Stuart L. Goldstein, MD Professor of Pediatrics

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

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

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

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

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

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)

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%)

Pediatric AKI Epidemiology Author Year Time span Cohort AKI Cause Williams 2002 1978-1998 All hospital 1978-88: HUS 38%, Oncology 8% 1988-98: HUS 22% Oncology 17% Hui-Stickle 2005 1999-2001 All hospital Ischemic 21% Nephrotoxins 16% Primary Renal 7% Akcan-Arikan 2007 2005-2006 PICU Pneumonia (33%) SIRS/sepsis(27%) Cardiogenic (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)

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

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

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

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

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

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

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

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

AKI RIFLE Criteria: ADQI II

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

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

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

“ Persistent” AKI on admission

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

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.

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.

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

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

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

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

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

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

Cardiac surgery Parikh et al,KI, 2006 Children

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

Critical illness population NGAL KIM-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

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

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

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%

0 2 4 6 uNGAL (ng/mg creatinine) -3 -2 -1 0 1 2 Days from Day of first pRIFLE (Day 0) AKI higher than controls from Day -2 to Day 2, p<0.05 ● ● ● ● ● ●

Increase in NGAL to predict AKI: AUC=0.78

Increase in NGAL to predict persAKI: AUC=0.80

0 100 200 300 400 Mean and Peak uIL18 (pg/ml) Control R I F Mean uIL18 Peak uIL18

All Patients Non-septic

P<0.05

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

Stuart L. Goldstein, MD Professor of Pediatrics

by cardiacinfo

Accessibility

Upload Details

Usage Rights

Statistics