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J Thorac Cardiovasc Surg 2005;129:391-400
© 2005 The American Association for Thoracic Surgery
Cardiopulmonary Support and Physiology |
a Department of Anesthesia, University Health Network, University of Toronto
b Department of Health Policy, Management, and Evaluation, University of Toronto
c Department of Surgery, Division of Cardiovascular Surgery, University Health Network, University of Toronto
d Department of Medicine, Division of Nephrology, University Health Network, University of Toronto, Toronto, Ontario, Canada
Received for publication January 11, 2004; revisions received June 2, 2004; accepted for publication June 22, 2004. * Address for reprints: Keyvan Karkouti, MD, MSc, Department of Anesthesia, 3 Eaton N, Toronto General Hospital, University Health Network, 200 Elizabeth St, Toronto, Ontario, Canada M5G 2C4 (E-mail: keyvan.Karkouti{at}uhn.on.ca).
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Abstract |
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METHODS: Data were prospectively collected on consecutive patients undergoing cardiac operations with cardiopulmonary bypass from 1999 to 2003 at a tertiary care hospital. The independent relationship was assessed between the degree of hemodilution during cardiopulmonary bypass, as measured by nadir hematocrit concentration, and acute renal failure necessitating dialysis support. Multivariate logistic regression was used to control for variables known to be associated with perioperative renal failure and anemia.
RESULTS: Of the 9080 patients included in the analysis, 1.5% (n = 134) had acute renal failure necessitating dialysis support. There was an independent, nonlinear relationship between nadir hematocrit concentration during cardiopulmonary bypass and acute renal failure necessitating dialysis support. Moderate hemodilution (nadir hematocrit concentration, 21%-25%) was associated with the lowest risk of acute renal failure necessitating dialysis support; the risk increased as nadir hematocrit concentration deviated from this range in either direction (P = .005). Compared with moderate hemodilution, the adjusted odds ratio for acute renal failure necessitating dialysis support with severe hemodilution (nadir hematocrit concentration <21%) was 2.34 (95% confidence interval, 1.47-3.71), and for mild hemodilution (nadir hematocrit concentration >25%) it was 1.88 (95% confidence interval, 1.02-3.46).
CONCLUSIONS: Given that there is an independent association between the degree of hemodilution during cardiopulmonary bypass and perioperative acute renal failure necessitating dialysis support, patient outcomes may be improved if the nadir hematocrit concentration during cardiopulmonary bypass is kept within the identified optimal range. Randomized clinical trials, however, are needed to determine whether this is a cause-effect relationship or simply an association.
The current practice of CPB, which entails the addition of 1.5 to 2 L or more of nonhematic fluids (crystalloid and colloid fluids used to prime the CPB circuit) to the patient's blood volume, frequently results in marked hemodilution, often to hematocrit concentrations less than 20%. This practice, which is in contrast to the early days of cardiac surgery, when allogeneic blood was used as a prime to avoid hemodilution, was adapted primarily to reduce the use of blood products.4 Although this practice has now been accepted for more than 4 decades, there is a renewed debate about the optimal degree of hemodilution during CPB.5,6 Recent studies have found a direct association between the severity of hemodilution during CPB and perioperative morbidity and mortality.6-9 More specifically, there is a growing body of evidence linking low hematocrit concentrations during CPB with an increased risk of renal dysfunction.6,10,11 Earlier evidence, however, suggested that hemodilution confers protection against renal injury.12,13
Although seemingly contradictory, these findings may be congruent if the relationship between the degree of hemodilution during CPB and post–cardiac operation ARF is more U-shaped than linear. Hematocrit concentrations at the trough of the curve would confer the lowest risk of renal dysfunction, with the risk increasing as the hematocrit deviates from this optimal concentration in either direction. The objective of this study was to determine whether such an optimal hematocrit concentration exists by assessing the relationship between nadir hematocrit concentration (nHct) during CPB and postoperative ARF-D while controlling for multiple perioperative variables known to be related to perioperative renal dysfunction and anemia. Such a finding would be important for it would suggest a means of protecting the kidneys against injury during cardiac operations.
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Methods |
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18 years) patients undergoing cardiac operation with CPB at the Toronto General Hospital from June 1999 to June 2003 were identified from a prospectively collected database, the details of which have been previously described.14,15 A full-time research nurse, who was blinded to the details of this study and to the intraoperative hematocrit data, adjudicated all outcomes from patients' medical records. Attending anesthesiologists, surgeons, and perfusionists collected all preoperative and intraoperative data, with the exception of blood-product transfusion data. A research assistant obtained the transfusion data from the transfusion laboratory's database (Hemocare, Mediware Information Systems, Melville, NY).
Study setting and clinical practice
The Toronto General Hospital is a tertiary care teaching hospital affiliated with the University of Toronto. A full range of adult cardiac surgery procedures, including such complex procedures as congenital heart disease repair and heart transplantation, is performed at this hospital.
During the study period, patients were managed according to standardized clinical protocols as described below.
Anesthetic management
Fast-track anesthesia with fentanyl (10-20 µg/kg), midazolam (0.1 mg/kg), pancuronium (0.15-0.20 mg/kg), isoflurane (0.5%-1.5%), and propofol (0.5-4 mg · kg–1 · h–1) was used. Patients were routinely monitored with pulmonary artery catheters. Transesophageal echocardiography was routinely used except for patients undergoing isolated aortocoronary bypass. Epiaortic scanning was not routinely used. Antifibrinolytic drugs—tranexamic acid (50-100 mg/kg) or aprotinin (6 x 106 U), depending on bleeding risk—were used prophylactically in every patient undergoing CPB.
CPB management
Anticoagulation was achieved with heparin to maintain an activated clotting time more than 480 seconds. The CPB circuit was primed with 1.8 L of lactated Ringer's solution and 50 mL of 20% mannitol. Albumin (25%) and synthetic colloids (Pentaspan; Bristol-Myers Squibb Canada Inc, Montreal, Quebec, Canada) were added to the circuit as needed. Management of CPB included systemic temperature drift to 34°C, alpha-stat pH management, targeted mean perfusion pressure between 50 and 70 mm Hg, and pump flow rates of 2.0 to 2.4 L · min–1 · m–2. Myocardial protection was achieved with intermittent antegrade and, occasionally, retrograde blood cardioplegia. When necessary, deep hypothermic circulatory arrest (DHCA) was achieved by cooling to 20°C with or without retrograde cerebral perfusion. Furosemide was administered in response to persistent oliguria or hyperkalemia.
During CPB, red blood cell concentrate (leukoreduced allogeneic or autologous) was transfused to maintain the hematocrit concentration more than 17%. Pericardial blood was salvaged into the cardiotomy suction reservoir and was reinfused via the CPB circuit as long as patients were anticoagulated. After separation from CPB, heparin was neutralized with protamine sulphate, 1 mg per 100 U of heparin, to achieve an activated clotting time within 10% of baseline. After CPB, red blood cell concentrate was transfused to maintain the hematocrit more than 21% to 24% in stable patients and more than 27% in bleeding or unstable patients.
Dependent variable
ARF was defined as a new requirement for postoperative dialysis.
Independent variables
The primary variable of interest was nHct during CPB. Variables that may be related to perioperative renal dysfunction1-3,16 or anemia15,17,18 were considered for inclusion in the multivariate analysis as confounding variables (Table 1).
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The bivariate associations between the independent variables and ARF-D were assessed by using appropriate tests (t test, Mann-Whitney U test, 
2 test, Fisher exact test, or Mantel-Haenszel test). The bivariate associations between nHct and other independent variables were assessed by the Pearson correlation test. Variables that were associated (P 
0.1) with both ARF-D and nHct were included in the logistic regression analysis.
The mathematical relationships between the continuous independent variables and the probability of ARF-D (logit transformation) were assessed with restricted cubic spline functions.19-21 Variables that were not linearly related were either mathematically transformed or categorized for the logistic regression analysis.22 A Pearson correlation matrix was used to identify collinear independent variables.22
Two logistic regression models were constructed that controlled for all identified confounders (for correlated variables, only the most predictive was included in the multivariable analysis) with ARF-D as the dependent variable. In model 1, nHct was included in its quadratic from (nHct – sample mean of nHct)2 in addition to its untransformed form to compensate for its nonlinear relationship with ARF-D (as identified by the cubic spline function analysis).22 In model 2, nHct was categorized into 3 hemodilution groups: mild (nHct >25%), moderate (nHct 21%-25%), and severe (nHct <21%). These cutoffs were defined by the 25th and 75th nHct percentiles. Each group was treated as a separate, independent variable in the logistic regression analysis.22 In sensitivity analyses, the robustness of the association between nHct and ARF-D was assessed by repeating model 2's regression analysis in 2 different subgroups: (1) excluding patients who had severe baseline renal dysfunction (defined as creatinine concentration more than twice the upper limit of normal) and were therefore at the highest risk for development of ARF-D and (2) including only patients who underwent isolated aortocoronary bypass (by providing a homogeneous patient population, this subgroup analysis removes many confounding issues, such as operative complexity, DHCA, and antifibrinolytic use). All models were constructed by using backward stepwise variable selection with P .05 as the criterion for variable retention. The models' fit was assessed by the Hosmer-Lemeshow (goodness-of-fit) test (a larger P value means better fit or reliability),23 and predictive accuracy was assessed by the c-index (which is equivalent to the area under the receiver operating characteristic [ROC] curve; an area of 0.5 indicates no predictive discrimination and an area of 1.0 indicates perfect separation of patients with different outcomes).24
To explore the effects of risk adjustment on the association between nHct and ARF-D, the distributions of the other independent predictors of ARF-D (covariates in model 2) were obtained for each of the hemodilution groups. The bootstrap technique25 was used to assess validity of model 2 as follows: 100 computer-generated samples, each including 9000 patients, were derived from the study population by random selection with replacement. For each sample, model 2 was refitted, and the confidence intervals (CIs) for the coefficients of the nHct categories were obtained.
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Results |
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The mortality rate was 1.7% (n = 150); the ARF-D rate was 1.5% (n = 134). The unadjusted relationships between ARF-D and the independent variables, including nHct as a continuous variable, are shown in Table 1. Figure 1 shows the spline function graph of the relationship between nHct and ARF-D. On the basis of the shape of this relationship, nHct was categorized as previously described into mild (>25%), moderate (21%-25%), and severe (<21%) hemodilution groups. The unadjusted relationship between ARF-D and nHct is presented in Figure 2.
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In models 1 and 2, nHct was independently associated with ARF-D. In model 1, which included the quadratic form of nHct, the risk of ARF-D was increased as nHct deviated from the mean nHct of 23% (P = .005). The model was reliable (Hosmer-Lemeshow test, P = .5) and discriminative (c-index, 0.94). When nHct was included as 3 categorical variables, moderate hemodilution (nHct, 21%-25%) was associated with the lowest risk of ARF-D. Compared with moderate hemodilution, the odds ratio for ARF-D with severe hemodilution (nHct <21%) was 2.34 (95% CI, 1.47-3.71), and for mild hemodilution (nHct >25%) it was 1.88 (95% CI, 1.02-3.46). This model, which is presented in Table 2, was also reliable (Hosmer-Lemeshow test, P = .4) and discriminative (c-index, 0.94). The sensitivity analyses (Table 3) showed the adjusted odds ratio for ARF-D to be stable in the 2 patient subsets analyzed. The risk estimate for the mild-hemodilution group, however, was not as robust as the estimate for the severe-hemodilution group. Table 4 outlines the risk profile of the hemodilution groups in terms of the independent predictors of ARF-D (covariates in model 2). In all 100 bootstrap samples, nHct remained in the logistic regression model, with the 95% CI of the coefficients within ±2% of those in model 2.
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Discussion |
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These adjusted odds ratios were markedly different from the unadjusted relationship between nHct and ARF-D (Figure 2). Adjustment for confounders reduced the risk of severe hemodilution and increased the risk of mild hemodilution relative to moderate hemodilution. This occurs because patients in the mild-hemodilution group have the most favorable risk profile and those in the severe-hemodilution group have the least favorable risk profile. The actual risk of ARF-D that is attributable to nHct, therefore, becomes evident only after these risk differences are accounted for by multivariate analysis.
The observed association between the degree of hemodilution during CPB and ARF-D is biologically plausible and is supported by existing literature. According to postmortem findings, the 2 most common etiologies for ARF after CPB are acute tubular necrosis caused by inadequate oxygen delivery and renal infarction caused, presumably, by microemboli.26,27 The degree of hemodilution during CPB affects both renal oxygen delivery and renal embolic load.
Hemodilution and renal oxygen delivery
Progressive hemodilution causes a proportional decrease in the oxygen-carrying capacity of the blood. As blood becomes more dilute, however, it also becomes less viscous, leading to increased blood flow in the macrocirculation and microcirculation.28,29 This increased flow compensates for the decreased oxygen-carrying capacity of blood, but only to an as-yet-undefined "critical" hematocrit concentration beyond which further hemodilution results in reduced tissue oxygen delivery.30 In vitro studies have found that even slight reductions in renal oxygen delivery can cause ischemic injury in certain highly susceptible areas of the kidney, especially if the kidney's energy requirements are increased.31,32 Hematocrit concentrations below this critical level would therefore place susceptible areas of the kidney at risk for ischemic injury. Further aggravating this risk may be the increased renal blood flow that occurs in response to hemodilution, which may increase the energy requirements of the kidney for tubular transport work by increasing renal perfusion and the glomerular filtration rate.31,33 Yet another aggravating factor is the proportional reduction in plasma oncotic pressure that occurs with hemodilution. This results in the accumulation of fluid in the interstitial space, which may ultimately lead to capillary closure and reduced tissue oxygen delivery.4,28,30
Hemodilution and renal embolic load
The conduct of CPB generates a large number of emboli of various origins.34,35 The increase in renal blood flow associated with hemodilution may increase the relative number of emboli flowing to the kidneys, thereby increasing the risk of renal infarction and ARF.
These pathophysiological mechanisms provide an explanation for this study's finding that severe hemodilution is associated with a higher risk of ARF-D than is moderate hemodilution. This finding is also supported by other observational studies that have found a direct relationship between the severity of hemodilution and increasing risk of renal, hepatic, and central nervous system dysfunction, as well as mortality.6-11
The other finding of this study, that mild hemodilution may be associated with a higher risk of ARF-D than moderate hemodilution, is equally plausible. Hemodilution during CPB reduces red blood cell injury,29 an important cause of renal dysfunction.27,36 Furthermore, hemodilution prevents the deleterious trapping of red blood cells that occurs in the renal microvasculature after renal ischemia.12,13 Through these mechanisms, as well as by improving microcirculatory blood flow as described previously, moderate hemodilution may therefore confer more protection than mild hemodilution against ischemic renal injury. In contrast to this study, however, previous observational studies in cardiac surgery did not find an increased risk of renal dysfunction with mild compared with moderate hemodilution.6,11 This discrepancy may be due to differences in the definition of ARF, sample size, study population, distribution of nHct, or statistical analyses. Of note, this study's estimated association between ARF-D and mild versus moderate hemodilution was not as robust as that for severe versus moderate hemodilution, as is evident by the 95% CIs in both the primary (Table 2) and sensitivity (Table 3) analyses.
Several steps were taken in this study to ensure that the results were a valid estimate of the "true" relationship between nHct during CPB and renal dysfunction. First, a clear and relevant measure of renal dysfunction—the need for dialysis—was used, as opposed to a surrogate measure, such as change in serum creatinine.37 Second, a prospectively collected and accurate database was used. Third, multiple confounders were identified and adjusted for, including several measures of severity of illness, intraoperative stability, surgical complexity, and perioperative complications. Moreover, sensitivity analyses were performed in different subgroups to further assess the role of several of the more important potential confounders. Fourth, logistic regression modeling was performed according to recommended guidelines, including using an appropriately large sample size (5 to 10 outcomes for each independent variable) and ensuring that the continuous independent variables were classified in such a manner as to conform to the linearity assumption of logistic regression.22 As a demonstration of the importance of the latter, when the nonlinear relationship of nHct with ARF-D was ignored and it was analyzed as a simple continuous variable, it was no longer independently associated with ARF-D (results not shown). Finally, this study included the entire cardiac surgery case-mix of a single tertiary referral center in which patient management was standardized. This increases the generalizability of the results and at the same time ensures that the observed association is not due to variations in clinical practice.
Study limitations
The results of our study must be interpreted cautiously for several reasons. First, the database was created before this study was conceived. Second, because it was an observational study, interpretation of the results should be limited to associations between variables of interest; no causal inferences should be drawn. Third, and most important, the influence of unmeasured but potentially confounding variables on the observed association cannot be entirely ruled out. For example, we did not collect, and therefore could not control for, patients' fluid balance. It is possible (but, given the standardized practice of CPB and fluid management at this institution, improbable) that patients with lower nHct were overhydrated and that those with higher nHct were underhydrated. Such a systematic difference in hydration status would confound the observed relationship between hemodilution during CPB and ARF-D. Other possible confounders include systematic differences in the type and the dose of colloids and antifibrinolytics, both of which may affect perioperative hemodilution and postoperative renal function. Fourth, given that the observed association between mild and moderate hemodilution was not significant in the subgroup analysis, it cannot be concluded that the risk of ARF-D is higher with mild versus moderate hemodilution. Larger studies are required to provide a more accurate estimate of this relationship.
Clinical implications
Thus, despite the strengths of this study, we cannot recommend that the practice of CPB be modified to maintain patients' hematocrit concentration within the "optimal" range identified in this study. Before one can make such a recommendation, which would entail increasing the currently accepted transfusion trigger during CPB, this finding must first be confirmed by randomized controlled trials that compare the renal effects of different hematocrit concentrations during CPB. This is particularly important given that some of the available options for maintaining higher hematocrit concentrations during CPB are not risk free. For example, increasing the transfusion trigger during CPB may reduce the risk of ARF, but it will concomitantly expose patients to all the attendant risks of blood transfusion. Other options, such as retrograde priming of the CPB circuit with autologous blood, reducing the prime volume by using smaller circuits, and ultrafiltration during CPB, may not be appropriate in every case and may increase costs.
On the basis of the results of this study, as well as those of other studies that have found an association between the degree of hemodilution during CPB and postoperative organ dysfunction and mortality, it is our conclusion that randomized controlled trials comparing different degrees of hemodilution are now mandated to determine whether there is an "optimal" degree of hemodilution during CPB.
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Footnotes |
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