AKI-6 Epidemiology of Acute Kidney Injury
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- Maryann Parker
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1 FACULTY OF MEDICINE AND HEALTH SCIENCES Academic Year AKI-6 Epidemiology of Acute Kidney Injury Anne NOBELS Promotor: Prof. Dr. E. Hoste Co-promotor: Prof. Dr. J. Kellum (Pittsburg) Dissertation presented in the 2 nd Master year in the program of Master in Medicine
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3 FACULTY OF MEDICINE AND HEALTH SCIENCES Academic Year AKI-6 Epidemiology of Acute Kidney Injury Anne NOBELS Promotor: Prof. Dr. E. Hoste Co-promotor: Prof. Dr. J. Kellum (Pittsburg) Dissertation presented in the 2 nd Master year in the program of Master in Medicine
4 The author and the promotor give the permission to use this thesis for consultation and to copy parts of it for personal use. Every other use is subject to the copyright laws, more specifically the source must be extensively specified when using results from this thesis. Date Anne Nobels (student) Prof. Dr. E. Hoste (promotor)
5 Foreword This master thesis is the result of two years hard work. I want to thank sincerely all those people who helped me during this period. First of all I want to thank my promotor, Prof. Dr. Eric Hoste, for his endless patience, for his critical view, for his feedback, for all the time he spend on my master thesis, and for the opportunity to work further on a scientific paper after this master thesis. I want to thank Prof. Dr. John Kellum and Dr. Nattachai Sisrawat to help me understand the AKI-6 database and the different AKI classifications. Chris Danneels and Bram Gadeyne, I want to thank for their ICT help and their patience with an ICTstarter like me. Special thanks to Chris Danneels for writing a program to calculate the duration of the AKI episodes. Jonathan De Rudder, I want to thank for his mathematical insight and his recalculation of the CKD- EPI equitation. My parents, family and friends I want to thank for their support during this master thesis and my studies in general.
6 Table of Contents 1. Abstract Introduction Materials and Methods Results Conclusion Introduction Materials and methods Literature Study Design Acute Kidney Injury (AKI) RIFLE classification for AKI Acute Kidney Injury Network (AKIN) diagnostic and classification system for AKI The Kidney Disease Improving Global Outcomes (KDIGO) definition and staging system for AKI Baseline serum creatinine concentration Classification of patients into AKI categories Transient Acute Kidney Injury Statistical analysis Presentation of the results Results Basic Characteristics of the study population Acute Kidney Injury Outcomes ICU Mortality Hospital Mortality ICU Length of stay Hospital Length of Stay Transient AKI Transient AKI defined as 3 days of AKI (AKIt3) Transient AKI defined as 2 days of AKI (AKIt2) Transient AKI defined as 1 day of AKI (AKIt1)... 26
7 Comparison of mortality between AKIt1, AKIt2 and AKIt Discussion Prevalence of AKI Outcomes Classifications of AKI AKI and transient AKI prevalence AKI and transient AKI outcomes Strengths and limitations Conclusion Nederlandse samenvatting Inleiding Methodologie Resultaten Besluit References... 42
8 1. Abstract 1.1. Introduction Acute Kidney Injury (AKI) is associated with increased mortality, even after correction for covariates (1). In 2004 the Acute Dialysis Quality Initiative (ADQI) group developed a consensus definition for AKI, the RIFLE classification (2). Up to two-thirds of all ICU patients will develop AKI defined by the RIFLE classification (1). In the meantime two modifications of the RIFLE classification were developed, the AKIN classification (3), and recently the KDIGO classification (4). Recently, transient AKI or transient azotemia (TA) was defined as AKI lasting for < 72 h (5). Patients with TA had a significantly higher odds ratio for hospital mortality, and long-term mortality (5) Materials and Methods The AKI-6 TRansient AKI Study (TRAK Study) is a retrospective multicenter international cohort study. Data were collected by the Acute Kidney Injury 6 study group (AKI-6). AKI-6 is a multicenter, transatlantic study group of intensivists of 6 centers, 2 centers in the USA, 2 European centers and 2 Australian centers. A total of 11,309 patients admitted on the Intensive Care Unit in the period were analyzed. When baseline creatinine was not available, this was calculated by the 4-variable (6) or equation (7). Therefore, AKI patients were classified according to 5 AKI classifications: RIFLE, RIFLE, AKIN, KDIGO and KDIGO. We analyzed 4 clinical outcomes: ICU mortality, hospital mortality, ICU length of stay, and hospital length of stay. AKI patients and patients without AKI were compared, as well as patients with transient AKI and patients with a longer AKI episode. We defined transient AKI in three different ways: 1. Transient AKI with duration of 3 days of AKI (AKIt3) 2. Transient AKI with duration of 2 days of AKI (AKIt2) 3. Transient AKI with duration of 1 days of AKI (AKIt1) 1.3. Results Acute Kidney Injury occurred in 17.8% to 31.0% of the ICU patients according to the AKI classification used and was associated with worse clinical outcomes. Patients with AKI had a higher 1
9 ICU mortality (17.6%-24.0%) compared to the patients without AKI (4.5%-5.5%). There was also higher hospital mortality in AKI patients (25.5%-32.9%) compared to patients without AKI (7.9%- 9.4%). Patients with AKI had a longer ICU and hospital length of stay compared to patients without AKI. Transient AKI occurred frequently. The period prevalence of AKIt3 varied according to the classification used between 13.9% and 22.7% of ICU patients, the period prevalence of AKIt2 varied between 8.0% and 19.7%, and the period prevalence of AKIt1 varied between 6.4% and 13.1%. AKIt3 occurred in 65.7% to 78% of AKI patients, AKIt2 in 34.0% to 67.1% and AKIt1 in 28.2% to 42.1%. Transient AKI (AKIt1, AKIt2 and AKIt3) was associated with a higher ICU and hospital mortality compared to patients without AKI. There was no difference in mortality between the different transient AKI definitions, and also not with all AKI. The duration of an AKI episode was associated with a longer ICU and hospital length of stay. We couldn t find an association with ICU mortality. Hospital mortality of patients with AKIt2 and 3 was lower compared to patients with longer duration of AKI. Patients with AKIt1 had a similar hospital mortality compared to patients with a longer AKI episode (>1 day). Comparing the five classification used in this analysis: RIFLE, RIFLE, AKIN, KDIGO and KDIGO, differences can be seen in AKI prevalence, duration of the first AKI episode, clinical outcomes, transient AKI prevalence and transient AKI outcomes Conclusion In this large multicenter international cohort of ICU patients, AKI was common and related to an increase of ICU and hospital mortality, and a longer ICU and hospital length of stay. Transient AKI occurred in up to 2 third of all AKI cases. ICU and hospital mortality was higher in transient AKI patients compared to patients without AKI, but similar between Transient AKI variants and all AKI. Compared to AKI with longer duration, most Transient AKI had similar ICU mortality, but lower hospital mortality. A longer AKI episode was associated with a longer length of stay. Although the AKI definitions are very similar, there was important variation in prevalence of AKI and transient AKI, and outcomes among the different AKI definitions. Duration of AKI should be incorporated in new AKI consensus definitions and used in clinical studies. 2
10 2. Introduction Acute Kidney Injury (AKI) is a common condition in critical ill patients with a significant higher risk of death. For years there was no consensus definition for AKI, but in the last decade three consensus definitions were developed using a combination of creatinine and urine output criteria. In 2004 the Acute Dialysis Quality Initiative (ADQI) group developed the RIFLE classification (2). Up to twothirds of all intensive care unit patients will develop AKI defined by the RIFLE classification (1). In 2007 The Acute Kidney Injury Network (AKIN) developed an adaptation of the RIFLE classification (3). The last definition was developed only a few months ago by the KDIGO group (4). The RIFLE and KDIGO classification work with a baseline creatinine value. If there is no baseline value available, the baseline is calculated out of the glomerular filtration rate (GFR) value by the 4-variable Modification of Diet in Renal Disease () equitation (6). In 2009 Levey et al. (7) proposed a new and more accurate equitation to calculate the GFR, the Chronic Kidney Disease Epidemiology Collaboration () equitation. Most AKI epidemiology studies examined the relation between morbidity and mortality based on the maximum RIFLE class. Uchino et al. (5) demonstrated that patients with transient AKI (<72h) had a significantly higher odds ratio for hospital mortality. Coca et al.(8) demonstrated that the duration of an postoperative AKI episode is associated with an increased risk of long-term mortality in diabetic US veterans. The aim of the TRAK study (AKI-6 Transient AKI Study) was to determine the influence of AKI duration on outcomes (mortality, length of stay) in an Intensive Care Unit (ICU) population. We compared different AKI classifications and different ways of calculating baseline creatinine value. 3
11 3. Materials and methods 3.1. Literature Before starting the analyses there was performed a literature study. Articles were found using Pubmed and following keywords: Acute kidney injury, RIFLE, AKIN, KDIGO,,. References of found articles were also used. These articles were used in the in the introduction and discussion section of this thesis. An overview of the articles can be found under references. The references were compiled using Endnote X Study Design The TRAK study is a retrospective multicenter international cohort study. Data were collected by the Acute Kidney Injury 6 study group (AKI-6). AKI-6 is a multicenter, transatlantic study group of intensivists of 6 centers, Dr. J.A. Kellum, University of Pittsburgh Medical Center, (Pittsburgh, PA, USA), Dr. G. Ognjen, the Mayo Clinic (Rochester, Minnesota, USA), Dr. S Webb, Royal Perth Hospital (Perth, Australia), Dr. R. Bellomo, Austin Health Center (Melbourne, Australia), Dr. E. Hoste, Ghent University Hospital (Ghent, Belgium), Dr. C. Ronco and Dr. D. Cruz, Ospedale San Bortolo di Vicenza (Vicenza, Italy). In the rest of this master thesis the participating centers will be referred as the cities were they are situated. In Pittsburg, Rochester, Perth and Ghent every patient admitted on the Intensive Care Unit (ICU) was registered from 2005 till In Melbourne and Vicenza patients were registered during a shorter time period within the same study period. This is the main reason for the unequal patient distribution in the database. During the whole ICU stay the following data were recorded: worst serum creatinine concentration, urine output, treatment with mechanical ventilation, and treatment with renal replacement therapy. ICU mortality, hospital mortality, ICU length of stay and hospital length of stay, were registered as outcomes. 4
12 To compare serum creatinine values in the different centers, the values had to be recalibrated to Isotope Dilution Mass Spectrometry reference measurement procedure (IDMS standards). Ghent, Mayo, Perth and Vicenza were already using the IDMS standards in their lab, so recalibration was not necessary. For Pittsburg and Melbourne we used the same recalibration formulas as Zavada et al. (9). Pittsburg: Austin: (SCr: Serum creatinine concentration) 3.3. Acute Kidney Injury (AKI) Acute kidney Injury (AKI) was defined according to the different consensus staging systems for AKI that have recently been published: the RIFLE criteria (2), AKIN criteria (3) and KDIGO criteria (4). AKIN and KDIGO are modifications of the RIFLE criteria, therefore the differences between the 3 staging systems are limited on first sight. In all three staging systems, AKI can be staged based on an increase of serum creatinine concentration or a period of oliguria. As urine output criteria were not available in the majority of patients, we used only the creatinine criteria for staging and classification of AKI RIFLE classification for AKI RIFLE is an acronym for three levels of renal dysfunction: Risk, Injury, Failure and two renal outcomes: Loss and End Stage Kidney Disease. In the TRAK study we only analyzed the renal dysfunction, not the renal outcomes. The creatinine criteria for the different stages are displayed in table 1. Table 1. RIFLE classification for AKI, creatinine criteria RIFLE Creatinine Criteria Risk SCr of 1.5 to 1.9 times baseline Injury SCr of 2.0 to 2.9 times baseline Failure SCr of 3.0 or more times baseline Acute on chronic AKI SCr 4mg/dl and acute rise 0.5 mg/dl SCr: serum creatinine concentration 5
13 Acute Kidney Injury Network (AKIN) diagnostic and classification system for AKI AKIN defines AKI as an abrupt (within 48u) reduction in kidney function defined as an absolute increase in serum creatinine of 0.3 mg/dl, a 50% increase in serum creatinine or a reduction in urine output (<0.5 ml/kg/h for more than 6 hours). We used the lowest creatinine value in 48u before the start of AKI as baseline creatinine value. AKIN classifies AKI patients in 3 stages of severity. In Table 2 the creatinine criteria for this stages are described. Table 2. Acute Kidney Injury Network (AKIN) diagnostic and classification system for AKI, creatinine criteria AKIN Creatinine Criteria Stage 1 Increase of SCr 0.3 mg/dl or increase of SCr 150% to 200% Stage 2 Increase of SCr 200% to 300% Stage 3 Increase of SCr 300% (or SCr 4 mg/dl and acute rise 0.5mg/dl) or initiation of RRT SCr: serum creatinine concentration, RRT: Renal Replacement Therapy The Kidney Disease Improving Global Outcomes (KDIGO) definition and staging system for AKI According to KDIGO, AKI is defined as any of the following: increase in serum creatinine by 0.3 mg/dl within 48 hours or increase in serum creatinine to 1.5 times baseline within 7 days or reduction of urine output <0.5 ml/kg/h for 6 hours. AKI patients are classified in 3 stages of severity. The creatinine criteria for these stages are described in table 3. 6
14 Table 3. The Kidney Disease Improving Global Outcomes (KDIGO) definition and staging system for AKI, creatinine criteria KDIGO Creatinine Criteria Stage 1 SCr of 1.5 to 1.9 times baseline or 0.3 mg/dl increase Stage 2 SCr of 2.0 to 2.9 times baseline Stage 3 SCr of 3.0 times baseline or initiation of RRT Acute on chronic AKI SCr of 4 mg/dl SCr: serum creatinine concentration, RRT: Renal Replacement Therapy In the RIFLE and KDIGO definitions acute on chronic AKI is described as a separate AKI stage (SCr 4 mg/dl ± an acute rise of 0.5mg/dl). In the AKIN classification acute on chronic AKI is considered as a part of stage 3. In the results section we will therefore report on acute on chronic AKI for RIFLE and KDIGO, while for AKIN we will only report stage Baseline serum creatinine concentration The RIFLE and KDIGO classifications use a baseline creatinine value measured before the current hospitalisation of the patient, for calculation of the increase in serum creatinine concentration. In 69.5% of the patients this baseline serum creatinine concentration value was unknown. If there was no baseline creatinine available, the re-expressed 4-variable (6) and CDK-EPI (7) equitation were used to calculate a baseline value. In patients who had absence of chronic kidney disease, we assumed a Glomerular Filtration Rate (GFR) of 75 ml/min (1, 2). r: : o o κ is 0.7 for females and 0.9 for males α is for females and for males 7
15 Classification of patients into AKI categories As we used for this analysis 3 different classifications for AKI, and 2 estimates for missing baseline serum creatinine concentrations, we classified patients according to 5 different classifications. 1) RIFLE : AKI was classified using the RIFLE classification. If there was no baseline creatinine available the re-expressed 4-variable was used to calculate a baseline value. 2) RIFLE : AKI was classified using the RIFLE classification. If there was no baseline creatinine available the equitation was used to calculate a baseline value. 3) AKIN: AKI was classified using the AKIN classification. We used the lowest creatinine value in 48u before the start of AKI as baseline creatinine value. 4) KDIGO : AKI was classified using the KDIGO classification. If there was no baseline creatinine available the re-expressed 4-variable was used to calculate a baseline value. 5) KDIGO : AKI was classified using the KDIGO classification. If there was no baseline creatinie available the equitation was used to calculate a baseline value. Only the first AKI episode was included in our analysis Transient Acute Kidney Injury Transient Acute Kidney Injury was defined in three different ways: 1. Transient AKI with duration of 3 days of AKI (AKIt3) 2. Transient AKI with duration of 2 days of AKI (AKIt2) 3. Transient AKI with duration of 1 days of AKI (AKIt1) 3.5. Statistical analysis To describe the characteristics of the study population MS Access 2010 was used. The number of AKI episodes per patient and duration of these episodes were calculated using MS Access Specific cases were selected and exported to SPSS for further statistical analysis 8
16 SPSS Statistics version 19 was used to perform the statistical analysis. Categorical variables are displayed as number (percentage). To analyze categorical variables we used the Chi-square test. Continuous variables are displayed as median and 25 th and 75 th percentiles. We tested continuous variables for normality by distribution plots, and compared means using Student s T-test when normally distributed, and Kruskall-Wallis test and Mann-Whitney-U test when not. A double sided p- value <0.05 was considered significant Presentation of the results Tables were made by MS Word The bar charts were made by MS Excel
17 4. Results 4.1. Basic Characteristics of the study population The AKI-6 database includes 55,486 patient days and 11,309 patients. Three of the AKI-6 centers contributed for 79% of the study cohort. Among these centers patient s inclusion was evenly distributed. The cohort represents a typical ICU population for a developed country. Two-thirds of patients were of male gender, median age was 62 years, and more than 80% of patients were Caucasian. In table 4 the baseline characteristics of the study population are described. Table 4. Baseline Characteristics of the study population Baseline Characteristics of the study population Number of patients per participating center (% of total study population) Pittsburgh 2974 (26.9%) Rochester 2852 (25.2%) Ghent 3044 (26.9%) Vicenza 267 (2.4%) Perth 2077 (18.4%) Melbourne 95 (0.8%) Number of AKI patients per participating center (% of AKI patients per center) Pittsburgh 923 (31,0%) Rochester 704 (24,7%) Ghent 679 (22,3%) Vicenza 99 (37,1%) Perth 811 (39,0%) Melbourne 61 (64,2%) Patient characteristics (% of study population) Gender Male 6776 (60%) Female 4532 (40%) Median age (in years) 62 (48, 73) Pittsburgh 61 (48,73) Rochester 66 (52,77) Ghent 62 (50,72) Vicenza 64 (45,74) Perth 55 (38,70) Melbourne 62 (45,74) Race Caucasian 9536 (84.3%) Black 450 (4.0%) Hispanic 572 (5.1%) Asian 43 (0.4%) American Indian 10 (0.09%) Other 149 (1.3%) Availability of baseline creatinine 3452 (30.5%) Pittsburgh 155 (5.2%) Rochester 2794 (98.0%) Ghent 181 (5.9%) 10
18 Vicenza 267 (100%) Perth 0 (0.0%) Melbourne 55 (58.0%) 11
19 4.2. Acute Kidney Injury A total of 11,309 patients were classified according to the 5 different classifications for AKI that were used in this analysis: RIFLE, RIFLE, AKIN, KDIGO and KDIGO CKD- EPI. We calculated the number of AKI episodes per classification, the number of patients who had 1, 2, 3, 4 or more than 4 AKI episodes and the duration of the first AKI episode. The results are described in tables 5 and 6. The KDIGO classification was the most sensitive for detection of AKI, and the AKIN classification the least sensitive. When defined by RIFLE the use of resulted in a higher number of AKI episodes, while with KDIGO, the use of the equation resulted in a higher number of AKI episodes detected. The prevalence of AKI varied according to the classification used between 17.8% and 31.0%. Table 5. Number of AKI episodes per AKI classification AKI episode RIFLE RIFLE AKIN KDIGO KDIGO Total episodes (23.5%) 2568 (22.7%) 2010 (17.8%) 3204 (28.3%) 3506 (31.0%) (2.5%) 274 (2.4%) 354 (3.1%) 290 (2.6%) 453 (4.0%) 3 59 (0.5%) 52 (0.5%) 114 (1.0%) 61 (0.5%) 96 (0.8%) 4 14 (0.1%) 14 (0.1%) 55 (0.5%) 21 (0.2%) 26 (0.2%) >4 2 (0.02%) 4 (0.04%) 59 (0.5%) 12 (0.1%) 21 (0.2%) In the majority of AKI patients, the duration of the first AKI episode was 1 or 2 days. So transient AKI was very common among AKI patients at ICU. There was a greater proportion of AKI patients with shorter duration of AKI ( 2 days) when classified according to AKIN. 12
20 Table 6. Duration of first AKI episode per AKI classification Duration of first AKI RIFLE RIFLE AKIN KDIGO KDIGO episode 1 day 763 (28.7%) 728 (28.3%) 806 (40.1%) 999 (31.1%) 1475 (42.1%) 2 days 621 (23.3%) 607 (23.6%) 544 (27.1%) 761 (23.8%) 759 (21.6%) 3 days 374 (14.0%) 363 (14.1%) 221 (11.0%) 397 (12.4%) 343 (9.8%) 4 days 245 (9.2%) 240 (9.3%) 124 (6.2%) 253 (7.9%) 244 (7.0%) 5 days 166 (6.2%) 152 (5.9%) 90 (4.5%) 177 (5.5%) 164 (4.7%) 6 days 99 (3.7%) 100 (3.8%) 38 (1.9%) 118 (3.7%) 116 (3.3%) 7 days 76 (2.8%) 72 (2.8%) 32 (1.6%) 87 (2.7%) 75 (2.1%) >7 days 320 (12.0%) 306 (11.9%) 155 (7.7%) 412 (12.9%) 330 (9.4%) 13
21 4.3. Outcomes The outcomes we analyzed were Intensive Care Unit Mortality (ICU Mortality), Hospital Mortality, Intensive Care Unit Length of Stay (ICU Length of Stay) and Hospital Mortality. We compared patients with and without AKI. AKI patients were classified according to the 5 different AKI classifications: RIFLE, RIFLE, AKIN, KDIGO and KDIGO. We also compared the outcomes of the different AKI stages. Only the first AKI episode was included in our analyses ICU Mortality Total ICU Mortality was 8.7%. Patients with AKI had a higher ICU mortality (17.6%-24.0%) compared to the patients without AKI (4.5%-5.5%) (table 7). We found a stepwise increase in mortality with increasing severity of AKI in all classifications. Patients who experienced acute on chronic AKI (Fc) had a lower mortality compared to Failure patients, when defined according to the RIFLE classification. When defined by KDIGO, this difference was less pronounced. Mortality for stage 1 and 2 patients defined according to AKIN was higher when compared to RIFLE and KDIGO with similar severity of AKI. Table 7: ICU mortality of patients without and with AKI, defined according to the different AKI classifications ICU Mortality No AKI R/1 (%) I/2 (%) F/3 (%) Fc (%) All AKI (%) (%) RIFLE 438 (5.1) 128 (14.8) 154 (22.8) 173 (33.8) 93 (15.5) 548 (20.7) RIFLE 446 (5.1) 124 (15.5) 158 (24.1) 166 (34.1) 93 (15.5) 541 (21.2) AKIN 507 (5.5) 198 (20.2) 32 (29.1) 253 (27.5) 483 (24.0) KDIGO 365 (4.5) 155 (13.5) 106 (18.6) 89 (27.5) 272 (23.7) 622 (19.5) KDIGO 373 (4.8) 173 (11.1) 119 (19.8) 51 (25.9) 270 (23.7) 613 (17.6) R/1: Risk/ Stage 1, I/2: Injury/Stage 2, F/3: Failure/ Stage 3, Fc: Acute on chronic AKI 14
22 The P-values of the comparison between the different AKI stages per classification are displayed in table 8. Patients with AKI had a significant higher mortality compared to patients without AKI, regardless of severity of AKI. The differences between Risk/Stage 1 and Injury/Stage 2 and Risk/Stage 1 and Failure/Stage 3 were also significant for all classifications. The difference between Risk/Stage 1 and Acute on chronic (Fc) was significant when defined according to KDIGO. When defined according to RIFLE the difference was not significant. For the comparison between Injury/Stage 2 and Failure/Stage 3, Injury/Stage 2 and Acute on chronic (Fc) and Failure/Stage 3 and Acute on chronic (Fc) the results were variable. Acute on chronic (Fc) defined according to RIFLE had lower mortality compared to Failure, while this was not the case when defined according to KDIGO. Table 8: P-values for ICU mortality of patients without and with AKI, defined according to the different AKI classifications ICU Mortality: P-values RIFLE RIFLE AKIN KDIGO KDIGO No AKI and R/1 <0.001 <0.001 <0.001 <0.001 <0.001 No AKI and I/2 <0.001 <0.001 <0.001 <0.001 <0.001 No AKI and F/3 <0.001 <0.001 <0.001 <0.001 <0.001 No AKI and Fc <0.001 <0.001 <0.001 <0.001 R/1 and I/2 <0.001 < <0.001 R/1 and F/3 <0.001 <0.001 <0.001 <0.001 <0.001 R/1 and Fc <0.001 <0.001 I/2 and F/3 <0.001 < I/2 and Fc < F/3 and Fc <0.001 < R/1: Risk/ Stage 1, I/2: Injury/Stage 2, F/3: Failure/ Stage 3, Fc: Acute on chronic AKI 15
23 Hospital Mortality Total Hospital Mortality was 13.6%. Hospital mortality showed a similar trend as ICU mortality among the different severity grades of AKI and definitions. Similar to ICU mortality, we found a higher mortality in AKI patients (25.5%-32.9%) compared to patients without AKI (7.9%-9.4%) (table 9). There was a stepwise increase in mortality with increasing severity of AKI in all classifications. Again, we found that patients who suffered from acute on chronic AKI (Fc) had lower hospital mortality than Failure patients when defined by RIFLE. When defined by KDIGO there was no significant difference. Table 9: Hospital mortality of patients without and with AKI, defined according to the different AKI classifications Hospital Mortality No AKI R/1 (%) I/2(%) F/3 (%) Fc (%) All AKI (%) (%) RIFLE 748 (8.7) 195 (22.9) 217 (32.6) 223 (43.7) 137 (22.9) 772 (29.4) RIFLE 764 (8.8) 187 (23.3) 218 (33.7) 214 (44.1) 138 (23.0) 757 (29.9) AKIN 864 (9.4) 277 (28.3) 41 (37.3) 341 (37.2) 659 (32.9) KDIGO 673 (7.9) 226 (19.9) 158 (28.1) 121 (37.5) 380 (33.2) 885 (28.0) KDIGO 640 (8.2) 255 (16.6) 180 (30.4) 70 (35.7) 377 (33.2) 882 (25.5) R/1: Risk/ Stage 1, I/2: Injury/Stage 2, F/3: Failure/ Stage 3, Fc: Acute on chronic AKI In table 10 the p-values for the comparison of the different AKI stages per classification are displayed. Patients with AKI had a significant higher hospital mortality compared to patients without AKI, regardless of severity of AKI. The difference between Risk/Stage 1 and Injury/Stage 2 and Risk/Stage 1 and Failure/Stage 3 was significant for all classifications. When defined by KDIGO classification there was a difference between Risk and Acute on chronic AKI (Fc), while when defined by RIFLE, the difference was not significant. The difference between Injury/stage 2 and Failure/stage 3 was only significant when defined by both RIFLE variants and KDIGO. For both RIFLE variants, the difference between Injury and Acute on chronic (Fc) and Failure and Acute and chronic (Fc) was significant. For the other classifications variable results were noticed. 16
24 Table 10: P-values for Hospital mortality of patients without and with AKI, defined according to the different AKI classifications Hospital Mortality: P-values RIFLE RIFLE AKIN KDIGO KDIGO No AKI and R/1 <0.001 <0.001 <0.001 <0.001 <0.001 No AKI and I/2 <0.001 <0.001 <0.001 <0.001 <0.001 No AKI and F/3 <0.001 <0.001 <0.001 <0.001 <0.001 No AKI and Fc <0.001 <0.001 <0.001 <0.001 R/1 and I/2 <0.001 < <0.001 <0.001 R/1 and F/3 <0.001 <0.001 <0.001 <0.001 <0.001 R/1 and Fc <0.001 <0.001 I/2 and F/3 <0.001 < I/2 and Fc <0.001 < F/3 and Fc <0.001 < R/1: Risk/ Stage 1, I/2: Injury/Stage 2, F/3: Failure/ Stage 3, Fc: Acute on chronic AKI ICU Length of stay Patients with AKI had a longer ICU length of stay compared to patients without AKI (table 11). In contrast to mortality, we could not find a stepwise increase with increasing severity of AKI. Patients with Failure/Stage 3 AKI had even a shorter length of stay than patients with Risk/Stage 1 AKI when defined by both the RIFLE variants and AKIN. For AKIN the difference was even significant. Probably this can be explained by the higher mortality associated with Failure. The AKI stage with the longest length of stay was different for every classification: when defined by RIFLE and KDIGO it was Risk/Stage 1. When defined by RIFLE it was Acute on chronic (Fc). When defined by AKIN it was Stage 2. When defined by KDIGO there was no difference between the different stages. 17
25 Table 11: ICU Length of Stay of patients without and with AKI, defined according to the different AKI classifications ICU Length of stay No AKI R/1 I/2 F/3 Fc RIFLE 2 (1.7; 4.0) 8 (2.1; 10.0) 5 (2.7; 9.0) 4 (2.1; 8.1) 5 (2.7; 10.0) RIFLE 2 (1.7; 4.0) 4 (2.1; 8.3) 4 (2.6; 9.0) 4 (2.1; 8.1) 5 (2.7; 10.0) AKIN 2 (1.7; 4.0) 6 (3.6; 12.0) 9 (5.0; 17.1) 5 (7.8; 12.0) KDIGO 2 (1.7; 4.0) 5 (2.6; 10.2) 4 (2.4; 8.0) 4 (2.5; 7.9) 4 (2.1; 9.9) KDIGO 2 (1.7; 4.0) 4 (2.0; 8.2) 4 (2.6; 8.0) 4 (2.0; 7.0) 4 (2.1; 9.6) R/1: Risk/ Stage 1, I/2: Injury/Stage 2, F/3: Failure/ Stage 3, Fc: Acute on chronic AKI The p-values for the comparison of the different AKI stages are displayed in table 12. There was a significant difference between patients with AKI and patients without AKI for all classifications. Only for AKIN there were significant results for all AKI stages. For the other classification variable results were noticed. When defined by RIFLE there was a significant difference between Risk and Injury, Risk and Acute on chronic (Fc) and Failure and Acute on chronic (Fc). When defined by RIFLE the difference was significant between Risk and Acute on chronic (Fc) and Failure and Acute on chronic (Fc). When defined by KDIGO there was a significant difference between Stage 1 and Stage 2, Stage 1 and Stage 3 and Stage 1 and Acute on chronic (Fc). When defined by KDIGO no significant results could be found between the different AKI stages. 18
26 Table 12: P-values for ICU Length of Stay of patients without and with AKI, defined according to the different AKI classifications ICU Length of stay: P-values RIFLE RIFLE AKIN KDIGO KDIGO No AKI and R/1 <0.001 <0.001 <0.001 <0.001 <0.001 No AKI and I/2 <0.001 <0.001 <0.001 <0.001 <0.001 No AKI and F/3 <0.001 <0.001 <0.001 <0.001 <0.001 No AKI and Fc <0.001 <0.001 <0.001 <0.001 R/1 and I/ < R/1 and F/ < R/1 and Fc I/2 and F/ < I/2 and Fc F/3 and Fc R/1: Risk/ Stage 1, I/2: Injury/Stage 2, F/3: Failure/ Stage 3, Fc: Acute on chronic AKI Hospital Length of Stay Patients with AKI had a longer Hospital Length of Stay compared to patients without AKI (table 13). Hospital Length of Stay showed similar trends as ICU Length of Stay, namely that we could not discover a stepwise increase when increasing AKI severity. When defined by both KDIGO variants, patients with Stage 3 AKI had even a significant longer length of stay compared to Stage 1 AKI patients. Probably this can be explained by the higher mortality associated with Stage 3. The AKI stage with the longest Hospital Length of Stay varied among the different classifications. When defined by both RIFLE variants and KDIGO it was Acute on chronic (Fc). When defined by AKIN it were Stage 1 and Stage 3. When defined by KDIGO it was Stage 1. 19
27 Table 13: Hospital Length of Stay of patients without and with AKI, defined according to the different AKI classifications Hospital Length of stay No AKI (%) R/1 (%) I/2 (%) F/3 (%) Fc (%) RIFLE 10 (6.0; 18.0) 14 (8.0; 26.0) 15 (7.0; 29.0) 14 (7.0; 27.0) 16 (9.0; 32.0) RIFLE 10 (6.0; 18.0) 14 (8.0; 27.0) 15 (7.0; 28.0) 14 (7.0; 26.5) 16 (9.0; 31.8) AKIN 10 (6.0; 18.0) 17 (10.0; 30.0) 20 (12.0; 41.5) 17 (8.0; 43.0) KDIGO 10 (6.0; 18.0) 15 (9;0; 29.4) 15 (7.8; 26.0) 13 (7.0; 26.0) 15 (7.9; 33.5) KDIGO 10 (6.0; 18.0) 14 (7.1; 26.0) 15 (7.0; 27.0) 12 (6.0; 21.8) 15 (7.9; 29.9) R/1: Risk/ Stage 1, I/2: Injury/Stage 2, F/3: Failure/ Stage 3, Fc: Acute on chronic AKI In table 14 the p-values for comparison of the different AKI stages are displayed. There was always a significant difference between AKI patients and patients without AKI except for Acute on chronic when defined by KDIGO. For the differences between the other AKI stages, the results were variable. For both RIFLE variants there were significant results for the difference between Risk/Injury/Failure and Acute on chronic (Fc). For AKIN we found significant results for the difference between Stage 1 and Stage 2, and Stage 2 and Stage 3. For KDIGO, significant results could be found for the difference between Stage 1 and Stage 2, Stage 1 and Stage 3, and Stage 3 and Acute on chronic (Fc). For KDIGO there were significant results for the difference between Stage 1 and Stage 3, Stage 2 and Stage 3, and Stage 3 and Acute on chronic (Fc). 20
28 Table 14: P-values for Hospital Length of Stay of patients without and with AKI, defined according to the different AKI classifications ICU Length of stay: P-values RIFLE RIFLE AKIN KDIGO KDIGO No AKI and R/1 <0.001 <0.001 <0.001 <0.001 <0.001 No AKI and I/2 <0.001 <0.001 <0.001 <0.001 <0.001 No AKI and F/3 <0.001 <0.001 <0.001 <0.001 <0.001 No AKI and Fc <0.001 <0.001 < R/1 and I/ R/1 and F/ R/1 and Fc I/2 and F/ I/2 and Fc F/3 and Fc <0.001 < <0.001 R/1: Risk/ Stage 1, I/2: Injury/Stage 2, F/3: Failure/ Stage 3, Fc: Acute on chronic AKI 21
29 4.4. Transient AKI One of the important aims of the TRAK study was to investigate the influence of AKI duration on outcomes in ICU patients. To explore this influence we compared patients with transient AKI and patients with a longer AKI episode. We defined transient AKI in three different ways: 1. Transient AKI with duration of 3 days of AKI (AKIt3) 2. Transient AKI with duration of 2 days of AKI (AKIt2) 3. Transient AKI with duration of 1 days of AKI (AKIt1) In table 15 to 23, the period prevalence of transient AKI and the influence of AKI duration on outcomes are described for the 5 different AKI classifications used in this analysis: RIFLE, RIFLE, AKIN, KDIGO, KDIGO. We also compared the ICU and hospital mortality of the different transient AKI definitions (figure 1, 2 and table 24 and 25) Transient AKI defined as 3 days of AKI (AKIt3) Period prevalence The period prevalence of AKIt3 varied according to the classification used between 13.9% and 22.7% of ICU patients (table 15), with KDIGO as most sensitive, and AKIN as the least sensitive classification for detecting AKIt3. AKIt3 occurred in the majority of AKI patients during their ICU stay and varied according to the classification used from 65.7% to 78.1% of AKI patients. Table 15. Period prevalence of AKIt3, defined according to the different AKI classifications Period prevalence of AKIt3 AKIt3 RIFLE RIFLE AKIN KDIGO KDIGO N % ICU % AKI N: number of patients, % ICU: % of all ICU patients, % AKI: % of all AKI patients, defined according to the different classification. 22
30 Mortality When defined by RIFLE, RIFLE and KDIGO, AKIt3 patients had a similar ICU mortality compared to patients with a longer AKI episode (> 3d) (table 16). When defined by AKIN and KDIGO, AKIt3 patients had a significant lower ICU mortality. Hospital mortality was significantly lower for AKIt3 patients for all AKI classifications (table 16). Table 16. ICU and hospital mortality of AKIt3 compared with a longer AKI episode (>3 days), defined according to the different AKI classifications. ICU Mortality (%) Hospital Mortality (%) 3 days >3 days p-value 3 days >3 days p-value RIFLE 359 (20.5) 187 (20.6) (27.5) 294 (32.7) RIFLE 360 (21.3) 187 (20.5) (28.2) 283 (32.8) AKIN 358 (22.8) 120 (27.3) (30.9) 174 (39.7) <0.001 KDIGO 397 (18.4) 222 (21.2) (25.0) 351 (33.8) <0.001 KDIGO 401 (15.6) 211 (22.7) < (21.8) 325 (35.2) < Length of Stay Both ICU and hospital length of stay were longer for patients who experienced a longer period of AKI (>3d) compared to AKIt3 patients (table 17). The results were strongly significant for all AKI classifications (p<0.001). 23
31 Table 17. ICU and hospital length of stay of AKIt3 compared with a longer AKI episode (>3 days), defined according to the different AKI classifications. ICU LOS Hospital LOS 3 days >3 days p-value 3 days >3 days p-value RIFLE 3 8 < <0.001 (2.0;5.3) (5.0;18;0) (6.0; 22.0) (14.0; 39.0) RIFLE 5 8 < <0.001 (2.0; 5.5) (5.0; 14.7) (6.0; 22;0) (14.0; 40.0) AKIN 5 10 < <0.001 (2.8; 10.0) (6.4; 19.0) (8.0; 29.0) (15.0; 44.0) KDIGO 3 8 < <0.001 (2.0; 6.0) (5.0; 15.0) (7.0; 23.0) (13.0; 39.0) KDIGO 3 (1.8; 5.8) 7 (4.0; 13.0) < (6.0; 22.0) 19 (11.0; 36.0) < Transient AKI defined as 2 days of AKI (AKIt2) Period prevalence Similar to AKIt3, the period prevalence of AKIt2 varied according to the definition used (table 18). KDIGO was the most sensitive classification (19.7%), RIFLE the least sensitive (8.0%) for detecting AKIt2. AKIt2 occurred in 34.0% to 67.1% of AKI patients. Table 18. Period prevalence of AKIt2, defined according to the different AKI classifications Period prevalence of AKIt2 AKIt2 RIFLE RIFLE AKIN KDIGO KDIGO N % ICU % AKI N: number of patients, % ICU: % of all ICU patients, % AKI: % of all AKI patients, defined according to the different classification. 24
32 Mortality AKIt2 patients had a similar ICU mortality compared to patients who experienced a longer AKI episode (>2d), except when defined by KDIGO. When defined by AKIN and both KDIGO variants, AKIt2 patients had a lower hospital mortality. When defined by both RIFLE variants, the hospital mortality is similar for AKIt2 patients and patients with a longer AKI episode (>2d). Table 19. ICU and hospital mortality of AKIt2 compared with a longer AKI episode (> 2 days), defined according to the different AKI classifications. ICU Mortality (%) Hospital Mortality (%) 2 days >2 days p-value 2 days >2 days p-value RIFLE 191 (21.1) 255 (19.9) (27.7) 393 (31.0) RIFLE 289 (21.7) 249 (20.2) (28.1) 385 (31.5) AKIN 306 (22.7) 172 (26.1) (30.6) 246 (37.3) KDIGO 327 (18.6) 292 (20.2) (24.5) 457 (31.9) <0.001 KDIGO 339 (15.2) 273 (21.5) < (20.7) 423 (33.6) < Length of Stay Similar to AKIt3, length of stay in the ICU, and in the hospital were longer in patients who experienced a longer AKI episode (>2) compared to AKIt2 patients (table 20). The results were strongly significant for all AKI classifications (p<0.001). 25
33 Table 20. ICU and hospital length of stay of AKIt2 compared with a longer AKI episode (>2 days), defined according to the different AKI classifications. ICU LOS Hospital LOS 2 days >2 days p-value 2 days >2 days p-value RIFLE 3 7 < <0.001 (1.9; 5.0) (4.0; 12.7) (6.0; 21.0) (11.0; 36.0) RIFLE 3 7 < <0.001 (1.9; 5.0) (4.0; 12.8) (6.0; 20.1) (11.0; 36;0) AKIN 5 9 < <0.001 (2.7; 10.0) (5.0; 16.9) (7.8; 28.0) (13.0; 41.8) KDIGO 3 7 < <0.001 (1.9; 6.0) (4.0; 12.7) (6.0; 23.0) (11.0; 35.0) KDIGO 3 (1.8; 5.8) 7 (4.0; 13.0) < (6.0; 22.0) 19 (11.0; 36.0) < Transient AKI defined as 1 day of AKI (AKIt1) Period prevalence The period prevalence of AKIt1 varied according to the definition used from 6.4% to 13.1% (table 21). Similar to AKIt3 and AKIt2, KDIGO was the most sensitive classification for detecting AKIt1. RIFLE was the least sensitive classification. AKIt1 occurred in 28.2% to 42.1% of AKI patients. Table 21. Period prevalence of AKIt1, defined according to the different AKI classifications Period prevalence of AKIt1 AKIt1 RIFLE RIFLE AKIN KDIGO KDIGO N % ICU % AKI N: number of patients, % ICU: % of all ICU patients, % AKI: % of all AKI patients, defined according to the different classification. 26
34 Mortality AKIt1 patients had a similar ICU mortality compared to patients who experienced a longer AKI episode (> 1 day), except when defined by KDIGO, where AKIt1 patients had a lower ICU mortality (table 22). Hospital mortality was similar for AKIt1 patients defined by both RIFLE variants and AKIN compared to patients who had a longer AKI episode (>1 day). When defined by both KDIGO variants, AKIt1 patients had lower hospital mortality. Table 22. ICU and hospital mortality of AKIt1 compared with a longer AKI episode (> 1 day), defined according to the different AKI classifications. ICU Mortality (%) Hospital Mortality (%) 1 day >1 day p-value 1 day >1 day p-value RIFLE 169 (22.3) 377 (19.8) (28.2) 560 (29.7) RIFLE 167 (23.1) 371 (20.2) (28.7) 551 (30.2) AKIN 198 (24.6) 280 (23.3) (31.2) 407 (33.9) KDIGO 197 (19.8) 422 (19.1) (25.5) 633 (28.9) KDIGO 223 (15.1) 389 (19.2) (20.0) 590 (29.3) < Length of Stay Similar to AKIt3 and AKIt2, patients with a longer AKI episode (>1 day) had a longer ICU and hospital length of stay compared to AKIt1 patients (table 23). The results were strongly significant for all classifications (p<0.001). 27
35 Table 23. ICU and hospital length of stay of AKIt1 compared with a longer AKI episode (>1 day), defined according to the different AKI classifications. ICU LOS Hospital LOS 1 day >1 day p-value 1 day >1 day p-value RIFLE 3 5 < <0.001 (1.6; 5.0) (3.0; 10.0) (5.0; 20.0) (9.0; 31.0) RIFLE 3 5 < <0.001 (1.5; 5.5) (3.0; 5.0) (5.0; 20.0) (9.0; 31.0) AKIN 4 7 < <0.001 (2.1; 9.2) (4.0; 13.7) (7.1; 27.0) (11.0; 35.0) KDIGO 3 5 < <0.001 (1.6; 6.0) (3.0; 10.0) (6.0; 22.0) (9.0; 31.0) KDIGO 3 (1.6; 5.9) 5 (3.0; 10.6) < (6.0; 22.0) 16 (9.0; 31.0) < Comparison of mortality between AKIt1, AKIt2 and AKIt ICU Mortality Patients with transient AKI had a higher ICU mortality compared to patients without AKI, even when AKI only lasted for 1 day (AKIt1) (figure 1). The duration of the transient AKI had no influence on the ICU mortality. AKIt1, AKIt2 and AKIt3 had a similar ICU Mortality in all AKI classifications, except when defined according to AKIN. 28
36 Figure 1. Comparison of ICU Mortality of patients with and without transient AKI (AKIt1, AKIt2 and AKIt3), defined according to the different AKI classifications. 30% 25% 20% 15% 10% no AKI AKIt1 AKIt2 AKIt3 all AKI 5% 0% RIFLE RIFLE AKIN KDIGO KDIGO The p-values for the comparison of ICU Mortality between the different definitions of transient AKI are displayed in table 24. The ICU Mortality was similar for AKIt1, AKIt2, AKIt3 for almost all classifications. Only when defined by AKIN there was a significant difference, more specifically there was a significant difference between AKIt1 and AKIt2 (p=0.042). Table 24. P-values for the comparison of ICU mortality between AKIt1, AKIt2 and AKIt3. P-values of ICU Mortality RIFLE RIFLE AKIN KDIGO KDIGO Hospital Mortality Transient AKI patients had a higher hospital mortality compared to patients without AKI, even when AKI only lasted for 1 day (AKIt1) (figure 1). The duration of the transient AKI had no influence on the hospital mortality. AKIt1, AKIt2 and AKIt3 had a similar hospital mortality. 29
37 Figure 2. Comparison of Hospital Mortality for patients with and without transient AKI (AKIt1, AKIt2 and AKIt3), defined according to the different AKI classifications. 35% 30% 25% 20% 15% no AKI AKIt1 AKIt2 AKIt3 all AKI 10% 5% 0% RIFLE RIFLE AKIN KDIGO KDIGO The p-values for the comparison of Hospital Mortality between the different definitions of transient AKI are displayed in table 25. The Hospital Mortality was similar for AKIt1, AKIt2, AKIt3 for all classifications. Table 25. P-values for the comparison of Hospital mortality between AKIt1, AKIt2 and AKIt3. P-values of Hospital Mortality RIFLE RIFLE AKIN KDIGO KDIGO
38 5. Discussion Acute Kidney Injury (AKI) was a common finding in this large cohort of ICU patients, and the period prevalence varied largely depending the AKI classification used. During ICU stay, 17.8 to 31.0% of the patients had an episode of AKI. This was associated with worse clinical outcomes such as increased length of stay and mortality. Transient AKI was prevalent amongst ICU and AKI patients, and was also associated with a higher mortality. ICU and hospital mortality of Transient AKI variants (1 to 3 days AKI) were comparable to that of all AKI. Finally, a longer duration of an AKI episode was associated with a higher mortality and a longer length of stay compared to transient AKI Prevalence of AKI In our TRAK study we found an overall AKI prevalence of % depending on which classification was used. The AKI prevalence per classification was: 23.5% for RIFLE, 22.7% for RIFLE, 17.8% for AKIN, 28.3% for KDIGO and 31.0% for KDIGO. The prevalence and incidence of AKI varied among ICU studies, depending on the study population (1, 10). In the NEiHROS-AKI study, the first prospective multicenter study of AKI, 10.8% of the 2164 ICU patients suffered from AKI (11). Thakar et al. (12) found in the Veteran Affairs Hospital ICUs across the US an overall incidence of AKI of 22% when AKI was defiend by creatinine criteria only. In the study by Ostermann and Chang (13) AKI occurred in 35.8% of the ICU patients. Bashaw et al. (14) analyzed AKI by RIFLE using only creatinine values. The incidence of AKI in their ICU population was 36.1%. Recently Mandelbnaum found an incidence of 57% when AKI was defined by AKIN criteria (15). Finally, in a study by Hoste et al. (16) in 5,383 ICU patients of University of Pittsburg Medical Center, AKI occurred in 67% of the patients. Differences between these cohorts can be explained by differences in the cohort observed (different patient characteristics or observation period) and differences in the definition for AKI used (creatinine criteria only, or combination of creatinine and urine output criteria, variant of urine output criteria, ). A remarkable result was that the AKI prevalence of the Pittsburg cohort in the TRAK study was only 31.0%, which was very low compared to the 67% found by Hoste et al. (16). Several reasons could be found to explain this difference. Firstly this was a different patient cohort. The Pittsburg cohort from the Hoste study was from 2000 to 2001, the Pittsburg cohort from the TRAK study was from 2005 to Secondly the urine output criteria were not included in the TRAK study in contrast to the Hoste study. Thirdly there was a different method of estimating baseline creatinine. In the study by Hoste et al. (16) the lowest creatinine value among the hospital admission creatinine, the ICU admission 31
39 creatinine or the creatinine value was used as the baseline value. This could result in an overestimating of the prevalence of AKI. In the TRAK study the baseline creatinine value was used when available. When there was no baseline available, the re-expressed 4-variable or CKD- EPI equitation were used to calculate a baseline value. This was also suggested by Zavada et al. (9). They stated that the use of the 4-variable equitation to calculate baseline creatinine may overor underestimate some mild AKI cases, but does not misclassify patients in Injury and Failure. Whenever possible, recorded creatinine values should be used as a reference of baseline. In a big cross-sectional analysis, the creatinine equitation proved to be better than the equation, especially at higher GFR, and could replace it for routine clinical use (7). In the TRAK study small differences were seen between the use of the re-expressed 4 variable and the equitation for calculating a baseline creatinine value. Further analyses will be needed to explore these differences in more detail Outcomes Patients with AKI had a higher ICU mortality (17.6%-24.0%) compared to the patients without AKI (4.5%-5.5%). Similar to ICU mortality we found higher hospital mortality in AKI patients (25.5%- 32.9%) compared to patients without AKI (7.9%-9.4%). AKI patients also had a longer ICU and hospital length of stay. Patients in the Risk stage of RIFLE or Stage 1 of AKIN and KDIGO had a significant higher ICU and hospital mortality and significant longer ICU and hospital length of stay compared to patients without AKI. This again emphasizes the importance of early AKI detection, AKI treatment and AKI prevention at ICU. Transient AKI patients had also a higher ICU and hospital mortality compared to patients without AKI, even when the AKI episode only lasted for 1 day. Also this result emphasizes the importance of early AKI detection, AKI treatment and AKI prevention at ICU. There was no difference in mortality between the different definitions of transient AKI and also not between Transient AKI and all AKI. The reason for this remained unclear. Further research will be needed to clarify this result. The longer the duration of AKI, the more impact we found on outcomes. Patients with AKIt3 had similar ICU mortality, but lower hospital mortality compared to patients with a longer AKI episode (>3 days). AKIt2 patients had similar ICU mortality compared to patients with a longer AKI episode (> 2 days). But, according to the classification used, AKIt2 patients had similar or lower hospital mortality compared to patients who experienced a longer AKI episode (>2 days). Finally, patients with 32
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