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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. #

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There has been increasing awareness of the need for monitoring the quality of health care, particularly in the area of surgery. The Cumulative Summation (Cusum) techniques have emerged as a popular tool for performance monitoring in surgery. They allow one to judge whether a given variation in performance is probably due to chance or greater than could be expected from random variation and thus a cause for concern. The Cusum techniques are simple to carry out and can be applied to any surgical process with a binary outcome. Four parameters need to be set in advance: acceptable outcome rate, unacceptable outcome rate, Type I and Type II error rates. In this article, we review the history, statistical methods and potential applications for the Cusum techniques in the field of surgery and illustrate the two common forms of charting (cumulative failure and Cusum charting) by using unadjusted outcome data from the Geelong Hospital and St Vincent's Hospital cardiac surgery databases.

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Objective: To assess the prevalence of obesity in patients undergoing coronary artery bypass grafting, heart valve surgery, or both procedures, and its association with postoperative outcomes. Design and setting: Retrospective analysis of data, collected by the Australasian Society of Cardiac and Thoracic Surgeons Victorian Cardiac Surgery Database Project, on patients undergoing coronary artery bypass grafting, heart valve surgery, or both procedures, between 1 June 2001 and 31 January 2006. Participants: 11 736 patients divided into four groups: underweight (body mass index [BMI], < 20), normal weight (BMI, 20–30), obese (BMI, > 30 to < 40), and morbidly obese (BMI, ≥ 40). Main outcome measures: Prevalence of obesity (compared with the age‐ and sex‐matched adult Australian population); associations between obesity and morbid obesity in cardiac patients and adverse postoperative outcomes. Results: 30.4% of patients had a BMI > 30 (28.6% obese, 1.8% morbidly obese) compared with an expected prevalence of 21.2%. Morbid obesity was associated with prolonged ventilation (adjusted odds ratio [OR], 2.4; 95% CI, 1.6–3.7), readmission to intensive care (adjusted OR, 2.2; 95% CI, 1.2–4.1), and length of stay > 14 days (adjusted OR, 2.1; 95% CI, 1.4–3.3). Both obesity and morbid obesity were associated with renal failure (adjusted ORs, 1.4 [95% CI, 1.1–1.7] and 2.9 [95% CI, 1.7–4.9], respectively) and deep sternal wound infection (adjusted ORs, 2.4 [95% CI, 1.5–3.8] and 7.2 [95% CI, 2.8–18.7], respectively). Conclusions: Obesity is 1.4 times more prevalent in patients having coronary artery bypass grafting or heart valve surgery in Victoria compared with the general adult Australian population. Both obesity and morbid obesity are associated with early morbidity, but not mortality, after operation.