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Eur J Cardiothorac Surg 2004;25:695-700
© 2004 Elsevier Science NL


Review

EuroSCORE: a systematic review of international performance

A. Gogbashiana*, A. Sedrakyana, T. Treasureb

a The Royal College of Surgeons of England, 35-43 Lincoln's Inn Fields, London WC2A 3PN, UK
b Department of Cardiothoracic Surgery, Guy's and St Thomas' Hospital NHS Trust, Guy's Hospital, St Thomas Street, London SE1 9RT, UK

Received 31 December 2003; received in revised form 13 February 2004; accepted 19 February 2004.

* Corresponding author. Tel./fax: +44-208-731-6176
e-mail: andrew{at}cardiacforum.com


    Abstract
 Top
 Abstract
 1. Introduction
 2. Materials and methods
 3. Results
 4. Discussion
 References
 
The validity of the cardiac surgical scoring system, EuroSCORE, has been assessed by several individual cardiac centres within and outside Europe. We chose to assess the overall international performance by systematic review of peer-reviewed literature. There were six studies meeting our criteria for assessment. Internationally, the evidence is highly suggestive that additive EuroSCORE performance generally over-estimates mortality at lower EuroSCOREs (EuroSCORE<=6) and under-estimates mortality at higher EuroSCOREs (EuroSCORE>13). The effect of this could have serious misrepresentations for surgeons and hospitals operating on differing case-mixes. We suggest that further studies need to be performed on the logistic EuroSCORE calculation to ascertain whether predictive ability is improved. Overall, however, EuroSCORE is the most rigorously evaluated scoring system in cardiac surgery.

Key Words: Cardiac surgery • EuroSCORE • Mortality • Risk stratification


    1. Introduction
 Top
 Abstract
 1. Introduction
 2. Materials and methods
 3. Results
 4. Discussion
 References
 
EuroSCORE is a prognostic scoring system developed in Europe for patients undergoing cardiac surgery [1]. Earlier scoring systems for predicting mortality in cardiac surgery include Parsonnet, The Cleveland Clinic coronary scoring system and the UK Society of Cardiothoracic Surgeons Risk Score [24]. These older scoring systems were developed from a single database of patients, the first two institutional and the third from a national database. There has been debate as to whether they can be generalised to other practices or other countries. Parsonnet was the founding father of systematic risk stratification [2] and the first to demonstrate that his method could be applied to European practice; Nashef and colleagues validated the method in Manchester, UK [5]. The principle was quickly adopted in UK practice [6] and incorporated in risk-adjusted CUSUM displays [7]. However, there has also been a question of whether the earlier systems were adequately objective [8] prompting a European scoring system based on explicit objective criteria.

1.1. The EuroSCORE
There was therefore an incentive to develop a more robust and objective scoring system to cover a wider population of cardiac surgical patients. EuroSCORE was derived from an European database of nearly 20,000 consecutive patients from 128 hospitals in eight European countries. Information on 97 risk factors was collected pre-operatively in all the patients. These risk factors were then compared to patient outcomes (survival or death). By means of logistic regression calculations, those risk factors that were robust in predicting mortality became part of the EuroSCORE calculation [9]. Two different scoring systems exist for the EuroSCORE. One is known as the additive model—a score that can be calculated by simple arithmetic—and the other known as the logistic model. The logistic model is more extensive and requires a computer to derive a score [10]. Since the EuroSCORE has been developed, it has been tested on several local populations around the world, including Europe, Japan, Scandinavia and the USA [1115].

1.2. Objective
There have been several individual centre studies as well as regional studies examining the effectiveness and validity of the EuroSCORE at a local level. We desired to undertake a review of overall international performance of EuroSCORE by assessing the available literature.


    2. Materials and methods
 Top
 Abstract
 1. Introduction
 2. Materials and methods
 3. Results
 4. Discussion
 References
 
2.1. Search strategy
Published studies, using the EuroSCORE as a means of risk stratification for patients undergoing cardiac surgery, were identified by searching Medline between 1/1966 and 8/2003; Embase between weeks 01/1980 and 34/2003; Current Contents between weeks 1/1993 and 35/2003. Search terms used for finding the articles were ‘Euroscore’, ‘Cardiac data’ and (cardi* or surg* or score*). Both English language and foreign language journals were searched. The references cited by these articles were then searched for further articles related to the EuroSCORE. Two of the authors searched independently and all authors participated in discussion of discrepancies.

2.2. Inclusion criteria
Only papers that included surgery on adult patients and reported findings based on prospectively collected data were included. Both the logistic calculation and the additive calculations of the EuroSCORE were accepted. Data were accepted regardless of the type of cardiac operation performed. Papers that separated patients into low and high-risk groups were accepted.

2.3. Exclusion criteria
Data from the original database by which the EuroSCORE was derived were excluded from the study. Also excluded were papers with identical or overlapping patient samples; studies that did not include a separation of their dataset into differing EuroSCORE risk groups; and articles from which we could not derive observed and predicted mortality.

2.4. Data extraction
Data were extracted directly from the text, tables and graphs from included papers. We attempted to get additional information from the authors by electronic mail to addresses cited in papers. Where the studies did not provide the full data required and the author did not provide the data by further correspondence we were unable to include them. Further data in addition to those provided in the original article were provided by Sergeant et al. [16]. In the study by Bridgewater et al. [17] data were extracted by reading off the axes of these graphs.


    3. Results
 Top
 Abstract
 1. Introduction
 2. Materials and methods
 3. Results
 4. Discussion
 References
 
3.1. Overview of included and excluded papers
Studies meeting the criteria can be found in Table 1.


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Table 1. Summary of reviewed studies

 
All six studies suitable for inclusion used the additive EuroSCORE calculation.

Table 2 shows the articles excluded from the systematic review and the reasons.


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Table 2. Summary of excluded studies

 
3.2. Observed and expected mortality
Table 3 summarises the observed and expected mortality of operations at various EuroSCORE sub-groups. The method of assimilating patients into EuroSCORE groups was particular to each study.


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Table 3. Results of observed and expected mortality

 
Only the article by Bridgewater et al. [17] contained data for ungrouped EuroSCOREs. Sergeant et al. [16] provided individual EuroSCORE data by further correspondence. All other authors assembled data within EuroSCORE groups, however, they did provide the groupings-predicted mortality as a percentage—in other words, the average EuroSCORE for the group. Observed mortality, as a percentage, was calculated from either the number of deaths quoted or a direct statement of percentage mortality from the studies.

Fig. 1 shows expected mortality (predicted EuroSCORE) plotted against observed–expected mortality% for each of the studies. If there is to be a good ‘match’ between observed and predicted mortality—an indicator that the EuroSCORE is predicting mortality accurately—the majority of points will cluster around 0 on the y-axis. Fig. 1 suggests (in this depiction there are no confidence intervals) that at EuroSCORE<=6 the additive EuroSCORE overestimates risk (expected is greater than observed) in several of studies. At EuroSCORE>=10, the overall appearance from the figure is that additive EuroSCORE underestimates risk.



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Fig. 1. Predicted additive EuroSCORE plotted against observed–predicted mortality %.

 
Table 4 summarises combined data from all six studies. Data were combined to provide an overall picture of EuroSCORE performance. At higher EuroSCORE percentages there are generally fewer numbers of patients in each individual study. We therefore started at the high-risk end creating groups of 100 or more patients, thus narrowing the confidence intervals (see Fig. 2) . Data at the very high end of EuroSCORE had to be merged into an EuroSCORE group of 11–24.


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Table 4. Combined data by weighted mean

 


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Fig. 2. Overall international performance: predicted additive EuroSCORE against observed mortality %.

 
Fig. 2 displays predicted mortality (EuroSCORE) on the x-axis against observed mortality (y-axis) for the combined data, with confidence intervals. The line of identity is where the points would fall for perfect prediction. This figure shows the significant over-estimation of additive EuroSCORE at lower predictions: EuroSCORE<=6. Additive EuroSCORE seems to overestimate risk above 13.


    4. Discussion
 Top
 Abstract
 1. Introduction
 2. Materials and methods
 3. Results
 4. Discussion
 References
 
There were large numbers of patients in all the articles reviewed at lower additive EuroSCORE predictions. The conclusion that EuroSCORE systematically over-estimates risk for these patients is therefore a robust finding which applies for all the studies representing five countries. It is therefore likely to be a universally true finding. In order to assess additive EuroSCORE performance at higher scores it was necessary to combine the data to produce significant numbers in order to produce a meaningful result. The conclusion is less certain but appears to be valid. Both Bridgewater et al. [17] and Sergeant et al. [16] have made this observation within their own data sets. What we have added is that this holds in all instances reported and when the data are pooled it becomes more certain. The consequence is that additive EuroSCORE is likely to be a little forgiving of high volume practice in low-risk patients. However, it has the effect of penalising the surgeon taking on high-risk cases. This is likely to be unimportant in a large mixed practice but will reflect adversely on the surgeon with a lower volume of routine cases and a relatively high proportion of unstable and higher risk patients. This was exactly the reason for Parsonnet introducing risk adjustment. The high-volume private USA practices of the 1980s reported operative mortality rates approaching zero which could not be matched by units with adverse case-mix or disadvantaged populations. The consequence is that the most deserving of patients, the ones where the difference between prospects without and with surgery are the greatest, may be deprived of the chance of surgery as surgeons protect their figures and their reputations.

Bridgewater's suggestion [17] is only to make comparison between surgeons and units for performance monitoring purposes at the lower risk end of the spectrum, the pros and cons of which he explores thoughtfully.

Michel et al. [10] suggest that the logistic EuroSCORE model will resolve this, a contention we have been unable to explore further because we have found insufficient reported data on which to test this. However, they base their assertion on data analysed by ROC curves. We agree with Sergeant et al. [16] that the ROC method merely balances the prediction errors at the low and high-risk ends. We prefer our more intuitively obvious and simpler display of how the risk model performs. ROC analysis is more complicated and more appropriate for the trade-off of sensitivity and specificity in setting a single threshold for a diagnostic test. In our view it may be misleading to regard EuroSCORE as a diagnostic test of death. Furthermore their own analysis shows very near identical ROC curves for additive and logistic EuroSCORE [10].

It may be argued that centres publishing their results within peer-reviewed literature may have overly favourable results, thus providing publication bias. However, centres that have published favourable mortality compared to predicted mortality by additive EuroSCORE within the same publication publish less favourable mortality rates at the higher predictions. This effect is reproducible in several of the studies and with large numbers of patients. We believe it is more likely that it is an inherent feature of additive EuroSCORE than publication bias.

In spite of these flaws EuroSCORE is overall the best-established and validated risk model for contemporary practice. However, it is important to continue to apply professional judgement and common sense in the interpretation of surgical results and to avoid making inappropriate comparisons that disadvantage both patient and surgeon.

4.1. Consideration for further research
From the systematic review performed there were no individual centre studies that calculated the logistic EuroSCORE from their patient data. New studies directly focusing on the logistic EuroSCORE could be started, however, former data from previous studies could still be utilised, as the input data for the required calculation is the same as for additive EuroSCORE. A systematic review could then be performed on the logistic EuroSCORE.


    References
 Top
 Abstract
 1. Introduction
 2. Materials and methods
 3. Results
 4. Discussion
 References
 

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NT-proBNP in cardiac surgery: a new tool for the management of our patients?
Interactive CardioVascular and Thoracic Surgery, June 1, 2005; 4(3): 242 - 247.
[Abstract] [Full Text] [PDF]


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Eur. J. Cardiothorac. Surg.Home page
I. K. Toumpoulis, C. E. Anagnostopoulos, D. G. Swistel, and J. J. DeRose Jr
Does EuroSCORE predict length of stay and specific postoperative complications after cardiac surgery?
Eur. J. Cardiothorac. Surg., January 1, 2005; 27(1): 128 - 133.
[Abstract] [Full Text] [PDF]


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Eur. J. Cardiothorac. Surg.Home page
B. Zingone, A. Pappalardo, and L. Dreas
Logistic versus additive EuroSCORE. A comparative assessment of the two models in an independent population sample
Eur. J. Cardiothorac. Surg., December 1, 2004; 26(6): 1134 - 1140.
[Abstract] [Full Text] [PDF]


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BMJHome page
T. Treasure
The learning curve
BMJ, August 21, 2004; 329(7463): 424 - 424.
[Full Text] [PDF]


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