AKI to CKD:
How Should We Look For It
Prasad Devarajan, MD
Professor of Pediatrics and Developmental Biology
University of Cincinnati College of Medicine
Director, Nephrology and Hypertension
Director, Nephrology Clinical Laboratory
CEO, Dialysis Unit
Cincinnati Children’s Hospital Medical Center
Natural History of AKI
Cerda CJASN 2008; 3:881-886
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Natural History of AKI
Hypothesis: AKI markers for AKI to CKD transition
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Outline
Look for AKI to CKD transition by measuring markers of
• Decreased function
• Glomerular damage
• Tubulo-interstitial damage
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Outline
Look for AKI to CKD transition by measuring markers of
• Decreased function
• GFR estimation using serum creatinine and cystatin C
• Glomerular damage
• Albuminuria
• Tubulo-interstitial damage
• Albuminuria and other Novel AKI biomarkers
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Estimating GFR from serum creatinine
0.43 X height (cm)/s. creat
0.413 X height (cm)/s. creat
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Barratt formula
eGFR in ml/min/1.73 m2
Children 0.2-14 years
Cr-EDTA
Only CKD
S creat by Jaffe
Counahan et al, Arch Intern Med
51:875-8, 1976
New Schwartz formula
eGFR in ml/min/1.73 m2
Children 1-16 years
Iohexol
Only CKD
S creat by Enzymatic
Schwartz et al, JASN 20:629-37,
2009
(For older kids: use MDRD formula or CKD-EPI formula
or the new combined creat plus cystatin C formula)
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Estimating GFR from serum creatinine
Advantages
Disadvantages
• Widely available
• Inexpensive
• Convenient bedside
estimate
• Confounded by age, gender, race,
hydration, diet, muscle mass, time
• Many medications increase serum creat
(TMP, aspirin, steroids)
• Overestimates GFR in CKD
• Confounded by “renal reserve”
• Colorimetric vs Enzymatic
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Estimating GFR using Cystatin C
Advantages of cystatin C
•
•
•
Much less affected by age, gender, race, diet,
hydration, muscle mass, and medications than serum
creatinine
Cystatin C levels are nearly identical in adults and
children over 1 year old (unlike creatinine levels) – so a
single reference range can be used for all individuals
greater than 1 year of age
Detects the early state of hyperfiltration
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Estimating GFR using Cystatin C
Advantages of cystatin C
•
Compared to gold standards, almost always
outperforms serum creatinine in children and adults,
with normal kidney function, AKI, or CKD from various
etiologies (three published meta-analyses)
Dharnidharka AJKD 40:221-6, 2002
Roos Clin Biochem 40:383-91, 2007
Zhang AJKD 58:356-65, 2011
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Cystatin C in AKI
(13 AKI publications)
Zhang AJKD 58:356-65, 2011
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Cystatin C in CKD
(23 CKD publications)
Roos Clin Biochem 40:383-91, 2007
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Estimating GFR using Cystatin C
Disadvantages of cystatin C
• Cystatin C levels are higher in hyperthyroidism, and in
patients receiving steroids or other immunosuppressants
• Two commonly used methods for measuring cystatin C
(nephelometry and turbidimetry) can give discrepant
results
• More expensive than serum creatinine
• GFR equations incorporating both cystatin C and
creatinine may perform better than either one
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Outline
Look for AKI to CKD transition by measuring markers of
• Decreased function
• GFR estimation using serum creatinine and cystatin C
• Glomerular damage
• Albuminuria
• Tubulo-interstitial damage
• Albuminuria and other Novel AKI biomarkers
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Albuminuria Associates with
Community-Acquired AKI
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ARIC Cohort
8 year follow up
11,200 subjects with baseline ACR
356 (3.2%) developed AKI
Grams JASN 2010; 21:1757-64
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Albuminuria Predicts AKI After Cardiac Surgery
No AKI
(> 2 yrs)
(< 2 yrs)
AKI
AUC
Clinical Model
Post-op ACR
Combination
Adults (n=1198)
0.75 (0.04)
0.59 (0.04)
0.81 (0.03)
Children (n=294)
0.79 (0.04)
0.63 (0.05)
0.82 (0.04)
Molnar CJASN 2012 ePub (TRIBE-AKI adults)
Zappitelli CJASN 2012 ePub (TRIBE-AKI children)
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Albuminuria Predicts AKI Progression After Cardiac Surgery
Predictor
Cut Point
Adjusted OR
Clinical Model
Adjusted AUC
0.75 (0.04)
Urine ACR
>133
3.41 (1.27, 9.11)
0.78 (0.04)
Urine NGAL
>141
2.02 (0.86, 4.73)
0.79 (0.04)
Urine IL-18
>185
3.63 (1.64, 8.03)
0.77 (0.04)
Plasma NGAL
>322
11.66 (4.49, 30.27)
0.80 (0.04)
Koyner JASN 2012 23:905-14 (TRIBE-AKI adults)
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Albuminuria for AKI to CKD Transition
Advantages
Disadvantages
• Widely available
• Inexpensive
• Established marker of
CKD and CKD outcomes
• Mechanisms unclear (glomerular versus
tubular)
• May reflect non-specific changes in
capillary permeability and/or a nonspecific inflammatory response
• Limited diagnostic accuracy in AKI
(AUCs in the 0.6 to 0.65 range)
• Many patients with CKD progress
despite having only mild proteinuria
• Many patients with significant
proteinuria do not progress
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Outline
Look for AKI to CKD transition by measuring markers of
• Decreased function
• GFR estimation using serum creatinine and cystatin C
• Glomerular damage
• Albuminuria
• Tubulo-interstitial damage
• Albuminuria and other Novel AKI biomarkers
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Novel Biomarkers for
AKI to CKD Transition
• Novel inducible urinary biomarkers of AKI are
being evaluated for use in the AKI-to-CKD
progression
• Unbiased gene expression profiling studies in
animal models of AKI-to-CKD transition show
NGAL and KIM-1 as two most persistently
upregulated genes (and proteins) in the kidney
Ko et al, AJP Renal 298:F1472-83, 2010
Viau et al, JCI 120: 4065-76, 2010
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NGAL – 2 Months After 75% Nephrectomy
NGAL mRNA
Viau et al, JCI 120: 4065-76, 2010
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NGAL protein
Human
Mouse
NGAL – Expression in PDK Models
Viau et al, JCI 120: 4065-76, 2010
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NGAL in Human CKD
• NGAL protein expression is increased in kidney
biopsies from humans with CKD, correlating with
histologic damage and degree of CKD
• Increased levels of urinary NGAL and an inverse
correlation with GFR have been documented in
patients with CKD from PDK, HIV, FSGS, and
diabetic nephropathy
Devarajan Adv Chr Kid Dis 2010; 17:469-79
Goldstein Pediatr Nephrol 2011; 26:509-22
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NGAL in Human CKD Progression
• Nickolas: 78 patients with CKD followed up for 200 days –
urine NGAL at baseline correlated with future worsening of
serum creatinine (r=0.77; p<0.001)
• Yang: 74 patients with diabetic nephropathy followed for 1
year – urine NGAL at baseline correlated with follow-up
eGFR (r=-0.57, p<0.001)
• Bolignano: 96 patients with CKD stages 2-4 followed up for
18.5 months – 32% reached the composite end point of
doubling of serum creatinine or onset of ESRD – urine and
plasma NGAL at baseline independently predicted CKD
progression with AUC 0.78
Nickolas et al, Curr Opin Nephrol Hypertens 17:127-32, 2008
Yang et al, Endocrine 36:45-51, 2009
Bolignano et al, CJASN 4:337-44, 2009
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NGAL in Human CKD Progression
• Bhavsar: case-control study (n=143 each) from ARIC cohort
prospectively followed for 8 years
• Cases progressed to CKD Stage 3
• High baseline urine NGAL values independently associated
with progression
Urinary Biomarker
Odds of CKD 3
P for trend
NGAL
2.36 (1.12-5.01)
0.01
KIM-1
1.51 (0.72-3.17)
0.2
Albumin
1.8 (0.95-3.43)
0.07
Bhavsar AJKD 2012; 60:233-40
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KIM-1 in Human CKD Progression
• Peralta: case-control study (n=343 each) from MESA cohort
prospectively followed for 5 years
• Cases progressed to CKD Stage 3
• High baseline urine KIM-1 values independently associated
with progression
Urinary Biomarker
Odds of CKD 3
KIM-1
2.35 (1.08-5.14)
NGAL
1.52 (0.76-3.05)
Peralta AJKD 2012; EPub
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Other Novel AKI-CKD Biomarkers
Devarajan Adv Chr Kid Dis 2010; 17:469-79
Fassett KI 2011; 80:806-821
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AKI to CKD – Studies in Progress
Claes, Goldstein et al: Long term follow up of children with AKI after cardiac
surgery - no evidence of hypertension, proteinuria, or decreased eGFR
NGAL
L-FABP
IL-18
KIM-1
Pre-op
(n=54)
16
8.7
0.81
258
Post-op Day 2
(n=54)
99
244
54
1010
5-8 years later
(n=14)
9.1
7.6
57*
473*
*P<0.05 compared to pre-op baseline
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AKI to CKD – Studies in Progress
AKI after cardiac surgery (adult/pediatric), ICU (adult) , community-acquired (adult)
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AKI to CKD – Studies in Progress
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AKI to CKD – Future Directions
• Targeted longitudinal assessments are required to
assess the implications of AKI for CKD progression
• AKI severity and cumulative burden should be
tracked for all patients at risk for AKI
• Biomarkers such as NGAL and KIM-1 should be
tested for their ability to stratify subjects who are
at greatest risk for AKI to CKD progression, who
might benefit from increased surveillance, early
prevention, and specific interventions
Goldstein & Devarajan, Pediatr Nephrol 26:509-22, 2011
The Center for Acute Care Nephrology
Acknowledgement of Collaborators
Chirag Parikh (Yale U)
Charles Edelstein (U Colorado)
Stuart Goldstein (CCHMC)
Didier Portilla (U Arkansas)
Pat Murray (U Dublin)
Jay Koyner (U Chicago)
Rinaldo Bellomo (Austin Hosp)
Zoltan Endre (U Otago)
David Humes (U Mich)
Adeera Levin (U Br Columbia)
Amit Garg (U London)
Sean Bagshaw (U Alberta)
Mike Zappittelli (McGill U)
Jon Barasch (Columbia U)
Tom Nickolas (Columbia U)
Joseph Bonventre (Harvard)
Karina Soto (U Lisbon)
Sarah Faubel (U Colorado)
Catherine Krawczeski (CCHMC)
David Askenazi (UAB)
Michael Haase (Charité Hosp)
Christoph Westenfelder (U Utah)
Uptal Patel (Duke U)
Tim Bunchman (VCU)
Kiyoshi Mori (Kyoto U)
Abbott Diagnostics
Neesh Pannu (U Alberta)
Biosite/Alere
Funding:
Thank You for your Attention!
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