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Ann Thorac Surg 2004;77:1235-1239
© 2004 The Society of Thoracic Surgeons

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Original article: cardiovascular

Early mortality in coronary bypass surgery: the EuroSCORE versus The Society of Thoracic Surgeons risk algorithm

^a Department of Cardiothoracic Surgery, University Hospital, Lund, Sweden
^b Department of Cardiothoracic Anesthesiology, Heart and Lung Center, University Hospital, Lund, Sweden
^c Department of Clinical Pharmacology, University Hospital, Lund, Sweden

Accepted for publication August 28, 2003.

^* Address reprint requests to Dr Nilsson, Department of Cardiothoracic Surgery, Heart and Lung Center, University Hospital, SE 221 85 Lund, Sweden.
e-mail: johan.nilsson{at}thorax.lu.se

	Abstract

Top Abstract Introduction Material and methods Results Comment References

 
BACKGROUND: We compare two widely used risk algorithms for coronary bypass surgery: The European System for Cardiac Operative Risk Evaluation (EuroSCORE) and The Society of Thoracic Surgeons (STS) risk stratification algorithm.

METHODS: Risk factors for all adult patients undergoing heart surgery at the University Hospital of Lund between 1996 and 2001 were collected prospectively at preoperative admission. Predictive accuracy for 30-day mortality was assessed by comparing the observed and the expected mortality for equal-sized quintiles of risk by using the Hosmer-Lemeshow goodness-of-fit test. The discriminatory power was evaluated by calculating the areas under receiver operating characteristics (ROC) curves.

RESULTS: The study included 4497 coronary artery bypass-only operations. The average age was 66.4 ± 9.3 years (range 31 to 90 years). Most patients were men (77.0% versus 23.0%). The actual 30-day mortality was 1.89%. The Hosmer-Lemeshow goodness-of-fit test gave a p value of 0.81 (EuroSCORE) and 0.83 (STS), which indicates a good accuracy of both models. The area under the ROC curve was 0.84 (95% confidence interval [CI] 0.80 to 0.88) for EuroSCORE and 0.71 (95% CI 0.66 to 0.77) for STS. The discriminatory power (area under the ROC curve) was significantly larger for EuroSCORE compared with STS (p < 0.00005).

CONCLUSIONS: In this large, single institution study the additive EuroSCORE algorithm had a significantly better discriminatory power to predict 30-day mortality than the STS risk algorithm for patients undergoing coronary artery bypass.

	Introduction

Top Abstract Introduction Material and methods Results Comment References

 
Operative mortality is widely used as an indicator of the quality of cardiac surgery. To make an accurate comparison between different institutions or surgeons, mortality data must be adjusted to the risk profiles of the patients. During the last decades several models to calculate mortality risk before surgery have been developed. The European System for Cardiac Operative Risk Evaluation (EuroSCORE) has been constructed from a multinational European adult cardiac surgery database [1, 2] and has gained wide acceptance in Europe. The Society of Thoracic Surgeons (STS) National Adult Cardiac Database, which is the largest of its kind, has been used to develop an algorithm to predict operative mortality [3–5]. This risk stratification model is widely used in North America.

The accuracy and discriminatory ability of the EuroSCORE and the STS risk stratification algorithms have been compared with other statistical models [6–9]. To our knowledge, however, the EuroSCORE and STS algorithms have not been compared with each other.

The aim of this study was to determine the most suitable risk stratification model for coronary bypass surgery by applying these two algorithms to a local, large Swedish adult cardiac surgery database.

	Material and methods

Top Abstract Introduction Material and methods Results Comment References

 
Data
Risk factors for all adult patients undergoing heart surgery at the University Hospital of Lund between January 1, 1996, and February 28, 2001, were collected prospectively when the patients were admitted to the Department of Cardiothoracic Surgery. The patient record form contained a total of 248 variables (preoperative, perioperative, and postoperative) based on the Higgins [10], Parsonnet [11], and STS [3] patient record forms. The data were stored in a local adult cardiac surgery database. The study was approved by the Ethical Committee of the Medical Faculty, Lund University.

Twenty-six variables (Table 1) were imported into the commercially available STS risk stratification software (Summit Vista For Windows version 1.55, 1996, Summit Medical Systems, Nice, France) together with 30-day mortality for the coronary artery bypass (CAB)-only population. This database software calculated the risk score for every patient according to the STS Risk Stratification Analysis version 2.0 algorithm, which is based on the STS National Cardiac Surgery Database 1990 to 1993 CAB-only population [3] and the EuroSCORE additive algorithm [1].

Statistics
Values are given as mean ± SD. Logistic regression analysis was performed to determine the accuracy and the discrimination of the two risk algorithms on the operative mortality (death within 30 days of operation). Predictive accuracy was assessed by comparing the observed and the expected mortality for equal-sized quantiles of risk by using the Hosmer-Lemeshow goodness-of-fit test [12, 13].

The discriminatory power, ie, the c-index of the logistic regression model, was evaluated by calculating the areas under receiver operating characteristics (ROC) curves [14]. The areas under curves are presented with 95% confidence limits. An area of 1.0 under the ROC curve indicates perfect discrimination, whereas an area of 0.50 indicates complete absence of discrimination. Any intermediate value is a quantitative measure of the ability of the risk predictor model to distinguish between survivors and nonsurvivors [15].

To compare the areas under the two resulting ROC curves we used a nonparametric approach [16]. Graphs and statistical analyses were performed with Intercooled Stata (version 8.1, 2003 statistical package for Mac OS X, Stata Corporation).

	Results

Top Abstract Introduction Material and methods Results Comment References

 
Between January 1, 1996, and February 28, 2001, 4,497 CAB-only operations were performed on 4,487 patients. There was accurate documentation of vital status at 30 days in all cases, and no patient was lost to follow-up. Preoperative characteristics are listed in Table 1. The average age was 66.4 ± 9.3 years (range 31 to 90 years). Most patients were men (77.0% versus 23.0%).

The actual 30-day mortality was 1.89% (95% confidence interval [CI] 1.49% to 2.28%). The predicted versus observed mortality for each risk score are plotted in Figure 1 (EuroSCORE) and Figure 2 (STS).

View larger version (34K): [in this window] [in a new window]   Fig 1. Graph of predicted versus observed 30-day mortality (left y-axis) for each European System for Cardiac Operative Risk Evaluation (EuroSCORE) risk group. Predicted mortality (dotted line) with 95% confidence intervals (shadowed area); observed mortality () with 95% confidence intervals (vertical bars). The histogram shows the number of patients (right y-axis) in each risk group.

View larger version (27K): [in this window] [in a new window]   Fig 2. Graph of predicted versus observed 30-day mortality (left y-axis) for each Society of Thoracic Surgeons (STS) risk stratification algorithm risk group. Predicted mortality (dotted line) with 95% confidence intervals (shadowed area); observed mortality () with 95% confidence intervals (vertical bars). The histogram shows the number of patients (right y-axis) in each risk group.

View larger version (23K): [in this window] [in a new window]   Fig 3. The receiver operating characteristic curves: the sensitivity of prediction of 30-day mortality is plotted versus the 1−Specificity for the European System for Cardiac Operative Risk Evaluation (EuroSCORE) (•) and the Society of Thoracic Surgeons (STS) () risk stratification algorithm. The area under the curve for EuroSCORE is larger compared with STS. 2 (1 df) = 22.90; p < 0.00005. The solid line represents no discrimination.

	Comment

Top Abstract Introduction Material and methods Results Comment References

At higher risk scores the EuroSCORE predictive performance was less than at lower scores, as previously found by others [17]. The lower number of patients in these risk score groups might have contributed to this finding, but the finding may also reflect a weakness of the risk score algorithm.

The additive EuroSCORE model has been shown to work well across many European countries [18] and was recently tested on the STS database in North America with good results [19]. EuroSCORE performs well compared with other risk algorithms such as the Higgins, Parsonnet, and French Score [6, 7]. Most studies present an equal or better c-index, ie, the area under the ROC curve, for EuroSCORE compared with these other scoring systems. However, a comparison between the EuroSCORE and STS scoring systems has hitherto been lacking. The more complicated STS database algorithms remain proprietary and confidential, which could explain why only a few studies comparing the STS database algorithm with other risk algorithms have been published. In these studies the STS scoring system had a discriminatory power with a c-index about 0.7 (0.64 to 0.81) [8, 9], which is similar to our finding.

One limitation of our study is that the STS risk analysis algorithm is based on the STS results from the years 1990 to 1993 (version 2.0). The EuroSCORE algorithm was developed approximately 5 years later. We used a patient form constructed in our unit in 1996, 3 years before the EuroSCORE was officially published. For this reason, our definition of one of the risk variables was not identical to the definition from the original EuroSCORE publication, as preoperative myocardial infarction was defined to be present within 21 days before operation (STS definition) rather than within 3 months preoperatively (EuroSCORE definition).

October 1, 1999 (after publication of the EuroSCORE), a risk variable for preoperative myocardial infarction within 3 months was added to our database. To evaluate if the change of definition may have influenced our overall results, we performed separate calculations for the patients included in the database after this date (n = 1130), applying both definitions for preoperative myocardial infarction. The area under the ROC curve remained significantly larger for the EuroSCORE algorithms compared with STS, regardless of the definition of preoperative myocardial infarction used (0.83 using the 21-day definition versus 0.84 using the 3-month definition; p < 0.05 for both compared with the STS).

The prevalence of risk factors in patient referred for CAB-only surgery may change over time, and this may influence the predictive accuracy of different risk scoring systems [20]. Geographical differences in patient risk factors may also occur. Importantly, our findings are based on patients treated in a single European institution. It would be of interest to perform a similar comparative study on a current material of North American patients.

The strength of the present study is that the EuroSCORE and the STS algorithms could be compared on a relatively large patient population, in which patient data were collected on a regular basis during the daily clinical work. The data were entered preoperatively into the database, generally by residents and not by the surgeon performing the operation.

During the last few decades at least 15 different cardiac surgery risk score algorithms have been published, but it still remains difficult to predict risk for individual patients. This is illustrated in Figures 1 and 2. At the higher risk score groups, with few patients, the mortality prediction has a wider confidence interval, and the observed mortality diverges from the prediction line. One method to improve the risk algorithm could be to include more patients with higher risk scores. Thus larger international cardiac surgery databases, as suggested by Wyse and Taylor [21], may produce a risk algorithm with a discriminatory power of the 30-day mortality superior to the present systems. Another method could be to use a more complex risk model, such as the EuroSCORE logistic model. The EuroSCORE study group has published the coefficients for their logistic model [22] with the aim of producing more accurate predictions for small subgroups, and compare mortality results of individual centers with the average result from 128 surgical units in Europe.

Recently, a study demonstrated that EuroSCORE could be correlated to costs of cardiac surgery [23]. Preoperative risk algorithms able to accurately predict the need for hospital resources and cost of care would be desirable. Such algorithms could be used to plan the optimal schedule for surgery, moderate the postoperative workload in the intensive care unit, and rationally allocate and save hospital resources.

This study tested the risk algorithms on CAB-only patients, as the STS algorithm version 2.0 was constructed for this specific patient category. Most other studies in this field have also been conducted with CAB-only patients. Even if most risk algorithms are developed to be used on this patient group, application to other cardiac surgical patients would merit further study.

	References

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This Article Abstract Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Add to Personal Folders Download to citation manager Author home page(s): Johan Nilsson Johan Brandt Permission Requests Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Nilsson, J. Articles by Brandt, J. Search for Related Content PubMed PubMed Citation Articles by Nilsson, J. Articles by Brandt, J. Related Collections Professional affairs