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Eur J Cardiothorac Surg 2006;29:441-446
© 2006 Elsevier Science NL

Validation of the EuroSCORE model in Australia

Cheng-Hon Yap a , 1 , * , Christopher Reid b , 1 , Michael Yii a , 1 , Michael A. Rowland c , 1 , Morteza Mohajeri d , 1 , Peter D. Skillington e , 1 , Siven Seevanayagam f , 1 , Julian A. Smith g , 1

a Department of Cardiothoracic Surgery, St Vincent's Hospital Melbourne, Melbourne, Australia
b Baker Heart Research Institute and CCRE Therapeutics, Monash University, Melbourne, Australia
c The Alfred Hospital, Melbourne, Australia
d The Geelong Hospital, Melbourne, Australia
e Royal Melbourne Hospital, Melbourne, Australia
f The Austin Hospital, Melbourne, Australia
g Monash Medical Centre, Melbourne, Australia

Received 2 November 2005; received in revised form 28 December 2005; accepted 29 December 2005.

* Corresponding author. Address: Department of Surgery, Geelong Hospital, Geelong, Vic. 3220, Australia. Tel.: +61 40201 5001; fax: +61 35226 7019. (Email: yapch{at}svhm.org.au).


   Abstract
Top
 Abstract
1. Introduction
 2. Methods
 3. Results
 4. Discussion
 References
 
Objective: There is an important role for accurate risk prediction models in current cardiac surgical practice. Such models enable benchmarking and allow surgeons and institutions to compare outcomes in a meaningful way. They can also be useful in the areas of surgical decision-making, preoperative informed consent, quality assurance and healthcare management. The aim of this study was to assess the performance of the European System for Cardiac Operative Risk Evaluation (EuroSCORE) model on the Australasian Society of Cardiac and Thoracic Surgeons (ASCTS) patient database. Methods: The additive and logistic EuroSCORE models were applied to all patients undergoing cardiac surgery at six institutions in the state of Victoria between 1st July 2001 and 4th July 2005 within the ASCTS database who have complete data. The entire cohort and a subgroup of patients undergoing coronary artery bypass grafting (CABG) only were analysed. Observed and predicted mortalities were compared. Model discrimination was tested by determining the area under the receiver operating characteristic (ROC) curve. Model calibration was tested by the Hosmer–Lemeshow chi-square test. Results: Eight thousand three hundred and thirty-one patients with complete data were analysed. There were significant differences in the prevalence of risk factors between the ASCTS and European cardiac surgical populations. Observed mortality was 3.20% overall and 2.00% for the CABG only group. The EuroSCORE models over estimated mortality (entire cohort: additive predicted 5.31%, logistic predicted 8.76%; CABG only: additive predicted 4.25%, logistic predicted 6.19%). Discriminative power of both models was very good. Area under ROC curve was 0.83 overall and 0.82 for the CABG only group. Calibration of both models was poor as mortality was over predicted at nearly all risk deciles. Hosmer–Lemeshow chi-square test returned P-values less than 0.05. Conclusions: The additive and logistic EuroSCORE does not accurately predict outcomes in this group of cardiac surgery patients from six Australian institutions. Hence, the use of the EuroSCORE models for risk prediction may not be appropriate in Australia. A model, which accurately predicts outcomes in Australian cardiac surgical patients, is required.

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


   1. Introduction
Top
 Abstract
 1. Introduction
2. Methods
 3. Results
 4. Discussion
 References
 
There is an important role for accurate risk prediction models in current cardiac surgical practice. Such models enable benchmarking and allow surgeons and institutions to compare outcomes in a meaningful way. They are also useful in the areas of surgical decision-making, preoperative informed consent, quality assurance and healthcare management [1]. The European System for Cardiac Operative Risk Evaluation (EuroSCORE), developed in 128 centres in eight European states [2], aims to predict 30-day mortality of patients undergoing cardiac surgery. It has been validated with good results in European, North American and Japanese populations [3–9]. It has also been used to predict other useful endpoints including long-term mortality [10], intensive-care unit stay [11], complications [12,13] and costs of cardiac surgery [11,14]. In the absence of a local model, the EuroSCORE is used for risk-adjustment in Australia [15].

Risk scoring systems are most applicable when the preoperative patient characteristics and treatment profiles are comparable with those on which the system was originated. For this reason any risk scoring system can only be used reliably when its validity has been tested in the local patient population [16]. A previously performed validation study of 2106 patients from two Australian cardiac surgical units [17] showed that the standard and logistic EuroSCORE models over predicted mortality. However, there was doubt as to whether the study was representative of cardiac surgery in Australia considering the small number of patients and institutions involved. Hence, in this study we aimed to validate the EuroSCORE model on a larger Australian cardiac surgical population by assessing the model within the Australian Society of Cardiac and Thoracic Surgeons (ASCTS) Cardiac Surgery Database.


   2. Methods
Top
 Abstract
 1. Introduction
 2. Methods
3. Results
 4. Discussion
 References
 
The ASCTS database project has prospectively collected data on patients undergoing cardiac surgery at all six publicly funded cardiac surgical units in the state of Victoria since July 2001 [18]. The ASCTS databases contained detailed information collected during the perioperative period on patient demographics, preoperative risk factors, operative details, postoperative hospital course and morbidity and mortality outcomes. This information was collected prospectively for all patients as part of clinical care and follow-up by surgeons, perfusionist, resident medical officers and database managers. Thirty-day mortality information was obtained by telephone contact with patient, family member or medical practitioner.

The development [2,19] and validation [4,6] of the EuroSCORE risk model has been previously described. The additive and logistic EuroSCORE models were applied to all patients undergoing cardiac surgery between 1st July 2001 and 4th July 2005 within the ASCTS database who have complete data. The database was searched for the information regarding relevant patient demographics, prevalence of risk factors, operative variables and mortality outcomes. Definitions of six risk factors in our database were not identical to the EuroSCORE definitions. However, a close approximation was achieved, comparable to that used in the Society of Thoracic Surgeons validation study [3]. Table 1 lists the risk factor definitions for comparison. The EuroSCORE standard additive algorithm [6] and logistic regression equation [19] were applied to determine the predicted additive (standard) and logistic EuroSCORE for the overall patient population (n = 8331), isolated coronary artery bypass graft (CABG) population (n = 5592) and risk tertiles. The outcome measured was operative mortality defined as death within 30 days from operation or later than 30 days if still in hospital.


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  		Table 1. Definitions of EuroSCORE model and Australian database
 
Statistical analysis was performed by chi-square test for categorical variables and Mann–Whitney test or unpaired t-test for continuous variables, as appropriate. P-values less than 0.05 were considered significant. Data acquisition was performed using Microsoft Access version 2000. Data analysis was performed using SPSS 11.5 statistical software package (SPSS Inc. Chicago, IL, USA).

Performance of the models was assessed by comparing the observed and predicted mortality figures with 95% confidence intervals. Model discrimination (statistical accuracy) and calibration (statistical precision) were analysed by determining the area under the receiver operating characteristic (ROC) curve [20] and Hosmer–Lemeshow goodness-of-fit statistic [21], respectively. The Hosmer–Lemeshow chi-square statistic measures the differences between expected and observed outcomes over deciles of risk. A well-calibrated model gives corresponding P-value greater than 0.05. Applicability of the models was further assessed by comparing the observed and expected mortality for risk tertiles. The thresholds were set to obtain approximately similar sized risk groups in the additive model.


   3. Results
Top
 Abstract
 1. Introduction
 2. Methods
 3. Results
4. Discussion
 References
 
There were significant differences between the Australian and European cardiac surgical populations. The frequency of risk factors in the two populations is shown in Table 2 . The Australian population was significantly older, with a mean age at time of surgery of 65.1 years and more than twice the proportion of patients over the age of 74 at time of surgery. Australian patients were more likely to have co-morbidities (chronic pulmonary disease, vascular disease chronic renal impairment and neurological disease) and cardiac-related risk factors (unstable angina, recent myocardial infarction and pulmonary hypertension) at the time of surgery. More Australian patients had severe left ventricular dysfunction and fewer had moderate left ventricular dysfunction. Australian patients were more likely to be in a ‘critical preop state’ or have isolated CABG. There were no significant differences in the prevalence of the risk factors female sex, previous cardiac surgery, active endocarditis, emergency surgery and acquired ventricular septal defect.


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  		Table 2. Prevalence of risk factors in the Australian and EuroSCORE populations
 
3.1 Entire cohort
Of the 8331 patients, there were 267 deaths observed, giving an overall observed mortality rate of 3.20%. The additive EuroSCORE model predicted a mortality rate of 5.31% (P < 0.001 vs observed) and the logistic EuroSCORE model predicted a mortality rate of 8.76% (P < 0.001 vs observed). This represents an over prediction of 66% for the additive model and 174% for the logistic model. Both models over estimated mortality at each risk tertile (Table 3 ). The discriminatory ability of both models was very good, with an area under the ROC curve of 0.83 in both models (Fig. 1 ). Model calibration, however, was poor. Both models over predicted deaths in all risk deciles except the additive model in the lowest and highest risk decile. Hosmer–Lemeshow chi-square goodness-of-fit statistic was 147 (additive) and 405 (logistic) with corresponding P-values less than 0.05.


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  		Table 3. Predicted and observed mortality by EuroSCORE risk level for whole cohort
 

Figure 1
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  		Fig. 1. Receiver operating characteristic (ROC) curves. Area under the curve is 0.83 for the additive and logistic EuroSCORE models when applied to the entire study cohort.

 
3.2 CABG only group
Of 5592 patients undergoing isolated CABG, there were 112 deaths observed, giving an observed mortality rate of 2.00%. The additive model over predicted a mortality rate of 4.25% and the logistic model 6.19% (both P < 0.001 vs observed). Both models over estimated mortality at each risk tertile (Table 4 ). Again the discriminatory ability of both models was very good; area under the ROC curve was 0.82 for both models. Model calibration was poor. Both models over predicted deaths in all risk deciles except the additive model in the lowest and highest risk decile. Hosmer–Lemeshow chi-square goodness-of-fit statistic was 91 (additive) and 196 (logistic) with corresponding P-values less than 0.05.


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  		Table 4. Predicted and observed mortality by EuroSCORE risk level for isolated CABG cohort
 

   4. Discussion
Top
 Abstract
 1. Introduction
 2. Methods
 3. Results
 4. Discussion
References
 
Risk prediction models play an important role in current cardiac surgical practice. They allow meaningful comparison of outcomes to be performed between institutions and surgeons by adjusting for differing case-mix. They also aid in surgical decision-making, preoperative patient education and consent, and quality assurance measures. The choices available to a surgical unit are to create a new model, recalibrate an existing model or use a ready-made model [16]. The former two options are impractical to most cardiac surgical units as they require comprehensive database management and accumulation of large patient numbers to allow creation or recalibration of a model. The use of a ready-made widely used model has the additional advantage of allowing meaningful comparisons to be made regionally and internationally. However, ready-made models may not accurately predict local outcomes and require validation prior to use [16].

We have shown, in this study of 8331 patients from six Australian cardiac surgical units, that the EuroSCORE models do not accurately predict outcomes in this group of patients. This is true of a mixed group of adult cardiac surgical patients as well as those undergoing isolated CABG. Both models over predicted outcomes, the logistic model more so than the additive model, at all risk tertiles. However, it is important to note that the discriminatory ability of the models were very good, with area under the ROC curve values of 0.82–0.83.

We obtained an identical definition match in 11 of the 17 EuroSCORE risk factors. A good approximation was achieved in the remaining six risk factors. The definition match used in this study was comparable to that used in the large North American (STS) validation study [3]. On this point the definition of ‘recent myocardial infarction’ (within 21 days in our study vs <90 days) and ‘moderate LV dysfunction’ (30–45% in our study vs 30–50%) if leading to a bias would underestimate mortality risk.

The reasons for the study results are unclear and likely to be multi-factorial. The epidemiology of ischaemic heart disease and co-morbid conditions in Australia may be different to that of the European population. This could be due to real differences in the prevalence of disease states. It is also likely to be artifactual due to the impact of good access to health care and the management of these conditions. For instance, the higher prevalence of ‘neurological disease’, ‘extracardiac arteriopathy’ and ‘chronic pulmonary disease’ may simply reflect better access to health care in a heavily government-subsidised healthcare system, and early and aggressive investigation and management of these diseases. Furthermore, with the now widespread use of serum troponin as a marker of myocyte necrosis, many more patients are being identified as having non-ST elevation myocardial infarction. Hence, the risk factor of ‘recent myocardial infarction’ does not distinguish between those with high creatinine kinase and troponin rise with its associated worse prognosis following cardiac surgery, from the many patients with mild troponin rises which carry little, if any, added operative risk. The provision of high-quality medical care with greater resource allocation leading to better outcomes, relative to the European validation population, may also contribute to the poor performance of the model. Lastly, it is important to note that the EuroSCORE was developed on data from patients in 1995 and may not reflect current cardiac surgical practice both in Australia and in Europe. For instance, on both continents patients are older and fitter due to decreased prevalence of smoking, increased attention placed on healthy lifestyles and improved medical treatment of cardiovascular diseases. Hence, the significant weight placed on increasing age in the EuroSCORE model may no longer be appropriate. There is a need for a European multi-centre revalidation of the EuroSCORE to establish its validity in today's cardiac surgical practice. Only then can we know whether the failure of the model in our study is likely to be due to factors unique to Australia or factors common to cardiac surgery worldwide.

The ASCTS cardiac surgical database has been collecting data on patients undergoing cardiac surgery in the state of Victoria, Australia, since 2001 [18]. The hospital databases are subjected to external audit and quality assurance measures. We believe the data accuracy to be high. The EuroSCORE model has been used as the risk-adjustment model in the interinstitutional comparisons of results within the ASCTS database. However, this may not be appropriate given our findings that the EuroSCORE over predicts outcomes. A local model from the ASCTS dataset has recently been developed [22], which will allow more accurate risk-adjusted comparisons to be performed between participating institutions. However, risk-adjusted comparisons of Australian results on the international level will remain problematic given the performance of the EuroSCORE models.

In conclusion, we could not validate the use of the additive or logistic EuroSCORE models on this multi-institution cohort of Australian adult cardiac surgical patients. The EuroSCORE models do not accurately predict outcomes in Australia. Thus, at present the EuroSCORE models should be used with caution for risk-adjustment or risk-prediction in Australia.


   Footnotes
 
{star} Presented at Australasian Society of Cardiac and Thoracic Society Annual Scientific Meeting, Noosa Heads, Queensland, Australia, 28th–30th October 2005.

1 On behalf of the ASCTS database surgeons. Back


   References
Top
 Abstract
 1. Introduction
 2. Methods
 3. Results
 4. Discussion
 References
 

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