Optimal follow-up time after continuous renal replacement therapy in actual renal failure patients stratified with the RIFLE criteria

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1 Nephrol Dial Transplant (2005) 20: doi: /ndt/gfh581 Advance Access publication 14 December 2004 Original Article Optimal follow-up time after continuous renal replacement therapy in actual renal failure patients stratified with the RIFLE criteria Max Bell 1, Eva Liljestam 1, Fredrik Granath 2, Jessica Fryckstedt 3, Anders Ekbom 2 and Claes-Roland Martling 1 1 Department of Anaesthesiology and Intensive Care, 2 Department of Medicine, Clinical Epidemiology Unit and 3 Department of Emergency Medicine, Karolinska University Hospital, Stockholm, Sweden Abstract Background. We wished to determine the optimal duration of follow-up for patients with acute renal failure (ARF) treated with continuous renal replacement therapy (CRRT) and tested the hypothesis that a 6 month follow-up would be the minimum to catch most of the mortalities. In addition, we evaluated the association between mortality and the RIFLE classification in the same patients. Methods. We analysed the data of 8152 consecutive patients who had been admitted to the intensive care unit (ICU) of a Swedish university hospital between 1995 and Of that population, 207 patients were treated with CRRT, excluding 16 treated for non-renal indications. Results. ICU mortality in this cohort was 34.8% and 30 day and in-hospital mortalities were 45.9% and 50.2%, respectively. The cohort s all-cause mortality 6 months after inclusion was 59.9%, but 54.6% died as early as after 60 days. Patients in the more severe RIFLE category, F (failure), had a 30 day mortality of 57.9% compared with 23.5% for those in the RIFLE-R (risk) category and 22.0% for RIFLE-I (injury) patients. Conclusions. In our opinion, a 60 day follow-up is sufficient to catch the majority of deaths in ARF patients treated with CRRT. The patients in the RIFLE-F category had a significantly higher mortality than RIFLE-R and -I patients. Keywords: acute renal failure; diagnostic criteria; long-term patient survival; outcome; renal replacement therapy Correspondence and offprint requests to: Max Bell, MD, Department of Anaesthesiology and Intensive Care, Karolinska University Hospital, S Stockholm, Sweden. max.bell@ karolinska.se Introduction It is well known that compared with the general intensive care unit (ICU) population, patients with acute renal failure (ARF) have a higher hospital mortality [1], ranging from 43% [2] to 88% [3]. Even the incidence of ARF varies: numbers from 1% to 25% have been reported [2,4,5]. One of the reasons for this variation might be the absence of an agreedupon biochemical definition of ARF and the lack of a uniform classification system. The already high mortality numbers become even higher for patients requiring renal support [6]. Another concern in studying the epidemiology of ARF is the use of mortality: a large number of studies use ICU mortality [2,7] or in-hospital mortality as endpoints [5,8]. There has been an ongoing debate about when a stable survival rate is reached in ARF patients. Reported data show that this may take days [9,10]. The consensus from the second Acute Dialysis Quality Initiative (ADQI) conference was presented by Palevsky and co-workers [10], who suggest using from 60 to 90 days of follow-up for the evaluation of all-cause mortality. In the present study, we investigated a cohort of 223 ICU patients who were treated with continuous renal replacement therapy (CRRT) 16 had been treated for non-renal indications and were dropped from the study. Our primary aim was to determine the optimal duration of follow-up. We hypothesized that a 6 month follow-up might be needed. This was an arbitrary endpoint, but we wanted the time frame to be achievable and to include most of the occurring deaths. We assessed ICU, 30 day and hospital mortalities, as well as mortalities 2, 3 and 6 months after the start of treatment. We also looked at the causes of death. Our second aim was to evaluate the recently presented ARF classification system, the RIFLE criteria, as a tool for predicting the mortality of patients with ARF. These classification criteria have been Nephrol Dial Transplant Vol. 20 No. 2 ß ERA EDTA 2004; all rights reserved

2 Optimal follow-up time after CRRT 355 The RIFLE criteria presented by the ADQI group, but as yet they have not been tested in a clinical setting. The RIFLE criteria were developed to allow a more accurate and standardized stratification of groups of patients with ARF. However, in the document written by the ADQI workgroup for definitions of renal failure, it is pointed out that the criteria can be used for patients treated with or without dialysis ( Subjects and methods Setting The study was carried out in the general, multidisciplinary ICU at the Karolinska Hospital, a major university hospital in Stockholm. The ICU is the trauma referral centre of the greater Stockholm area (1.8 million inhabitants). The departments admitting there are surgery, urology, gynaecology, obstetrics, otorhinolaryngology and internal medicine. Thoracic and neurosurgical cases are admitted to the unit only if these conditions are part of a major trauma. The general ICU is an 8 13 bed unit treating around 1100 patients per year. About 50% of the patients stay >24 h and 40% are treated with mechanical ventilation. Treatment modality Three CRRT modalities [continuous veno-venous haemofiltration (CVVH), continuous veno-venous haemodialysis and continuous veno-venous haemodiafiltration (CVVHDF)] were in use in the ICU during the study period. Lactatebuffered solutions were preferred initially, but bicarbonatebuffered solutions have been used exclusively since Over the years, the trend has been away from CVVHDF towards CVVH, with replacement fluid amounts of ml/kg/h. The filters in use are AN 69 M100 (Gambro, Sweden) with pre-dilution. Recently, however, CVVHDF using citrate as anticoagulant has become the most common treatment modality. The treatment is initiated by an intensive care physician and then carried out by ICU nurses. Data collection Between January 1995 and December 2001, a total of 8152 patients were admitted to the ICU. All admissions were documented and all but 16 CRRT patients were included in the study. The following information was recorded for each patient at entry and during treatment in a standardized manner by an intensive care nurse: demographic data, common pre-existing diseases, indication for ICU admission, main diagnosis, APACHE II score, major ICU interventions and laboratory results. The indication for dialysis was documented and specific data regarding the renal replacement therapy (RRT) were recorded daily. In reviewing the patients files we looked at previous health status, organ function at the start of dialysis [11] and the relevant physiological and pharmacological data needed for the RIFLE classification. Moreover, we gathered information on the causes of death for the 29 patients who died within days of admission. The study protocol was approved by the local ethics committee. The RIFLE criteria were established during the second ADQI conference held in Vicenza in May 2002 and, subsequently, they were posted on the Internet for external review ( They were published by the working group in a preliminary draft [12] and then were presented at the 8th International Conference on Continuous Renal Replacement Therapies in San Diego in The most recent document concerning RIFLE can be found on the Internet on the critical care forum [13]. The RIFLE classification system (Table 1) offers the tools to categorize and stratify a population of patients based on their renal function. According to glomerular filtration rate (GFR), serum creatinine (where change from the patient s individual baseline is measured) and urine output (UO), patients are classified into three severity categories: risk, injury and failure. Additionally, there are two outcome categories: loss and end-stage renal disease. We assigned the patients in our cohort, i.e. those who had dialysis initiated, to RIFLE categories according to either their GFR/creatinine or their UO (whichever was more severe). The baseline creatinine of each patient was retrieved from the hospital laboratory database. If the baseline renal function was unknown, we used a reference creatinine as estimated from the MDRD (modification of diet in renal disease) equation [13]. The patient s RIFLE level (R, I or F) was then determined by calculating the relative change in functional criteria. The patients who did not fulfill the criteria were excluded from the study. These patients were treated with CRRT for non-renal indications. A patient with pre-existing renal disease might pose a problem, since his or her baseline GFR and serum creatinine usually differ from the normal patient s. Theoretically, this relative difference in the patient s creatinine could be quite small and, thus, result in placing the patient in a misleading RIFLE category. Kellum and co-workers propose that a separate criterion should be used for an ARF superimposed on chronic renal disease ( an acute rise in creatinine (of 0.5 mg/dl or 44 mmol/l) to >4 mg/dl or >350 mmol/l identifies most patients with ARF when their baseline serum creatinine is abnormal. We used this criterion for the cases with acute-on-chronic ARF. A number of the patients had end-stage renal disease, as defined here by the need for dialysis for >3 months (RIFLE-E). A very small number of patients was enrolled in the study with persistent ARF; they had had RRT for between Table 1. RIFLE criteria for acute renal dysfunction GFR criteria UO criteria Risk Increased creatinine 1.5 UO <0.5 ml/kg/h 6h or GFR decrease >25% Injury Increased creatinine 2 UO <0.5 ml/kg/h 12 h or GFR decrease >50% Failure Increased creatinine 3 or GFR decrease >75% or SCreat 4 mg/dl UO <0.3 ml/kg/h 24 h or anuria 12 h Loss Persistent ARF ¼ complete loss of renal function >4 weeks ESRD End-stage renal disease (>3 months) SCreat, serum creatinine.

3 356 M. Bell et al. 4 weeks and 3 months previously (RIFLE-L). Even though L and E are outcome categories in the RIFLE system, we chose to use those designations for the patients with preexisting renal disease requiring chronic dialysis. Otherwise, this subgroup would have been assigned to the F category, which we felt would have been misleading. Outcome We documented the cases discharged from the ICU still needing RRT. By using the national registration numbers assigned to Swedish residents since 1947 [14], we could link our CRRT database with SRAU, the Swedish Register of Active Treatment of Uremia [15]. The registry was established in 1991 and includes each individual who, due to chronic renal disease had dialysis, kidney transplantation or both. Every change in treatment (haemodialysis, peritoneal dialysis, transplantation and discontinuation of treatment) is reported to the registry, to which all of the clinical departments in Sweden that offer some form of active uraemic care contribute data. By using this registry we could identify patients who left the ICU but needed chronic renal support. Those who left the ICU needing RRT for a finite period of time were documented in our own database, but not entered in SRAU. Most of the patients found after linkage with SRAU were dialysis-dependent prior to their ICU admissions. These patients, documented in our database, were found in SRAU both before and after their admission to the ICU. A smaller group of patients was found who had been entered in the registry only after their critical illness. The mortality rate was calculated at multiple points of time. ICU mortality was recorded and data on hospital mortality were extracted from the Karolinska Hospital s in-house database. This database is linked and cross-matched (via the national registration numbers) to the population registry run by Statistics, Sweden. Births and deaths are entered into the database on a daily basis. Therefore, we could compute all-cause mortality at 30, 60, 90, 120, 150 and 180 days (or for any given point of time further on). Statistical methods Crude survivals were estimated using the Kaplan Meier estimator and are presented with 95% confidence intervals (CI). Cox regressions were performed for the univariate and multivariable analyses of mortality within 30 days of the start of dialysis, i.e. all subjects being censored at day 31. The variables included in these models are displayed in Table 2. The final model is shown in Table 3. The estimated impact of the RIFLE score did not change significantly after dropping selected variables. It should be noted that the multivariate analysis only looked at the patients scoring R, I or F; patients with pre-existing renal disease were excluded from the model. The multivariate analysis was performed to assess potential confounding by comparing the estimates derived from the univariate analysis and from the full multivariate analysis. The time-dependence of the prognostic value of the RIFLE score was assessed by considering it a pseudo-time-dependent covariate, allowing for differences in the influence of RIFLE during follow-up. These analyses showed no significant difference in influence in the period between days 0 and 15 compared with the period between days 16 and 30 the estimates indicated a slightly higher impact of high RIFLE scores for the first period (data not shown). Similarly, we explored predictors for mortality beyond 30 days and found no significant predictors. We explored, in particular, the influence of the RIFLE score between days 31 and 60 and found no association between mortality and RIFLE in this interval. Results are presented as hazard ratios (HR) with 95% CI. It should be kept in mind, however, that these comparisons over time are hampered by a relatively low power and the lack of significant effects should not be interpreted as a demonstration of lack of effect. Wald tests were used to assess the overall statistical significance of each variable in the multivariate analysis. All analyses were performed using the Statistical Analysis System (SAS Õ ) package. Results During the 7 year study period, 223 adult, critically ill patients developed the need for acute RRT. Of them, 16 patients were treated with CRRT for non-renal indications and, therefore, were not included in the cohort for analysis. Some 120 (58.0%) and 78 (37.7%) cases were admitted from surgical and medical departments, respectively, and nine (4.3%) patients came from other units; 153 patients (73.9%) had an APACHE II score of 18 or higher and 54 (26.1%) had a score of 28 or higher. Also illustrating the high illness severity in this cohort, 176 (85.0%) patients were treated with mechanical ventilation and inotropic support was used in 162 (78.3%) patients. Lengths of stay in the ICU averaged 14 days. CRRT was initiated within 24 h of ICU admission in 109 (52.7%) cases. Table 2 presents the clinical features of the cohort along with mortalities at 30 days as compared with mortalities between 31 days and 6 months. ICU mortality was 34.8% and hospital mortality was 50.2% compared with a mortality of 45.9% at 30 days. At 6 months, all-cause mortality reached 59.9%, but as early as after 2 months the mortality was 54.6%. A Kaplan Meier plot illustrates this (Figure 1). Overall, 16 (7.7%) patients were dialysis-dependent prior to their admission to the ICU. These patients were categorized in the RIFLE-E group. Only three patients fitted the RIFLE-L criteria. The 19 cases (9.2%) of RIFLE-L and RIFLE-E that were treated with CRRT in the ICU had a mortality of 52.6% at 30 days (Table 2). Patients categorized RIFLE-F had a higher mortality rate; these 121 (54.3%) patients had a HR of 3.4 (95% CI: ) (Table 3) and a mortality at 30 days of 57.9%. The RIFLE-I group comprised 50 patients; their mortality rate was 22.0% at 30 days. The 17 patients in RIFLE-R had a 23.5% mortality (Table 2). The RIFLE-F group also had a higher mortality rate for the period 31 days to 6 months as compared with RIFLE-R and -I (Table 2). When the Kaplan Meier plot is stratified according to RIFLE classifications, the differences between the survival curves of the

4 Optimal follow-up time after CRRT 357 Table 2. Patient data Mortality between 0 and 30 days Mortality between 31 and 180 days Alive day 0 Deaths Percentage dead (95% CI) Alive day 31 Deaths Percentage dead (95% CI) All patients (39 53) (18 34) Sex Female (42 67) (0 22) Male (34 50) (21 41) Age (years) < (22 78) (0 71) (28 72) (0 29) (34 70) (11 61) (23 54) (5 37) (27 58) (5 39) (39 65) (15 49) > (0 49) (0 62) APACHE II score (23 48) (18 49) (36 56) (15 39) > (42 69) (0 26) Number of failing organs (20 50) (7 39) (37 55) (18 39) > (41 71) (3 39) Diabetes No (36 51) (17 34) Yes (41 75) (6 56) RIFLE R (3 44) (6 56) I (11 33) (1 20) F (49 67) (24 51) L þ E (30 75) (0 49) Creatinine (mmol/l) < (20 61) (6 56) (37 63) (18 53) > (36 54) (12 31) UO (ml/h) 6 h prior to CRRT Missing (44 94) (0 0) < (43 67) (3 30) (29 54) (17 48) > (26 48) (16 43) UO (ml) 24 h prior to CRRT Missing (17 103) (0 0) < (43 70) (5 40) (29 52) (5 27) > (32 54) (24 52) Table 3. Multivariable analysis for 30 day mortality Variable Crude Adjusted a HR 95% CI P-value b HR 95% CI P-value b RIFLE R 1.0 Ref. < Ref. < I 1.0 ( ) 0.9 ( ) F 3.4 ( ) 3.4 ( ) Sex Female 1.0 Ref Ref Male 0.7 ( ) 0.7 ( ) Age Per year 0.99 ( ) ( ) 0.15 APACHE II Ref Ref ( ) 1.3 ( ) > ( ) 1.9 ( ) Diabetes No 1.0 Ref Ref Yes 1.2 ( ) 1.2 ( ) a Mutually adjusted for all variables shown in the table. b Wald s test of heterogeneity.

5 358 M. Bell et al. 1 Five years survival 0.8 Proportion survived Time since start of dialysis (months) Fig. 1. Five-year survival after start of CRRT. Fig. 2. One-year survival after stratification with the RIFLE criteria. three groups are obvious (Figure 2). It is interesting to point out how the mortality of the RIFLE-L and -E patients, i.e. patients with pre-existing renal disease, actually surpasses that of the RIFLE-F group at 6 months of follow-up (Figure 2). The causes of death are as follows. Of the 18 patients who died days after inclusion in the cohort (i.e. initiation of dialysis in the ICU), 11 were categorized to have died from multiorgan failure, four cardiovascular deaths were recorded, two patients died from uraemia and one from cancer. For the late mortalities, i.e. the 11 patients dying in the days interval, five cardiovascular deaths were found, three patients died from cancer, two from multiorgan failure and one from uraemia. Considering the survivors after 30 days, there were 112 patients. Seven of these, designated RIFLE-E, had had pre-admission RRT (and were included in the SRAU registry). When they were excluded, 105 patients were left. Out of this group, only five (4.8%) were permanently dialysis-dependent after their stays in the ICU (and were included in the SRAU registry). Four out of these five started chronic RRT as soon as they left the ICU and a fifth patient was monitored by nephrologists, but was not started on RRT until 3 years after the episode of critical illness. Discussion We have focused on two problems in the field of ARF epidemiology. First, optimal follow-up time remains to be determined. Second, the definition of ARF has been an issue for all researchers. The Novis et al. [4] review of 28 studies examining post-operative renal failure revealed 28 different definitions of ARF. In most cases, arbitrary biochemical cut-off points have been used, but some researchers have favoured the pragmatic approach, defining ARF as the need for RRT [16]. The patients needing RRT in the critical-care setting do have a particularly poor prognosis [17 19]. They were the focus of our investigation. Since clinicians initiate artificial renal support at different time-points, we felt that the use of the RIFLE criteria in the context of our study was warranted. Our general results are in line with data from other studies. First, the mortality rate of severe ARF in the ICU is high, albeit lower in our cohort than in most comparable studies. Second, some patients are dialysisdependent prior to having a critical illness. Third, this group as a whole has a high level of illness severity, as illustrated by high APACHE II scores and the fact that 80% of the patients had associated respiratory and circulatory failure needing support. The protocol for managing ARF in our ICU is similar to that used in most Scandinavian centres and in Australia. Criticalcare physicians and critical-care nurses initiate and apply RRT and CRRT is almost always the method of choice. Due to a number of practical reasons, in many previous studies the mortality measured has been ICU mortality or in-hospital mortality. This may not be sufficient, for this investigation shows a difference of 19.8% between ICU and 2 month mortalities. Also, taking into consideration the whereabouts of the patient at the time of death may reveal that local traditions influence mortality: the time for when patients are discharged from both the ICU and hospital varies between centres and countries. Comparing the ICU mortality to the mortality at 6 months, we see a difference of 25.1%. It could be argued that all-cause mortality at 6 months is too blunt an instrument; that it does not accurately measure the effects of ARF as such. This makes some sense. The higher mortality in our cohort at 6 months as compared with 30 days or 2 months could be a result of the general poor health of the population. Looking at the causes of death, we restricted our analysis to patients dying between

6 Optimal follow-up time after CRRT and 2 months and between 2 and 6 months. The numbers are small, but more cases of multiorgan failure were seen in the day time-frame, implying that these mortalities were associated with the critical illness. Based on this patient cohort, in our opinion, a 2 month follow-up period is sufficient. First, the number of additional deaths between 61 and 180 days is small; second, the causes of death in this more distant time-frame do not seem to be associated strongly with the critical illness. Applying the RIFLE criteria revealed new insights. Firstly, the RIFLE classification is feasible and fairly straightforward. To our knowledge, this is the first group of ARF patients to whom it has been applied and it does add transparency and comparability to this type of cohort. Secondly, we found that the patients categorized as RIFLE-F had a far higher mortality than RIFLE-I and -R patients. Figure 2 illustrates the increased mortality for the F category both in the first 30 days after inclusion in the cohort and during the period from 31 days to 6 months. Interestingly, in our study elevated creatinine alone was not associated with increased mortality (Table 2), but, in contrast, oliguria seemed to be (Table 2). One conclusion that might be drawn is that the use of patients baseline GFR/creatinine levels and the measured relative changes combined with UO sharpens the predictive ability of the system. We did not identify any confounding factors that biased the predictive ability of the RIFLE criteria neither higher numbers of failing organs nor higher APACHE II scores (Table 3). An important consideration that might, in part, explain the higher mortality of the F category is the fact that the category consists of different patient groups. The patients in this category could have a 3-fold increase in creatinine or anuria for 12 h or they could have a 5-fold creatinine increase or anuria for 24 h, but they still would be designated RIFLE-F. The RIFLE classification is designed to have a high sensitivity in the RIFLE-R group and a high specificity in the RIFLE-F group. Patients in the latter group do, indeed, suffer from renal failure, but the group as a whole is not as well defined. The fact that the mortality was much higher in RIFLE category F, compared with R and I, may support previous research showing that an early start of RRT can be beneficial [20]. The fact that RIFLE-I patients actually had a lower mortality than RIFLE-R patients might reflect only the small numbers of patients in the different categories. It needs to be emphasized that this investigation was carried out in a clinical setting. This leads to heterogeneity in our cohort, making the RIFLE criteria useful. The data on the prognostic abilities of RIFLE must, however, be seen in light of the limits of this single-centre study. The higher mortality in the F category does not mean that RIFLE can be used as a predictor of treatment with impunity. Moreover, we cannot extrapolate these data to all cases of ARF this study focused on CRRT. It would have been interesting to study all patients with ARF, but we did not have that opportunity. We are currently using the RIFLE criteria in a new project where all patients with ARF are included, not just those requiring CRRT. Also, testing the predictive abilities of the RIFLE criteria against other existing ARFspecific models calls for a separate study. Lastly, only five patients out of 118 (4.2%) were left with a dialysis-dependent renal insufficiency after their critical illness. It has to be kept in mind that one of these patients started RRT almost 3 years after his episode of ARF. After the study ended in December of 2001, some patients have only been followed for 18 months and it is possible that more patients may eventually require RRT. In conclusion, the mortality of patients treated with CRRT is very high. While ICU and in-hospital mortalities reflect local traditions of patient discharge, a 2 month follow-up period may be optimal for determining mortality rates in other more or less similar cohorts. The recently developed RIFLE classification system was found to be a valuable tool. It adds transparency to this study of ARF and it may be even more useful in studies where conservative treatment and RRT are compared. Acknowledgements. We wish to thank Staffan Scho n, at SRAU, Sweden, for help with SRAU linkage. Gambro, Stockholm (Sweden) provided financial support. Conflict of interest statement. None declared. References 1. Metnitz PG, Krenn CG, Steltzer H et al. Effect of acute renal failure requiring renal replacement therapy on outcome in critically ill patients. Crit Care Med 2002; 30: de Mendonca A, Vincent JL, Suter PM et al. Acute renal failure in the ICU: risk factors and outcome evaluated by the SOFA score. Intensive Care Med 2000; 26: Spiegel DM, Ullian ME, Zerbe GO, Berl T. Determinants of survival and recovery in acute renal failure patients dialyzed in intensive-care units. Am J Nephrol 1991; 11: Novis BK, Roizen MF, Aronson S, Thisted RA. Association of preoperative risk factors with postoperative acute renal failure. Anesth Analg 1994; 78: Brivet FG, Kleinknecht DJ, Loirat P, Landais PJ. Acute renal failure in intensive care units causes, outcome, and prognostic factors of hospital mortality; a prospective, multicenter study. French Study Group on Acute Renal Failure. Crit Care Med 1996; 24: Jochimsen F, Schafer JH, Maurer A, Distler A. Impairment of renal function in medical intensive care: predictability of acute renal failure. Crit Care Med 1990; 18: Schwilk B, Wiedeck H, Stein B, Reinelt H, Treiber H, Bothner U. Epidemiology of acute renal failure and outcome of haemodiafiltration in intensive care. Intensive Care Med 1997; 23: Liano F, Junco E, Pascual J, Madero R, Verde E. The spectrum of acute renal failure in the intensive care unit compared with that seen in other settings. The Madrid Acute Renal Failure Study Group. Kidney Int Suppl 1998; 66: S16 S24 9. Ronco C, Bellomo R, Homel P et al. Effects of different doses in continuous veno-venous haemofiltration on outcomes of acute

7 360 M. Bell et al. renal failure: a prospective randomised trial. Lancet 2000; 356: Palevsky PM, Metnitz PG, Piccinni P, Vinsonneau C. Selection of endpoints for clinical trials of acute renal failure in critically ill patients. Curr Opin Crit Care 2002; 8: Knaus WA, Wagner DP. Multiple systems organ failure: epidemiology and prognosis. Crit Care Clin 1989; 5: Kellum JA, Levin N, Bouman C, Lameire N. Developing a consensus classification system for acute renal failure. Curr Opin Crit Care 2002; 8: Bellomo R, Kellum C, Mehta R, Palevsky P, the ADQI Workgroup. Acute renal failure definition, outcome measures, animal models, fluid therapy and information technology needs: the Second International Consensus Conference of the Acute Dialysis Quality Initiative (ADQI) Group. Critical Care Forum 2004; 8: 14. Lunde AS, Lundeborg S, Lettenstrom GS, Thygesen L, Huebner J. The person-number systems of Sweden, Norway, Denmark, and Israel. Vital Health Stat ; 2: SRAU. Renal Replacement Therapy in Sweden Svenskt Register fo r Aktiv Uremivård: Silvester W, Bellomo R, Cole L. Epidemiology, management, and outcome of severe acute renal failure of critical illness in Australia. Crit Care Med 2001; 29: Chertow GM, Christiansen CL, Cleary PD, Munro C, Lazarus JM. Prognostic stratification in critically ill patients with acute renal failure requiring dialysis. Arch Intern Med 1995; 155: Douma CE, Redekop WK, van der Meulen JH et al. Predicting mortality in intensive care patients with acute renal failure treated with dialysis. J Am Soc Nephrol 1997; 8: Cosentino F, Chaff C, Piedmonte M. Risk factors influencing survival in ICU acute renal failure. Nephrol Dial Transplant 1994; 9 [Suppl 4]: Gettings LG, Reynolds HN, Scalea T. Outcome in posttraumatic acute renal failure when continuous renal replacement therapy is applied early vs. late. Intensive Care Med 1999; 25: Received for publication: Accepted in revised form:

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