PoCT for the Early Detection of Acute Kidney Injury

Dr. Gustavo F Méndez Machado MD MSC FESC

Cardiología / Fellow of the European Society of Cardiology

Sub-Director Médico [Nocturno L-M-V]

Hospital General de Zona No 11 Xalapa IMSS

gmendezuk@yahoo.co.uk

Evolución en el Diagnóstico Cardiaco y

Renal

1950 ’s

1960 ’s

1970 ’s

1980 ’s

1990 ’s

2000

The renal testing arena is in need of the introduction

of novel, early and more sensitive and specific biomarkers

AMI

WBC count

LDH, SGOT, SGPT

CPK

CK -MB

Troponin -T

Troponin - I

AKI

Change in serum creatinine

Change in serum creatinine

No

Ch

an

ge

Time

Conger JD, Am J Kidney Dis 26:565-576, 1995.

Star RA, Kidney Int 54:1817-1831, 1998.

3

Daño renal agudo (AKI)

AKI, anteriormente denominado

insuficiencia renal aguda, es comun

– Definicion de AKI es subjectiva y condiciona

dificultades en la detecion y diagnostico

La disminucion subita de la funcion renal

condiciona la acumulacion de los

desechos nitrogenados, tales como el

nitrogeno ureico, urea y creatinina

La nomenclatura de AKI describe

condiciones con daño estructural y

disfuncion Devarajan P. J Am Soc Nephrol. 2006;17:1503-1520.

Ricci Z, Ronco C. Crit Care. 2008;12:230-236.

4

Daño Renal Agudo (AKI):

Incidencia y Prevalencia

Incidencia de 1% a 25% en países desarrollados

– Incidencia de terapia de reemplazo renal (RRT) entre 3.4% a 4.9%

– Mortalidad Hospitalaria secundaria a falla renal aguda severa con necesidad de terapia de reemplazo 60 al 70% en varios países.

Prevalencia en la Terapia Intensiva (ICU)

– 5% to 6% requieren RRT en ICU

– Mortalidad General en pacientes con AKI de hasta 60.3%

Uchino S. Curr Opin Crit Care. 2006:12:538-543.

Uchino S, et al. JAMA. 2005;294:813-818.

5

Factores que contribuyen a la Falla Renal

Aguda

48%

34%

27% 26%

19%

6%3%

12%

0

10

20

30

40

50

Sep

tic S

hock

Maj

or Surg

ery

Car

diogen

ic S

hock

Hyp

ovole

mia

Dru

g-induce

d

Hep

atore

nal S

yndro

me

Obst

ruct

ive

Uro

pathy

Oth

er

% o

f P

ati

en

ts

Uchino S, et al. JAMA. 2005;294:813-818.

6

Age-Adjusted Hospitalization Rates for

Kidney Disease by Type of Kidney Failure

(1980-2005)

MMWR Morb Mortal Wkly Rep. 2008;57:309-312.

Rate of hospitalization from ARF increased from

1.8 per 10,000 population in 1980 to 36.5 in 2005

7

Mortality in Acute Renal Failure

No ARF ARF0%

25%

50%

75%M

ort

ali

ty

ARF is an independent risk factor for death

Star RA, Kidney Int 54:1817-1831, 1998.

7%

34%

8

RIFLE Criteria for Defining Acute Renal

Failure

Bellomo R, et al. Crit Care. 2004;8:R204-R212.

ARF, acute renal failure; GFR, glomerular filtration rate; SCr, serum creatinine

*With an acute rise >0.5 mg/dL

GFR Criteria Urine Output Criteria

Increased SCr x 1.5 or

GFR decrease >25%<0.5 mL/kg/h x 6 h

Increased SCr x 2 or

GFR decrease >50%<0.5 mL/kg/h x 12 h

Increased SCr x 3

GFR decrease 75%

or SCr ≥4 mg/dL*

<0.3 mL/kg/h x 24 h

or

anuria x 12 hours

Persistent ARF = complete loss

of kidney function >4 weeks

End stage kidney disease

(>3 months)

Risk

Injury

Failure

Loss

ESKD

High

Sensitivity

High

Specificity

9

Acute Kidney Injury Network Criteria

for the Definition and Classification of AKI

RRT, renal replacement therapy; SCr, serum creatinine

Stage SCr Criteria

Urine Output

Criteria

Stage 1Increase in SCr ≥26.4 µmol/L

or increase to ≥1.5-2.0-fold

from baseline

<0.5 mL/kg/h for >6 h

Stage 2Increase in SCr to >2.0-3.0-fold

from baseline<0.5 mL/kg/h for >12 h

Stage 3

Increase in SCr to ≥3-fold

or SCr ≥354 µmol/L

with an acute rise >44 µmol/L

or initiation of RRT

<0.3 mL/kg/h for >24 h

or anuria ≥12 h

Mehta RL, et al. Crit Care. 2007;11:R31.

Serum Creatinine

Gold standard, but far from ideal

• Not sensitive to kidney insults that don’t affect

filtration

• Creatinine is affected by non-renal factors:

– Protein intake

– Muscle mass

– Age

– Race

– Sex

• In AKI it takes 24-48 hours for serum creatinine to

rise.

– As much as 50% of kidney function can be lost in that

time

11

Creatinina Serica

AKI es actualmente diagnosticado utilizando la

creatinina serica

Indicador no confiable durante cambios agudos

– Concentraciones podrian no cambiar hasta una

reduccion del 50% de la funcion renal

– No refleja de forma aguda la funcion renal hasta que se

alcanza un estado de estabilidad (puede tomar hasta 48

hrs)

– El daño renal ocurre durante el retraso en el

diagnostico

Util marcador para estimar la GFR

Pobre valor en el periodo postquirurgico

El retraso en el diagnostico previene el optimo

traamiento de AKI Bellomo R, et al. Intensive Care Med. 2004;30:33-37.

Nguyen MT, et al. Pediatr Nephrol. 2008;23:2151-2157.

Star RA. Kidney International. 1998;54:1817-1831.

12

Adapted from Moran SM, Myers BD. Kidney International. 1985;27:928-937

GFR

(mL/min)

Serum

Creatinine (SCr)

(mg/dL)

Creatininina no es el Biomarcador Ideal

0

1

2

3

4

5

6

70

20

40

60

80

100

120 Surgery, MI, sepsis

Reversal of ischemia

0 7 14 21 28

Time, days

Urine Output

May be misleading

Legrand M and Payen D. Ann Intensive Care. 2011;1:13.

• A minimum of 6 hours must

pass to determine urine

output.• Nonsustained decreases of

urine output do not

necessarily imply decreased

GFR.

– Can represent a physiological

renal adaptation for

homeostasis

BIOMARKER NEEDS

AKI Biomarkers

BIOMARKERS

IL-18

NGAL

KIM1

L-FABP

Cystatin C

• Early detection

• Differential diagnosis

• Prognosis

MOST AKI MARKERS ARE NOT FDA

APPROVED

AND AVAILABLE ONES DO NOT MEET

CURRENT CLINICAL NEEDS.

Possible Utility of New Biomarkers

Early detection

Differential diagnosis

Prognosis

– Predict need for dialysis

– Reversibility

– Risk of death

Unmet Clinical Needs

AKI is difficult to assess.

Mortality is high and it carries a very

high cost.

Currently available methodologies

and biomarkers are not meeting

clinical needs.

New biomarkers are on the horizon

to assist with AKI risk assessment.

Biomarcadores de Daño Renal

17

Clasificacion ADHF

18

19

20

Fonarow GC JAMA 2005:572

21

22

23

24

25

26

Definition and Pathophysiology of Cardiorenal

Syndrome Subtypes – HF and AKI

Ronco C et al. Eur Heart J 2010;31:70-711

28

Neutrophil Gelatinase Associated Lipocalin

(NGAL), Lipocalin-2, Siderocalin: Physiology

and Clinical Relevance Member of the lipocalin superfamily

Normally expressed at very low levels in kidney, lungs, heart, stomach, and colon

Increased after injury and ischemia– One of the most highly induced proteins in kidney after

ischemic or nephrotoxic AKI in animal models

– Highly up-regulated in the distal convoluted tubule during injury/ischemia, leading to a marked increase of NGAL in the urine

Protective role– Murine models of renal ischemia-reperfusion showed

amelioration of morphologic and functional injury when treated with NGAL

Early diagnostic biomarker for AKI

Devarajan P. Nephrol Dial Transplant. 2008;23:3737-3743.

Parikh CR, Devarajan P. Crit Care Med. 2008;36(suppl):S159-S165.

Mishra J, et al. J Am Soc Nephrol. 2004;15:3073-3082.

29

Induction of Mouse Kidney NGAL After

Ischemia

25 kD

55 kD

Mishra J, et al. J Am Soc Nephrol. 2003;14:2534-2543.

Unilateral Ischemia Reperfusion Bilateral Ischemia Reperfusion

NGAL

Tubulin

NGAL

Tubulin

25 kD

55 kD

Con 3 hr 12 hr 24 hr Con 3 12 24 48 72 Hours

Con = control

NGAL expression was highly induced after ischemia

30

Ischemic Kidneys Synthesize Renal NGAL

mRNA

Adapted from Schmidt-Ott KM, et al. J Am Soc Nephrol. 2007;18:407-413.

mR

NA

Levels

, fo

ld c

han

ge

Hours Post-Ischemia

*P≤.05

NGAL

FGF2 (basic fibroblast growth factor)

HF (hypoxia-inducible factor)

BMP7 (bone morphogenic protein 7)

0 10 20 30 40 50

**

**

1000

100

10

1

0.1

0.01

*

*

***

*

*

** *

**

31

Function of NGAL

Role in kidney development

– Promotes epithelial differentiation by

targeting a stromal/intestinal/progenitor niche

at the periphery of the developing kidney

– Affects the structure of established epithelia

Binds labile iron in cytosol and

pericellular space

Iron-associated NGAL regulates iron-

responsive genes (ferritin, transferrin

receptor)

Devarajan P. Nephrol Dial Transplant. 2008;23:3737-3743.

Schmidt-Ott KM, et al. J Am Soc Nephrol. 2007;18:407-413.

NGAL

Siderophore

Labile Iron

·O 2

-

Haber Weiss

Fe3+

Fe2+

O 2

OH ·H 2O 2

Fenton

Ferric Iron = Fe3

+ ; Ferrous iron= Fe2

+ ; hydrogen peroxide = H2

O2

;

Hydroxyl radical = OH. ;Hydroxide anion = OH - ; oxygen = O2;

superoxide anion = . O2

-

ACS

AKIOxidative Stress Reactions

OH-H2O

++

Pe

rce

nt

N>100,000 patients

Slide courtesy of Christopher De Filippi

Prevalence of Renal Dysfunction in Patients

with AHF

• Renal dysfunction is a likely element of pathophysiology of

heart failure and highly prevalent as demonstrated in

findings from the ADHERE database.

Adams KF et al. Am Heart J. 2005; 149:209-216

34

NGAL for the Diagnosis of AKI in the

Emergency Department

Nickolas TL, et al. Ann Intern Med. 2008;148:810-819.

N = 635

0

250

500

750

1000

1250

1500

*

*

*

* *

*

AKI Prerenal

Azotemia

CKD Normal

Kidney

Function

Uri

ne

NG

AL

, μ

g/g

0.00

2.00

4.00

6.00

8.00

10.00

12.00

14.00

16.00

18.00

20.00

*

*

*

**

***

*

AKI Prerenal

Azotemia

CKD Normal

Kidney

Function

Pre

se

nti

ng

Se

rum

Cre

ati

nin

e, m

g/d

L

NGAL Serum Creatinine

35

Meta-Analysis: Accuracy of NGAL in AKI

Meta-analysis of 19 diagnostic studies (2538 patients)

NGAL was a valuable and early predictor of AKI, both overall and across a diverse range of clinical settings

The cutoff NGAL value for optimum sensitivity and specificity across all settings was >100 ng/mL

A more consistent cutoff value of >150 ng/mL was identified when using standardized platforms Haase M, et al. Am J Kidney Dis. 2009;54:1012-1024.

Setting Specificity AUC-ROC

Diagnostic

Odds Ratio

AKI across settings 85.1 0.815 18.6

AKI after cardiac surgery 75.1 0.775 13.1

AKI in critically ill patients 75.5 0.728 10.0

AKI after contrast infusion 96.3 0.894 92.0

AKI prediction using

serum NGAL86.6 0.775 17.9

AKI prediction using

urine NGAL84.3 0.837 18.6

Diagnostic and Prognostic Accuracy of NGAL

Cardiorenal Syndrome Type 1: Creatinine

Increase in Acute HF Patients.

Gottlieb SS et al. J Card Fail. 2002;8:136. Smith G, J Card Fail. 2003 Feb;9(1):13-25

X X X X X X X X X X X X X X

X

0.5

0.4

0.3

0.2

0.1

0

20

40

60

80

100

1 3 5 7 9 11 13 15

Days

%

Cr

Small increases in Cr are associated with poor

outcomes and occur in 30% of patients

hospitalized for HF

“Type 1 CardioRenal Syndrome ”

NO. OF PATIENTS

REFERENCE TP FP FN TN NGAL CUTOFF (NG/ML)

SENSITIVITY (%; 95% CI) SPECIFICITY (%; 95% CI)

Mishra et al, 2005 (p) 14 3 6 48 > 25 70.0 (45.7-87.2) 94.1 (82.8-98.5)

Mishra et al, 2005 (u) 20 1 0 50 > 50 100.0 (80.0-100.0) 98.0 (88.2-99.9)

Wagener et al, 2006 11 23 5 42 > 400 68.8 (41.5-87.9) 64.6 (51.7-75.8)

Dent et al, 2007 38 5 7 73 > 150 84.4 (69.9-93.0) 93.6 (85.0-97.6)

Zappitelli et al, 2007 12 7 4 16 > 10 75.0 (47.4-91.7) 69.6 (47.0-85.9)

Hirsch et al, 2007 (p) 8 1 3 79 >100 72.7 (39.3-92.7) 98.8 (92.3-99.9)

Hirsch et al, 2007 (u) 8 0 3 80 > 100 72.7 (39.3-92.7) 100.0 (94.3-100.0)

Wagener et al, 2008 44 172 24 186 > 450 64.7 (52.1-75.6) 52.0 (46.7-57.2)

Bennett et al, 2008 78 8 21 89 >150 78.8 (69.2-86.1) 91.8 (83.9-96.1)

Ling et al, 2008 10 8 3 19 -- 76.9 (46.0-93.8) 70.4 (49.7-85.5)

Koyner et al, 2008 (p) 8 13 10 41 > 280 44.4 (22.4-68.7) 75.9 (62.1-86.1)

Koyner et al, 2008 (u) 12 19 6 35 > 550 66.7 (41.2-85.6) 64.8 (50.6-77.0)

Nickolas et al, 2008 20 16 3 502 > 80 87.0 (65.3-96.6) 96.9 (94.9-98.2)

Lima et al, 2008 5 12 1 34 -- 83.3 (36.5-99.1) 73.9 (58.6-85.3)

Wheeler et al, 2008 19 74 3 47 > 140 86.4 (64.0-96.4) 38.8 (30.3-48.2)

Xin et al, 2008 2 8 1 22 > 250 66.7 (12.5-98.2) 73.3 (53.8-87.0)

Cruz et al, 2009 47 46 17 191 > 150 73.4 (60.7-83.3) 80.6 (74.9-85.3)

Makris et al, 2009 (CIN) 5 6 1 44 60 90.0 (54.1-99.5) 88.0 (75.0-95.0)

Makris et al, 2009 (ICU) 6 7 1 17 > 190 85.7 (42.0-99.3) 70.8 (48.8-86.6)

Constantin et al, 2009 43 1 9 35 > 155 82.7 (69.2-91.3) 97.2 (83.8-99.9)

Tuladhar et al, 2009 (p) 7 13 2 28 > 420 77.8 (40.2-96.1) 68.3 (51.8-81.4)

Tuladhar et al, 2009 (u) 8 9 1 32 > 390 88.9 (50.7-99.4) 78.1 (62.0-88.9)

Haase-Fielitz et al, 2009 18 17 5 60 > 150 78.3 (55.8-91.7) 77.9 (66.8-86.3)

Sensitivity and Specificity of Studies for NGAL to Predict AKI

Haase M, Bellomo R, Devarajan R et al. Am J Kidney Dis. 2009;54:1012-24.

Discusión

3.METODOS DE MEDIDA DE UNGAL

• Los diferentes métodos existentes son inmunoensayos (reacciones antígeno-anticuerpo)

• Dependiendo de las secuencias del antígeno (uNGAL) que reconocen los anticuerpos utilizados, las concentraciones de uNGAL pueden variar significativamente método a método

• El uNGAL no es una forma molecular única

Discusión

4. Isoformas de NGAL en orina

ORIGEN DEL uNGAL

-Epitelio renal: DRA

-Neutrófilos infiltrando epitelio renal: DRA

-:Neutrófilos activados: Infección tracto urinario (ITU)

-Tejidos extrarrenales

MONOMÉRICO (25 KDa)

HOMODIMÉRICO (50 KDa)

HETERODIMÉRICO (135 KDa)

DRA

ITU

DRA

©2013 Astute Medical, Inc. PN 0138 Rev B 2013/03/19

A Rigorous Discovery-Validation Path

Was Taken

44

Discovery Study

340 proteins analyzed

(including KIM-1, urine

NGAL, plasma NGAL,

Cystatin-C, IL-18, pi-GST,

and L-FABP)

Validation Study

Primary Endpoint:

moderate to severe AKI

(KDIGO stage 2-3) within

12 hours of

sample collection

(based on serum

creatinine and hourly

urine output)

Sapphire Study

35 sites

(20 North America, 15 Europe)

Age > 21, Critically Ill3,

no AKI (Stage 2 or 3)4

N = 744

Vienna Cohort

Age > 18,

in ICU + Sepsis

N = 134

Duke Cohort

Age > 18,

At least 1 risk factor1

N = 123

Mayo Cohort

Age > 18,

At least 1 risk factor2

N = 265

N = 7285

No AKI

N = 416

AKI Stage 1

N = 211

AKI Stage 2

N = 83

AKI Stage 3

N = 18

16 patients excluded

(2 withdrew consent, 7

lost to follow-up, 7 with

invalid or missing test

results)

Best Two Markers

Dis

cov

ery

Va

lid

ati

on

Within

12 hrs

Kashani et al. Critical Care 2013, 17:R25

Revolutionary Biomarkers Were Identified

Biomarkers identified through hypotheses based on AKI pathophysiology

340 candidate biomarkers identified

Biomarkers ranked by ability to predict development of AKI RIFLE I or F within 12 to 36 hours

All possible combinations of two-four biomarkers (novel or previously described) were ranked

Top performing biomarkers identified– Tissue Inhibitor of Metalloproteinases-2 (TIMP-2)

– Insulin-like Growth Factor Binding-Protein 7 (IGFBP7)

45Kashani et al. Critical Care 2013, 17:R25

TIMP-2 and IGFBP7 Outperform Existing

Biomarkers

AUC for [TIMP-2]•[IGFBP7] was significantly greater than any existing

biomarkers 46

Kashani et al. Critical Care 2013, 17:R25

47

TIMP-2 and IGFBP7 Work Well In

Important Subgroups

Sepsis Surgery

Kashani et al. Critical Care 2013, 17:R25

[TIMP-2]•[IGFBP7] Has a Compelling

Specificity Profile

48

Urine NGAL (ng/mL) [TIMP-2]•[IGFBP7] ((ng/mL)2 / 1000)

Kashani et al. Critical Care 2013, 17:R25

[TIMP-2]•[IGFBP7] Has a

Compelling Specificity Profile

49

Urine KIM-1 (ng/mL) [TIMP-2]•[IGFBP7] ((ng/mL)2 / 1000)

Kashani et al. Critical Care 2013, 17:R25

TIMP-2 and IGFBP7 Have Compelling Mechanistic Origins

in Early Cellular Injury

50

Proposed mechanismIGFBP7 & TIMP-2 are markers of G1

cell cycle arrest during early cell

injury

Renal tubular cells enter a short

period of G1 cell-cycle arrest

following injury

G1 cell-cycle arrest presumably

prevents the cells from dividing

when the DNA may be damaged

IGFBP7 & TIMP-2 may also signal in

autocrine and paracrine fashions,

spreading ‘alarm’ from the site of

injury

These processes and marker signals occur early enough in injury to take action

Kashani et al. Critical Care 2013, 17:R25

TIMP-2 and IGFBP7 Remain Highly

Significant In Clinical Models With Risk

Factors

51

VariableP-value

(Cox PH Model)

P-value

(GEE Model)

[TIMP-2]•[IGFBP7] <0.0001 <0.0001

Age 0.35 0.32

APACHE III Score 0.35 0.067

Hypertension 0.004 0.013

Nephrotoxic drugs 0.12 0.013

Liver Disease 0.069 0.057

Sepsis 0.32 0.64

Diabetes 0.29 0.35

Chronic Kidney Disease 0.27 0.64

Serum Creatinine <0.0001 <0.0001

C-stat (AUC) 0.87 0.87

Endpoint was KDIGO 2-3 (RIFLE I/F) within 12 hours. All clinical risk factors with univariate p-value ≤ 0.1 for predicting the endpoint were included in the models. Net reclassification and integrated discrimination improvement

analyses were also performed and showed significant enhancement of the models by [TIMP-2][IGFBP7].

Key Messages

Both IGFBP7 and TIMP-2 are inducers of G1 cell cycle arrest, a key mechanism implicated in AKI

IGFBP7 and TIMP-2 are new biomarkers for AKI and perform better than existing biomarkers for predicting the development of moderate or severe AKI (KDIGO stage 2 or 3) within 12 hours of sample collection

[TIMP-2]•[IGFBP7] significantly improved risk stratification when analyzed using Cox proportional hazards model, generalized estimating equation, integrated discrimination improvement or net reclassification improvement

Risk for major adverse kidney events within 30 days (MAKE30) elevated sharply above [TIMP-2]•[IGFBP7] values > 0.3 and doubled when [TIMP-2]•[IGFBP7] values were > 2.0

52

Kashani et al. Critical Care 2013, 17:R25

The NEPHROCHECK® Test System

The NEPHROCHECK® Test quantitatively

measures two urinary biomarkers --

tissue inhibitor of metalloproteinase 2

(TIMP-2) and insulin-like growth factor

binding protein 7 (IGFBP-7), which are

thought to be involved in G1 cell cycle

arrest in the earliest phases of inju

53

The NEPHROCHECK® Test System

54

MediBeacon has created a research grade technique that is clinically applicable

for real-time point-of-care Glomerular Filtration Rate measurement (mGFR).

MediBeacon has invented a fluorescent tracer agent (MB-102) that is removed

from the blood exclusively by the GFR mechanism of the kidneys.

57

Conclusiones

Sìndrome Cardio-Renal

Se requieren predictores tempranos, confiables

y exactos de daño renal agudo Biomarcadores.

NGAL POCT

IGFBP7 and TIMP-2 POCT

Mayor investigación en el tema

59

Cystatina C

Inhibidor proteasa Cysteina

– Sintetizada y liberada dentro de la sangre en rangos constantes por todas las celulas nucleadas

Cuantificación GFR

– Sus niveles sanguineos no se afectan po rla edad, genero, raza o desarrollo muscular

– Ventajas en los niños, ancioanos, UCI y paciente de alto riesgo (diabetes)

– Detecta camibios ligeros en la funcion renal

Incremento mas temprano que la creatinina en AKI

Nguyen MT, et al. Pediatr Nephrol. 2008;23:2151-2157.

Koyner JL, et al. Kidney Int. 2008;74:1059-1069.

Herget-Rosenthal S, et al. Kidney Int. 2004;66:1115-1122.

60

Interleukin-18 (IL-18)

Citokina proinflamatoria

Inducida y liberada en le tubulo proximal y se detecta en la urina siguiendo AKI isquemico – Detección 4–6 hours post-cardiopulmonary bypass

– Deteccíon UCI 48 horas antes de AKI

Marcador predictivo temprano de AKI y mortalidad – Predice desarrollo de AKI 24 horas antes que la creatinina

serica

Puede diferenciar entre necrosis tubular aguda y otros tipos de enfermedad aguda renal

No predice AKI mas rapido que NGAL urinario

Puede ser influenciado por otras variables y estados fisiopatologicos.

Parikh CR, et al. J Am Soc Nephrol. 2005;16:3046-3052.

Coca SG, et al. Kidney International. 2008;73:1008-1016.

Devarajan P. Expert Opin Med Diagn. 2008;2:387-398.

61

Kidney Injury Molecule 1 (KIM-1)

Proteina de transmembrana, altamente sobreexpresada en celulas del tubulo proximal despues de AKI isquemico o nefrotoxico

Bueno para evaluar el diagnostico de AKI

– No es solido para facilitar el diagnostico temprano

KIM-1 urinario distingue AKI isquemico de azoemia prerenal y CKD

Puede predecir los desenlaces adeversos y se asocia con medidas de severidad de la enfermedad

– Predice el riesgo de mortalidad despues de AKI

Muy especifico en daño isquemico o nefrotoxico, pero no es sensible en estadios tempranos

Nguyen MT, et al. Pediatr Nephrol. 2008;23:2151-2157.

Coca SG, et al. Kidney International. 2008;73:1008-1016.

Parikh CR, et al. J Am Soc Nephrol. 2005;16:3046-3052.

Devarajan P. Expert Opin Med Diagn. 2008;2:387-398.