI Biomarker Study Previous published pediatric AKI biomarker reports from homogeneous patients populations, many with primary renal disease Prospective study of 150 patients admitted to TCH PICU who received mechanical ventilation and/or vasoactive medications Outcome Measures pRIFLEmax at 14 days of ICU admission Persistent AKI (AKI that did not resolve in 48 hours Predict AKI prior to pRIFLE

39 Texas Children’s AKI Biomarker Study 150 patients (enrolled in pRIFLE study) 10 patients excluded from biomarker study for anuria or no indwelling Foley Urine obtained at 2 PM for up to four days after study enrollment NGAL (Devarajan) IL-18 (Edelstein) KIM-1 (Bonventre) pRIFLE creatinine calculated from Day 1 to Day 14 of ICU admission

40 140 patients’ urine samples available Mean age 6.3 years (1 year to 21 years) Mean ICU day of admission = 3 + 1.5 days pRIFLE No AKI:24.3% R:33.7% I:22.1% F:17.9%

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42 0 2 4 6 uNGAL (ng/mg creatinine) -3-2012 Days from Day of first pRIFLE (Day 0) AKI higher than controls from Day -2 to Day 2, p<0.05 ● ● ●

43 Increase in NGAL to predict AKI: AUC=0.78

44 Increase in NGAL to predict persAKI: AUC=0.80

45 0 100 200 300 400 Mean and Peak uIL18 (pg/ml) ControlRIF Mean uIL18Peak uIL18

46 All PatientsNon-septic

47 P<0.05

48 Pediatric AKI and Biomarkers: Conclusions Pediatric AKI is seen as a complication of other systemic illness Earlier recognition and treatment of AKI sequelae may improve outcome Active investigation/validation of urinary biomarkers may lead to therapies to prevent or mitigate the effects of AKI


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