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Ann Thorac Surg 2005;79:1902-1908
© 2005 The Society of Thoracic Surgeons

Original article: Cardiovascular

EuroSCORE Predicts Long-Term Mortality After Heart Valve Surgery

Ioannis K. Toumpoulis, MDa,b,*, Constantine E. Anagnostopoulos, MDa,b, Stavros K. Toumpoulis, MDa,b, Joseph J. DeRose, Jr, MDa, Daniel G. Swistel, MDa

a Department of Cardiothoracic Surgery, Columbia University College of Physicians and Surgeons, St. Luke’s-Roosevelt Hospital Center, New York, New York
b Department of Cardiac Surgery, University of Athens School of Medicine, Attikon Hospital Center, Athens, Greece

Accepted for publication December 20, 2004.

* Address reprint requests to Dr Toumpoulis, St. Luke’s-Roosevelt Hospital Center at Columbia University, 515 West 59th Street, New York, NY 10019 (E-mail: toumpoul{at}otenet.gr).


   Abstract
Top
 Abstract
Introduction
 Patients and methods
 Results
 Comment
 References
 
BACKGROUND: The European System for Cardiac Operative Risk Evaluation (EuroSCORE) is the most rigorously evaluated scoring system in cardiac surgery. We sought to evaluate the performance of EuroSCORE in the prediction of long-term mortality in patients undergoing heart valve surgery.

METHODS: Medical records of patients with isolated or combined heart valve surgery, who were discharged alive (n = 1035), were retrospectively reviewed. Their operative surgical risks were calculated according to EuroSCORE model (standard and logistic). Long-term survival data (mean follow-up 4.5 ± 3.1 years) were obtained from the National Death Index. Kaplan-Meier curves of the quartiles of standard and logistic EuroSCORE were plotted.

RESULTS: The estimated 5-year survival rates of the quartiles in the standard and logistic EuroSCORE model were: 90.0% ± 2.3%, 85.1% ± 2.3%, 64.8% ± 3.3%, and 55.1% ± 3.7% (p < 0.0001, log-rank test with adjustment for trend) and 90.4% ± 2.2%, 86.4% ± 2.5%, 66.9% ± 3.3%, and 56.1% ± 3.3% (p < 0.0001, log-rank test with adjustment for trend) respectively. The odds of death in the highest-risk quartile were 7.46- and 7.82-fold higher than the odds of death in the lowest-risk quartile for standard and logistic EuroSCORE respectively.

CONCLUSIONS: EuroSCORE can be used to predict not only in-hospital mortality, for which it was originally designed, but also long-term mortality in the whole context of heart valve surgery. This outcome can be predicted using the standard EuroSCORE, which is very simple and easy in its calculation.


   Introduction
Top
 Abstract
 Introduction
Patients and methods
 Results
 Comment
 References
 
Risk stratification has become an essential element in the practice of cardiac surgery. Great progress has been made in identifying risk factors for early mortality and morbidity and these are the outcomes to be assessed by many models. Recently, a number of studies with large numbers of patients with heart valve surgery have provided a detailed analysis of risk factors associated with heart valve operations to predict operative mortality [1–4]. However, patients with heart valve surgery may have a periprocedural mortality extending up to 1 year after surgery [5].

The European System for Cardiac Operative Risk Evaluation (EuroSCORE), based on a large patient database drawn across Europe, has been developed for the prediction of in-hospital mortality after adult cardiac surgery [6]. It has also been demonstrated that EuroSCORE has good discrimination and calibration in predicting early mortality after heart valve surgery [7]. Standard EuroSCORE was first introduced in 1999 [8] and since its validation in the Society of Thoracic Surgeons database [9] it has been increasingly adopted worldwide, because of its ease of calculation. Recently, the full logistic model became available and may be a better risk predictor especially in high-risk patients [10].

Both operative and long-term mortality may be largely influenced by the same set of covariates and we have demonstrated that standard and logistic EuroSCORE can be used for the prediction of long-term mortality in patients undergoing coronary artery bypass grafting (CABG) [11]. The purpose of the present study was to evaluate and compare the performance of standard and logistic EuroSCORE in the prediction of long-term mortality in a series of 1035 consecutive patients with isolated and combined heart valve surgery who discharged alive from the hospital.


   Patients and methods
Top
 Abstract
 Introduction
 Patients and methods
Results
 Comment
 References
 
Patient Population and Data
Our study consisted of 1035 consecutive adult patients who underwent isolated or combined heart valve surgery between January 1992 and March 2002 at the St. Luke’s-Roosevelt Hospital Center. Therefore, the time zero for follow-up in this study was the date of hospital discharge. Registry databases were studied for preoperative, intraoperative, and postoperative data of the patients.

Data were prospectively collected during patient’s admission as part of routine clinical practice and entered into the New York State (NYS) adult cardiac surgery report. Risk stratification was performed according to standard and logistic EuroSCORE model. The factors used by the EuroSCORE formula, their definition, and their score for both standard and logistic EuroSCORE are shown in Table 1. The standard EuroSCORE system consists of three risk groups: low risk (0–2) with an expected mortality under 2%; medium risk (3–5) with an expected mortality under 5%; and high risk (≥ 6) with an expected mortality greater than 10%, but logistic EuroSCORE system tends to be more accurate in high-risk patients.


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  		Table 1. Risk Factors, Definitions, and Weights in Standard (Score) and Logistic (ß Coefficient) EuroSCORE Model
 
Although NYS cardiac surgery report used different data fields compared with EuroSCORE and its risk factor definitions changed several times during the collection interval used in our study, we were able to transfer accurately most risk factors into the EuroSCORE formula including age, sex, chronic obstructive pulmonary disease, extracardiac arteriopathy, previous cardiac surgery, active endocarditis, critical preoperative state, unstable angina, left ventricular dysfunction, pulmonary hypertension, emergent operation, other procedure than isolated CABG, surgery on thoracic aorta and postinfarct septal rupture. However, there were differences in some definitions including neurological dysfunction, serum creatinine, and recent myocardial infarction. Neurological dysfunction in the EuroSCORE algorithm was defined to be the disease that severely affects ambulation or day-to-day functioning, whereas the NYS database was defined to be a history of stroke with or without residual deficit. Serum creatinine was scored in EuroSCORE algorithm when found greater than 200 µmol/L, whereas in NYS database preoperative renal failure was defined when serum creatinine was found greater than 220 µmol/L. Finally, a myocardial infarction was defined to be recent when occurring within 90 days before operation in EuroSCORE algorithm, whereas in NYS database it was defined to be recent when occurring within 21 days before operation.

Data Analysis
Long-term patient mortality data were obtained from the United States Social Security Death Index database (http://ssdi.genealogy.rootsweb.com). The sensitivity of the National Death Index to identify deaths is between 92% and 99% depending on which identifiers are available [12]. Social Security number alone has the best accuracy of any combination of other identifiers (first initial, last name, day of birth, month of birth, year of birth, etc) with a sensitivity of 97% and a specificity of 99% [12]. In this study we used only Social Security numbers, which were available in all analyzed patients and this allowed avoiding utilization of patients’ names. The Index was queried in September 2002 and patients not found in the Index were assumed to be alive at the time of censoring, which was 3 months before the date of inquiry.

Ethical Issues
The need for informed consent was waived because the data used in this study had already been collected for clinical purposes. Furthermore, the present study did not interfere with the treatment of patients and the database was organized in a way that makes the identification of an individual patient impossible.

Statistical Methods
Numerical variables were presented as mean ± standard deviation and discrete variables were summarized by percentages. For the two models tested, we generated Kaplan-Meier curves [13] for their quartiles and the long-rank test with adjustment for trend was used for comparisons. We also estimated for each model the extreme quartile odds ratio (EQuOR) [14], ie, the odds of death in the high-risk quartile divided by the odds of death in the low-risk quartile. The larger the EQuOR value, the better the discrimination of a model between high-risk and low-risk patients. Finally, we used univariate Cox regression analysis [15] to test whether standard and logistic EuroSCORE are associated with long-term mortality after heart valve surgery. All analyses were performed in SPSS 11.0 (SPSS, Inc, Chicago, IL) and p values are two-tailed.


   Results
Top
 Abstract
 Introduction
 Patients and methods
 Results
Comment
 References
 
A total of 1105 patients underwent heart valve surgery in our institution between January 1992 and March 2002. The observed in-hospital mortality was 6.3% (n = 70). The remaining 1035 patients who were discharged alive were analyzed. Heart valve surgical procedures are listed in Table 2. Table 3 presents patients’ characteristics according to the 17 variables used by logistic EuroSCORE after divided in quartiles. There was an increase in mean age and a percentage increase in risk factors and in patients with lower ejection fraction as the risk stratification grows. During 4598 person-years of follow-up (mean 4.5 ± 3.1 years) 296 deaths (28.6%) were recorded. Both standard (Fig 1) and logistic EuroSCORE (Fig 2) revealed very good discriminatory ability in predicting long-term mortality and the Kaplan-Meier curves of the quartiles diverged widely. The 5-year survival rates of standard and logistic model were: 90.0% ± 2.3%, 85.1% ± 2.3%, 64.8% ± 3.3%, and 55.1% ± 3.7% (p < 0.0001, log-rank test with adjustment for trend) and 90.4% ± 2.2%, 86.4% ± 2.5%, 66.9% ± 3.3% and 56.1% ± 3.3% (p < 0.0001, log-rank test with adjustment for trend), respectively. Univariate Cox regression analysis confirmed that both standard (hazard ratio 1.169, 95% confidence interval [CI] 1.137–1.201; p < 0.001) and logistic EuroSCORE (hazard ratio 1.025, 95% CI 1.020–1.031; p < 0.001) were strong predictors of long-term mortality. Hazard ratios of the quartiles of standard and logistic EuroSCORE models when the lowest-risk quartile was set as the reference group are indicated in Tables 4 and 5, respectively. EQuOR was 7.46 in the standard model and 7.82 in the logistic model.


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  		Table 2. Heart Valve Surgical Procedures in the Quartiles of Logistic EuroSCORE
 

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  		Table 3. Patient and Disease Characteristics According to Factors Used by EuroSCORE in the Quartiles of the Logistic Model
 


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  		Fig 1. Kaplan-Meier survival plots of the quartiles in all patients with heart valve surgery who were discharged alive from the hospital according to standard EuroSCORE. (EuroSCORE = European System for Cardiac Operative Risk Evaluation.)

 


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  		Fig 2. Kaplan-Meier survival plots of the quartiles in all patients with heart valve surgery who were discharged alive from the hospital according to logistic EuroSCORE. (EuroSCORE = European System for Cardiac Operative Risk Evaluation.)

 

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  		Table 4. Hazard Ratios of the Quartiles of Standard EuroSCORE
 
Furthermore, we estimated the 5-year survival rates of age quartiles (Fig 3) because mean age was different among EuroSCORE quartiles and we found that age was a significant predictor of long-term survival. The survival rates of age quartiles were 91.5% ± 2.0%, 78.5% ± 3.0%, 66.4% ± 3.3%, and 60.1% ± 3.4% (p < 0.0001, log-rank test with adjustment for trend) indicating that age alone is a strong predictor for long-term mortality among patients with a heart valve operation. However, EQuOR was 6.29 and this was lower when compared with standard or logistic EuroSCORE.



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  		Fig 3. Kaplan-Meier survival plots of age quartiles in all patients with heart valve surgery who were discharged alive from the hospital. (EuroSCORE = European System for Cardiac Operative Risk Evaluation.)

 

   Comment
Top
 Abstract
 Introduction
 Patients and methods
 Results
 Comment
References
 
Most predictive models in cardiac surgery use early mortality as an endpoint and most cardiac surgical registries follow patients only to the point of discharge from the hospital. However, it is well known that 30-day or in-hospital mortality is only one aspect of the periprocedural mortality [16]. Therefore, a sophisticated risk stratification system needs to consider also late outcomes [17]. The EuroSCORE, however, was developed to score the mortality during hospital stay after cardiac or heart valve surgery [6, 7]. In addition, large studies focused on risk stratification for heart valve surgery, they only evaluated early mortality as an endpoint [1–4]. Both early and late outcomes are important to consider and optimization of prognosis may require separate models, although simple models that cover both early and late outcomes would be attractive.

EuroSCORE works very well for early mortality and we showed in the present study that it also works very well for long-term mortality after heart valve surgery. We excluded in-hospital deaths to avoid results being influenced by operative mortality. This study evaluated the discriminatory ability of a preoperative risk stratification model in predicting long-term mortality after heart valve surgery. We also compared, for the first time in the same dataset, the discrimination of standard and logistic EuroSCORE model in predicting long-term mortality after heart valve surgery.

Patients at higher risk for early mortality according to EuroSCORE stratification continue to be at higher risk for long-term mortality in the whole context of heart valve surgery. There are reasons for estimating the risk of long-term mortality after heart valve surgery. These range from determination of indications for heart valve surgery, proper informed consent, quality monitoring of surgeons and institutions, as well as identification of patients in high risk for long-term mortality in order to have more frequent follow-up and to ensure that they receive the appropriate conservative therapy.

Both standard and logistic EuroSCORE can be considered as applicable models in predicting long-term mortality after heart valve surgery and the two models revealed similar discriminatory ability (EQuOR values were 7.46 and 7.82 for the standard and logistic EuroSCORE, respectively). In addition, we analyzed the effect of age in long-term survival, which is one of the factors utilized by EuroSCORE and there was a significant increase in mean age among EuroSCORE quartiles. We found that age alone was a strong predictor for long-term mortality in patients with heart valve surgery; however, its discriminatory ability as measured by EQuOR was lower compared with EuroSCORE models. The odds of death in the age highest-risk quartile was 6.29-fold higher than the odds of death in the lowest-risk quartile, indicating that age was the major contributor in the discriminatory ability of EuroSCORE models.

The EuroSCORE model is based on 17 preoperative risk factors and does not take into consideration possible negative intraoperative events such as prolonged cross-clamp time, cardiopulmonary bypass time, and requirement for mechanical support at the end of the procedure or major postoperative complications, which have been proved to be strong predictors for early and long-term mortality after heart valve surgery [5, 18]. However, EuroSCORE has been reported to have sufficient power to predict postoperative complications [19–21] after cardiac surgery and their effects on long-term mortality may be covered by EuroSCORE algorithm.

EuroSCORE is the best established and validated risk model for contemporary practice in cardiac surgery [22]. Recently, a study demonstrated that EuroSCORE could be correlated to costs of cardiac surgery [23] and postoperative complications [19–21], whereas we have demonstrated that both standard and logistic EuroSCORE can be used to predict long-term mortality after CABG [11]. The ability of a single model such as the standard EuroSCORE, which can be calculated at the bedside, to predict accurately all the above-mentioned outcomes renders it to a powerful tool in the every day clinical cardiac surgical practice both for the surgeon and the patient.

There are several limitations in our study. First, this is a retrospective investigation. Nevertheless, the collected information on preoperative, intraoperative, and postoperative factors has been performed prospectively with the highly standardized methods of the NYS audited database. Second, the NYS database used different variables than EuroSCORE and there were differences in definitions regarding neurological dysfunction, serum creatinine, and recent myocardial infarction. Third, this study refers to a single center regional database, thus the results need to be further evaluated for generalizability across diverse institutions and countries. Fourth, our intention was neither to develop a new score nor to investigate the impact of individual variables on long-term mortality after heart valve surgery. Fifth, we examined all-cause mortality and were unable to determine cause of death (cardiac or noncardiac). However, for practical purposes, prediction of overall mortality is probably more important than cardiac death alone. Finally, we did not evaluate other models than EuroSCORE in this study because other models such the Society of Thoracic Surgeons database has chosen not to publish its algorithms, while other models such the ACC/AHA guidelines include only CABG operations.

In conclusion, standard and logistic EuroSCORE can be used to predict long-term mortality after heart valve surgery and age alone is a strong predictor for long-term mortality, but with lower discriminatory ability compared to EuroSCORE algorithms. The standard EuroSCORE model may be useful for simple calculations at the bedside in the whole context of heart valve surgery. However, the development of a new model based on selected variables for long-term mortality may provide even better information for late-term prognosis.


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  		Table 5. Hazard Ratios of the Quartiles of Logistic EuroSCORE
 

   References
Top
 Abstract
 Introduction
 Patients and methods
 Results
 Comment
 References
 
  1. Edwards FH, Peterson ED, Coombs LP, et al. Prediction of operative mortality after valve replacement surgery J Am Coll Cardiol 2001;37:885-892.[Abstract/Free Full Text]
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  4. Nowicki ER, Birkmeyer NJ, Weintraub RW, et al. Multivariable prediction of in-hospital mortality associated with aortic and mitral valve surgery in Northern New England Ann Thorac Surg 2004;77:1966-1977.[Abstract/Free Full Text]
  5. Vesey JM, Otto CM. Complications of prosthetic heart valves Curr Cardiol Rep 2004;6:106-111.[Medline]
  6. Roques F, Nashef SA, Michel P, et al. Risk factors and outcome in European cardiac surgeryanalysis of the EuroSCORE multinational database of 19030 patients. Eur J Cardiothorac Surg 1999;15:816-822.[Abstract/Free Full Text]
  7. Roques F, Nashef SA, Michel P. Risk factors for early mortality after valve surgery in Europe in the 1990slessons from the EuroSCORE pilot program. J Heart Valve Dis 2001;10:572-577.[Medline]
  8. Nashef SA, Roques F, Michel P, Gauducheau E, Lemeshow S, Salamon R. European system for cardiac operative risk evaluation (EuroSCORE) Eur J Cardiothorac Surg 1999;16:9-13.[Abstract/Free Full Text]
  9. Nashef SA, Roques F, Hammill BG, et al. Validation of European System for Cardiac Operative Risk Evaluation (EuroSCORE) in North American cardiac surgery Eur J Cardiothorac Surg 2002;22:101-105.[Abstract/Free Full Text]
  10. Michel P, Roques F, Nashef SA. Logistic or additive EuroSCORE for high-risk patients? Eur J Cardiothorac Surg 2003;23:684-687.[Abstract/Free Full Text]
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