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Eur J Cardiothorac Surg 2004;25:51-58
© 2004 Elsevier Science NL
a Department of Cardiac Surgery, University Hospital of Ioannina, Ioannina, Greece
b St. Luke's Roosevelt Hospital Center at Columbia University, New York, NY, USA
Received 11 August 2003; received in revised form 18 September 2003; accepted 4 October 2003.
* Corresponding author. St. Luke's/Roosevelt Hospital Center at Columbia University, 45 East 89th Street, New York, NY 101 28, USA. Tel.: +1-212-289-8654; fax: +1-212-523-5344
e-mail: cea8{at}columbia.edu
| Abstract |
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Key Words: Coronary artery bypass grafting EuroSCORE Long-term mortality
| 1. Introduction |
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The purpose of this study was to evaluate the prediction of long-term survival in patients with coronary artery bypass grafting (CABG) by using their predicted surgical risk as calculated by EuroSCORE and, if so, to determine the adjusted hazard ratios for various groups of EuroSCORE.
| 2. Materials and methods |
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Data, prospectively collected during patient's admission as part of routine clinical practice and entered into the New York State adult cardiac surgery report, were for the following variables: age, sex, ethnicity, race, body mass index (BMI), number of arteries diseased, urgency of operation, prior cardiac surgery, Canadian Cardiovascular Society (CCS) angina class, history of myocardial infarction, smoking, diabetes mellitus, hypertension, peripheral vascular disease, chronic pulmonary disease, neurological dysfunction, renal dysfunction, previous percutaneous coronary intervention (PCI), current or past congestive heart failure and left ventricular ejection fraction. Procedural data were also collected on the use of cardiopulmonary bypass, the number and type of grafts used as well as the number of distal anastomoses. Postoperative data collected included 30-day mortality, in-hospital mortality, intra-aortic balloon pump (IABP) support, postoperative length of stay (LOS) and major complications after surgery: stroke, transmural myocardial infarction, deep sternal wound infection, re-exploration for bleeding, endocarditis and/or sepsis, gastrointestinal complications, renal failure and respiratory failure.
Risk stratification was performed according to the EuroSCORE (standard and full logistic EuroSCORE model; http://www.euroscore.org) [1,7]. In study A we used the standard EuroSCORE model and the patients were divided into six groups: 02 (n=610), 35 (n=1479), 68 (n=1099), 911 (n=452), 1214 (n=103) and >14 (n=17). In study B we used the full logistic EuroSCORE model and the patients were divided into seven groups: 0.002.00 (n=447), 2.015.00 (n=1190), 5.0110.00 (n=890), 10.0120.00 (n=686), 20.0130.00 (n=234), 30.0160.00 (n=254) and >60.00 (n=59). The number of groups were chosen to confirm to general clinical impression of very low risk, low risk, medium risk, high risk, higher risk and highest risk patients, while seven categories of patients were chosen to reflect higher discrimination ability of the logistic EuroSCORE to predict mortality in high risk patients. Despite substantial demographic differences between Europe and North America, EuroSCORE performs very well in the STS database, and can be recommended as a simple risk stratification system on both sides of the Atlantic [5]. The standard EuroSCORE system consists of three risk groups: low risk (02) with an expected mortality under 2%; medium risk (35) with an expected mortality under 5%; and high risk (
6) with an expected mortality >10% [1], but logistic EuroSCORE system tends to be more accurate in high risk patients [3].
2.2. Data analysis
Long-term patient survival data were obtained from the United States Social Security Death Index database, using a combination of name, social security number, date of birth, sex and state of last known residence for each patient (http://ssdi.genealogy.rootsweb.com), which was queried in September 2002. This corresponds to a minimum and maximum follow-up time of 7 months (March 2002 patients) and 123 months (January 1992 patients), respectively. The sensitivity of the National Death Index to identify deaths is between 92 and 99% depending on which identifiers are available [8]. Then the database was updated for all deceased patients with the exact date of death; the 123-month KaplanMeier survival plots were determined and compared for all the groups of patients in study A and B.
2.3. Statistical methods
Numerical variables were presented as the mean±standard deviation, while discrete variables were summarized by percentages. Thirty-day mortality, in-hospital mortality, total number of complications and the number of arterials grafts used were compared using the Fisher's exact test or the
2 test where appropriate. The LOS before discharge and the total number of distal anastomoses were compared using the non-parametric KruskalWallis test. The survival KaplanMeier curves were compared by using the log-rank test. A Cox proportional hazards regression model was used to calculate hazard ratios of various groups in study A and B while adjusting for pre, intra and postoperative factors, other than these included in the EuroSCORE formula, such as ethnicity, race, BMI, number of arteries diseased, CCS, more than one previous myocardial infarction, hypertension, left ventricular hypertrophy, congestive heart failure, calcified aorta, diabetes mellitus, smoking, previous PCI, off-pump coronary artery bypass (OPCAB), number of arterial grafts and number of distal anastomoses. Hazard ratios (HR) and 95% confidence intervals (95% CI) were calculated. The model selection was first done with backward stepwise method and variables at a P value of less than 0.05 level were retained in the model as independent predictors. The model was then confirmed using forward stepwise selection. The receiver operating characteristic (ROC) curves were plotted to assess the discrimination ability of the standard and logistic EuroSCORE. The area under the ROC curve was calculated as an index for how well the EuroSCORE could discriminate patients who lived and those who died after CABG (long-term follow-up). The discriminative power of the model is thought excellent if the area under the ROC curve is >0.80, very good if >0.75 and good if >0.70 [9]. A P value of less than 0.05 was considered significant as determined with SPSS 11.0 Software (SPSS, Inc, Chicago, IL).
| 3. Results |
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| 4. Discussion |
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There are reasons for estimating the risk of long-term mortality after CABG. These range from determination of indications for CABG versus cardiac transplantation, proper informed consent, quality monitoring of surgeons and institutions, as well as identification of higher risk patients for long-term mortality in order to have more frequent follow-up. Standard or logistic EuroSCORE works very well for early mortality and we showed in this study that it also works very well for long-term mortality.
We have further examined this relationship by excluding in-hospital deaths (data not shown), in order to demonstrate a true relationship not purely due to operative mortality, and we found that this relationship is still valid; therefore EuroSCORE predicts long-term mortality in patients who survived after CABG.
Our study clearly demonstrates that groups at higher risk for early mortality according to the EuroSCORE continue to be at higher risk for long-term mortality after CABG. With regard to long-term mortality EuroSCORE showed area under the ROC curve of 0.72 and qualified as an applicable model, as an area under the ROC curve greater than 0.70 is usually considered to be associated with a good predictive value [9]. To our knowledge this is the first study in the literature which tests the discrimination ability of a preoperative risk stratification model in predicting long-term mortality.
There are several limitations of this study. First, this retrospective study refers to a single center regional database, thus the results may not be generalized for the population as a whole since patient populations may differ significantly between institutions and countries. Second, we examined all-cause mortality and were unable to determine the cause of death (cardiac or non-cardiac). Third, we had no follow-up data assessing the reinterventions after the operation, which is a valuable parameter and affects long-term outcome. Fourth, in this study we included only CABG patients, who represented only 64% of the original EuroSCORE study.
In conclusion standard or logistic EuroSCORE predicted long-term mortality in our series of patients with isolated CABG. After adjustment for other risk factors affecting long-term mortality (not included in the EuroSCORE formula) EuroSCORE remains a highly significant predictor for long-term mortality in CABG patients.
| Footnotes |
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| References |
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