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Eur J Cardiothorac Surg 2005;27:128-133
© 2005 Elsevier Science NL

Does EuroSCORE predict length of stay and specific postoperative complications after cardiac surgery?

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

Received 24 June 2004; received in revised form 22 September 2004; accepted 24 September 2004.

^* Corresponding author. Address: Department of Cardiothoracic Surgery, Columbia University College of Physicians and Surgeons, St Luke's-Roosevelt Hospital Center, 515 West 59th Street, New York, NY, USA. Tel.: +1 30 697 724 3942; fax: +1 646 365 6006. (E-mail: toumpoul{at}otenet.gr).

	Abstract

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

 
Objective: To evaluate the performance of EuroSCORE in the prediction of in-hospital postoperative length of stay and specific major postoperative complications after cardiac surgery. Methods: Data on 5051 consecutive patients (isolated [74.4%] or combined coronary artery bypass grafting [11.1%], valve surgery [12.0%] and thoracic aortic surgery [2.5%]) were prospectively collected. The EuroSCORE model (standard and logistic) was used to predict in-hospital mortality, 3-month mortality, prolonged length of stay (>12 days) and major postoperative complications (intraoperative stroke, stroke over 24h, postoperative myocardial infarction, deep sternal wound infection, re-exploration for bleeding, sepsis and/or endocarditis, gastrointestinal complications, postoperative renal failure and respiratory failure). A C statistic (or the area under the receiver operating characteristic curve) was used to test the discrimination of the EuroSCORE. The calibration of the model was assessed by the Hosmer–Lemeshow goodness-of-fit statistic. Results: In-hospital mortality was 3.9% and 16.1% of patients had one or more major complications. Standard EuroSCORE showed very good discriminatory ability and good calibration in predicting in-hospital mortality (C statistic: 0.76, Hosmer–Lemeshow: P=0.449) and postoperative renal failure (C statistic: 0.79, Hosmer–Lemeshow: P=0.089) and good discriminatory ability in predicting sepsis and/or endocarditis (C statistic: 0.74, Hosmer–Lemeshow: P=0.653), 3-month mortality (C statistic: 0.73, Hosmer–Lemeshow: P=0.097), prolonged length of stay (C statistic: 0.71, Hosmer–Lemeshow: P=0.051) and respiratory failure (C statistic: 0.71, Hosmer–Lemeshow: P=0.714). There were no differences in terms of the discriminatory ability in predicting these outcomes between standard and logistic EuroSCORE. However, logistic EuroSCORE showed no calibration (Hosmer–Lemeshow: P<0.05) except for sepsis and/or endocarditis (Hosmer–Lemeshow: P=0.078). EuroSCORE was unable to predict other major complications such as intraoperative stroke, stroke over 24h, postoperative myocardial infarction, deep sternal wound infection, gastrointestinal complications and re-exploration for bleeding. Conclusions: EuroSCORE can be used to predict not only in-hospital mortality, for which it was originally designed, but also 3-month mortality, prolonged length of stay and specific postoperative complications such as renal failure, sepsis and/or endocarditis and respiratory failure in the whole context of cardiac surgery. These outcomes can be predicted accurately using the standard EuroSCORE which is very simple and easy in its calculation.

Key Words: Cardiac surgery • EuroSCORE • Length of stay • Postoperative complications

	1. Introduction

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

 
Risk stratification plays an important role in cardiac surgical practice worldwide. Early mortality and morbidity have been the clinical outcomes to be assessed by many models [1–6], because their prediction is useful and range from helping determine the indications for surgery, estimate the need for resources, proper informed consent and quality monitoring of surgeons and institutions. The European System for Cardiac Operative Risk Evaluation (EuroSCORE) used logistic regression analysis to identify and give appropriate weight to various risk factors related to in-hospital mortality in adult cardiac operations [7]. Standard EuroSCORE was first introduced in 1999 [8] as an additive system and has gained wide acceptance in Europe [9], while it has also been validated in North America [10] and Japan [11]. Recently, the logistic algorithm became available [12] and it has been found to be a better risk predictor especially in high-risk patients [13]. The standard EuroSCORE model has also been evaluated in the prediction of direct costs in cardiac surgery [14], postoperative complications and postoperative length of stay [1,4–6] with various successes.

The purpose of the present study was to evaluate and compare the performance of standard and logistic EuroSCORE in the prediction of in-hospital mortality, 3-month mortality, prolonged postoperative length of stay and major postoperative complications in a series of 5051 consecutive patients with cardiac surgery at a single institution. In this study we evaluated major postoperative complications both as one variable as well as separate variables in order to test the performance of EuroSCORE in predicting specific complications.

	2. Methods

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

 
2.1. Patient population and data
Our study consisted of 5051 consecutive adult patients who underwent cardiac surgery between January 1992 and March 2002 at the St Luke's-Roosevelt Hospital Center affiliated with Columbia University. Registry databases were studied for pre, intra 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 adult cardiac surgery report. Risk stratification was performed according to the standard and logistic EuroSCORE model. Except for the variables utilized by the EuroSCORE model postoperative data was also collected and included 30-day mortality, in-hospital mortality, postoperative length of stay and major complications after surgery: stroke, transmural myocardial infarction, deep sternal wound infection, re-exploration for bleeding, sepsis and/or endocarditis, gastrointestinal complications, renal failure and respiratory failure.

Prolonged postoperative in-hospital length of stay (>12 days) was defined as exceeded the 75th centile of its distribution. Stroke was defined as intraoperative stroke when a permanent new focal neurological deficit was occurred intraoperatively to 24h postoperatively, while the neurological deficit was defined as stroke over 24h when occurred over 24h postoperatively. Transmural myocardial infarction was defined by the appearance of new Q waves on the electrocardiogram combined with a rise in CK-MB isoenzyme (>100µg/l). The diagnosis of deep sternal wound infection required at least one of the following criteria: (i) an organism was isolated from culture of mediastinal tissue or fluid; (ii) evidence of mediastinitis was seen during operation; or (iii) one of the following: chest pain, sternal instability, or fever (>38°C), was present and there was either purulent discharge from the mediastinum or an organism isolated from blood culture or culture of drainage of the mediastinal area. Return to the operating room within 36h postoperatively for reoperation to control bleeding or evacuate large hematomas in the thorax or pericardium was defined as re-exploration for bleeding. Sepsis and/or endocarditis was defined as fever (>38°C) and two or more positive blood cultures related to the procedure associated with systemic signs of infection but without intracardiac localization (sepsis) and two or more positive blood cultures with demonstrated valvular vegetation, or acute valvular dysfunction caused by infection (endocarditis). These two variables were considered as a single postoperative complication in the New York State adult cardiac surgery report. Gastrointestinal complications considered any postoperative episode, while still in the hospital, of vomiting blood, gross blood in the stool or perforation or necrosis of stomach or intestine. Postoperative renal failure was diagnosed in patients with normal renal function preoperatively who presented with creatinine >220µmol/l for more than 7 postoperative days or required temporary or permanent renal dialysis of any type. Finally, respiratory failure was diagnosed as pulmonary insufficiency requiring intubation and ventilation for a period of 72h or more, at any time during the postoperative stay, while for patients who are placed on and taken off ventilation several times, the total of these episodes should be 72h or more. All patients received postoperative follow-up care during their hospitalization and were routinely seen 4 weeks after discharge from the hospital. Therefore, all patients were subject to postdischarge surveillance with a minimum of 30 days of follow-up.

2.2. Data analysis
Three-month all-cause 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 [15]. 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% [15]. In this study we used only Social Security numbers, which were available in most patients (99.3%) and this allowed avoiding utilization of patients' names.

2.3. 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.

2.4. Statistical methods
Numerical variables were presented as mean±SD and discrete variables were summarized by percentages. A C statistic (or the area under the receiver operating characteristic curve) was used to assess the discriminatory ability of standard and logistic EuroSCORE model. The area under the receiver operating characteristic curve [16] was calculated as an index (C statistic) for how well the EuroSCORE could discriminate patients who lived and those who died or patients with a complication and those without this complication after cardiac surgery. The discriminative power of the model is thought excellent if the area under the receiver operating characteristic curve is >0.80, very good if >0.75 and good if >0.70 [17]. The calibration of the model was assessed by the Hosmer–Lemeshow goodness-of-fit statistic [18]. For the Hosmer–Lemeshow statistic, the predicted risks of individual patients were rank-ordered and divided into ten groups of roughly equal size, based on their predicted probability. Within each group of estimated risk, the number of predicted deaths (or complications) were accumulated against the number of observed deaths (or complications), a P>0.05 indicates acceptable calibration of the model. All analyses were performed in SPSS 11.0 (SPSS, Inc, Chicago, Ill) and P values are two-tailed.

	3. Results

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

 
A total of 5051 patients underwent cardiac surgery in our institution. Cardiac surgical procedures are shown in Table 1. The median standard EuroSCORE was 6 (interquartile range, 4–9) and the median logistic EuroSCORE was 6.46 (interquartile range, 3.13–15.05). The mean age (±SD) within the study sample was 64.4±11.3 years. Table 2 shows patient and disease characteristics according to the factors utilized by standard EuroSCORE after divided in six subgroups. There was an increase in mean age and a percentage increase in risk factors, other than isolated coronary artery bypass grafting procedures and in patients with lower ejection fraction as the risk stratification grows. In-hospital mortality was 3.9% (n=199), while in or out of hospital 30-day mortality was 4.4% (n=224) and 3-month mortality was 6.2% (n=315). The mean (±SD) postoperative in-hospital length of stay was 12.0±14.3 days and 16.1% (n=811) of patients had at least one major complication. Table 3 summarizes the early outcome after dividing the patients in six subgroups according to standard EuroSCORE. There was an increase in in-hospital mortality, postoperative length of stay, prolonged length of stay and major complications as the risk stratification grows.

View larger version (22K): [in this window] [in a new window]   Fig. 1. Receiver operating characteristic curves for postoperative renal failure. There is no difference in the area under the receiver operating characteristic curve between standard and logistic EuroSCORE.

	4. Discussion

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

 
Most predictive models in cardiac surgery use early mortality as an endpoint. Only a few models evaluate other relevant outcomes as morbidity and postoperative in-hospital length of stay or length of stay in the intensive care unit [2–6,19]. The EuroSCORE, however, was developed to score the mortality during hospital stay [7]. There are some studies which tested the accuracy of EuroSCORE in predicting postoperative morbidity after coronary artery bypass grafting [4] or cardiac surgery [5,6,20] with contradictory results, depending on the selected parameters. Because morbidity is comprised of heterogeneous parameters it appears to be difficult to find a model to predict overall postoperative complications. However, risk stratification and preoperative prediction of specific postoperative complications and prolonged length of stay appears to be desirable, especially when this can be performed by already widely used risk stratification models.

To our knowledge this is the first study in the literature which evaluates the discriminatory ability of a preoperative risk stratification model in predicting specific postoperative complications after cardiac surgery. We also compared for the first time in the same dataset the calibration of standard and logistic EuroSCORE model in predicting in-hospital mortality, 3-month mortality, prolonged postoperative length of stay and specific postoperative complications.

Despite substantial demographic differences between Europe and North America, EuroSCORE performs very well in the STS database [10] and this was confirmed in the present study, where the discriminatory ability of standard and logistic EuroSCORE in predicting in-hospital mortality (C statistic: 0.76 and 0.77, respectively) was very good. Other published studies have shown C statistics for standard EuroSCORE between 0.79 and 0.84 in patients with cardiac surgery [2,5,6,11,20], while in the original EuroSCORE database the C statistic was 0.78 and 0.79 for the standard and logistic model, respectively [13], indicating that there was no difference between the two models. We also confirmed this observation in the present study. However, we found that only standard EuroSCORE had a good calibration (P=0.449) when compared to logistic EuroSCORE (P<0.001). This was observed because logistic EuroSCORE was inaccurate in predicting in-hospital mortality in low and medium deciles of risk.

Both standard and logistic EuroSCORE can be considered as applicable models (C statistic 0.73 in both models) in predicting 3-month mortality and prolonged length of stay (>12 days, C statistic 0.71), but only standard EuroSCORE was well-calibrated (P=0.051). Both models were unable to predict patients with one or more major postoperative complications according to the definitions of the New York State adult cardiac surgery report. However, the EuroSCORE algorithms were qualified as applicable models in predicting postoperative renal failure (C statistic: 0.79 and 0.80 for the standard and logistic model), sepsis and/or endocarditis (C statistic 0.74 for both models) and respiratory failure (C statistic 0.71 for both models). None of the EuroSCORE models can be used for the prediction of intraoperative stroke, stroke over 24h, postoperative myocardial infarction, deep sternal wound infection, re-exploration for bleeding and gastrointestinal complications. 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, which have been proved to be strong predictors for postoperative morbidity after cardiac surgery [20]. On the other hand, some postoperative complications occurred in very small numbers (stroke over 24h, postoperative myocardial infarction and deep sternal wound infection) in our dataset and their incidence may be inadequate for receiver operating characteristic curve analysis and validation since 50 events are considered enough for these analyses [16,18].

EuroSCORE is overall the best-established and validated risk model for contemporary practice in cardiac surgery [21]. Recently, a study demonstrated that EuroSCORE could be correlated to costs of cardiac surgery, therefore it may be used to allocate and save hospital resources [14]. In addition, we have shown that both standard and logistic EuroSCORE can be used to predict long-term mortality after coronary artery bypass grafting [22] and the identification of high-risk patients for long-term mortality is very important in order to ensure that these patients will have more frequent follow-up. In the present study we clearly showed that EuroSCORE can be used to predict prolonged postoperative length of stay and postoperative renal failure, respiratory failure and sepsis and/or endocarditis. The preventing process for many postoperative complications starts with the stratification of patients into high and low-risk groups. Thus, the identification of high-risk patients for the development of the above devastating complications could help in their reduction by bringing the patient preoperatively to an optimal condition (renal function, appropriate antibiotic prophylaxis, chronic obstructive pulmonary disease) and by modifying the surgical procedure to achieve the highest benefit. 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 this study. First, this is a retrospective investigation. Nevertheless, the collected information on pre, intra and postoperative factors has been performed prospectively with the highly standardized methods of the New York State audited database. Second, this study refers to a single center regional database, thus the results need to be further evaluated for generalizability across diverse institutions and countries. Third, our intention was neither to develop a new score nor to investigate the impact of individual variables on prolonged length of stay and specific postoperative complications. It is known that for most risk factors the predictive value for mortality differs considerably from that for morbidity [6], while the inclusion of intraoperative parameters in a model could further increase its discriminatory ability [20].

In conclusion standard and logistic EuroSCORE can be used to predict in-hospital mortality and postoperative renal failure with a very good discriminatory ability as well as 3-month mortality, sepsis and/or endocarditis, prolonged postoperative length of stay (>12 days) and respiratory failure with a good discriminatory ability. However, only standard EuroSCORE model showed a good calibration in predicting these outcomes and this model may be useful for simple calculations at the bedside in the whole context of cardiac surgery.

	References

Top Abstract 1. Introduction 2. Methods 3. Results 4. Discussion 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): Daniel G. Swistel Joseph J. DeRose, Jr Permission Requests Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Toumpoulis, I. K. Articles by DeRose, J. J. Search for Related Content PubMed PubMed Citation Articles by Toumpoulis, I. K. Articles by DeRose, J. J., Jr Related Collections Cardiac - other