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Ann Thorac Surg 2011;91:137-142. doi:10.1016/j.athoracsur.2010.08.063
© 2011 The Society of Thoracic Surgeons
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Original Articles: Adult Cardiac

Prognosis of Patients on Extracorporeal Membrane Oxygenation: The Impact of Acute Kidney Injury on Mortality

Yung-Chang Chen, MDa,c,*, Feng-Chun Tsai, MDb,c, Chih-Hsiang Chang, MDa,c, Chan-Yu Lin, MDa,c, Chang-Chyi Jenq, MDa,c, Kuo-Chang Juan, MDa, Hsiang-Hao Hsu, MD, PhDa,c, Ming-Yang Chang, MD, PhDa,c, Ya-Chung Tian, MD, PhDa,c, Cheng-Chieh Hung, MD, PhDa,c, Ji-Tseng Fang, MDa,c, Chih-Wei Yang, MDa,c

a Kidney Research Center, Department of Nephrology, Chang Gung Memorial Hospital, Taipei, Taiwan
b Division of Cardiovascular Surgery, Chang Gung Memorial Hospital, Taipei, Taiwan
c Chang Gung University College of Medicine, Taoyuan, Taiwan

Accepted for publication August 31, 2010.

* Address correspondence to Dr Chen, Chang Gung University College of Medicine, Division of Critical Care Nephrology, Department of Nephrology, 199 Tung Hwa N Rd, Taipei 105, Taiwan (Email: cyc2356{at}adm.cgmh.org.tw).


   Abstract
Top
 Abstract
Introduction
 Material and Methods
 Results
 Comment
 References
 
Background: Extracorporeal membrane oxygenation (ECMO) has been utilized for patients in critical condition, such as those with life-threatening respiratory failure or postcardiotomy cardiogenic shock. This study analyzed the outcomes of patients treated with ECMO and identified the relationship between prognosis and the Acute Kidney Injury Network (AKIN) scores obtained at pre-ECMO support (AKIN0-hour); and at post-ECMO support 24 hours (AKIN24-hour) and 48 hours (AKIN48-hour).

Methods: This study reviewed the medical records of 102 critically ill patients on ECMO support at a specialized intensive care unit at a tertiary care university hospital between March 2002 and January 2008. Demographic, clinical, and laboratory variables were retrospectively collected as survival predicators.

Results: The overall mortality rate was 57.8%. The most common condition requiring ECMO support was cardiogenic shock. Goodness-of-fit was good for AKIN0-hour, AKIN24-hour, and AKIN48-hour criteria. The AKIN0-hour, AKIN24-hour, and AKIN48-hour scoring systems also had excellent areas under the receiver operating characteristic curve (0.804 ± 0.046, 0.811 ± 0.045, and 0.858 ± 0.040, respectively). Furthermore, multiple logistic regression analysis indicated that AKIN48-hour, age, and Glasgow Coma Scale score on the first day of intensive care unit admission were independent risk factors for hospital mortality. Finally, cumulative survival rates at 6-month follow-up after hospital discharge differed significantly (p < 0.05) for AKIN48-hour stage 0 versus AKIN48-hour stages 1, 2, and 3; and AKIN48-hour stage 1 and 2 versus AKIN48-hour stage 3.

Conclusions: During ECMO support, the AKIN48-hour scoring system proved to be a reproducible evaluation tool with excellent prognostic abilities for these patients.


   Introduction
Top
 Abstract
 Introduction
Material and Methods
 Results
 Comment
 References
 
Extracorporeal membrane oxygenation (ECMO) is effective in treating severe, reversible myocardial dysfunction (eg, myocarditis, cardiomyopathy, or postoperative cardiogenic shock) and for providing a bridge to another treatment modality. Acute kidney injury (AKI) developing during ECMO is associated with very poor outcome [1, 2], possibly due to accumulated extravascular water causing interstitial overload, impaired oxygen transport through tissues, and increased extravascular lung water volume with impaired O2 transport. Increased water is associated with subsequent organ dysfunction, particularly of the heart, lungs, and brain [3, 4].

The RIFLE (an acronym for risk of renal failure, injury to the kidney, failure of kidney function, loss of kidney function, and end-stage renal failure) classification was first proposed by the Acute Dialysis Quality Initiative (ADQI) group to standardize AKI study [5]. The authors of this study group previously demonstrated the good discriminative power of the RIFLE classification system for predicting hospital mortality on the first day of ECMO support [1]. Recently, the Acute Kidney Injury Network (AKIN) group, which is composed of nephrologists and intensivists, proposed modifying the RIFLE criteria. In AKIN stage 1 (analogous to RIFLE-risk), a smaller change within 48 hours in serum creatinine (SCr) exceeding 0.3 mg/dL (≥26.2 µmol/L) was suggested as an AKI threshold. Moreover, patients receiving renal replacement therapy were reclassified as AKIN stage 3 (RIFLE-failure; Table 1) [6].


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  		Table 1 Categorical Severity Stage Metrics of Acute Kidney Injury Network (AKIN)
 
Renal failure is common for critically ill patients on ECMO, and its occurrence has an extremely high mortality rate. The commonly observed decrease in urine output during ECMO may be associated with AKI. Several studies have documented a high mortality rate for patients treated with ECMO and continuous renal replacement therapy (CRRT [AKIN stage 3 includes patients who need renal replacement therapy at any stage]) [1–3]. Thus, AKIN criteria enhance the ability to predict short-term outcome in ECMO patients compared with the RIFLE classification. The aim of this study was to identify the relationship between hospital mortality and short-term prognosis and AKIN score in this subset of critically ill ECMO patients.


   Material and Methods
Top
 Abstract
 Introduction
 Material and Methods
Results
 Comment
 References
 
Patient Information and Data Collection
The local Institutional Review Board approved the study protocol (96-0004B). The medical records of 102 of 120 patients on ECMO support in a 20-bed specialized cardiovascular surgery intensive care unit between March 2002 and January 2008 were examined. Patients on ECMO support who did within 48 hours (18 patients) were excluded.

Retrospective data obtained are as follows: demographics; primary diagnosis for ECMO implementation; AKIN scores at pre-ECMO support (AKIN0-hour); at post-ECMO 24 hours (AKIN24-hour) and at post-ECMO 48 hours (AKIN48-hour); duration of hospitalization; and outcome. The primary study outcome was hospital mortality. Follow-up at 6 months after hospital discharge was performed using charts or telephone interviews when necessary.

Definitions
The ADQI group first proposed the RIFLE system at the second ADQI conference held in Vicenza, Italy, in May 2002. The classification system comprises individual criteria for SCr levels and urine output. A patient can fulfill the criteria through changes in SCr concentrations or changes in urine output, or both [5]. The criteria leading to worst possible classification were employed. Patients were classified into three severity categories (risk, injury, and failure) and two clinical outcome categories (loss and end-stage renal disease) [1, 2, 7–10]. The AKIN scheme [6] differs from the RIFLE classification as follows. The AKIN classification system reduces the need for baseline SCr level but requires at least two SCr values within 48 hours (this study used SCr level at pre-ECMO support as the baseline SCr concentration for AKIN categories [AKIN48-hour]). Notably, AKIN stage 1 is similar to RIFLE-risk, but includes an abrupt (within 48 hours) reduction in kidney function (increase in SCr concentration of ≥0.3 mg/dL); injury and failure are the same as stages 2 and 3, respectively. Stage 3 also includes patients who require renal replacement therapy at any stage. Two outcome classes, loss and end-stage kidney disease, were omitted (Table 1).

Clinical Management
Patients were treated with CRRT when their fluid overload was inadequately controlled by diuretic therapy, or when patients had severe metabolic acidosis, a need for hyperalimentation with insufficient urine output, or a sign or symptom, such as encephalopathy, for which uremia could not be ruled out as a cause. Thus, CRRT was employed to regulate intravascular volume and overall fluid balance, enable rapid administration of blood products without inducing volume overload, and correct azotemia, acid-base as well as electrolyte imbalances.

Statistical Analysis
Descriptive statistics are expressed as means ± SE. Primary analysis compared hospital survivors with nonsurvivors. All variables were tested for normal distributions using the Kolmogorov-Smirnov test. The Student t test was applied to compare means of continuous variables and normally distributed data; otherwise, the Mann-Whitney U test was employed. Categorical data were tested using the {chi}2 test. This study utilized the {chi}2 test for trend to assess categorical data associated with AKIN0-hour, AKIN24-hour, and AKIN48-hour scores. Correlations between paired variables within groups were assessed by linear regression using Pearson analysis. Finally, risk factors were assessed by univariate analysis, and variables that were statistically significant (p < 0.05) in the univariate analysis were included in multivariate analysis by applying a multiple logistic regression based on forward elimination of data.

Calibration was assessed using the Hosmer-Lemeshow goodness-of-fit test to compare the number of observed and predicted deaths in risk groups for the entire range of death probabilities. Discrimination was assessed using the area under the receiver operating characteristic curve. Areas under the receiver operating characteristic curves were compared using a nonparametric approach. The area under the receiver operating characteristic curve analysis was also utilized to calculate cutoff values, sensitivity, specificity, and overall correctness. Finally, cutoff points were calculated by acquiring the best Youden index (sensitivity + specificity –1). Cumulative survival curves as a function of time were generated utilizing the Kaplan-Meier approach, and compared using the log rank test. All statistical tests were two-tailed; a value of p less than 0.05 was considered statistically significant. Data were analyzed using SPSS 12.0 for Windows (SPSS, Chicago, IL).


   Results
Top
 Abstract
 Introduction
 Material and Methods
 Results
Comment
 References
 
Subject Characteristics
The study population comprised 102 patients on ECMO support at the cardiovascular surgery intensive care unit between March 2002 and January 2008. Patient median age was 52 years; 62 (61%) were male and 40 (39%) were female. In-hospital mortality for the entire group was 57.8% (59 of 102). Table 2 lists patient demographic data and clinical characteristics for both survivors and nonsurvivors. An extremely high mortality rate, 85% (22 of 26) was noted for patients treated with ECMO and CRRT, 83% (35 of 42) for AKIN0-hour stage 3, 86% (37 of 43) for AKIN24-hour stage 3, and 89% (42 of 47) for AKIN48-hour stage 3. Table 3 presents primary diagnosis for intensive care unit admission and the primary reason for ECMO support. The most frequent indication for ECMO support in this patient subset was cardiogenic shock (80%).


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  		Table 2 Patients' Demographic Data and Clinical Characteristics
 

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  		Table 3 Primary Diagnosis for Intensive Care Unit (ICU) Admission and Extracorporeal Membrane Oxygenation (ECMO) Support
 
Calibration, Discrimination, and Correlation for Illness Scoring Systems
Calibration for AKIN48-hour (Lemeshow-Hosmer {chi}2= 0.486, 2 degrees of freedom, p = 0.384) and the AKIN48-hour calibration curves was close to the line of perfect predictive ability. The AKIN0-hour and AKIN24-hour also had good calibration, estimated by the Hosmer-Lemeshow goodness-of-fit test. Table 4 shows the goodness-of-fit, as measured by the Hosmer-Lemeshow {chi}2 test for predicted mortality risk, and the predictive accuracy of those scores. Table 4 also lists the discrimination for AKIN0-hour, AKIN24-hour, and AKIN48-hour scores.


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  		Table 4 Comparison of Calibration and Discrimination of the Scoring Methods in Predicting Hospital Mortality
 
Next, AKIN0-hour, AKIN24-hour, and AKIN48-hour scores were assessed for correlations. Table 5 lists correlations between scoring systems used at pre-ECMO, and 24 hours and 48 hours post-ECMO. The AKIN0-hour, AKIN24-hour, and AKIN48-hour scores were positively correlated (all, r > 0.6, p < 0.001). An inverse correlation (p < 0.001) was noted between those scores and mean arterial pressure. Nevertheless, there was no significant association between mean arterial pressure and baseline SCr levels (Table 5).


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  		Table 5 Correlation Between Scoring Systems and Variables
 
Hospital Mortality and Short-Term Prognosis
Univariate analysis identified 15 (Table 6) of 28 variables (Tables 2 and 3) as prognostically valuable. Multivariate analysis identified the following variables as of independent prognostic significance: AKIN48-hour, age, and Glasgow coma scale (Table 6). Regression coefficients of these variables were utilized to calculate a logit of death for each patient as follows:


Formula 0005

(0005)


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  		Table 6 Variables Showing Prognostic Significance
 
To assess the predictive value of each measure for hospital mortality, sensitivity, specificity, and overall correctness of prediction were determined. The AKIN48-hour had the best Youden index and highest overall prediction correctness (Table 7). Cumulative survival rates differed significantly (p < 0.05) for AKIN48-hour stage 0 versus AKIN48-hour stages 1, 2, and 3; and AKIN48-hour stage 1 and 2 versus AKIN48-hour stage 3 (Fig. 1).


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  		Table 7 Prediction of Subsequent Hospital Mortality
 

Figure 1
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  		Fig 1. Cumulative survival rate for 102 critically ill patients based on their AKIN48-hour stage at post-ECMO treated 48 hours. (AKIN = Acute Kidney Injury Network; ECMO = extracorporeal membrane oxygenation.)

 

   Comment
Top
 Abstract
 Introduction
 Material and Methods
 Results
 Comment
References
 
Several previous studies have identified a mortality rate of 48% to 76% for patients on ECMO support [1, 2, 11, 12]. The hospital mortality rate for patients in this study was 57.8%. Analytical results confirm this grave prognosis for this patient subgroup on ECMO support. The AKIN group attempted to improve the sensitivity and reproducibility of AKI criteria and defined the AKIN classification. We propose that AKIN48-hour score can increase the accuracy of short-term prognosis in this patient cohort.

An earlier retrospective study by the authors of this study group enrolled 46 critically ill patients treated by ECMO, most of whom had postcardiotomy cardiogenic shock [1]. Scoring systems were examined only during the first day of ECMO support. Hospital mortality was 20% for non-AKI, 57.1% for RIFLE0-hour-risk, 72.2% for RIFLE0-hour-injury, and 100% for RIFLE0-hour-failure ({chi}2 for trend, p < 0.001). A progressive and significant increase in mortality was associated with an increasing RIFLE0-hour classification for all patients. Another investigation by this research team reviewed the medical records of 78 critical ill patients on ECMO support [2]. The RIFLE0-hour criteria classified 78.2% of patients as having AKI. Multivariate analysis indicated that the Acute Physiology, Age, and Chronic Health Evaluation (APACHE) IV and RIFLE0-hour classifications had independent prognostic significance. As demonstrated previously, this at least in part explains why the RIFLE0-hour criteria can precisely predict hospital mortality of critically ill patients on their first day of ECMO. After ECMO for 48 hours, the analytical results of this study confirm and extend those observations by demonstrating that AKIN48-hour is a simple, reproducible, and easily applied evaluation tool with good prognostic ability that can generate objective information for patient's families and physicians, and supplement judgments of clinical prognosis.

Patients who have AKI have high mortality rates and resource utilization. Most studies agree that patients exhibiting signs of renal failure typically respond poorly to ECMO. In a study by Morris and associates [13], all 13 children managed with ECMO and slow continuous ultrafiltration died. In such cases, a fatal outcome is often related to progression of conduction disturbance to electromechanical dissociation and asystole [13]. In a study by Balasubramanian and colleagues [14], 30 pediatric cardiac surgical patients requiring renal replacement therapy during ECMO support had a significant risk for hospital mortality (p < 0.001) [14]. Kolovos and colleagues [15] also demonstrated that children who had undergone postcardiotomy ECMO requiring hemofiltration had a mortality rate five times that of patients without AKI [15]. In a previous study by our group, 21 AKI patients treated by ECMO and CRRT died during hospitalization [2]. In a subsequent study, 2 patients with myocardial dysfunction survived after ECMO and CRRT treatment [3]. Early diagnosis and aggressive treatment of patients with fewer than three failed organs resulted in a favorable outcome. Timely administration of ECMO and CRRT is effective in supporting circulation and renal function for myocardial dysfunction refractory to conservative treatment, and will likely be the standard treatments in the near future. These studies indicated that advanced cardiac failure may require more aggressive and earlier initiation of ECMO support before AKI develops.

The AKIN group aimed to improve the sensitivity and reproducibility of the AKI criteria and defined the AKIN classification. Nevertheless, some studies found that AKIN criteria may not improve sensitivity and predictive ability [16-19]. Notably, AKIN stage 1 is similar to RIFLE-risk, but includes abrupt (within 48 hours) reduction in kidney function (increase in SCr ≥0.3 mg/dL); additionally, stage 3 encompasses patients who require renal replacement therapy at any stage. Emerging evidence suggests that even small increases in SCr levels after cardiac surgery significantly increase mortality. Several studies have documented a high mortality rate for patients treated with ECMO and CRRT [1–3].

Despite the promising analytical results obtained by this study, several important limitations must be recognized. First, this retrospective study was performed at a single tertiary care medical center; thus, the generalizability of findings is limited. Second, the patient group comprised patients on ECMO and excluded those who died within 48 hours; therefore, experimental results may not be directly extrapolated to other patient populations. Finally, the number of patients and outcome events were insufficient for identifying substantial differences among AKIN0-hour, AKIN24-hour, and AKIN48-hour scores.

This study of critically ill patients on ECMO identified a hospital mortality rate of 57.8%. Prognosis for these patients is poor. Analytical data demonstrate the excellent discriminative power of AKIN48-hour in predicting hospital mortality of critically ill patients already on ECMO support. We recommend physicians use AKIN48-hour to assess short-term prognosis in this patient group.


   References
Top
 Abstract
 Introduction
 Material and Methods
 Results
 Comment
 References
 

  1. Lin CY, Chen YC, Tsai FC, et al. RIFLE classification is predictive of short-term prognosis in critically ill patients with acute renal failure supported by extracorporeal membrane oxygenation Nephrol Dial Transplant 2006;21:2867-2873.[Abstract/Free Full Text]
  2. Lin CY, Tsai FC, Tian YC, et al. Evaluation of outcome scoring systems for patients on extracorporeal membrane oxygenation Ann Thorac Surg 2007;84:1256-1262.[Abstract/Free Full Text]
  3. Lin CY, Chen YC, Tsai FC, et al. Continuous renal replacement therapy combined with extracorporeal membrane oxygenation in advanced cardiac failure patients J Nephrol 2008;21:789-792.[Medline]
  4. Journois D. Hemofiltration during cardiopulmonary bypass Kidney Int 1998;66(Suppl):174-177.
  5. Bellomo R, Ronco C, Kellum JA, Mehta RL, Palevsky P, Acute Dialysis Quality Initiative 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 Crit Care 2004;8:R204-R212.[Medline]
  6. Mehta RL, Kellum JA, Shah SV, et al. Acute Kidney Injury Network: report of an initiative to improve outcomes in acute kidney injury Crit Care 2007;11:R31.[Medline]
  7. Chen YC, Fang JT, Yang CW. The use of RIFLE classification in critically ill patients Int J Intens Care 2008;15:83-86.
  8. Jenq CC, Tsai MH, Tian YC, et al. RIFLE classification can predict short-term prognosis in critically ill cirrhotic patients Intens Care Med 2007;33:1921-1930.[Medline]
  9. Chen YC, Jenq CC, Tian YC, et al. RIFLE classification for predicting in-hospital mortality in critically ill sepsis patients Shock 2009;31:139-145.[Medline]
  10. Lin CY, Kao KC, Tian YC, et al. The RIFLE score increases the accuracy of outcome prediction in patients with acute respiratory distress syndrome undergoing open lung biopsy Respiration 2009;77:398-406.[Medline]
  11. Doll N, Kiaii B, Borger M, et al. Five-year results of 219 consecutive patients treated with extracorporeal membrane oxygenation for refractory postoperative cardiogenic shock Ann Thorac Surg 2004;77:151-157.[Abstract/Free Full Text]
  12. Smedira NG, Moazami N, Golding CM, et al. Clinical experience with 202 adults receiving extracorporeal membrane oxygenation for cardiac failure: survival at five years J Thorac Cardiovasc Surg 2001;122:92-102.[Abstract/Free Full Text]
  13. Morris MC, Ittenbach RF, Godinez RI, et al. Risk factors for mortality in 137 pediatric cardiac intensive care unit patients managed with extracorporeal membrane oxygenation Crit Care Med 2004;32:1061-1069.[Medline]
  14. Balasubramanian SK, Tiruvoipati R, Amin M, et al. Factors influencing the outcome of paediatric cardiac surgical patients during extracorporeal circulatory support J Cardiothorac Surg 2007;2:4.[Medline]
  15. Kolovos NS, Bratton SL, Moler FW, et al. Outcome of pediatric patients treated with extracorporeal life support after cardiac surgery Ann Thorac Surg 2003;76:1435-1441.[Abstract/Free Full Text]
  16. Bagshaw SM, George C, Bellomo R. A comparison of the RIFLE and AKIN criteria for acute kidney injury in critically ill patients Nephrol Dial Transplant 2008;23:1569-1574.[Abstract/Free Full Text]
  17. Lopes JA, Fernandes P, Jorge S, et al. Acute kidney injury in intensive care unit patients: a comparison between the RIFLE and the Acute Kidney Injury Network classifications Crit Care 2008;12:R110.[Medline]
  18. Chang CH, Lin CY, Tian YC, et al. Acute kidney injury classification: comparison of AKIN and RIFLE criteria Shock 2010;33:247-252.[Medline]
  19. Yan X, Jia S, Meng X, et al. Acute kidney injury in adult postcardiotomy patients with extracorporeal membrane oxygenation: evaluation of the RIFLE classification and the Acute Kidney Injury Network criteria Eur J Cardiothorac Surg 2010;37:334-338.[Abstract/Free Full Text]

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