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J Thorac Cardiovasc Surg 1999;117:794-802
© 1999 Mosby, Inc.
CARDIOPULMONARY SUPPORT AND PHYSIOLOGY |
From the Department of Surgery A, Institute of Surgical Research, Department of Anaesthesiology, and Department of Clinical Chemistry, The National Hospital, Oslo University, Oslo; Department of Immunology and Blood Bank and Department of Microbiology, The Regional Hospital, Norwegian University of Science and Technology, Trondheim; and Department of Immunology and Transfusion Medicine, Nordland Central Hospital, Bodø, University of Tromsø, Tromsø, Norway.
The study was supported by The Norwegian Research Council, Medical Innovation at The National Hospital, and the Norwegian Council on Cardiovascular Research.
Received for publication March 10, 1998. Revisions requested July 9, 1998. Revisions received Oct 26, 1998. Accepted for publication Nov 6, 1998. Address for reprints: Vibeke Videm, MD, PhD, Department of Immunology and Blood Bank, The Regional Hospital, N-7006 Trondheim, Norway.
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Abstract |
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 Top Abstract IntroductionPatients and methodsResultsDiscussionAppendix References |
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.01) and platelet activation (P < .05), heparin/protamine dose ratio (P = .02), duration of cardiopulmonary bypass (P < .01), and gender (P < .05). Therefore measures reducing complement activation alone will not necessarily reduce granulocyte activation sufficiently for clinical significance. |
Introduction |
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TopAbstractIntroductionPatients and methodsResultsDiscussionAppendix References |
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1 eosinophil, 2 monocyte, 1 platelet, 3 complement, 4 and contact activation 5 and decreased cytokine release, 6 few studies have been able to demonstrate significant clinical benefits from heparin coating. However, most studies were small, increasing the risk of drawing false negative conclusions. Furthermore, many studies included low-risk patients, rendering differences more or less impossible to detect because of low overall postoperative morbidity and mortality, as in the Duraflo II Multicentre Study. 7 The first aim of the present study was therefore to investigate possible clinical benefits of heparin coating with full systemic heparinization when including patients with a broad range of preoperative risk factors.
Complement activation is often used when comparing "biocompatibility" of CPB setups, that is, the extent of the evoked inflammatory reaction. Activated complement may directly induce tissue damage. The clinical relevance of measuring complement activation rests mainly on the study by Kirklin and coworkers 8 from 1983, showing correlations between plasma C3a concentrations and organ dysfunction. Presently, a number of sensitive immunoassays for complement activation at various levels of the cascade are available. In vitro studies have shown that quantitation of the terminal SC5b-9 complement complex (TCC) very sensitively discriminates between different CPB setups. 9 The second aim of the study was to evaluate whether TCC measurements are related to clinical outcome.
In vitro, there are great individual differences in degree of complement activation on a given stimulus, and activation during CPB also varies substantially among individuals. 4 The third aim of the study was to identify clinical predictors of increased complement activation.
Granulocyte activation is regarded as an important link between many inflammatory mediators formed during CPB and organ damage. Activated granulocytes adhere to the activated vascular endothelium and release a host of substances further damaging the endothelial cells, permitting edema formation and extravasation of granulocytes. Activated complement is a significant factor responsible for granulocyte activation during CPB. Other potential granulocyte activators are also present (eg, endotoxin, various cytokines, and platelet activation products), but their relative importance is unknown. The fourth aim of the investigation was to find correlates of granulocyte activation during cardiac surgery.
Data from a subgroup of 29 patients, in whom we explored mechanisms for the reduced complement activation observed using heparin-coated CPB circuitry, are presented separately. 10
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Patients and methods |
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TopAbstractIntroductionPatients and methodsResultsDiscussionAppendix References |
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Patients were randomized to CPB with one of the following setups:
Registered variables
Age, gender, height, weight, preoperative condition, noncardiac illness, and medication were registered on admission. Type of operation, total heparin and protamine administration, duration of the operation, CPB, and aortic occlusion, chest tube drainage, and transfusions were recorded. The following postoperative complications were registered prospectively according to defined criteria:
Infective complications: Wound infection, pneumonia, mediastinitis, or sepsis
Cardiac dysfunction: Sustained need for epinephrine or intra-aortic balloon pump to maintain adequate blood pressure
Renal dysfunction: Serum creatinine level greater than 200 µmol/L and/or anuria in patient with normal preoperative kidney function
Adult respiratory distress syndrome: Arterial oxygen tension less than 10 kPa with inspired oxygen fraction greater than 0.5 and bilateral chest effusions on x-ray films, without indications of cardiac failure
Gastrointestinal dysfunction: Bilirubin level greater than 50 µmol/L or acute gastrointestinal bleeding
Central nervous system dysfunction: Peripheral paralysis
Death: During primary hospital stay without recovery after operation, that is, "hospital mortality" 11
The patient's preoperative risk status was summarized with the use of the clinical severity score published by Higgins and coworkers, 12 denoted as the "Higgins' score."
Blood samples and analyses
Samples with or without anticoagulants were obtained just before systemic heparinization, after 30 minutes of CPB, at termination of CPB, during closure of the skin over the sternum, and 3 hours after the operation. The exact sampling times were recorded. All tubes containing anticoagulants were kept on ice until centrifugation within 8 hours. Plasma or serum was stored at –70°C.
Hemoglobin, hematocrit, and blood cell counts were determined in an automated analyzer (Technicon H-1, Miles, Tarrytown, NY).
Complement activation measured as C3 activation products (C3bc), C5a-desArg, and TCC was quantitated in enzyme immunoassays in ethylenediaminetetraacetic acid plasma. 13
Granulocyte activation was analyzed with the use of enzyme immunoassays specific for the degranulation products myeloperoxidase (MPO) and lactoferrin (LF) in ethylenediaminetetraacetic acid plasma. 14,15
Platelet degranulation was assessed by determination of ß-thromboglobulin (BTG) in citrate-theophylline-adenosine-dipyridamole–containing plasma (Diatube-H, Diagnostica Stago, Asnieres-sûr-Seine, France) in a novel competitive enzyme immunoassay (see appendix).
Endotoxin was analyzed in heparin-anticoagulated samples drawn into pyrogen-free tubes at termination of CBP (n = 136) by Limulus amebocyte lysate assay (Chromogenix, Endosafe, Charleston, SC).
To obtain a preoperative complement profile of each patient, we quantitated C3 and C4 antigen in the baseline serum samples by nephelometry (Behring laser nephelometer, Behringwerke AG, Marburg, Germany) according to the manufacturer's instructions. Classical (CH50-c) and alternative (CH50-a) total hemolytic complement activity were measured by means of microwell techniques. 16
No measurements were corrected for hemodilution.
Statistics
Data are given as mean with 95% confidence intervals in parenthesis. For the complement, granulocyte, and platelet activation data, the highest concentration for each patient irrespective of time of occurrence was identified and denoted "maximal C3bc," "maximal TCC," and so on, in the following. As a summary measure, the area under the time curve for the activation parameters was calculated for each patient and is denoted "C3bc area," "TCC area," and so on. 17
The activation parameters were analyzed with 2-way repeated-measures analysis of variance (ANOVA) after logarithmic transformation, using duration of CPB as a covariate. Other comparisons of variables between groups were performed with the 
2 test, Fisher's exact test, 2-tailed t test, or ANOVA, or with the Mann-Whitney U test or Kruskal-Wallis test if not normally distributed.
Factors correlated to each complication were identified with standard methods for logistic regression using the SPSS program package (SPSS, Inc, Chicago, Ill). Linear regression identifying clinical predictors of complement activation and correlates of granulocyte activation was performed by means of standard methods in SPSS (details in the appendix).
The study was approved by the regional ethical committee on February 25, 1993.
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Results |
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TopAbstractIntroductionPatients and methodsResultsDiscussionAppendix References |
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The mean Higgins' score was 3.4 (3.0-3.9). Sixty-nine patients (44%) had scores of more than 3, and 34 patients (22%) had scores of more than 5, confirming that our study included a large proportion of high-risk patients.
Complication
(Table II). One hundred three patients (66%) had an uneventful recovery. Fifty-three patients (34%) experienced one or more complications, including revisions for bleeding. Twenty-four reoperations were necessitated by surgical bleeding (n = 12), bleeding caused by generalized oozing (n = 6), mediastinitis (n = 4), paravalvular leakage (n = 1), and endocarditis (n = 1). No patients fulfilled the criteria for adult respiratory distress syndrome. Seven patients died before the tenth postoperative day, 1 on day 20, and 1 on day 36. There were no significant differences between the heparin-coated and uncoated groups for any complication (Table II) or in total thoracic drainage (uncoated, 1109 mL [895-1324 mL]; heparin-coated, 1020 mL [798-1242 mL]; P = .57) or duration of respiratory support (uncoated, 18 hours [7-28 hours]; heparin-coated, 16 hours [4-29 hours]; P = .88).
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Activation parameters are shown in Table III. By ANOVA using CPB duration as covariate, differences in LF (P < .05), C3bc (P < .0005), and TCC (P < .0005) between the heparin-coated and uncoated groups were significant (Figs. 1 to 3).
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Logistic regression model
(Table IV). No model was fitted for gastrointestinal dysfunction (n = 3). For death, only maximal concentrations of the activation parameters were used during model fitting, because some patients died before all samples were drawn. For all models, fit was good by the Hosmer-Lemeshow test. If only the MPO, TCC, and BTG variables were included instead of all the activation parameters, a substantial loss of model significance and fit was observed (data not shown).
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Significant variables explaining the granulocyte activation parameters included complement and platelet activation, heparin/protamine dose ratio, duration of CPB, and gender (Table V). The models explained approximately 50% of the variation in MPO area and LF area, but less than 35% of the variation in maximal MPO and LF. The models were not improved by including the other intraoperative variables mentioned above, and plasma endotoxin concentrations at termination of CPB were not correlated to granulocyte activation.
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Discussion |
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TopAbstractIntroductionPatients and methodsResultsDiscussionAppendix References |
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18-20 Reduced systemic heparinization may increase the benefits of heparin coating, 21 pointing at heparin- and protamine-induced effects on the body's defense systems as more harmful than previously acknowledged. However, not all agree that reduction of systemic heparin is sufficiently safe. We used full systemic heparinization in both groups to study only one variable—heparin coating. Our study demonstrates that significant differences in biochemical markers cannot directly be interpreted into clinical relevance, even in a study including more than 150 patients and a fair number of outcome "events." Obviously, very many different factors may contribute to post-CPB morbidity and mortality in each patient, not all of which are related to biocompatibility. The present knowledge about pathogenesis is probably fragmentary, rendering it difficult to find efficient measures to reduce risk.
TCC and clinical outcome
No clear-cut relationship between TCC and clinical outcome was found, even if TCC was significant in the logistic regression models for infections, renal dysfunction, and central nervous system dysfunction. The logistic regression model coefficients should be interpreted cautiously in a study of 156 patients. The TCC concentration had a negative coefficient in the models for infections and renal dysfunction. Thus the patients with less TCC formation were at higher risk for the development of these complications. The explanation for this finding is unknown. Maybe the shape of the activation curve is of importance, for example, whether the patient responds with a rapid, intense production of TCC that peaks early or tends to produce less TCC per unit of time, but over a longer period.
For central nervous system dysfunction and cardiac dysfunction, the activation parameters significantly improved models including widely known risk factors such as carotid artery surgery and difficult weaning from CPB, respectively. Most variables that were tested other than the activation parameters had P values of much more than .20 (data not shown). Thus, as a whole, the indicators of complement, granulocyte, and platelet activation were all clinically relevant parameters of biocompatibility, but each marker including TCC had varying significance with respect to the different complications. Whether inclusion of activation markers of other cellular and humoral defense systems such as endothelial cells, monocytes, coagulation, and fibrinolysis improves assessment of biocompatibility, warrants further study.
Clinical predictors of complement activation
Our study clearly showed that the present knowledge of individual factors influencing complement activation during cardiac surgery is insufficient. The Higgins' score was a significant explanatory variable for all complement activation parameters. To our knowledge, this is a new observation. The Higgins' score was developed for patients undergoing CABG. 12 We used it for all patient groups because it is a well-established risk score predicting postoperative morbidity, not only mortality, in cardiac surgical patients, and testing of each potential risk factor itself would necessitate a much larger study population. The risk factors included in the Higgins' score were picked because of their proven relationship with postoperative complications and mortality. Perhaps one reason that these factors carry such an increased risk is their tendency to influence complement activation. Six of the 13 variables in the Higgins' score (ie, reduced left ventricular ejection fraction, prior vascular surgery, chronic obstructive pulmonary disease, anemia, operative aortic stenosis, and diabetes) are related to an increased risk of reduced peripheral oxygenation. Ischemia is known to induce complement activation, 22 and patients with these conditions may have a relative tissue ischemia during CPB, increasing complement activation. Furthermore, patients with reduced organ function in the preoperative period may be more susceptible to complement-related damage, giving them an additional disadvantage.
Correlates of granulocyte activation
Inclusion of markers of contact activation might have further improved the regression models. An important explanatory variable for granulocyte activation in addition to complement activation was duration of CPB. Ischemia in the lower part of the body, including the abdomen, is likely during crossclamping. Release of mediators from ischemic tissues on reperfusion activates the coagulation and fibrinolytic systems 23 and may also activate granulocytes. 24
Granulocyte activation and release of BTG from platelets were significantly correlated. These cells may both activate and inhibit each other, but in general they tend to positively stimulate activation of one another during CPB. 25 The present study demonstrates that platelet-induced granulocyte activation is of practical importance.
Protamine neutralizes heparin by reversible complex formation. Heparin may later be released, because protamine has a shorter half-life than heparin. 26 In vitro, heparin preincubation results in more extensive granulocyte activation on later stimulation with the complement-analog N-formyl-met-leu-phe. 14 Granulocyte activation was correlated to the heparin/protamine dose ratio, with relatively more heparin increasing activation. The clinical significance of heparin-induced granulocyte activation is supported by previous observation of reduced granulocyte activation with heparin-coated CPB only accompanied by reduced systemic heparin, whereas complement activation decreased also with full systemic heparinization. 27
Female gender was an additional significant variable for granulocyte activation. Women carry a higher complication risk after cardiac surgery, in part because they tend to be sicker before the operation. 28 On the basis of our investigation, increased granulocyte activation may be one factor increasing the risk of complications in women.
Our study demonstrates that granulocyte activation during cardiac surgery is multifactorial. Therefore measures reducing complement activation alone may not be sufficient to achieve a clinically relevant reduction in postoperative organ dysfunction.
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Appendix |
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TopAbstractIntroductionPatients and methodsResultsDiscussionAppendix References |
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Logistic regression modeling. For each defined complication, type of operation, age, gender, use of heparin-coated or uncoated CPB circuit, Higgins' score, body weight, aortic occlusion time, duration of CPB, and the activation parameters were entered into multivariate logistic regression model fittings, as well as possibly relevant variables identified in univariate logistic regression. Near-significant variables (P values between .05 and .10) were kept in the model if removal substantially reduced model fit, and goodness-of-fit was assessed by the Hosmer-Lemeshow test. Linearity of the logits for all continuous variables was checked by plotting and, if necessary, transformations were applied to achieve linearity. The variables were scaled by the following factors to achieve a reasonable size of the coefficients: LF area in model for infections: 10–3, TCC area in models for cardiac and central nervous system dysfunction: 10–3, square of LF area in model for renal dysfunction: 10–6.
Linear regression modeling. The dependent variables for complement activation were maximal C3bc, C3bc area, maximal TCC, and TCC area after logarithmic transformation. The independent variables were age, gender, scheduled type of operation, height, weight, Higgins' score, heparin-coated or uncoated CPB set, and the intraoperative variables heparin and protamine doses, duration of aortic occlusion and CPB, and whether the patient required more than one attempt at weaning from CPB. After fitting the best model, we tested whether the model was significantly improved by inclusion of antigen C3, antigen C4, CH50-c, and CH50-a. The dependent variables for granulocyte activation were maximal MPO, MPO area, maximal LF, and LF area after logarithmic transformation. The independent variables were age, gender, scheduled type of operation, height, weight, Higgins' score, heparin-coated or uncoated CPB set, aortic occlusion time, duration of CPB, duration of CPB after release of aortic crossclamp, doses of heparin and protamine, relationship of heparin/protamine, C3bc area, TCC area, BTG area, and endotoxin concentration at termination of CPB. For all models, residual plots were examined and, if necessary, explanatory variables were transformed. Some variables were scaled by a factor of 10–1 to 10–5 to achieve a reasonable size of the coefficients.
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Acknowledgments |
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