BJA Advance Access published online on September 13, 2007
British Journal of Anaesthesia, doi:10.1093/bja/aem252
Cardiac surgery with cardiopulmonary bypass: does aprotinin affect outcome?
1 Department of Anaesthesiology, Centre Hospitalier Universitaire (CHU) Brugmann, Hôpital Universitaire des Enfants Reine Fabiola, Brussels, Belgium
2 Department of Anaesthesiology, CHU Montreal, Canada
3 Department of Anaesthesiology, CHU Charleroi, Belgium
4 Department of Anaesthesiology, University Hospital Antwerp, Wilrijkstraat 10, B-2650 Edegem, Belgium
* Corresponding author. E-mail: stefan.dehert{at}ua.ac.be
Accepted for publication June 18, 2007.
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Abstract |
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Background: Aprotinin, a non-specific serine protease inhibitor, has been used for two decades to reduce perioperative blood loss and the risk for allogeneic transfusion in cardiac surgery. This study evaluated the effects of aprotinin on outcome (mortality, cardiac events, renal failure, and cerebrovascular events) in such patients undergoing cardiac surgery with cardiopulmonary bypass.
Methods: Data were obtained in patients who received a strict blood conservation protocol: no antifibrinolytic therapy when at low risk (n=854) and aprotinin (n=1210) when at high risk for blood transfusion. Relative risk of different pre- and intra-operative variables was calculated for the different outcome variables. Backward stepwise logistic regression analysis was used to identify the independent risk factors associated with the different outcome variables. Statistical significance was accepted at P<0.01.
Results: Postoperative mortality and morbidity were higher in the aprotinin group but this was related to an increased incidence of perioperative risk factors. Mortality was similar to that predicted by the Euroscore. Complex surgery was the only independent variable associated with postoperative cardiac events. Preoperative heart failure, preoperative creatinine >1.5 mg dl–1, urgent, and redo surgery were the independent variables associated with postoperative haemodialysis. Age >70 yr was identified as the only independent variable associated with neurologic dysfunction.
Conclusions: In the present study, patients receiving aprotinin as part of a strict blood conservation strategy represent a population at high risk for postoperative complications. For the outcome variables studied, aprotinin administration was not identified as an independent risk factor.
Keywords: anaesthesia, cardiac; aprotinin; blood, loss; outcome; surgery, cardiac
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Introduction |
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In cardiac surgery patients, perioperative transfusion has been associated with an increased risk for postoperative morbidity and mortality.1 2 Therefore, strategies allowing safe reduction in allogeneic transfusion can be associated with risk reduction during cardiac surgery and also improve utilization of a scarce resource.3 Aprotinin, a non-specific serine protease inhibitor, has been used for two decades to reduce perioperative blood loss and the risk for allogeneic transfusion in cardiac surgery. In a Cochrane meta-analysis, reviewing 55 studies in cardiac surgery (n=3814 patients), aprotinin treatment was associated with a 30% reduction in the risk of allogeneic transfusion compared with placebo. In 27 studies that assessed the incidence of re-thoracotomy, aprotinin was associated with a 60% reduction of re-exploration.4 In another meta-analysis5 reviewing 35 coronary artery surgery trials (n=3879 patients), aprotinin treatment was associated with a 40% reduction in transfusion requirements and a 47% reduction in the risk of stroke when compared with placebo. The largest meta-analysis (72 trials, n=8409 patients) showed that, compared with placebo, aprotinin treatment was associated with a 63% reduction in blood transfusion, a 63% reduction in re-exploration, and a 45% reduction in mortality.6 A meta-analysis of 64 randomized controlled trials of aprotinin conducted between 1987 and 20027 reported that the effectiveness of aprotinin on perioperative blood loss and transfusion requirements was already clearly established in the early 1990s in a patient population of primary and repeat cardiac surgery.
Recently, three retrospective observational studies have reported an association between aprotinin treatment and an increased incidence of postoperative morbidity and mortality.8–10 The difference between evidence from the randomized trials and these multivariate-adjusted cohort studies could be explained by the fact that observational studies were subjected to sources of bias that did not affect the randomized trials and that findings from multivariate-adjusted cohort studies are not necessarily generally applicable to clinical practice.11 This latter point indicates that the analysis of risk profiles and outcomes in patients in whom drugs were given according to strict clinical guidelines is relevant. To address this issue, we conducted a non-sponsor-supported single-institutional study to assess the incidence and risk of adverse outcomes associated with the use of aprotinin in cardiac surgery patients at high risk for blood transfusion due to perioperative blood loss.
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Methods |
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After institutional Ethical Committee approval, data on consecutive adult (>18 yr) patients undergoing cardiac surgery with cardiopulmonary bypass (CPB) from October 1997 (beginning of the database) until September 2005 at the Centre Hospitalier Universitaire de Charleroi (n=2064) were obtained from the departmental database in order to perform the present retrospective observational study. Perioperative data were obtained throughout hospitalization by independent investigators.
All patients received a specific blood conservation strategy according to a protocol that was defined before the surgical intervention. In all patients with a prebypass haematocrit greater than 33%, normovolemic haemodilution was performed. The amount of blood collected was calculated in order to reach a haematocrit of 20% on CPB. Aprotinin was administered when the following indications were present: a low red blood cell volume (<1500 ml), complex operations (coronary artery bypass grafting combined with valvular surgery, aortic reconstructions, multiple valve replacement, etc.), a low preoperative platelet count (<125 000 mm–3), and when aortic cross-clamp time was expected to be >120 min. A high dose regimen was used in all cases [2x106 kallikrein inhibiting units (KIU) as a bolus dose, followed by a continuous infusion of 500 000 KIU h–1 until the end of the operation, and 2x106 KIU in the CPB priming fluid].12 The presence of preoperative renal dysfunction (creatinine >1.5 mg dl–1) was not considered as a contraindication for aprotinin therapy.
A cell saver device (Cell Saver 5, Haemonetics CO, Braintree, MA, USA) was used in case of re-do operations and during aortic reconstruction procedures. Haemofiltration was used when excess volume (>1000 ml) was present in the extracorporeal circuit at the end of CPB.
Initial anticoagulation consisted of 400 IU kg–1 heparin. Additional doses were administered throughout CPB to maintain the activated clotting time (measured with kaolin as activator) >700 s. The extracorporeal circuit was primed with 1 litre of 3.5% urea-linked gelatine (Haemacel®, Hoechst SA, Brussels, Belgium). Patients were transfused when the haematocrit was <20%, in the presence of a low CPB volume and when no autologous blood was available. All CPB procedures were performed under moderate hypothermia (28–32°C) and the heart was arrested with cold high potassium (30 mEq litre–1) crystalloid cardioplegic solution. All patients were re-warmed to a bladder temperature >36°C before coming off CPB. At the end of the procedure, reversal of heparin activity was obtained with protamine sulphate, titrated using the heparinase-activated clotting time (Hepcon® HMS plus, Medtronic, MN, USA). Blood from the extracorporeal circuit was returned to all patients upon completion of the operation and thereafter the blood collected during normovolemic haemodilution was retransfused in the inverse order of collection.
Intra- and postoperative care was guided in all patients by strict haemodynamic, ventilatory, and blood transfusion protocols that have been described earlier.13 14 Transfusion of fresh frozen plasma and platelets were also administered according to an algorithm.15
Each outcome event was predefined and classified as mortality, cardiac event (postoperative myocardial infarction or heart failure), renal failure or cerebrovascular event. Postoperative myocardial infarction was defined by the presence of new Q waves, or an increase in creatine kinase isoenzyme MB levels >100 U ml–1 (up to March 2000) or troponin T levels >3.5 ng ml–1 (from April 2000). Postoperative myocardial dysfunction was defined as a cardiac index of less than 2.0 litre m–2 min–1 associated with a pulmonary artery wedge pressure above 18 mm Hg or a central venous pressure above 12 mm Hg. Renal failure was defined as renal dysfunction requiring haemodialysis. Criteria for institution of haemodialysis were presence of oliguria (<0.5 ml kg–1 h–1) and/or presence of fluid accumulation, a blood urea level >200 mg dl–1, the presence of acidosis (pH<7.20) or the presence of hyperkalaemia (>6 mEq litre–1). Postoperative renal dysfunction was defined as a creatinine level >2 mg dl–1.16 Creatinine clearance was calculated using the Cockcroft–Gault formula. Cerebrovascular events included a clinically diagnosed cerebrovascular accident, transient ischaemic attack or coma of cerebral origin. Intraoperative blood loss was evaluated by measuring the volume of blood collected in the suction reservoir and by weighing the surgical sponges and drapes. Postoperative blood loss was assessed as chest-drain output until their removal.
Baseline preoperative and intraoperative characteristics were controlled for normal distribution (Kolmogorov–Smirnov test) and compared using a one-way analysis of variance (ANOVA) followed by the Tukey test for pairwise comparisons between groups. If the normality test failed, the different groups were compared using a one-way ANOVA on ranks followed by the Dunn test for pairwise comparisons between groups. Categorical variables between groups were compared using a 
2 test.
Relative risk of the different pre- and intra-operative variables was calculated for the different outcome variables (mortality, cardiac event, haemodialysis, renal dysfunction, and cerebral event). The variables that represented a statistically significant risk factor were entered into a backward stepwise logistic regression analysis to identify the independent risk factors associated with the different outcome variables. Sample size was estimated based on the methods proposed by Green17 and Cohen.18 For a power of 0.8 and an 
of 0.01, a minimum sample size of 310 patients in each group was calculated to be appropriate.
Statistical analysis was performed using the SigmaStat 2.03 software package (SPSS, Leuven, Belgium) and the GraphPad software (version Prism 4, GraphPad Software Inc, San Diego, CA, USA). Data are expressed as mean (SD) or median (25–75 percentile) where appropriate. Statistical significance was accepted at P<0.01 (two-tailed).
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Results |
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Patients in the aprotinin group were more frequently female and older and a higher proportion of them had a preoperative ejection fraction <35%, a recent myocardial infarction (<6 weeks), heart failure on admission, a higher creatinine level, and a lower creatinine clearance (Table 1), resulting in higher preoperative risk scores. Fewer patients in the aprotinin group were receiving ß-blocking agents but more were receiving aspirin, angiotensin converting enzyme (ACE) inhibitors, diuretics, low molecular weight heparin, and clopidogrel.
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Intra-operatively (Table 2), patients receiving aprotinin therapy had significantly more combined, complex or redo procedures, and the incidence of urgent interventions was also higher. The frequency of normovolemic haemodilution and the volume of blood collected were lower in these patients. Preoperative haemoglobin and red blood cell mass were lower in patients receiving aprotinin (Table 3). Patients in the aprotinin group experienced lower per- and postoperative blood losses, but the number of patients requiring transfusion of a blood product was higher in this group. In the patients who required blood transfusion, perioperative blood losses were lower in the aprotinin group. The number of red blood cell, fresh frozen plasma, and platelet units transfused was not different between groups.
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After operation (Table 4), the in-hospital postoperative mortality was highest in the aprotinin group. In both groups in-hospital mortality corresponded to the one predicted by the EuroSCORE. Postoperative pulmonary, cardiac, renal, and abdominal morbidity was higher in patients receiving aprotinin.
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Univariate analysis identified the following perioperative variables as risk factors for postoperative in-hospital mortality: female gender [relative risk (RR) and 95% confidence intervals: 1.72 (1.25–2.36); P<0.001], heart failure on admission [RR: 5.58 (4.09–7.61); P<0.001], preoperative creatinine >1.5 mg dl–1 [RR: 2.33 (1.63–3.34); P<0.001], calculated creatinine clearance <50 ml min–1 [RR: 3.70 (2.71–5.07); P<0.001], not on preoperative ß-blocking therapy [RR: 1.16 (1.13–1.86); P<0.001], the use of diuretics [RR: 2.68 (1.95–3.67); P<0.001], low molecular weight heparin [RR: 2.10 (1.53–2.88); P<0.001], urgent [RR: 5.41 (3.98–7.35); P<0.001], complex [RR: 2.76 (2.01–3.78) P<0.001] and redo [RR: 2.28 (1.56–3.33); P<0.001] surgery, and aprotinin [RR: 3.15 (2.08–4.78); P<0.001]. However, backward stepwise regression analysis identified only preoperative heart failure, urgent, and complex surgery as independent variables associated with an increased risk of mortality (P<0.001). Aprotinin was not identified as an independent variable associated with increased mortality. The power of this statistical analysis was 1.0.
Univariate analysis identified the following perioperative variables as risk factors for the occurrence of postoperative cardiac morbidity (myocardial infarction or dysfunction): female gender [RR: 2.14 (1.80–2.55); P<0.001], age >70 yr [2.14 (1.80–2.56); P<0.001], preoperative ejection fraction <35% [RR: 2.46 (2.02–2.99); P<0.001], preoperative acute myocardial infarction (<6 weeks) [RR: 1.40 (1.13–1.73); P<0.001], heart failure on admission [RR: 3.34 (2.81–3.98); P<0.001], creatinine >1.5 mg dl–1 [RR: 1.66 (1.34–2.06); P<0.001], calculated creatinine clearance <50 ml min–1 [RR: 2.07 (1.74–2.47); P<0.001], not on preoperative ß-blockers [RR: 1.07 (1.02–1.12); P=0.004] and calcium channel blocking [RR: 2.82 (2.60–3.05); P<0.001] therapy, the use of ACE inhibitors [RR: 1.33 (1.12–1.60); P=0.002], diuretics [RR: 2.12 (1.78–2.52); P<0.001], low molecular weight heparin [RR: 1.52 (1.27–1.82); P<0.001], urgent [RR: 2.85 (2.38–3.41); P<0.001], complex [RR: 2.22 (1.87–2.64); P<0.001] and redo [RR: 1.92 (1.55–2.37); P<0.001] surgery, and aprotinin [RR: 2.03 (1.65–2.51); P<0.001]. However, backward stepwise regression analysis identified complex surgery as the only independent variable (P<0.001) associated with an increased risk of postoperative cardiac morbidity. The power of this statistical analysis was 0.9.
Univariate analysis identified the following perioperative variables as risk factors for postoperative haemodialysis: age >70 yr [RR: 2.23 (1.59–3.14); P<0.001], preoperative ejection fraction <35% [RR: 1.97 (1.29–3.01); P=0.003], heart failure on admission [RR: 4.40 (3.13–6.18); P<0.001], neurological dysfunction [RR: 2.16 (1.42–3.27); P<0.001], creatinine >1.5 mg dl–1 [RR: 7.92 (5.78–10.84); P<0.001], calculated creatinine clearance <50 ml min–1 [RR: 7.17 (5.05–10.19); P<0.001], not on preoperative ß-blocking therapy [RR: 1.07 (1.04–1.10); P<0.001], the use of diuretics [RR: 2.81 (2.02–3.89); P<0.001], low molecular weight heparin [RR: 1.80 (1.29–2.51); P<0.001] and clopidogrel [RR: 2.06 (1.24–3.41); P<0.001], urgent [RR: 5.20 (3.65–7.40); P<0.001], complex [RR: 1.93 (1.37–2.70); P<0.001] and redo [RR: 2.48 (1.69–3.63); P<0.001] surgery, and aprotinin [RR: 2.91 (1.91–4.42); P<0.001]. However, backward stepwise regression analysis identified only heart failure on admission, preoperative creatinine >1.5 mg dl–1, urgent and redo surgery as the independent variables (P<0.001) associated with an increased risk of postoperative haemodialysis. Aprotinin was not identified as an independent risk factor for postoperative haemodialysis. The power of this statistical analysis was 1.0.
Univariate analysis identified the following perioperative variables as risk factors for the occurrence of postoperative renal dysfunction, defined as a maximum postoperative creatinine >2 mg dl–1: female gender [RR: 1.35 (1.08–1.69); P=0.009], age >70 yr [RR: 2.34 (1.88–2.92); P<0.001], preoperative ejection fraction <35% [RR: 2.19 (1.69–2.85); P<0.001], heart failure on admission [RR: 3.77 (3.04–4.68); P<0.001], peripheral arterial disease [RR: 1.41 (1.12–1.78); P=0.003], diabetes [RR: 1.43 (1.14–1.79); P=0.002], neurological dysfunction [RR: 1.48 (1.13–1.93); P=0.005], preoperative creatinine >1.5 mg dl–1 [RR: 6.63 (5.47–8.05); P<0.001], calculated creatinine clearance <50 ml min–1 [RR: 4.88 (3.93–6.05); P<0.001], not on preoperative ß-blocking therapy [RR: 1.11 (1.06–1.15); P<0.001], the use of diuretics [RR: 2.75 (2.23–3.41); P<0.001], low molecular weight heparin [RR: 1.35 (1.08–1.70); P=0.009], and clopidogrel [RR: 1.65 (1.15–2.36); P=0.009], urgent [RR: 3.10 (2.48–3.88); P<0.001], complex [RR: 1.83 (1.47–2.28); P<0.001] and redo [RR: 2.35 (1.84–3.01); P<0.001] surgery, and aprotinin [RR: 1.49 (1.18–1.88); P<0.001]. However, backward stepwise regression analysis identified only age >70 yr, preoperative ejection fraction <35%, preoperative heart failure, preoperative creatinine >1.5 mg dl–1, urgent, complex and redo surgery as the independent variables (P<0.001) associated with an increased risk for postoperative renal dysfunction. The power of this statistical analysis was 1.0.
Univariate analysis identified the following perioperative variables as risk factors for the occurrence of postoperative neurologic dysfunction (coma, stroke or transient ischaemic attack): age >70 yr [RR: 1.88 (1.19–2.96); P=0.006], heart failure on admission [RR: 2.79 (1.61–4.82); P<0.001], preoperative neurological dysfunction [RR: 2.27 (1.36–3.77); P=0.001], creatinine >1.5 mg dl–1 [RR: 3.79 (2.38–6.05); P<0.001], calculated creatinine clearance <50 ml min–1 [RR: 2.36 (1.50–3.73); P<0.001], not on preoperative ß-blocking therapy [RR: 1.03 (1.01–1.05); P=0.003], the use of diuretics [RR: 2.23 (1.42–3.52); P<0.001], urgent [RR: 3.52 (2.16–5.74); P<0.001] and complex [RR: 2.21 (1.40–3.49); P<0.001] surgery. However, backward stepwise regression analysis identified increased age >70 yr as the only independent variable (P=0.012) associated with an increased risk for postoperative neurologic dysfunction. The power of this statistical analysis was 1.0.
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Discussion |
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Aprotinin is administered with the aim of reducing perioperative bleeding and therefore the potential need for, and risks of, blood transfusion. In the present study, patients who received aprotinin according to a predefined protocol had significantly more risk factors for adverse events than those who did not receive aprotinin. In this high risk population, aprotinin was not an independent risk factor for in-hospital mortality, and cardiac (myocardial infarction and heart failure), renal (haemodialysis and renal dysfunction), and neurological (coma, stroke, and transient ischaemic attack) morbidity.
This study differs from three recent observational studies8–10 which reported an association between the use of aprotinin and the risk for postoperative morbidity and mortality. Several methodological issues may be implicated. First, in these studies, indication for aprotinin treatment was not standardized among participating centres or over time in the same centre. In our study, aprotinin use was guided by a strict algorithm which was part of a multidisciplinary and standardized blood conservation strategy.14 Secondly, exclusion criteria in these studies resulted in the loss of a significant number of patients, which might have introduced a bias.19 20 In our study, the only patients excluded were those requiring emergency surgery for whom, obviously, no prospective blood conservation strategy could be applied. Finally, the definition of some outcome variables used in these studies was rather liberal, resulting in a very high incidence of adverse events compared with the literature.20 21 The results from these three observational studies also contrast with those from randomized trials and meta-analyses where aprotinin alone does not appear as a risk factor for postoperative morbidity or mortality. The results of the present study are in line with these latter observations.
Several reports have suggested a causal relationship between perioperative aprotinin treatment and an increased risk for early graft occlusion.22–26 However, this finding has not been confirmed by other investigators5 and the issue remains controversial. In the present study, the administration of aprotinin was not identified as an independent risk factor for postoperative cardiac events. Another adverse event associated with the administration of aprotinin is the occurrence of postoperative renal dysfunction.23 27 28 Aprotinin has a high affinity for the kidneys.29 It is deposited in the proximal tubular cells where it accumulates and interferes with normal tubule protease secretion.30 It is not significantly excreted until 5–7 days after its administration. Risk factors responsible for renal dysfunction after cardiac surgery include female gender, increasing age, increased preoperative creatinine, emergency and valve surgery, duration of and degree of haemodilution on CPB,31 and postoperative haemodynamic dysfunction.32 33 Our data show that the patients allocated to the aprotinin group had a significantly higher incidence of most of these risk factors. Hence, it can be expected that postoperative renal dysfunction will occur more frequently in this group. This was confirmed in our analysis of the postoperative outcome data. However, backward stepwise regression analysis did not identify administration of aprotinin as an independent risk factor for postoperative haemodialysis and renal dysfunction defined as a maximal postoperative creatinine level >2 mg dl–1. Of interest, the results of a recent study34 challenged the previously observed8 dose-dependent negative effects of aprotinin on renal function. A few studies have associated the use of aprotinin with adverse cerebrovascular events.8 24 This finding was not confirmed by others.35 36 Our data did not show any relationship between postoperative neurological adverse events and the administration of aprotinin.
Although the aprotinin patients underwent more complex surgery, they had lower perioperative blood loss than those with no aprotinin. However, a higher number of aprotinin patients required allogeneic blood products. The independent predictive factors for perioperative blood transfusion are the transfusion trigger, perioperative blood loss, and the preoperative red blood cell mass.37 As the same transfusion trigger was used in all patients, the higher rate in the aprotinin patients could be related to their lower preoperative red blood cell mass.
A number of limitations of the present observations should be taken into account. The study design was observational and retrospective. As for any observational study, interpretation of our results may be influenced by the absence of randomization, which may introduce a bias due to the presence of confounding factors. Propensity matching has been used to minimize differences between populations to examine the effect of a non-randomly administered therapy. However, with this matching, the assumption still remains that the choice of treatment is not based on the benefits of alternative treatments. This means that among individuals who exhibit the characteristics used for matching, the model assumes that these individuals are sorted into different treatments as if randomly assigned.38 When aprotinin is administered according to a strict algorithm, confining its use to a well-defined population, such randomization can never be obtained. Hence, the higher incidence of adverse events might very well be related to the fact that patients receiving aprotinin constitute a population at higher risk for postoperative complications. Our study would confirm this hypothesis. Patients who were allocated to the aprotinin treatment had significantly higher pre- and intra-operative risk factors as evidenced by a higher EuroSCORE.39 Therefore, it could be expected that outcome would be different. This indicates that the analysis of risk profiles and outcomes in patients in whom drugs are given according to strict clinical guidelines is of clinical relevance. Only sufficiently powered randomized trials will allow to definitively assess whether aprotinin administration, as such, is associated with an increased incidence of adverse events. However, studies that analyse the risk stratification and the outcome of patients who are put on aprotinin therapy based on a clear protocol may help to understand the risk profile of these patients. This may put into perspective the apparent discrepancy between the positive results of the different meta-analyses and the negative results of the recent multivariate-adjusted cohort studies.
In conclusion, patients allocated to receive aprotinin therapy based on clinical decision making constitute a higher risk subpopulation. From our analysis, aprotinin is not an independent risk factor for postoperative adverse events in such population. The present observations should further be confirmed by adequately powered prospective randomized controlled trials.
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