Acute Kidney Injury

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Ravindra L. Mehta

Disclosure of Interest

The details of each Disclosure of Interest are available at the Invited Speakers’ desk

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No interest conflicts to declare

ASN HIGHLIGHTS 2015

ACUTE KIDNEY INJURY

Ravindra L. Mehta, MD, FASN

Susceptibility

Identifying High risk patients

• Lipid Lowering agents

• Amit GargPrimary

Prevention

Risk Assessment

Interaction between demographics,

hypertension and diabetes with eGFR and

ACR

CKD Prognosis Consortium

BMI and AKI

Associations of eGFR and Albuminuria with Acute Kidney Injury in Individuals with and without Diabetes and Hypertension:

A Collaborative Meta-Analysis

MT James, ME Grams, M Woodward, CR Elley, JA Green, DC Wheeler,P de Jong, RT Gansevoort, AS Levey, DG Warnock, MJ Sarnak,

for the CKD Prognosis Consortium

Kidney Measures, Demographics, and Acute Kidney Injury:A Collaborative Meta-Analysis of Cohort Studies

Morgan Grams, Yingying Sang, Shoshana Ballew, Ron Gansevoort, Heejin Kim, Csaba Kovesdy, David Naimark, Cecilia Oien, David Smith,

Josef Coresh, Mark Sarnak, Benedicte Stengel, and Marcello Tonellifor the CKD Prognosis Consortium

Included Studies: 13 cohorts with 18,567 events

5

Study Region N Cases eGFR % Albuminuria Age (SD)

%

Female % Blacks

General population cohort

AKDN Canada 920,686 9,060 92 (20) 5% 47 (17) 55% 0%

ARIC* USA 11,424 655 84 (15) 8% 63 (6) 56% 22%

CHS* USA 2,968 115 71 (17) 20% 78 (5) 59% 17%

HUNT* Norway 9,670 281 85 (20) 13% 62 (15) 55% 0%

Maccabi Israel 265,800 6,112 86 (21) 15% 57 (14) 49% 0%

PREVEND* Netherlands 8,377 54 84 (16) 11% 49 (13) 50% 1%

Severance Korea 65,021 151 85 (16) 5% 46 (12) 48% 0%

ULSAM* Sweden 1,103 52 76 (11) 16% 71 (1) 0% 0%

Overall 1,285,049 16,480 90 (20) 7% 49 (16) 53% 0.2%

Chronic kidney disease cohorts

CRIB* UK 207 51 26 (8) 80% 62 (14) 30% 6%

GeisingerACR* USA 4,043 561 52 (8) 43% 69 (10) 53% 2%

GeisingerDip USA 920 185 50 (9) 38% 68 (12) 49% 2%

KPNW USA 1,624 51 46 (11) 31% 72 (10) 56% 3%

Sunnybrook* Canada 1,994 51 68 (32) 61% 60 (18) 47% 0%

VA CKD* USA 70,731 1,188 64 (21) 56% 71 (10) 2% 12%

Overall 79,519 2,087 63 (21) 55% 70 (11) 7% 11%

*Studies with ACR

‡Proportion of participants with ACR ≥30 mg/g or PCR ≥50 mg/g or dipstick protein ≥1+.

Associations of kidney measures with AKI

6

•Lower eGFR and higher albuminuria were strong and consistent risk factors for AKI across subgroup of age, sex, and race

•Age as a risk factor was less important in lower eGFR and higher ACR

•Male sex and black race appeared to be risk factors throughout the range of eGFR & ACR

7

Interaction between age, sex and race with eGFR and ACR

Hazard Ratios of AKI according to eGFR/ACR and Diabetes

Implications

Individuals at risk of AKI are best identified using measures of eGFR and albuminuria in addition to the presence or absence of diabetes or hypertension.

Future strategies to identify individuals at risk of AKI should combine information on diabetes, hypertension, kidney measures, and consider their interactions in order to target AKI prevention and care strategies to high risk individuals.

November 15, 2014

Obesity, Weight Distribution and the Risk of Acute Kidney Injury

The Atherosclerosis Risk in Communities Study

Keiko Greenberg, MD

Aims

• Evaluate the association of BMI and risk of AKI, independent of kidney function

• Evaluate whether waistto hip ratio adds additional information on AKI risk, independent of BMI and kidney function

11http://www.mayoclinic.org/diseases-conditions/metabolic-syndrome/multimedia/apple-and-pear-body-shapes/img-20006114

Study Population

• The Atherosclerosis Risk in Communities Study: a prospective community-based cohort designed to study etiology and natural history of atherosclerosis

• Sites: Washington County, MD; Forsyth County, NC; Jackson, MS; Minneapolis, MN

• Extensive clinical exams and laboratory studies collected roughly every 3 years

• 11,063 visit 4 attendees included (1996-99)

12

Methods

• Exposures: BMI and waist to hip ratio

• Measured once at baseline

• Outcome: AKI occurring in the hospital setting between visit 4 and 12/31/10

• ICD codes (584.x, N17.x) abstracted from discharge summaries/death certificates

5

Baseline CharacteristicsVariable BMI < 30

(n = 7,193)BMI ≥ 30

(n = 3,870)Low WHR(n = 2,396)

High WHR(n = 8,667)

Age (Years) 64 63* 63 64*

Male (%) 46 40* 55 41*

Black (%) 18 30* 25 21*

Diabetes (%) 11 27* 8 19*

HTN (%) 41 59* 36 50*

CHD (%) 8 8 8 8

eGFR (ml/min/1.73m2) 86 87* 87 86

eGFR < 60 (%) 6 7* 5 7*

Moderate albuminuria1 6 8* 5 7*

Severe albuminuria2 1 2* 1 2*

BMI ≥ 30 (%) 0 100 11 42*

*p < 0.05 for the comparison by subgroup of BMI or WHR. 130-300mg albumin/g Cr. 2>300mg albumin/g Cr.

Results

15

.5

1

2

4

8

Ad

juste

d H

aza

rd R

atio

10 20 30 40 50 60Body Mass Index (kg/m2)

95% CI

Relative Hazard

.5

1

2

4

8

Ad

juste

d H

aza

rd R

atio

10 20 30 40 50 60Body Mass Index (kg/m2)

95% CI

Relative Hazard

Adjusted Association between BMI and AKI Risk*

*Adjusted for 8 covariates and WHR

For BMI < 30: aHR 0.97 (0.94, 0.99) per 1kg/m2

p = 0.04

For BMI > 30: aHR 1.07 (1.06, 1.09) per 1kg/m2

p < 0.001

Results

16

Adjusted Association between WHR and AKI Risk*

*Adjusted for 8 covariates and BMI

1

2

3

4

0.5

Ad

juste

d H

aza

rd R

atio

.4 .6 .8 1 1.2 1.4Waist-to-Hip Ratio

95% CI

Relative Hazard

1

2

3

4

0.5

Ad

juste

d H

aza

rd R

atio

.4 .6 .8 1 1.2 1.4Waist-to-Hip Ratio

95% CI

Relative Hazard

aHR 1.03 (1.01, 1.04) per 0.01 increasep < 0.001

Sensitivity Analyses

Group N

Adjusted Hazard Ratio

BMI < 30 kg/m2

BMI ≥ 30 kg/m2 WHR

Entire cohort 11,063 0.97 1.07 1.03

Addition of hospitalizations as time varying covariate

11,063 0.97 1.07 1.03

Exclusion of AKI occurring with cardiac procedures

10,978 0.96 1.08 1.03

Use of creatinine-based AKI (KDIGO1)

2,486* 1.00 1.05 1.03

Addition of eGFR as time varying covariate

2,486* 1.00 1.07 1.02

17

Bold indicates p<0.05. 1KDIGO Clinical Practice Guideline for AKI. KI 2012;2:1-138. *Analyses in a subset of participants from Washington County, MD for whom laboratory data from January 1, 2002 through December 31, 2012 were available.

Conclusions

• Both BMI and waist to hip ratio were associated with hospitalized AKI in ARIC, independent of each other and eGFR

• There was an apparent U-shaped relationship between BMI and hospitalized AKI

• The relationship between waist to hip ratio and hospitalized AKI was linear

18

Amit X. Garg , M D , M A ( E d u c a t i o n ) , P h D

Nephrologist,

London Health Sciences Centre

Professor, Medicine and Epidemiology

Western University

London, Ontario, CANADA

Cholesterol Lowering Drugs

and Acute Kidney Injury

Blight

↑ risk

Benefit

↓ risk

Benign

no effect

Cholesterol Lowering Drugs

and Acute Kidney Injury

Fibrates

Statins

↑ creatinine

• fibrate: median 15

μmol/L (0.17 mg/dL)

• ezetimibe: no change

in creatinine

> 50% increase serum

creatinine

• fibrate: ~ 1 in 10

patients

Zhao et al. Ann Intern Med 2012

Within 90 days of new fibrate use

↑ 14 umol/L

0.16 mg/dL↑ 33 umol/L

0.4 mg/dL

eGFR ≥ 60 eGFR < 60

Greater absolute increase in

serum creatinine in CKD

Mechanism by which fibrates

cause increase in serum creatinine

is uncertain and controversial

• increased creatinine production

• impaired prostaglandin generation

• rhabdomyolysis (concurrent use of statin)

• renally excreted: can accumulate in CKD

↑ creatinine observed with fenofibrate, benzafibrate,

& ciprofibrate. Evidence with gemfibrozil is conflicting.

without true

kidney damage

reversible

no dialysis /

ESRD risk

Blight

↑ risk

Benefit

↓ risk

Benign

no effect

Fibrates and Acute Kidney Injury

Subacute increases in serum

creatinine from fibrates meant

more hospital and nephrology

encounters in routine care.

Increases in

creatinine likely

not from kidney

tubular injury

Fibrates reduce

proteinuria

(renoprotective)

Until then, as done in RCTs

1. Start prescription at low dose

and appropriate for GFR

2. Monitor renal function

Need to better understand

• mechanism by which fibrates

increase serum creatinine level

• long-term renal effects

• safety in CKD

Blight

↑ risk

Benefit

↓ risk

Benign

no effect

Cholesterol Lowering Drugs

and Acute Kidney Injury

Fibrates

Statins

Do statins cause

Acute Kidney Injury?

Dormuth C et al. BMJ 2013

Information on use

in routine practice (less regimented than RCT; millions of patients and 1000s of events)

Confounding by indication?

JUPITER RCT

Multi-National Randomized Double Blind Placebo Controlled Trial of Rosuvastatin in the Prevention of Cardiovascular EventsAmong Individuals With Low LDL and Elevated hsCRP

Statins and the Risk of Renal-Related

Serious Adverse Events

An Analysis from the IDEAL, TNT, CARDS, ASPEN,

SPARCL and Other Placebo-Controlled RCTs

Bangalore S et al. Am J Cardiol 2014

Statin Placebo

Less SAEs with

StatinMore SAEs with

Statin

0.04% 0.10%

Statins and the Risk of Renal-Related

Serious Adverse Events

An Analysis from the IDEAL, TNT, CARDS, ASPEN,

SPARCL and Other Placebo-Controlled RCTs

Bangalore S et al. Am J Cardiol 2014

High Low

Less SAEs with

High DoseMore SAEs with

High Dose

0.05% 0.02%

0% 0.04%

SHARP RCTHaynes R, Landray M et al. JASN 2014

Sivastatin +

ezetimibePlacebovs Kidney failure events

Simvastatin

+ ezetimibePlacebovs Kidney failure events

SHARP RCTHaynes R, Landray M et al. JASN 2014

Exploratory Outcomes

Proteinuria levels follow-up

- no difference between the 2 groups (p=0.20)

Acute on chronic renal failureas reported by study investigators

6.7% vs. 7.4%, RR 0.91 (95% CI 0.75 to 1.09; P=0.30)

Do statins prevent

Acute Kidney Injury?

Potential mechanisms by which statins may prevent acute kidney injury

Renal injury

HMG-CoA Reductase Inhibitors

↓Adhesion molecules(eg. VCAM-1, ICAM-1, E-selectin)

↓ MCP, ↓IL-8

↓CRP, ↓COX-2, ↓IL-6, ↓TNFα

↑NO

↓ADHESION

↓MIGRATION

↑ENDOTHELIAL FUNCTION

ANTI-INFLAMMATORY and IMMUNOMODULATORY EFFECTS

May prevent reabsorption of

contrast from urinary space

Statin use and post-operative AKI

Statin usevs

Statin non-use

Less perioperative

AKI

associates

Molnar A, et al. J Am Soc Nephrol 2012

Brunelli S, et al. Am J Med 2012

Statin not heldvs

Statin held

Lower levelsUrine IL-18

Urine NGAL

Urine KIM-1

Plasma NGAL

Urine L-FABP

Urine albumin

associates

Molnar A, Parikh C et al. Ann Thorac Surg 2014

Meta-analysis 13 RCTs Lee JM et al. PLOS ONE Nov 2014

3.6% 8.3%

50% relative risk reduction in AKI

High-Dose Statin Pre-treatment to Prevent

Contrast Induced AKI

Can statins cause

Acute Kidney Injury

through drug-drug

interactions?

Cytochrome P450 isoenzyme 3A4 metabolized statins:

Atorvastatin, simvastatin, lovastatin

Cyp3A4 Statin +

Clarithromycin or

Erythromcyin(n = 75,000)

vs.

Cyp3A4 Statin +

Azithromcyin(n = 68,000)

associates

A higher risk of

Rhabdomyolysis

Acute Kidney Injury

Hyperkalemia

Mortality

Patel A et al. Ann Intern Med 2013

Blight

↑ risk

Benefit

↓ risk

Benign

no effect

Statins and Acute Kidney Injury

In a large observational study

analysis, high dose (vs. low dose)

statin associated a higher risk of

AKI

In RCTs of chronic

statin use, no

effect on AKI risk

High dose statin

before radiocontrast

prevents AKI

(renoprotective)

Statin + drug which inhibits

statin metabolism associates

with a higher risk of AKI

Diagnosis and Staging

• Damage, Furosemide Stress Test

• Jay Koyner, Univ of Chicago

• Sepsis Associated AKI

• Pathology

• Joseph Gaut

Biomarkers

Active Surveillance

Recognition of AKI

Glomerular Filtration • Serum Creatinine• Blood urine Nitrogen • Serum Cystatin C• Plasma NGAL

Glomerular Injury• Urine albumin excretion

Proximal Tubule Injury•Urine IL-18•Urine KIM-1•Urine L-FABP•Urine Cystatin C•α1-microglobulin•β2-microglobulin•Urine α-GST•Urine Netrin-1•Urine NAG

Loop of Henle Injury•Uromodulin

Distal Tubule•Urine NGAL•Urine π-GST

Biomarkers in Relation to Site of Injury in

Nephron

Other Mechanisms / Sites of Injury not specific to the Nephron•Hepcidin – Iron trafficking•TIMP-2/ IGFBP7 – G1 cell cycle arrest

Adapted from

Koyner and Parikh-

Brenner and

Rector’s The

Kidney – In press

2014

New Biomarker and Outcome

AUC>90%

No Yes

YesNo

Biomarker Not Helpful

Good Classifier

NRI/IDIChange in AUC/C-Index

Not A Good Classifier

Multivariate Association (OR/RR)

Clinically and Statistically Significant

Check incremental valueon existing clinical models

Simplified Framework for Biomarker Analysis

ROC Analysis

Slide courtesy

of Chirag

Parikh- but

then modified

10th ADQI Consensus Conference

• Increasing enthusiasm to include biomarkers in assessment panel in patients with AKI

“Subclinical AKI”

No functional changes or damage

Damage without loss of function

Loss of function without damage

Damage with loss of function

BiomarkerNegative

BiomarkerPositive

CreatinineNegative

CreatininePositive

Adapted from Endre, Kellum Koyner Goldstein et al Contrib Neph 2013- Courtesy of Steve Coca

TIMP-2 *IGFBP7-FDA Approved 2014

Bihorac et al AJRCCM 2014

Sapphire LTFU: Death or RRT

Koyner J, et al. JASN e-pub 22 Jan 2014 (doi:10.1681/ASN.2014060556)

Back to Basics: Actually Looking at Urine

Perazella et al CJASN 2010, Bagshaw et al NDT 2012

• 77 patients multi-center trial

• Challenging those with early AKI w/ a one

time dose of:

– 1 mg/ kg (loop naïve)

– 1.5 mg/kg (prior loop exposure)

• Exam Urine output following FST

Furosemide Stress Test (FST) Results

Outcome AUC (SE) P-value

Progress to AKIN 3

0.87 (0.09)

<0.001

RRT 0.86 (0.08)

0.001

Inpatient Mortality

0.70 (0.09)

0.02

Progress or Death

0.81 (0.06)

<0.001

Chawla and Koyner et al. Crit Care 2013

Prediction of Progression to Stage 3: N=25 (32%)

Prediction of Inpatient RRT: n=11(14%)

PATHOLOGY OF SEPTIC AKI

Joseph P. Gaut, MD, PhD

DEFINING THE PATHOLOGY OF KIDNEY INJURY IN SEPSIS

What are the histomorphologic changes that occur in kidneys from patients dying of sepsis?

What is the extent of acute kidney injury in septic patients?

Do these changes correlate with the need for dialysis in septic patients?

STUDY DESIGN○ Septic patients who died in surgical/medical intensive care

units were studied.

○ Sepsis was defined as microbiologically-proven, clinically-proven, or suspected infection and presence of systemic inflammatory response syndrome.

○ Sepsis was confirmed by post-mortem examination of tissues.

○ Patients with pre-existing dialysis-dependent renal failure were excluded.

○ All tissues were obtained at the bedside within 30-180 minutes of death.

○ Control kidneys were obtained from patients undergoing nephrectomy for renal cancer.

○ Additional control kidneys were obtained from patients who underwent nephrectomy for trauma.

PATIENT CHARACTERISTICSSepsis (n = 39) Controls (n =20)

Age (mean, range) 67 (18-94) 56 (26-76)

Gender (M/F) 24/20 22/7

Days of sepsis 4, 1-40

Acute Kidney Injury 36/39 0

Dialysis 14/36

Sites of infection

Intrapelvic abscess 4

Catheter 3

Necrotizing fasciitis 2

Osteomyelitis 1

Pneumonia 27

Peritonitis 19

Retroperitoneal abscess 1

UTI 2

HISTOLOGY OF KIDNEYS FROM SEPTIC PATIENTS

Control Septic

• Cytoplasmic blebbing is a common feature of kidney injury in sepsis.

• Autophagosomes are also frequently seen in septic kidney injury.

QUANTITATION OF KIDNEY INJURY

p = 0.06

p = 0.008

KIM-1 IN HUMAN SEPSIS

Control Sepsis

QUANTITATION OF KIM-1 STAINING

SEPTIC KIDNEY INJURY

Acute tubular injury occurs in human patients dying of sepsis.

Apoptosis occurs, but is rare.

Severity and extent of ischemic injury correlate with dialysis in human septic patients.

% KIM-1 immunostaining correlates with dialysis in human septic patients.

Reversibility and

Optimization

• Novel Therapies of AKI

• Remote ischemic preconditioning

• Christine Hsu

Targeted Interventions

Focus on Recovery

Response for AKI

Remote Ischemic Preconditioning

May Reduce Acute Kidney Injury

and Myocardial Injury in Children

Undergoing Cardiac Surgery

Christine Hsu, Matthew Toma, Ronit Katz, Cassianne

Robinson-Cohen, Bryan Kestenbaum, Yuk Law,

Jonathan Himmelfarb

Remote Ischemic Preconditioning (RPC)

Kharbanda et al. Lancet 2009; 374: 1557-65

Previous Studies

Authors N Results after RPC (Compared to Control)

Cheung (2006) 37 troponin I, TNF-a, inotrope requirementIL-10

Zhou (2010) 60 troponin I, CK, CK-MB, IL-6, IL-8, TNF-a lung compliance, IL-10

Luo (2011) 60 troponin I, CK-MB

Pavione (2012) 22 pro-BNPNo difference in troponin I, IL-8, IL-10

Jones (2013) 39 No difference in plasma troponin I, NGAL

Pedersen (2012) 105 AKI (RIFLE) from 59% to 50% (p>0.2)No difference in plasma cystatin C, plasma or urine NGAL

McCrindle (2014) 299 No difference in creatinine, cystatin

Methods

• Double-blind randomized controlled trial

– Randomized to RPC vs control

– Stratified by age and surgical complexity

(RACHS)

• Intervention:

– RPC: Lower-limb ischemia (4 cycles of 5 min,

using a BP cuff inflated to 15 mmHg above

SBP)

– Control: Deflated BP cuff over lower-limb

Results – RIPC for AKI

AKI Definition Control (%) RPC (%)

50% PlasmaCreatinine

20 (51.3%) 16 (35.6%)

50% PlasmaCystatin C

4 (10.3%) 3 (6.7%)

Renal Support

Modality

Dose and Intensity

• Timing and modality of RRT

• Martin Gallagher,

• Univ of MelbourneTiming of

intervention

Timing: RENAL study

• RENAL study sub-study• 439 participants• Analysed time:

• RIFLE “Injury” criteria to CRRT initiation (randomization)

• Regression models analysing impact of this time upon outcomes• Adjusted for covariates

• Time divided by quartiles:• < 7.1• 7.1 - 17.6• 17.6 - 46• ≥ 46 hrs

Timing of Initiation of RRT in RENAL Study

Timing: RENAL unadjusted survival

Timing: what about Urea in RENAL

RENAL study: conclusions

There may be a signal in favour or earlier treatment

Late dialysed patients in the ICU are systematically different to other patients

• Adjustment is unlikely to be complete

Urea is probably a better marker of mortality than time from “injury” to dialysis

Effect size does not appear large

• Separation between groups is large by clinical standards

Is ‘risk homeostasis’ at play here?

Ability to identify the late starters?

The nature of decision making

AKI at ASN Kidney Week 2014Rehabilitation

Referral

Active Interventions

• Outcomes• Chi Yuan Hsu

• Austin StackFollow up

Increased Risk of Elevated BP after AKI

Division of Nephrology

Chi-yuan Hsu, Raymond K. Hsu, Jingrong Yang,

Juan D. Ordonez, Sijie Zheng, Alan S. Go

2014 ASN Kidney Week

Philadelphia, PA

Saturday, November 15, 2014

Division of Nephrology, University of California-San Francisco, San Francisco, CA

Division of Research, Kaiser Permanente Northern California, Oakland, CA

AKI Severity

Adjusted* OR Ratio (95% CI) for elevated BP post discharge

180 days(N=40,861)

365 days(N=42,845)

540 days(N=43,407)

730 days(N=43,611)

AKI vs no AKI

1.40 (1.28 - 1.54)

1.36 (1.25 - 1.49)

1.27 (1.17 - 1.39)

1.22 (1.12 - 1.33)

Stage 1 AKI vs no AKI

1.23 (1.10-1.37)

1.21 (1.09-1.34)

1.13 (1.02-1.26)

1.09 (0.98-1.21)

Stage 2 AKI vs no AKI

1.66(1.33-2.08)

1.53 (1.23-1.90)

1.51 (1.22-1.87)

1.45 (1.17-1.79)

Stage 3 AKI vs no AKI

2.18 (1.74-2.74)

2.17 (1.73-2.71)

1.89 (1.51-2.37)

1.82 (1.45-2.29)

*Adjusted for age, sex, race, BMI, last ambulatory SBP and DBP, smoking status, DM, CHF, CHD, last ambulatory eGFR and proteinuria.

Results

Patterns of Recovery from Acute Kidney Injury and Risk of Progression in the Irish Population

Austin G Stack, Els H Gillis, Mohamed Elsayed,

Hoang T Nguyen, Ailish Hannigan, Patrick T. Murray,

Howard Johnson, Liam F. Casserly and John P Ferguson.

Methods

• Laboratory data from two Irish regional systems linked with Dialysis registers and National Mortality files

• Record matching based on probabilistic algorithm using the EM algorithm with 99% probability of match

• Median baseline creatinine determined prior to index AKI event within a 3 month window (71 % of patients)

• Where no creatinine record available (29%) prior to AKI event, we used post AKI test median, and 2 day post test minimum

• Lab data collection from 1999-2014 in the Irish Midwest and 2005-2011 in the Irish Northwest

Severity of AKI and Relative Risk for Death and 50% Decline in eGFR

1.00 3.40 4.39 5.25 6.481.00

10.04

22.76

57.89

101.19

0

20

40

60

80

100

120

no AKI(referent)

Transient Stage 1 Stage 2 Stage 3

Death 50% Decline in eGFR

Rela

tive R

isk

Model included: age, sex, location of initial supervision, country of residence, baseline eGFR pre-AKI event, haemoglobin, serum albumin

Recovery Status and Relative Risk for Death, Dialysis and Advanced CKD

1.00

3.84 4.26

6.51

4.16

1.00

2.78

6.21

9.88

1.271.001.95

4.94

27.23

2.31

0

5

10

15

20

25

30

no AKI (referent) Full Recovery Partial Recovery Failure toRecover

Unknown

Death Dialysis Advanced CKD (eGFR<10 ml/min)

Rela

tive R

isk

Model included: age, sex, location of initial supervision, country of residence, baseline eGFR pre-AKI event, haemoglobin, serum albumin