Mortality risk prediction in coronary surgery: a locally developed model outperforms external risk models

This study aimed at assessing the performance of three external risk-adjusted models - logistic EuroSCORE, Parsonnet score and Ontario Province Risk (OPR) score - in predicting in-hospital mortality in patients submitted to coronary artery bypass graft (CABG) and to develop a local risk-score model. Data on 4567 patients who underwent isolated CABG (1992-2001) were extracted from our clinical database. Hospital mortality was 0.96% (44 patients). For the three external systems, observed and predicted mortalities were compared, and discrimination and calibration were assessed. A local risk model was developed and validated by means of logistic regression and bootstrap analysis. The EuroSCORE predicted a mortality of 2.34% (P<0.001 vs. observed), the Parsonnet 4.43% (P<0.0001) and the OPR 1.66% (P<0.005). All models overestimated mortality significantly in almost all tertile risk groups. The areas under the ROC curve (AUC) for EuroSCORE, Parsonnet and OPR were 0.754, 0.664 and 0.683, respectively. The local model exhibited good calibration and discrimination AUC, 0.752. In conclusion, the three risk-score systems analyzed do not accurately predict in-hospital mortality in our coronary surgery patients; hence their use for risk prediction may not be appropriate in our population. We developed a risk-prediction model that can be used as an instrument to provide accurate information about the risk of in-hospital mortality in our patient population.     

EuroSCORE Predicts Short- and Mid-Term Mortality in Combined Aortic Valve Replacement and Coronary Artery Bypass Patients

Abstract   Background and Aim of the Study: European system for cardiac operative risk evaluation (EuroSCORE) has been studied for its effectiveness in predicting operative mortality, and more recently, long-term mortality in a wide variety of cardiac surgical procedures. Combined coronary artery bypass and aortic valve replacement (AVR-CABG) carries increased perioperative risk, and tends to have higher-risk patients. Performance of the EuroSCORE system in patients undergoing concomitant AVR-CABG has not been well established. Thus, we aimed to analyze the accuracy of both additive and logistic EuroSCOREs in predicting operative and mid-term mortality. Methods: We retrospectively reviewed and calculated EuroSCOREs for all patients who underwent AVR-CABG between January 2000 and December 2004. Patients who had previous cardiac surgery and those undergoing any concomitant procedures were excluded. Areas under the receiver operator curves (ROC) were determined to assess EuroSCORE's accuracy in predicting operative mortality. Kaplan-Meier analysis and Cox regression were used to determine mid-term survival, freedom from repeat revascularization, and predictors of these outcomes. Results: There were 233 patients who met study criteria. Mean follow-up period was 2.2 ± 1.7 years with one patient lost to follow-up. Mean additive and logistic EuroSCOREs were 8.77 and 16.1, respectively, with an observed mortality of 9.44%. The area under the ROC curves for additive EuroSCORE was 0.76 and for logistic EuroSCORE was 0.75. Regression analysis revealed additive EuroSCORE, but not logistic EuroSCORE, to be predictive of mid-term mortality. Conclusions: Both additive and logistic EuroSCOREs were accurate in predicting operative morality. Only additive EuroSCORE was predictive of mid-term mortality in AVR-CABG patients. EuroSCORE remains a good and well-validated risk stratification model applicable to patients who undergo concomitant AVR-CABG.     

Risk stratification analysis of operative mortality in heart and thoracic aorta surgery: comparison between Parsonnet and EuroSCORE additive model.

OBJECTIVE: Our purpose was to compare the performance of risk stratification model between Parsonnet and European System for Cardiac Operative Risk Evaluation (EuroSCORE) in our patient database. METHODS: From August 1994 to December 2000, 803 consecutive patients have undergone heart and thoracic aorta surgery using cardiopulmonary bypass and scored according to Parsonnet and EuroSCORE algorithm. The population was divided into five clinically relevant risk categories. We compared correlation of predicted mortality and observed mortality between these two models. Score validity was assessed by calculating the area under the receiver operating characteristic (ROC) curve. RESULTS: Overall hospital mortality was 4.5%. In Parsonnet model, predicted mortality was 2.4% for 0-4% risk, 6.7% for 5-9% risk, 12% for 10-14% risk, 17% for 15-19% risk, 25% for 20% plus risk, and 10.4% for overall patients. Observed mortality was 2.4, 0.4, 5.9, 8.7, 11, and 4.5%, respectively. The thoracic aorta and valve cohort indicated poor correlation between predicted and observed mortality compared to coronary cohort. In the EuroSCORE model, predicted mortality was 1.4% for 0-2% risk, 4.0% for 3-5% risk, 6.7% for 6-8% risk, 9.7% for 9-11% risk, 13% for 12% plus risk, and 5.3% for overall patients. Actual mortality was 0, 1.5, 6.8, 11, 21, and 4.5%, respectively. Each of the thoracic aorta, valve, and coronary cohort indicated good correlation between predicted and observed mortality. Areas under the ROC curves were 0.72 in Parsonnet and 0.82 in EuroSCORE. CONCLUSIONS: The EuroSCORE additive model yielded good predictive value for hospital mortality of Japanese patients undergoing not only cardiac but also thoracic aortic surgery.     

Logistic or additive EuroSCORE for high-risk patients?

OBJECTIVES: To assess whether the use of the full logistic European System for Cardiac Operative Risk Evaluation (EuroSCORE) is superior to the standard additive EuroSCORE in predicting mortality in high-risk cardiac surgical patients. METHODS: Both the simple additive EuroSCORE and the full logistic EuroSCORE were applied to 14,799 cardiac surgical patients from across Europe, of whom there were 4293 high-risk patients (additive EuroSCORE of 6 or more). The systems were compared for absolute prediction and discrimination (area under the receiver operating characteristic (ROC) curve). RESULTS: Actual mortality was 4.72%. The logistic model was closer to this than the additive model (4.84% (4.72-4.94) versus 4.21 (4.21-4.26)). Most of this difference was due to high-risk patients where actual mortality was 11.18% and predicted was 7.83% (additive) and 11.23% (logistic). Discrimination was similar in both systems as measured by the area under the ROC curve (additive 0.783, logistic 0.785). CONCLUSIONS: The additive EuroSCORE model remains a simple "gold standard" for risk assessment in European cardiac surgery, usable at the bedside without complex calculations or information technology. The logistic model is a better risk predictor especially in high-risk patients and may be of interest to institutions engaged in the study and development of risk stratification.     

Additive and logistic EuroSCORE performance in high risk patients

We compared the performances of the additive and logistic EuroSCORE in predicting mortality in high-risk cardiac surgical patients, at a single institution. Both models were applied to 6535 patients, operated on at the Western Infirmary, Glasgow from March 1994 to August 2004. Calibration and discrimination were assessed using the Hosmer-Lemeshow [HL] Chi-square test and areas under the ROC curve. Overall mortality was 2.95%. Predicted mortalities were 4.1% [additive] and 5.2% [logistic]. Actual mortality was 0.6% in the low risk (additive EuroSCORE 1-2), 2.1% in the medium risk (EuroSCORE 3-5) and 7% in the high-risk groups (EuroSCORE 6 plus). Actual mortality increased beyond a predicted risk of 8-10%. At the low risks both systems slightly over-estimated mortality, with the logistic EuroSCORE being more accurate. At EuroSCOREs between 10-20, the additive EuroSCORE under-estimated risk, while the logistic EuroSCORE over-estimated mortality. Both systems were inaccurate at high risk. The HL statistics were 11.15 [P<0.64] for the additive and 37.78 [P<0.47] for the logistic models. ROC curve areas were 0.749+/-0.04 [additive] and 0.746+/-0.03 [logistic]. The additive EuroSCORE model remains a simple system for cardiac risk assessment. The logistic EuroSCORE was not more accurate even in high-risk patients.     

Assessment of validity for EuroSCORE risk stratification system

Prognostic scoring helps doctors, patients and their families to weigh the risks and benefits of medical care and clarifies their expectations. OBJECTIVE: We aimed to analyze the risk stratification performance of the EuroSCORE system because of its common use in Lithuania. DESIGN: EuroSCORE performance is assessed in terms of sensitivity, specificity, accuracy and area under the receiver operating characteristic (ROC) curve (AUC). Logistic regression is carried out for modeling categorical data and odds ratio calculations of being a non-survivor case for each EuroSCORE risk group. RESULTS: The study was completed on 1002 patients. Mean score for EuroSCORE was 4.77 +/- 2.8; ROC curve of 0.71; accuracy was 65.5%; 65.4% sensitivity and 67.2% specificity. CONCLUSIONS: EuroSCORE created a moderately predictive area under the ROC curve for our patient population. Probability of non-survival by logistic regression model for each EuroSCORE risk group is statistically significantly higher compared to the lower risk group. Predictions available from prognostic scoring systems could be useful in decision making when there is uncertainty in whether to carry out surgery or not.     

Validation of the EuroSCORE model in Australia.

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.     

Predicting adverse outcomes of cardiac surgery with the application of artificial neural networks

Risk-stratification models based on pre-operative patient and disease characteristics are useful for providing individual patients with an insight into the potential risk of complications and mortality, for aiding the clinical decision for surgery vs non-surgical therapy, and for comparing the quality of care between different surgeons or hospitals. Our study aimed to apply artificial neural networks (ANN) models to predict mortality and morbidity after cardiac surgery, and also to compare the efficacy of this model to that of the logistic regression model and Parsonnet score. The accuracy of the ANN, logistic regression and Parsonnet score in predicting mortality was 83.8%, 87.9% and 78.4%. The accuracy of the ANN, logistic regression and Parsonnet score in predicting major morbidity was 79.0%, 74.3% and 68.6%. The area under the receiver operating characteristic curves (AUC) of the ANN, logistic regression and Parsonnet score in predicting in-hospital mortality were 0.873, 0.852 and 0.829. The AUCs of the ANN, logistic regression and Parsonnet score in predicting major morbidity were 0.852, 0.789 and 0.727. The results showed the ANN models have the best discriminating power in predicting in-hospital mortality and morbidity among these models.     

不同心脏手术风险预测评分系统对中国冠状动脉旁路移植术后患者早期死亡的预测

目的 评价STS评分系统[the Society of Thoracic Surgeons(STS)2008 Cardiac Surgery Risk Models]、欧洲心脏手术风险评估系统(EuroSCORE)、Parsonnet评分系统和美国心脏病学院/美国心脏协会(American College of Car...     

EuroSCORE overestimates the cardiac operative risk

INTRODUCTION: It was the purpose of our study to assess the validity of EuroSCORE (European system for cardiac operative risk evaluation) in our patient population. MATERIALS AND METHODS: Between March 1999 and August 2001, information on risk factors and mortality was collected for 1123 consecutive adult patients undergoing heart surgery with cardiopulmonary bypass. EuroSCORE was used for risk stratification. Mean age +/- standard deviation was 58.6 +/- 10.9 and 29.1% of the patients were female. The area under the receiver operating characteristic (ROC) curve was calculated as an index for the predictive value of the scoring system. RESULTS: The area under the ROC curve was 0.824 for all patients and 0.828 for the isolated CABG subgroup which shows an excellent predictive ability.When the scoring system was applied in low, medium, and high risk groups, there was no overlap between 95% confidence intervals of observed and expected mortality in all three groups both for the isolated CABG cases and for all patients. Decreased left ventricular ejection fraction, emergent operation, and preoperative unstable angina requiring i.v. nitrate treatment were significant predictive variables for early mortality. CONCLUSION: EuroSCORE is a simple and objective system for predicting the risk of heart surgery. The predictive power of the EuroSCORE is excellent, however it seems that mortality is considerably overestimated by this score.     

EuroSCORE模型对心瓣膜手术患者死亡风险的预测

目的评价欧洲心脏手术风险评估系统（European System for Cardiac Operative Risk Evaluation,EuroSCORE）模型预测行心脏瓣膜手术患者在院死亡率的准确性。方法收集1998年1月至2008年12月于第二军医大学长海医院因心脏瓣膜疾病行外科治疗4 155例患者的临床资料,其中男1 955例,女2 200例;年龄45.90±13.64岁。先按additive及logistic EuroSCORE两种方法评分,将患者分为低风险（n=981）、中风险（n=2 492）、高风险（n=682）3个亚组,比较全组及各亚组患者的实际与预测死亡率。模型预测的校准度用Hosmer-Lemeshow卡方检验,预测的鉴别度采用受试者工作特征（receiver operating characteristic,ROC）曲线下面积检验。结果 4 155例患者在院死亡205例,实际在院死亡率4.93%;additive EuroSCORE预测死亡率为3.80%,而logisticEuroSCORE为3.30%;提示两种评分方法均低估了实际在院死亡率（χ2=11.13,44.34,P〈0.05）。additiveEuroSCORE对高风险亚组在院死亡预测校准度较高（χ2=3.61,P=0.31）,但对低风险亚组（χ2=0.00,P〈0.01）及中风险亚组（χ2=14.72,P〈0.01）较低;而logistic EuroSCORE对低风险亚组（χ2=1.66,P=0.88）及高风险亚组（χ2=11.71,P=0.11）在院死亡预测准确性均较高,却低估了中风险亚组（χ2=17.48,P〈0.01）的实际在院死亡率。两种评分方法对全组患者在院死亡预测的鉴别度均较差（ROC曲线下面积分别为0.676和0.677）。结论 EuroSCORE模型对本中心心瓣膜手术患者死亡风险预测的准确性较差,不适合本中心心瓣膜手术的风险预测,在今后的临床实践中应慎重使用。     

Inaccuracy of four coronary surgery risk-adjusted models to predict mortality in individual patients.

OBJECTIVES: This study was undertaken to evaluate the accuracy of four different risk-adjusted models in predicting mortality in individual patients who are undergoing coronary artery by-pass graft surgery. In the last decade several models to stratify patients before open heart surgery, according to factors affecting mortality, were developed with the aim of retrospectively comparing outcomes of open heart surgery, based on reliable stratification of case-mix, and of prospectively identifying high risk patients as a basis for a meaningful informed consent for patients counseling. METHODS: The pre-operative risk of death was calculated with four different models in 418 consecutive patients who underwent coronary artery by-pass surgery and then compared with the actual outcome. To discriminate patients with favorable and unfavorable outcome, the logistic regression analysis and the areas under the receiver-operating-characteristic curves were applied. The accuracy score was used to evaluate the reliability of each score to predict the individual outcome. RESULTS: Seven deaths (1.7%) were observed within 30 days from the operation, and the overall incidence was similar to that predicted by all models. Only the NBI score was not able to discriminate survivors from patients who will die, and the areas under the curves were 0.596 for the Parsonnet score, 0.861 for the Cleveland Clinic Foundation score, 0.823 for the French score, and 0.806 for the EuroSCORE. The four models were highly accurate (between 0.97 and 0.98) to predict the overall mortality. In seven patients who died the mean predictive scores were very low and ranged between 2.1 and 4.6, but were significantly higher than those of patients who survived (between 1.1 and 2.2). CONCLUSIONS: The four pre-surgical predictive models were similarly able to discriminate favorable vs. unfavorable outcomes and highly accurate to predict overall mortality, but very inaccurate to predict mortality in individual patients.     

非体外循环冠状动脉旁路移植术后早期死亡风险预测——SinoSCORE与EuroSCORE评分的对比

目的 比较中国冠状动脉旁路移植手术评分系统(SinoSCORE)和欧洲心脏外科手术风险评分系统(EuroSCORE)对中国人群非体外循环冠状动脉旁路移植(OPCAB)术后早期死亡风险的预测价值.方法 OPCAB病人资料来自中国心血管外科注册登记研究2004-2005年数据库,观察终点为术后院内死亡.分别用SinoSCORE和logistic EuroSCORE两种模型计算病人预计病死率,并与实际病死率比较.校准度采用Hosmer-Lemeshow拟合优度检验,利用 ROC曲线下面积(AUC)评价模型的区分度.结果 4920例病人中73例发生院内死亡,实际病死率1.48%,SinoSCORE模型和EuroSCORE模型预测的病死率分别为2.73%、4.13%.SinoSCORE模型Hosmer-Lemeshow拟合优度检验P=0.636,AUC=0.794;EuroSCORE模型Hosmer-Lemeshowrny拟合优度检验P=0.01,AUC=0.756.SinoSCORE和logistic EuroSCORE两种模型的区分度均较好,但SinoSCORE的校准度明显优于后者,即两种模型均能预测术后死亡,但SinoSCORE对术后病死率的预测更加准确.结论 SinoSCORE模型比EuroSCORE模型更适用于中国非体外循环冠状动脉旁路移植病人术后早期死亡预测.     

Assessment of validity for EuroSCORE risk stratification system

Prognostic scoring helps doctors, patients and their families to weigh the risks and benefits of medical care and clarifies their expectations.

Objective We aimed to analyze the risk stratification performance of the EuroSCORE system because of its common use in Lithuania.

Design EuroSCORE performance is assessed in terms of sensitivity, specificity, accuracy and area under the receiver operating characteristic (ROC) curve (AUC). Logistic regression is carried out for modeling categorical data and odds ratio calculations of being a non-survivor case for each EuroSCORE risk group.

Results The study was completed on 1002 patients. Mean score for EuroSCORE was 4.77±2.8; ROC curve of 0.71; accuracy was 65.5%; 65.4% sensitivity and 67.2% specificity.

Conclusions EuroSCORE created a moderately predictive area under the ROC curve for our patient population. Probability of non-survival by logistic regression model for each EuroSCORE risk group is statistically significantly higher compared to the lower risk group. Predictions available from prognostic scoring systems could be useful in decision making when there is uncertainty in whether to carry out surgery or not.     

Performance of three preoperative risk indices; CABDEAL, EuroSCORE and Cleveland models in a prospective coronary bypass database.

OBJECTIVES: The aim of the present study was to evaluate the performance of three different preoperative risk models in the prediction of postoperative morbidity and mortality in coronary artery bypass (CAB) surgery. METHODS: Data on 1132 consecutive CAB patients were prospectively collected, including preoperative risk factors and postoperative morbidity and in-hospital mortality. The preoperative risk models CABDEAL, EuroSCORE and Cleveland model were used to predict morbidity and mortality. A C statistic (receiver operating characteristic (ROC) curve) was used to test the discrimination of these models. RESULTS: The area under the ROC curve for morbidity was 0.772 for the CABDEAL, 0.694 for the EuroSCORE and 0.686 for the Cleveland model. Major morbidity due to postoperative complications occurred in 268 patients (23.6%). The mortality rate was 3.4% (n=38 patients). The ROC curve areas for prediction of mortality were 0.711 for the CABDEAL, 0.826 for the EuroSCORE and 0.858 for the Cleveland model. CONCLUSIONS: The CABDEAL model was initially developed for the prediction of major morbidity. Thus, it is not surprising that this model evinced the highest predictive value for increased morbidity in this database. Both the Cleveland and the EuroSCORE models were better predictive of mortality. These results have implications for the selection of risk indices for different purposes. The simple additive CABDEAL model can be used as a hand-held model for preoperative estimation of patients' risk of postoperative morbidity, while the EuroSCORE and Cleveland models are to be preferred for the prediction of mortality in a large patient sample.     

Prospective comparison of POSSUM and P-POSSUM with clinical assessment of mortality following emergency surgery

BACKGROUND: Tools to accurately estimate the risk of death following emergency surgery are useful adjuncts to informed consent and clinical decisions. This prospective study compared the Physiological and Operative Severity Score for the Enumeration of Mortality and Morbidity (POSSUM) and Portsmouth POSSUM (P-POSSUM) scoring systems with clinical judgement in predicting mortality from emergency surgery. METHODS: Data were collected prospectively from 163 patients. Details of the physiological and operative severity scores were recorded for POSSUM and P-POSSUM. The estimates of both the surgeon and anaesthetist for 30-day and in-hospital mortality were also recorded pre-operatively. The accuracies of the four predictions were then compared with actual mortalities using linear and exponential analysis and receiver operator characteristics (ROC). RESULTS: P-POSSUM gave the most accurate prediction of 30-day mortality using linear analysis [observed to expected ratio (O : E) = 1.0]. POSSUM gave the most accurate prediction using exponential analysis (O : E = 1.15). Clinical judgement of mortality from both operating surgeons and anaesthetists compared favourably with the scoring systems for 30-day mortality (O : E = 0.83 and O : E = 0.93, respectively). ROC analyses showed both clinical judgement and the POSSUM scores to be good predictors of 30-day mortality with area under the curve values (AUC) of 0.903, 0.907, 0.946 and 0.940 for surgeons, anaesthetists, POSSUM and P-POSSUM respectively. CONCLUSIONS: POSSUM and P-POSSUM appear to be useful indicators for the prediction of mortality. Clinical judgement compares strongly with scoring systems in predicting post-operative mortality, but may underestimate mortality in very high-risk patients with more than 90% mortality.     

Thirty-day and one-year predictors of death in noncardiac major surgical procedures

BACKGROUND: We evaluated the predictive value of the American College of Cardiology/American Heart Association (ACC/AHA) cardiac risk classification, as well as other potential risk factors (procedure risk, smoking, obesity, hyperlipidemia, and renal insufficiency), on all-cause mortality at 30 days and at 1 year postoperatively. METHODS: In the year 2000, 1238 consecutive patients undergoing general anesthesia for various noncardiac surgical procedures at the Houston Veterans Affairs Medical Center were screened preoperatively and classified according to the ACC/AHA guidelines. Patients' charts were reviewed for the above-mentioned risk factors. RESULTS: A logistic regression analysis demonstrated that older age and higher procedure risk were associated with higher 30-day mortalities (P = 0.0012 and 0.0441, respectively). The ACC/AHA classification was positively correlated with mortality at 1 year (P = 0.0071). CONCLUSIONS: The ACC/AHA classification predicts mortality at 1 year but not at 30 days for major noncardiac surgeries; procedure-related risk is a better predictor of 30-day postoperative mortality in our patient population.     

The cardiac anesthesia risk evaluation score: a clinically useful predictor of mortality and morbidity after cardiac surgery

BACKGROUND: The Cardiac Anesthesia Risk Evaluation (CARE) score is a simple risk classification for cardiac surgical patients. It is based on clinical judgment and three clinical variables: comorbid conditions categorized as controlled or uncontrolled, surgical complexity, and urgency of the procedure. This study compared the CARE score with the Parsonnet, Tuman, and Tu multifactorial risk indexes for prediction of mortality and morbidity after cardiac surgery. METHODS: In this prospective study, 3,548 cardiac surgical patients from one institution were risk stratified by two investigators using the CARE score and the three tested multifactorial risk indexes. All patients were also given a CARE score by their attending cardiac anesthesiologist. The first 2,000 patients served as a reference group to determine discrimination of each classification with receiver operating characteristic curves. The following 1,548 patients were used to evaluate calibration using the Pearson chi-square goodness-of-fit test. RESULTS: The areas under the receiver operating characteristic curves for mortality and morbidity were 0.801 and 0.721, respectively, with the CARE score rating by the investigators; 0.786 and 0.710, respectively, with the CARE score rating by the attending anesthesiologists (n = 8); 0.808 and 0.726, respectively, with the Parsonnet index; 0.782 and 0.697, respectively, with the Tuman index; 0.770 and 0.724 with the Tu index, respectively. All risk models had acceptable calibration in predicting mortality and morbidity, except for the Parsonnet classification, which failed calibration for morbidity (P = 0.026). CONCLUSIONS: The CARE score performs as well as multifactorial risk indexes for outcome prediction in cardiac surgery. Cardiac anesthesiologists can integrate this score in their practice and predict patient outcome with acceptable accuracy.     

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

BACKGROUND: We compare two widely used risk algorithms for coronary bypass surgery: The European System for Cardiac Operative Risk Evaluation (EuroSCORE) and The Society of Thoracic Surgeons (STS) risk stratification algorithm. METHODS: Risk factors for all adult patients undergoing heart surgery at the University Hospital of Lund between 1996 and 2001 were collected prospectively at preoperative admission. Predictive accuracy for 30-day mortality was assessed by comparing the observed and the expected mortality for equal-sized quintiles of risk by using the Hosmer-Lemeshow goodness-of-fit test. The discriminatory power was evaluated by calculating the areas under receiver operating characteristics (ROC) curves. RESULTS: The study included 4497 coronary artery bypass-only operations. The average age was 66.4 +/- 9.3 years (range 31 to 90 years). Most patients were men (77.0% versus 23.0%). The actual 30-day mortality was 1.89%. The Hosmer-Lemeshow goodness-of-fit test gave a p value of 0.81 (EuroSCORE) and 0.83 (STS), which indicates a good accuracy of both models. The area under the ROC curve was 0.84 (95% confidence interval [CI] 0.80 to 0.88) for EuroSCORE and 0.71 (95% CI 0.66 to 0.77) for STS. The discriminatory power (area under the ROC curve) was significantly larger for EuroSCORE compared with STS (p < 0.00005). CONCLUSIONS: In this large, single institution study the additive EuroSCORE algorithm had a significantly better discriminatory power to predict 30-day mortality than the STS risk algorithm for patients undergoing coronary artery bypass.     

Comparative study of left colonic Peritonitis Severity Score and Mannheim Peritonitis Index

BACKGROUND: Prognostic evaluation of patients with left colonic perforation is useful in predicting mortality. The aims of this prospective study were to determine the prognostic value of the left colonic Peritonitis Severity Score (PSS) and to compare it with the Mannheim Peritonitis Index (MPI). METHODS: One-hundred and fifty-six patients underwent emergency operation for distal colonic peritonitis. The PSS and MPI were calculated for each patient. The Spearman rank correlation coefficient was used to measure the association between the two scores. The predictive power of the two scoring systems and their differences were studied using the area under the receiver-operator characteristic (ROC) curve. RESULTS: Forty-one patients died (26.3 per cent). The relationship between scores and mortality was statistically significant for each scoring system (P < 0.001). The Spearman rank correlation coefficient for the correlation between the MPI and PSS was 0.55 (P < 0.001). There was no difference between areas under the ROC curves for the two systems. CONCLUSION: The PSS and MPI are both well validated scoring systems for left colonic peritonitis. Their routine use might allow stratification of patients according to mortality risk.