Intra-institutional prediction of outcome after cardiac surgery: comparison between a locally derived model and the EuroSCORE

EuroScore and IL-6 predict the course in ICU after cardiac surgery

BACKGROUND

Despite modern advances in intensive care medicine and surgical techniques, mortality rates in cardiac surgical patients are still about 3%. Considerable efforts were made to predict morbidity and mortality after cardiac surgery. In this study, we analysed the predictive properties of EuroScore and IL-6 for mortality in ICU, prolonged postoperative mechanical ventilation, and prolonged stay in ICU.

METHODS

We enrolled 2972 patients undergoing cardiac surgery. The patients either underwent aortic valve surgery (AV), mitral valve surgery (MV), coronary artery bypass grafting (CABG), and combined operations of aortic valve and coronary artery bypass grafting (AV + CABG) or of mitral and tricuspid valve (MV + TV). Different laboratory and clinical parameters were analysed.

RESULTS

EuroScore as well as IL-6 were associated with increased mortality after cardiac surgery. Furthermore, a higher EuroScore and elevated levels of IL-6 were predictors for prolonged mechanical ventilation and a longer stay in ICU. Especially, highly significant elevated IL-6 levels and an increased EuroScore showed a strong association. Statistics suggested superiority when both parameters were combined in a single model.

CONCLUSION

Our results suggest that EuroScore and IL-6 are helpful in predicting the course in ICU after cardiac surgery, and therefore, the use of intensive care resources. Especially, the combination of highly elevated levels of IL-6 and EuroScore may prove to be excellent predictors for an unfortunate postoperative course in ICU.

Scoring Systems for Risk Stratification in Patients Undergoing Cardiac Surgery

Cardiac surgery is associated with significant mortality rates. Careful selection of surgical candidates is, therefore, vital to optimize morbidity and mortality outcomes. Risk scores can be used to inform this decision-making process. The European System for Cardiac Operative Risk Evaluation Score and the Society of Thoracic Surgeons score are among the most commonly used risk scores. There are many other scoring systems in existence; however, no perfect scoring system exists, therefore, additional research is needed as clinicians strive toward a more idealized risk stratification model. The purpose of this review is to discuss the advantages and limitations of some of the most commonly used risk stratification systems and use this to determine what an ideal scoring system might look like. This includes not only the generalizability of available scores but also their ease of use and predictive power.

Impaired right ventricular ejection fraction after cardiac surgery is associated with a complicated ICU stay

Background

Right ventricular (RV) dysfunction is a known risk factor for increased mortality in cardiac surgery. However, the association between RV performance and ICU morbidity is largely unknown.

Methods

We performed a single-centre, retrospective study including cardiac surgery patients equipped with a pulmonary artery catheter, enabling continuous right ventricular ejection fraction (RVEF) measurements. Primary endpoint of our study was ICU morbidity (as determined by ICU length of stay, duration of mechanical ventilation, usage of inotropic drugs and fluids, and kidney dysfunction) in relation to RVEF. Patients were divided into three groups according to their RVEF; < 20%, 20-30%, and > 30%.

Results

We included 1109 patients. Patients with a RVEF < 20% had a significantly longer stay in ICU, a longer duration of mechanical ventilation, higher fluid balance, a higher incidence of inotropic drug usage, and more increase in postoperative creatinine levels in comparison to the other subgroups. In a multivariate analysis, RVEF was independently associated with increased ICU length of stay (OR 0.934 CI 0.908-0.961, p < 0.001), prolonged duration of mechanical ventilation (OR 0.969, CI 0.942-0.998, p = 0.033), usage of inotropic drugs (OR 0.944, CI 0.917-0.971, p < 0.001), and increase in creatinine (OR 0.962, CI 0.934-0.991, p = 0.011).

Conclusions

A decreased RVEF is independently associated with a complicated ICU stay.

External Validation of European System for Cardiac Operative Risk Evaluation II (EuroSCORE II) for Risk Prioritization in an Iranian Population

INTRODUCTION

The European System for Cardiac Operative Risk Evaluation II (EuroSCORE II) is a prediction model which maps 18 predictors to a 30-day post-operative risk of death concentrating on accurate stratification of candidate patients for cardiac surgery.

OBJECTIVE

The objective of this study was to determine the performance of the EuroSCORE II risk-analysis predictions among patients who underwent heart surgeries in one area of Iran.

METHODS

A retrospective cohort study was conducted to collect the required variables for all consecutive patients who underwent heart surgeries at Emam Reza hospital, Northeast Iran between 2014 and 2015. Univariate and multivariate analysis were performed to identify covariates which significantly contribute to higher EuroSCORE II in our population. External validation was performed by comparing the real and expected mortality using area under the receiver operating characteristic curve (AUC) for discrimination assessment. Also, Brier Score and Hosmer-Lemeshow goodness-of-fit test were used to show the overall performance and calibration level, respectively.

RESULTS

Two thousand five hundred eight one (59.6% males) were included. The observed mortality rate was 3.3%, but EuroSCORE II had a prediction of 4.7%. Although the overall performance was acceptable (Brier score=0.047), the model showed poor discriminatory power by AUC=0.667 (sensitivity=61.90, and specificity=66.24) and calibration (Hosmer-Lemeshow test, P<0.01).

CONCLUSION

Our study showed that the EuroSCORE II discrimination power is less than optimal for outcome prediction and less accurate for resource allocation programs. It highlights the need for recalibration of this risk stratification tool aiming to improve post cardiac surgery outcome predictions in Iran.

A pragmatic approach for mortality prediction after surgery in infective endocarditis: optimizing and refining EuroSCORE

OBJECTIVE

To simplify and optimize the ability of EuroSCORE I and II to predict early mortality after surgery for infective endocarditis (IE).

METHODS

Multicentre retrospective study (n = 775). Simplified scores, eliminating irrelevant variables, and new specific scores, adding specific IE variables, were created. The performance of the original, recalibrated and specific EuroSCOREs was assessed by Brier score, C-statistic and calibration plot in bootstrap samples. The Net Reclassification Index was quantified.

RESULTS

Recalibrated scores including age, previous cardiac surgery, critical preoperative state, New York Heart Association >I, and emergent surgery (EuroSCORE I and II); renal failure and pulmonary hypertension (EuroSCORE I); and urgent surgery (EuroSCORE II) performed better than the original EuroSCOREs (Brier original and recalibrated: EuroSCORE I: 0.1770 and 0.1667; EuroSCORE II: 0.2307 and 0.1680). Performance improved with the addition of fistula, staphylococci and mitral location (EuroSCORE I and II) (Brier specific: EuroSCORE I 0.1587, EuroSCORE II 0.1592). Discrimination improved in specific models (C-statistic original, recalibrated and specific: EuroSCORE I: 0.7340, 0.7471 and 0.7728; EuroSCORE II: 0.7442, 0.7423 and 0.7700). Calibration improved in both EuroSCORE I models (intercept 0.295, slope 0.829 (original); intercept -0.094, slope 0.888 (recalibrated); intercept -0.059, slope 0.925 (specific)) but only in specific EuroSCORE II model (intercept 2.554, slope 1.114 (original); intercept -0.260, slope 0.703 (recalibrated); intercept -0.053, slope 0.930 (specific)). Net Reclassification Index was 5.1% and 20.3% for the specific EuroSCORE I and II.

CONCLUSIONS

The use of simplified EuroSCORE I and EuroSCORE II models in IE with the addition of specific variables may lead to simpler and more accurate models.

Prognostic value of hypoalbuminemia for adverse outcomes in patients with rheumatic heart disease undergoing valve replacement surgery

High-risk patients with rheumatic heart disease (RHD) who were undergoing valve replacement surgery (VRS) were not identified entirely. This study included 1782 consecutive patients with RHD who were undergoing VRS to explore the relationship between hypoalbuminemia and adverse outcomes and to confirm whether hypoalbuminemia plays a role in risk evaluation. A total of 27.3% of the RHD patients had hypoalbuminemia. In-hospital deaths were significantly higher in the hypoalbuminemic group than in the non-hypoalbuminemic group (6.6% vs 3.1%, P = 0.001). Hypoalbuminemia was an independent predictor of in-hospital death (OR = 1.89, P = 0.014), even after adjusting for the Euro score. The addition of hypoalbuminemia to Euro score enhanced net reclassification improvement (0.346 for in-hospital death, P = 0.004; 0.306 for 1-year death, p = 0.005). A Kaplan-Meier curve analysis revealed that the cumulative rate of 1-year mortality after the operation was higher in patients with a new Euro score ≥6. These findings indicated that hypoalbuminemia was an independent risk factor for in-hospital and 1-year mortality after VRS in patients with RHD, which might have additive prognostic value to Euro score.

Evaluation of Quality Of Life after Cardiac Surgery in High-Risk Patients

<p><b>Background:</b> Conventionally, there is controversy over subjecting high-risk patients to cardiac operations, due to major postoperative complications. Higher survival rates and less morbidity as well as better quality of life can be good predictors of the outcome of surgery. This study evaluates the quality of life before and 12 months after cardiac operations on high-risk patients.</p><p><b>Methods:</b> In this study, the European System for Cardiac Operative Risk Evaluation (EuroSCORE) II was used to separate high-risk patients from others. The quality of life was assessed using the Medical Outcomes Study 36-item Short Form Health Survey (SF-36) before surgery and one year afterward. Based on SF-36, the score for each of the eight different dimensions of the quality of life was quantified; and, their differences between pre-surgery and post-follow up period were analyzed.</p><p><b>Results:</b> 126 high-risk patients were included in this study. The mean age of the patients was 64.29 � 12.35 years. The median of EuroSCORE II score in these cases was 6.83 (6.04-25.98). The results reveal that the majority of the quality of life dimensions, except mental health, improved significantly after the follow-up period.</p><p><b>Conclusion:</b> Cardiac surgery on high-risk patients can noticeably promote the different aspects of their quality of life; although, such improvements should be considered against surgical complications.</p>

EuroSCORE and neutrophil adhesion molecules predict outcome post-cardiac surgery

BACKGROUND

This study tested the hypothesis that surgical stress and the host response to this trauma trigger an inflammatory cascade in which the neutrophil plays a central role. We hypothesised that pre-operative neutrophil migratory responses will correlate with post-operative clinical outcome in our shock model of open-heart surgery patients. We also tested the hypothesis that surface expression of adhesion molecules involved in the migratory process - CD11b, CD47 and CD99 - could be used to predict outcome. We believe that combining neutrophil migratory response, CD11b, CD47 and CD99 with the logistic European System for Cardiac Operative Risk Evaluation (EuroSCORE) will strengthen the power of the EuroSCORE not only in predicting post-operative mortality but also other clinical endpoints.

MATERIALS AND METHODS

Neutrophils were isolated pre-operatively from n = 31 patients undergoing open-heart surgery and allowed to migrate across endothelial monolayers in response to N-formyl-methionine-leucine-phenylalanine (fMLP). Isolated neutrophils were also assessed for surface expression of CD11b, CD47 and CD99 in response to fMLP by flow cytometry. Post-operative clinical parameters collected included days 1-5 white cell count and creatinine levels as well as intensive care unit (ICU) and post-operative hospital stay.

RESULTS

Pre-operative surface expression of CD99 and CD47 correlates with post-operative creatinine levels (P < 0·05), a measurement of renal injury. We also show that while the logistic EuroSCORE alone can be used as a predictor of ICU stay, when combined with pre-operative CD99 surface expression, it improves its AUC value (0·794).

CONCLUSION

Immunological markers, specifically the ability of the neutrophil to migrate, combined with the logistic EuroSCORE lead to improved sensitivity and specificity to predict patient outcome.

Length of intensive care unit stay following cardiac surgery: is it impossible to find a universal prediction model?

OBJECTIVES

Accurate models for prediction of a prolonged intensive care unit (ICU) stay following cardiac surgery may be developed using Cox proportional hazards regression. Our aims were to develop a preoperative and intraoperative model to predict the length of the ICU stay and to compare our models with published risk models, including the EuroSCORE II.

METHODS

Models were developed using data from all patients undergoing cardiac surgery at St. Olavs Hospital, Trondheim, Norway from 2000-2007 (n = 4994). Internal validation and calibration were performed by bootstrapping. Discrimination was assessed by areas under the receiver operating characteristics curves and calibration for the published logistic regression models with the Hosmer-Lemeshow test.

RESULTS

Despite a diverse risk profile, 93.7% of the patients had an ICU stay <2 days, in keeping with our fast-track regimen. Our models showed good calibration and excellent discrimination for prediction of a prolonged stay of more than 2, 5 or 7 days. Discrimination by the EuroSCORE II and other published models was good, but calibration was poor (Hosmer-Lemeshow test: P < 0.0001), probably due to the short ICU stays of almost all our patients. None of the models were useful for prediction of ICU stay in individual patients because most patients in all risk categories of all models had short ICU stays (75th percentiles: 1 day).

CONCLUSIONS

A universal model for prediction of ICU stay may be difficult to develop, as the distribution of length of stay may depend on both medical factors and institutional policies governing ICU discharge.

Performance of the original EuroSCORE

The European system for cardiac operative risk evaluation (EuroSCORE) is a commonly used risk score for operative mortality following cardiac surgery. We aimed to conduct a systematic review of the performance of the additive and logistic EuroSCORE. A literature search resulted in 67 articles. Studies applying the EuroSCORE on patients undergoing cardiac surgery and which reported early mortality were included. Weighted meta-regression showed that the EuroSCORE overestimated mortality. However, this performance depended on the risk profile of patients: in high-risk patients, the additive model actually underestimated mortality. Discriminative performance was good. Given the poor predictive performance, the EuroSCORE may not be suitable as a tool for patient selection nor for benchmarking.

Computerized prediction of intensive care unit discharge after cardiac surgery: development and validation of a Gaussian processes model

Background

The intensive care unit (ICU) length of stay (LOS) of patients undergoing cardiac surgery may vary considerably, and is often difficult to predict within the first hours after admission. The early clinical evolution of a cardiac surgery patient might be predictive for his LOS. The purpose of the present study was to develop a predictive model for ICU discharge after non-emergency cardiac surgery, by analyzing the first 4 hours of data in the computerized medical record of these patients with Gaussian processes (GP), a machine learning technique.

Methods

Non-interventional study. Predictive modeling, separate development (n = 461) and validation (n = 499) cohort. GP models were developed to predict the probability of ICU discharge the day after surgery (classification task), and to predict the day of ICU discharge as a discrete variable (regression task). GP predictions were compared with predictions by EuroSCORE, nurses and physicians. The classification task was evaluated using aROC for discrimination, and Brier Score, Brier Score Scaled, and Hosmer-Lemeshow test for calibration. The regression task was evaluated by comparing median actual and predicted discharge, loss penalty function (LPF) ((actual-predicted)/actual) and calculating root mean squared relative errors (RMSRE).

Results

Median (P25-P75) ICU length of stay was 3 (2-5) days. For classification, the GP model showed an aROC of 0.758 which was significantly higher than the predictions by nurses, but not better than EuroSCORE and physicians. The GP had the best calibration, with a Brier Score of 0.179 and Hosmer-Lemeshow p-value of 0.382. For regression, GP had the highest proportion of patients with a correctly predicted day of discharge (40%), which was significantly better than the EuroSCORE (p < 0.001) and nurses (p = 0.044) but equivalent to physicians. GP had the lowest RMSRE (0.408) of all predictive models.

Conclusions

A GP model that uses PDMS data of the first 4 hours after admission in the ICU of scheduled adult cardiac surgery patients was able to predict discharge from the ICU as a classification as well as a regression task. The GP model demonstrated a significantly better discriminative power than the EuroSCORE and the ICU nurses, and at least as good as predictions done by ICU physicians. The GP model was the only well calibrated model.

Predicting prolonged intensive care unit stays in older cardiac surgery patients: a validation study

PURPOSE

In cardiac surgery prediction models identifying patients at risk of prolonged stay at the Intensive Care Unit (ICU) are used to optimize treatment and use of ICU resources. A recent systematic validation study of 14 of these models identified three models with a good predictive performance across patients of all ages. It is however unclear how these models perform in older patients, who nowadays form a considerable part of this patient population. The current study specifically validates the performance of these three models in older cardiac surgery patients and quantifies how their performance changes with increasing age of patients.

METHODS

The Parsonnet model, the EuroSCORE, and a model by Huijskes and colleagues were validated using prospectively collected data of 11,395 cardiac surgery patients. Performance of the models was described by discrimination (area under the ROC curve, AUC) and calibration.

RESULTS

For the Parsonnet model, the EuroSCORE and the Huijskes model discrimination clearly decreased with increasing age (AUCs of 0.76, 0.71 and 0.72 for ages 70-75 and 0.72, 0.70 and 0.72, respectively, for ages 75-80 and 0.68, 0.64 and 0.69, respectively, above 80 years). The models showed poor calibration in patients aged >70 (p values for fit of the models <0.006).

CONCLUSIONS

To optimize treatment and ICU resources, risk prediction for prolonged ICU stay after cardiac surgery using the existing models should be done with great care for older patients.

Prediction models for prolonged intensive care unit stay after cardiac surgery: systematic review and validation study

BACKGROUND

Several models have been developed to predict prolonged stay in the intensive care unit (ICU) after cardiac surgery. However, no extensive quantitative validation of these models has yet been conducted. This study sought to identify and validate existing prediction models for prolonged ICU length of stay after cardiac surgery.

METHODS AND RESULTS

After a systematic review of the literature, the identified models were applied on a large registry database comprising 11 395 cardiac surgical interventions. The probabilities of prolonged ICU length of stay based on the models were compared with the actual outcome to assess the discrimination and calibration performance of the models. Literature review identified 20 models, of which 14 could be included. Of the 6 models for the general cardiac surgery population, the Parsonnet model showed the best discrimination (area under the receiver operating characteristic curve=0.75 [95% confidence interval, 0.73 to 0.76]), followed by the European system for cardiac operative risk evaluation (EuroSCORE) (0.71 [0.70 to 0.72]) and a model by Huijskes and colleagues (0.71 [0.70 to 0.73]). Most of the models showed good calibration.

CONCLUSIONS

In this validation of prediction models for prolonged ICU length of stay, 2 widely implemented models (Parsonnet, EuroSCORE), although originally designed for prediction of mortality, were superior in identifying patients with prolonged ICU length of stay.

Gastrointestinal complications after cardiac surgery - improved risk stratification using a new scoring model

Gastrointestinal (GI) complications are serious consequences of cardiac surgery. The aim of this study was to develop, evaluate and validate a new risk score model for GI complications after cardiac surgery. The risk score model, named gastrointestinal complication score (GICS), was developed using prospectively collected data from 5593 patients who underwent 5636 cardiac surgical procedures between 1996 and 2001. The model was validated on 1031 cardiac surgery patients between 2005 and 2006. The scoring system's ability to predict GI complications was estimated by receiver operating characteristic (ROC)-curves and Hosmer-Lemeshow test. Fifty GI complications were identified in 47 patients (0.8%) in the developmental data set and eight (0.8%) in the validation data set. The ROC area in the developmental data set was 0.81 with a good calibration estimated by Hosmer-Lemeshow test (P=0.89). In the validation data set, the area under the curve was 0.83. The estimated probability for the patient to develop a GI complication after cardiac surgery at a GICS >or=15 is >20% and at a GICS <or=5 is <0.4%. Risk stratification according to GICS, specifically developed to predict GI complications after cardiac surgery, showed a good predictive ability.

A comparative analysis of predictive models of morbidity in intensive care unit after cardiac surgery - part I: model planning

Background

Different methods have recently been proposed for predicting morbidity in intensive care units (ICU). The aim of the present study was to critically review a number of approaches for developing models capable of estimating the probability of morbidity in ICU after heart surgery. The study is divided into two parts. In this first part, popular models used to estimate the probability of class membership are grouped into distinct categories according to their underlying mathematical principles. Modelling techniques and intrinsic strengths and weaknesses of each model are analysed and discussed from a theoretical point of view, in consideration of clinical applications.

Methods

Models based on Bayes rule, k-nearest neighbour algorithm, logistic regression, scoring systems and artificial neural networks are investigated. Key issues for model design are described. The mathematical treatment of some aspects of model structure is also included for readers interested in developing models, though a full understanding of mathematical relationships is not necessary if the reader is only interested in perceiving the practical meaning of model assumptions, weaknesses and strengths from a user point of view.

Results

Scoring systems are very attractive due to their simplicity of use, although this may undermine their predictive capacity. Logistic regression models are trustworthy tools, although they suffer from the principal limitations of most regression procedures. Bayesian models seem to be a good compromise between complexity and predictive performance, but model recalibration is generally necessary. k-nearest neighbour may be a valid non parametric technique, though computational cost and the need for large data storage are major weaknesses of this approach. Artificial neural networks have intrinsic advantages with respect to common statistical models, though the training process may be problematical.

Conclusion

Knowledge of model assumptions and the theoretical strengths and weaknesses of different approaches are fundamental for designing models for estimating the probability of morbidity after heart surgery. However, a rational choice also requires evaluation and comparison of actual performances of locally-developed competitive models in the clinical scenario to obtain satisfactory agreement between local needs and model response. In the second part of this study the above predictive models will therefore be tested on real data acquired in a specialized ICU.

Relation of the Sequential Organ Failure Assessment Score to Morbidity and Mortality After Cardiac Surgery

BACKGROUND

Organ dysfunction evaluation using Sequential Organ Failure Assessment (SOFA) has been shown to predict mortality and morbidity in adult cardiac surgical patients with prolonged recovery. The purpose of this study was to evaluate the utility of SOFA in prediction of mortality and morbidity in a cohort of heterogeneous consecutive adult cardiac surgical patients.

METHODS

A prospective study of 857 consecutive patients entering in a single cardiac postoperative intensive care unit was assigned during the year 2004. The European System for Cardiac Operative Risk Evaluation (EuroSCORE) of each patient was assessed preoperatively. SOFA was calculated daily until intensive care unit discharge or for a maximum of 7 days. SOFA change between the first and the third postoperative day, maximum SOFA during the first 3 days, and maximal SOFA were calculated. Length of intensive care unit stay and 30-day mortality were assessed.

RESULTS

Maximum SOFA during the first 3 days and maximal SOFA-predicted 30-day mortality (area under the curve, 0.763 and 0.779, respectively) also correlated with the length of intensive care unit stay (p < 0.001 and p < 0.001, respectively). The EuroSCORE predicted both mortality and intensive care unit stay (p < 0.0001 and p < 0.0001). The correlation coefficient between the EuroSCORE and maximum SOFA during the first 3 days or maximal SOFA was low (r = 0.34 and 0.33, respectively, p < 0.0001 and p = 0.0001).

CONCLUSIONS

The SOFA score is an independent predictor of mortality and length of stay in cardiac surgical patients. The SOFA score is associated with mortality and morbidity even when assessed in the early postoperative period after adult cardiac surgery.

Risk Evaluation of Cardiac Surgery in Octogenarians

OBJECTIVE

To assess the predictive value of risk factors in the European System for Cardiac Operative Risk Evaluation (EuroSCORE) for cardiac surgery on octogenarians.

DESIGN

An observational study of octogenarians undergoing cardiac surgery and average-aged controls matched according to the cardiac surgical procedure.

SETTING

A university hospital.

PARTICIPANTS

One hundred sixty-two consecutive patients 80 years or older who underwent cardiac surgery between January 1, 2001, and June 30, 2003, and 162 average-aged controls.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Risk factors according to the EuroSCORE (The European System for Cardiac Risk Evaluation) model and EuroScore algorithm without an age component (EuroSCOREex) were evaluated. The EuroSCORE model and EuroSCOREex predicted mortality (odds ratio 1.4) and morbidity (odds ratio 1.2 and 1.3, respectively) equally well in both age groups. Adding age group information into the EuroSCOREex model in combined data, the odds ratio estimate was 3.5 for age group. The 30-day mortality of octogenarians was 8.6% versus 1.9% in controls (p < 0.01). Incidences of organ-related complications were comparable. Octogenarians spent more days in the hospital's intensive care unit and surgical ward than did controls (3.4 +/- 3.3 days v 2.7 +/- 3.1 days, p < 0.01; 9.9 +/- 5.8 days v 8.6 +/- 3.8 days, p = 0.02). Only 31 (19.1%) octogenarians were discharged home, whereas the corresponding number was 66 (40.7%) in controls (p < 0.01).

CONCLUSIONS

Risk factors other than age were not higher in octogenarians, and the EuroSCORE model predicted mortality and morbidity. Age was an important single risk factor predicting mortality.

A multivariate Bayesian model for assessing morbidity after coronary artery surgery

Introduction

Although most risk-stratification scores are derived from preoperative patient variables, there are several intraoperative and postoperative variables that can influence prognosis. Higgins and colleagues previously evaluated the contribution of preoperative, intraoperative and postoperative predictors to the outcome. We developed a Bayes linear model to discriminate morbidity risk after coronary artery bypass grafting and compared it with three different score models: the Higgins' original scoring system, derived from the patient's status on admission to the intensive care unit (ICU), and two models designed and customized to our patient population.

Methods

We analyzed 88 operative risk factors; 1,090 consecutive adult patients who underwent coronary artery bypass grafting were studied. Training and testing data sets of 740 patients and 350 patients, respectively, were used. A stepwise approach enabled selection of an optimal subset of predictor variables. Model discrimination was assessed by receiver operating characteristic (ROC) curves, whereas calibration was measured using the Hosmer-Lemeshow goodness-of-fit test.

Results

A set of 12 preoperative, intraoperative and postoperative predictor variables was identified for the Bayes linear model. Bayes and locally customized score models fitted according to the Hosmer-Lemeshow test. However, the comparison between the areas under the ROC curve proved that the Bayes linear classifier had a significantly higher discrimination capacity than the score models. Calibration and discrimination were both much worse with Higgins' original scoring system.

Conclusion

Most prediction rules use sequential numerical risk scoring to quantify prognosis and are an advanced form of audit. Score models are very attractive tools because their application in routine clinical practice is simple. If locally customized, they also predict patient morbidity in an acceptable manner. The Bayesian model seems to be a feasible alternative. It has better discrimination and can be tailored more easily to individual institutions.

Does EuroSCORE predict length of stay and specific postoperative complications after coronary artery bypass grafting?

BACKGROUND

To evaluate the performance of EuroSCORE in the prediction of in-hospital postoperative length of stay and specific major postoperative complications after coronary artery bypass grafting (CABG).

METHODS

Data on 3760 consecutive patients with CABG were prospectively collected. The EuroSCORE model (standard and logistic) was used to predict in-hospital mortality, prolonged length of stay (>12 days) and major postoperative complications (stroke, myocardial infarction, sternal infection, bleeding, sepsis and/or endocarditis, gastrointestinal complications, renal and respiratory failure). A C statistic (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 2.7%, and 13.7% of patients had one or more major complications. EuroSCORE showed very good discriminatory ability in predicting renal failure (C statistic: 0.80) and good discriminatory ability in predicting in-hospital mortality (C statistic: 0.75), sepsis and/or endocarditis (C statistic: 0.72) and prolonged length of stay (C statistic: 0.71). There were no differences in terms of the discriminatory ability between standard and logistic EuroSCORE. Standard EuroSCORE showed good calibration (Hosmer-Lemeshow: P>0.05) in predicting these outcomes except for postoperative length of stay, while logistic EuroSCORE showed good calibration only in predicting renal failure.

CONCLUSIONS

EuroSCORE can be used to predict not only in-hospital mortality, for which it was originally designed, but also prolonged length of stay and specific postoperative complications such as renal failure and sepsis and/or endocarditis after CABG. These outcomes can be predicted accurately using the standard EuroSCORE which is very simple and easy in its calculation.

Validation of Euroscore model in an Australian patient population

BACKGROUND

The purpose of the present paper was to assess the performance of the European system for cardiac operative risk evaluation (EuroSCORE) model in an Australian adult cardiac surgical population.

METHODS

The additive and logistic EuroSCORE models were retrospectively applied to predict operative mortality in 2106 consecutive patients undergoing cardiac surgery at St Vincent's Hospital, Melbourne between June 2001 and August 2003, and at Geelong Hospital between June 2001 and April 2004. The entire cohort and a subset of patients undergoing isolated coronary artery bypass graft (CABG) surgery were analysed. Model discrimination and calibration was tested by determining the area under the receiver operating characteristic (ROC) curve and Hosmer-Lemeshow chi2, respectively.

RESULTS

There were significant differences in the prevalence of risk factors between the Australian and European cardiac surgical populations. There were 81 deaths (observed mortality 3.85%) in the entire cohort and 39 deaths in the isolated CABG group (observed mortality 2.60%). The EuroSCORE models overestimated mortality (entire cohort: additive predicted 5.75%, logistic predicted 9.93%; isolated CABG: additive predicted 4.87%, logistic predicted 7.71%). Discriminative power was very good for the entire cohort (area under ROC curve, 0.81 (additive) and 0.82 (logistic)). Calibration of both models was poor.

CONCLUSION

The additive and logistic EuroSCORE model of risk prediction was not validated in the present population of cardiac surgical patients. The models may not accurately predict outcomes of patients undergoing cardiac surgery in Australia.

Open lung ventilation improves functional residual capacity after extubation in cardiac surgery*

OBJECTIVE

After cardiac surgery, functional residual capacity (FRC) after extubation is reduced significantly. We hypothesized that ventilation according to the open lung concept (OLC) attenuates FRC reduction after extubation.

DESIGN

A prospective, single-center, randomized, controlled clinical study.

SETTING

Cardiothoracic operating room and intensive care unit of a university hospital.

PATIENTS

Sixty-nine patients scheduled for elective coronary artery bypass graft and/or valve surgery with cardiopulmonary bypass.

INTERVENTIONS

Before surgery, patients were randomly assigned to three groups: (1) conventional ventilation (CV); (2) OLC, started after arrival in the intensive care unit (late open lung); and (3) OLC, started directly after intubation (early open lung). In both OLC groups, recruitment maneuvers were applied until Pao2/Fio2 was >375 Torr (50 kPa). No recruitment maneuvers were applied in the CV group.

MEASUREMENTS AND MAIN RESULTS

FRC was measured preoperatively and 1, 3, and 5 days after extubation. Peripheral hemoglobin saturation (Spo2) was measured daily till the third day after extubation while the patient was breathing room air. Hypoxemia was defined by an Spo2 value < or =90%. Averaged over the 5 postoperative days, FRC was significantly higher in the early open lung group and tended to be higher in the late open lung group, in comparison with the CV group (mean +/- sem: CV, 1.8 +/- 0.1; late open lung,1.9 +/- 0.1; and early open lung, 2.2 +/- 0.1l). In the CV group, 37% of the patients were hypoxic on the third day after extubation, compared with none of the patients in both OLC groups.

CONCLUSIONS

After cardiac surgery, earlier application of OLC resulted in a significantly higher FRC and fewer episodes of hypoxemia than with CV after extubation.

Coronary artery bypass surgery in high-risk patients

Background

In high-risk coronary artery bypass patients; off-pump versus on-pump surgical strategies still remain a matter of debate, regarding which method results in a lower incidence of perioperative mortality and morbidity. We describe our experience in the treatment of high-risk coronary artery patients and compare patients assigned to on-pump and off-pump surgery.

Methods

From March 2002 to July 2004, 86 patients with EuroSCOREs > 5 underwent myocardial revascularization with or without cardiopulmonary bypass. Patients were assigned to off-pump surgery (40) or on-pump surgery (46) based on coronary anatomy coupled with the likelihood of achieving complete revascularization.

Results

Those patients undergoing off-pump surgery had significantly poorer left ventricular function than those undergoing on-pump surgery (28.6 ± 5.8% vs. 40.5 ± 7.4%, respectively, p < 0.05) and also had higher Euroscore values (7.26 ± 1.4 vs. 12.1 ± 1.8, respectively, p < 0.05). Differences between the two groups were nonsignificant with regard to number of grafts per patient, mean duration of surgery, anesthesia and operating room time, length of stay intensive care unit (ICU) and rate of postoperative atrial fibrillation

Conclusion

Utilization of off-pump coronary artery bypass graft (CABG) does not confer significant clinical advantages in all high-risk patients. This review suggest that off-pump coronary revascularization may represent an alternative approach for treatment of patients with Euroscore ≥ 10 and left ventricular function ≤ 30%.

Canonical Correlation Analysis of Risk Factors and Clinical Outcomes in Cardiac Surgery

Assessment of the association between risk factors and outcomes in cardiac surgery is a complex problem. The aim of this study was to explore the relationship between possible risk factors and several clinical outcomes in cardiac surgery by using canonical correlation analysis (CCA). This retrospective study of 2605 consecutive adult patients who underwent cardiac surgery, evaluated 74 potential risk factors and up to 12 outcomes by canonical correlation analysis. For three serious outcomes, sternal wound complications/mediastinitis, cerebral complications, and perioperative myocardial infarctions, CCA was preceded by univariate analyses and backward stepwise multivariate logistic regression analyses. The CCA suggests that the major risk factors for complications in these models are intraoperative and postoperative risk factors. The power of risk prediction models developed with multivariate regression analysis can be enhanced by application of canonical correlation analysis, thereby offering new ways of analyzing and interpreting sets of potential risk factors in relation to sets of clinical outcomes.

EuroSCORE Predicts Long-Term Mortality After Heart Valve Surgery

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.

Substantial effective sample sizes were required for external validation studies of predictive logistic regression models

BACKGROUND AND OBJECTIVES

The performance of a prediction model is usually worse in external validation data compared to the development data. We aimed to determine at which effective sample sizes (i.e., number of events) relevant differences in model performance can be detected with adequate power.

METHODS

We used a logistic regression model to predict the probability that residual masses of patients treated for metastatic testicular cancer contained only benign tissue. We performed standard power calculations and Monte Carlo simulations to estimate the numbers of events that are required to detect several types of model invalidity with 80% power at the 5% significance level.

RESULTS

A validation sample with 111 events was required to detect that a model predicted too high probabilities, when predictions were on average 1.5 times too high on the odds scale. A decrease in discriminative ability of the model, indicated by a decrease in the c-statistic from 0.83 to 0.73, required 81 to 106 events, depending on the specific scenario.

CONCLUSION

We suggest a minimum of 100 events and 100 nonevents for external validation samples. Specific hypotheses may, however, require substantially higher effective sample sizes to obtain adequate power.

EuroSCORE Predicts Intensive Care Unit Stay and Costs of Open Heart Surgery

BACKGROUND

This study aimed to determine whether the preoperative risk stratification model EuroSCORE predicts the different components of resource utilization in open heart surgery.

METHODS

Data for all adult patients undergoing heart surgery at the University Hospital of Lund, Sweden, between 1999 and 2002 were prospectively collected. Costs were calculated for the surgery and intensive care and ward stay for each patient (excluding transplant cases and patients who died intraoperatively). Regression analysis was applied to evaluate the correlation between EuroSCORE and costs. The predictive accuracy for prolonged postoperative intensive care unit (ICU) stay was assessed by the Hosmer-Lemeshow goodness-of-fit test. The discriminatory power was evaluated by calculating the areas under receiver operating characteristics curves.

RESULTS

The study included 3,404 patients. The mean cost for the surgery was 7,300 dollars, in the ICU 3,746 dollars, and in the ward 3,500 dollars. Total cost was significantly correlated with EuroSCORE, with a correlation coefficient of 0.47 (p < 0.0001); the correlation coefficient was 0.31 for the surgery cost, 0.46 for the ICU cost, and 0.11 for the ward cost. The Hosmer-Lemeshow p value for EuroSCORE prediction of more than 2 days' stay in the ICU was 0.40, indicating good accuracy. The area under the receiver operating characteristics curve was 0.78. The probability of an ICU stay exceeding 2 days was more than 50% at a EuroSCORE of 14 or more.

CONCLUSIONS

In this single-institution study, the additive EuroSCORE algorithm could be used to predict ICU cost and also an ICU stay of more than 2 days after open heart surgery.

Emergency and elective coronary artery bypass grafting: comparisons of risk profiles, postoperative outcomes, and resource requirements

OBJECTIVE

To investigate the association between preoperative risk factors and postoperative outcomes in emergency and elective coronary artery bypass graft (CABG) patients and to quantify resource requirements.

DESIGN

Retrospective database review.

SETTING

New York State SPARCS database.

PARTICIPANTS

Data from 4,001 emergency and 7,489 elective CABG patients were evaluated retrospectively.

INTERVENTIONS

Data were compared between groups using chi-squares, t tests, and logistic regression analysis.

MEASUREMENTS AND MAIN RESULTS

Preoperatively, 47.1% of patients in the emergency group had unstable angina and 34.1% had acute myocardial infarction compared with 33.9% and 15.2% in the elective group, respectively (p < 0.0001). There were no marked differences in the preoperative noncardiac risk factors between groups. The mortality rate was 4.7% in the emergency group and 2.6% in the elective group (p < 0.0001). The emergency group had more postoperative cardiac complications (18.3% v 8.3%, p < 0.0001). The length of hospital stay in the emergency group was 17.5 +/- 15.8 days (median 14 days) compared with 12.9 +/- 15.1 days (median 9 days) in the elective group (p < 0.00001). Total hospital charges in the emergency and elective groups were 46,700 US dollars +/- 42,400 US dollars (median 35,600 US dollars ) and 34,800 US dollars +/- 36,400 US dollars (median 26,500 US dollars) (p < 0.00001), respectively. The median total cost was 26,300 US dollars for emergency and 19,600 US dollars for elective group (p < 0.00001).

CONCLUSION

Patients undergoing emergency CABG had greater postoperative morbidity and mortality, longer LOS, and higher total costs than patients undergoing elective surgery. This difference is predictable on the basis of preoperative cardiac risk factors. Emergency operations have a major impact on the rates of morbidity, mortality, and use of resources.

Evaluation of the quality of cardiovascular surgery care using risk stratification analysis according to the EuroSCORE additive model

Risk stratification according to the EuroSCORE additive model of 803 consecutive patients undergoing heart and thoracic aorta surgery using cardiopulmonary bypass from August 1994 to December 2000 was performed. The population was divided into 5 clinically relevant risk categories: 0-2% risk, 3-5% risk, 6-8% risk, 9-11% risk, and 12+% risk. Observed and predicted mortalities were compared within 3 groups of patients divided by year of operation (early: August 1994 to September 1996, n=260; middle: October 1996 to September 1998, n=259; late: October 1998 to December 2000, n=284). Overall hospital mortality was 4.5%; predicted mortality was 5.3% in the early, 5.1% in the middle, and 5.4% in the late period; observed mortality was 6.5%, 3.9%, and 3.2%, respectively (p=0.0024 in early vs late). In the early period, observed mortality was lower than predicted mortality in the 0-2% and 3-5% risk categories, but higher in the other categories. Moreover, observed mortality increased markedly with the increase in predicted mortality. In the late period, observed mortality was lower than predicted mortality in all 5 risk categories. The EuroSCORE is clinically relevant index for constructing a risk stratification scoring system for Japanese cardiovascular patients as well and shows that the quality of surgical care has improved gradually over the years.