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ENDPOINTS FOR AKI STUDIES Raymond Vanholder, University Hospital, Ghent, Belgium

SUMMARY! AKI as an endpoint! Endpoints for studies in AKI 2

AKI AS AN ENDPOINT

BEFORE RIFLE THE LIST OF DEFINITIONS WAS ENDLESS Lameire et al, Nature Clin Pract Nephrol, 2: 364-377; 2006 4

RIFLE + AKIN = KDIGO?! Stage 1: one of the following:! Screa increased 1.5-1.9 x baseline! Screa increased > 0.3 mg/dl (26.5 µmol/l)! Urinary output < 0.5 ml/kg/h during a 6 hour block! Stage 2: one of the following:! Screa increased 2.0-2.9 x baseline! Urinary output < 0.5 ml/kg/h during two six hour blocks! Stage 3: one of the following:! Screa increased > 3.0 x baseline! Screa increased > 4.0 mg/dl (353.0 µmol/l)! Initiation of RRT! Urinary output < 0.3 ml/kg/h for more than 24 hours! Anuria for more than 12 hours 5

ADDING URINARY VOLUME TO SERUM CREATININE IDENTIFIES MORE AKI Figure 1 Distribu-on of RIFLE class based on a single or both criteria. Based on the urinary and the crea0nine criteria together (AKIboth), 35.5% of pa0ents had no AKI, versus 20.6%, 31.8%, and 12.1% with RIFLE R, I, and F. Based on the urinary output criterion only (AKIuo), 58.9% pa0ents were classified as having no- AKI, versus 10.3%, 27.1%, and 3.7% as RIFLE- R, I, or F, respec0vely. Based on the crea0nine criterion only (AKIc), 57% had no AKI, versus 17.8%, 15%, and 10.3% classified as RIFLE R, I, and F (P < 0.03). Vanmassenhove et al, Crit Care, 17:R234; 2013 8

TAKING INTO ACCOUNT URINARY VOLUME HAS ADDED VALUE TO SCREA TO DETECT HIGH RISK PATIENTS Macedo et al, KI, 80:760-767; 2011 9

DEFINING OLIGURIA BY 6 HOUR BLOCKS IDENTIFIED A LARGE NUMBER OF HIGH RISK PATIENTS Macedo et al, NDT, 26:509-515; 2011 10

CAN NOVEL BIOMARKERS REPLACE CLASSICAL KIDNEY FUNCTION ENDPOINTS IN STUDIES OF AKI?

An overlap between AKI and the others Nickolas TL et al. Ann Intern Med. 2008;148:810 819. 12

SERUM CREATININE! Fig 3! Influencing factors! Kidney function! Muscle mass! Age! Gender! Food intake! Kidney perfusion! Hudrataion! ACEi, ARB Stevens et al, NEJM, 354:2473-2483; 2006 13

RELATIONSHIP WITH INFLAMMATION Wheeler DS et al. Crit Care Med., 36:1297 1303; 2008 14

RELATIONSHIP WITH INFLAMMATION Wheeler DS et al. Crit Care Med., 36:1297 1303; 2008 15

An overlap between AKI and the others Nickolas TL et al. Ann Intern Med. 2008;148:810 819. 16

CYSTATIN C 17

CYSTATIN C 18

ENDPOINTS FOR STUDIES IN AKI

ENDPOINTS IN STUDIES ON AKI! Hard and semi-hard! Mortality! Evolution renal function! Recovery renal function! Need for RRT! Time on dialysis! Definitive stay on dialysis! MOF! Soft! Blood pressure! Use of vasopressors! Ventilator need! Length hospitalization! Length hospitalization ICU 20

Natural history of AKI Cerda et al, Clin J Am Soc Nephrol, 3: epub; 2008 23

INCREASED RISK OF POST-AKI CKD NECESSITATES POST HOC CHECK-UP Meta-analysis of chronic kidney disease (CKD) and end-stage renal disease (ESRD) associated with acute kidney injury (AKI). (a) Pooled adjusted hazard ratios (HRs) for CKD after AKI. (b) Pooled adjusted HRs for ESRD after AKI. Coca et al, KI, 81: 442-448; 2012 24

ENDPOINTS IN STUDIES ON AKI! Hard and semi-hard! Mortality! Evolution renal function! Recovery renal function! Need for RRT! Time on dialysis! Definitive stay on dialysis! MOF! Mortality after discharge!! Soft! Blood pressure! Use of vasopressors! Ventilator need! Length hospitalization! Length hospitalization ICU 28

MORTALITY OF AKI PATIENTS AFTER HOSPITAL DISCHARGE IS HIGH Allegretti et al, Crit Care, 17: R109 2013 29

CONCLUSIONS! Defining a well-specified threshold Screa for defining AKI has increased sensitivity and consistency! Adding urinary volume to Screa further increases sensitivity! Biomarkers are useful as a statistical tool but are sensitive to confounders! Useful outcomes in studies on settled AKI are mortality, length of stay and recovery of renal function! Interesting aspects not much considered are mortality after discharge from the ICU and the hospital 30

BACK-UPS

IMPACT ON MORTALITY V. Seabra et al, AJKD, 52: 272-284; 2008 32

IMPACT ON RECOVERY RENAL FUNCTION V. Seabra et al, AJKD, 52: 272-284; 2008 33

Table 1 Baseline characteristics for Sapphire study patients Endpoint positive Endpoint negative All patients P values All patients 101 627 728 Male 65 (64%) 384 (61%) 449 (62%) 0.58 Age 65 (57-77) 64 (52-73) 64 (53-73) 0.048 Race 0.98 White 81 (80%) 492 (78%) 573 (79%) Black 11 (11%) 76 (12%) 87 (12%) Other/Unknown 9 (9%) 59 (9%) 68 (9%) Chronic comorbidities Chronic kidney disease 14 (14%) 51 (8%) 65 (9%) 0.14 Diabetes mellitus 39 (39%) 171 (27%) 210 (29%) 0.064 Congestive heart failure 23 (23%) 99 (16%) 122 (17%) 0.17 Coronary artery disease 33 (33%) 187 (30%) 220 (30%) 0.48 Hypertension 76 (75%) 357 (57%) 433 (59%) 0.001 Chronic obstructive pulmonary disease 21 (21%) 141 (22%) 162 (22%) 0.80 Cancer 25 (25%) 163 (26%) 188 (26%) 0.53 Reason for ICU admission Respiratory 47 (47%) 263 (42%) 310 (43%) 0.39 Surgery 32 (32%) 215 (34%) 247 (34%) 0.65 Cardiovascular 41 (41%) 202 (32%) 243 (33%) 0.11 Sepsis 26 (26%) 110 (18%) 136 (19%) 0.055 Neurological 8 (8%) 62 (10%) 70 (10%) 0.72 Trauma 4 (4%) 51 (8%) 55 (8%) 0.16 Other 21 (21%) 105 (17%) 126 (17%) 0.32 Enrollment serum creatinine 1.4 (0.9-1.8) 0.9 (0.7-1.2) 0.9 (0.7-1.2) <0.001 APACHE III 85 (59-106) 67 (51-88) 69 (51-91) <0.001 Kashani et al, Critical Care, 17: R25; 2013 34

Table S4. Cox Proportional Hazards Models For [TIMP-2] [IGFBP7] and Clinical Covariates for the Sapphire Cohort Clinical Model Clinical Model with [TIMP-2] [IGFBP7] Variable Hazard Ratio p-value 1 Hazard ratio p-value 1 Age 0.99 0.32 0.99 0.35 Serum Creatinine 2 NA 3 <.0001 NA 3 <.0001 APACHE III Score 1.0 0.001 1.0 0.35 Hypertension 2.2 0.002 2.1 0.004 Nephrotoxic drugs 1.6 0.033 1.4 0.12 Liver Disease 2.4 0.037 2.2 0.069 Sepsis 1.4 0.18 1.3 0.32 Diabetes 1.4 0.16 1.3 0.29 Chronic Kidney Disease 0.52 0.031 0.70 0.27 [TIMP-2] [IGFBP7] 4 Not included in model 4.1 <.0001 C-statistic (95% CI) 5 0.81 (0.76-0.85) 0.87 (0.84-0.90) 1 Likelihood ratio chi-square test. P-value <0.0001 for the model with [TIMP-2] [IGFBP7] and clinical covariates shows that [TIMP-2] [IGFBP7] adds significant predictive power compared with the clinical covariates alone. 2 Transform for serum creatinine was a restricted cubic spline with 6 degrees of freedom. 3 The hazard ratio for serum creatinine is not shown because it changes throughout the range of serum creatinine values, owing to the continuous non-linear shape of the transformation. 4 [TIMP-2] [IGFBP7] was log transformed. 5 Harrell's c-statistic 35

NGAL IN CRITICALLY ILL PATIENTS Siew ED et al.,j Am Soc Nephrol., 20:1823 1832; 2009 37

NGAL IN CRITICALLY ILL PATIENTS Siew ED et al.,j Am Soc Nephrol., 20:1823 1832; 2009 38

NGAL IN CRITICALLY ILL PATIENTS Siew ED et al.,j Am Soc Nephrol., 20:1823 1832; 2009 39

NGAL IN CRITICALLY ILL PATIENTS Fig. 5 The AUC-ROCs for AKI development within 24 h as predicted by ungal at enrollment (red line), a clinical prediction model (yellow line), and a combined model (blue line). Clinical predictors included age, modified APACHE II score, serum creatinine closest to enrollment, the presence of sepsis, and unit location. The AUC values and 95% CIs are listed within the figure. Siew ED et al.,j Am Soc Nephrol., 20:1823 1832; 2009 40

OTHER SIMPLE TESTS DISTINGUISH PRE- RENAL FROM RENAL 100 90 80 70 60 50 40 30 20 10 0 PR without diuretics PR with diuretics PR-total FENa FE Na FE UN FEUN U/PCr Cr Carvounis CP et al., Kidney Int., 62:2223 2229; 2002 41

MORTALITY ASSOCIATED WITH CHANGES IN SERUM CREATININE 1000 50 Number of patients 800 600 400 200 0 Mortality (%) within 30 days (,-0.5) [-0.5,-0.4) [-0.4,-0.3) [-0.3,-0.2) [-0.2,-0.1) [-0.1,0.0) [0.0,0.1) [0.1,0.2) [0.2,03) [0.3,0.4) [0.4,0.5) [0.5,0.6) [0.6,0.7] [0.7,0.8) [0.8,0.9) [0.9, ) (,-0.5) [-0.5,-0.4) [-0.4,-0.3) [-0.3,-0.2) [-0.2,-0.1) [-0.1,0.0) [0.0,0.1) [0.1,0.2) [0.2,03) [0.3,0.4) [0.4,0.5) [0.5,0.6) [0.6,0.7] [0.7,0.8) Δ Serum creatinine (mg/dl -1 ) Δ Serum creatinine (mg/dl -1 ) 40 30 20 10 0 [0.8,0.9) [0.9, ) Lassnigg et al, J Am Soc Nephrol 15:1597-1605; 2004 43

Shiao et al, J Crit Care, 13: R171; 2009 44

Shiao et al, J Crit Care, 13: R171; 2009 45

0 Shiao et al, J Crit Care, 13: R171; 2009 46

Shiao et al, J Crit Care, 13: R171; 2009 47

Shiao et al, J Crit Care, 13: R171; 2009 48

Chou et al, J Crit Care, 15: R134; 2011 50

Chou et al, J Crit Care, 15: R134; 2011 51

Chou et al, J Crit Care, 15: R134; 2011 52

BASELINE KIDNEY FUNCTION! KDIGO: Calculate presumed Screa for age subject assuming an MDRD egfr of 75 ml/min! ERBP: Focus on first documented Screa 53

Chou et al, J Crit Care, 15: R134; 2011 55

Chou et al, J Crit Care, 15: R134; 2011 56

Chou et al, J Crit Care, 15: R134; 2011 57

Shiao et al, J Crit Care, 13: R171; 2009 59

Shiao et al, J Crit Care, 13: R171; 2009 60

Shiao et al, J Crit Care, 13: R171; 2009 61

NGAL: USEFUL IN THE EARLY PREDICTION OF AKI, INITIATION OF RRT AND IN-HOSPITAL MORTALITY Haase M et al., Am J Kid Dis., 54:1012 1024; 2009 62

NGAL AFTER CARDIAC SURGERY: NO GAIN Figure 3. Urinary neutrophil gelatinase-associated lipocalin (NGAL) levels before (PreOP) and after (PostOP) cardiac surgery (hours) in patients with or without acute kidney injury (AKI; mean ± SEM). *P < 0.05 comparing patients with and without AKI. Wagener G et al., Am J Kidney Dis., 52:425 433; 2008 63

NGAL AS AN ALTERNATIVE MARKER? REMOTE ISCHEMIC CONDITIONING IN CHILDREN Open: control Closed: exp. Pedersen et al, J Thorac Cardiovasc Surg, 143:576-583; 2012 64

Vanmassenhove et al, Plos One, in press 65

Vanmassenhove et al, Plos One, in press 66

CYSTATIN C AS AN ALTERNATIVE MARKER? REMOTE ISCHEMIC CONDITIONING IN CHILDREN Open: control Closed: exp. Pedersen et al, J Thorac Cardiovasc Surg, 143:576-583; 2012 67

COMPARISON OF HEMODYNAMIC TOLERANCE BETWEEN CAVH AND HD mm Hg or percent Misset et al Int Care Med 22:742; 1996 68

USE OF ADRENERGIC DRUGS IN CAVH AND IHD Misset et al. Int Care Med 22:742;1996 69

NGAL: USEFUL IN THE EARLY PREDICTION OF AKI, INITIATION OF RRT AND IN-HOSPITAL MORTALITY Haase M et al., Am J Kid Dis., 54:1012 1024; 2009 70