The contribution of the anaesthetist to risk-adjusted mortality after cardiac surgery

It is widely accepted that the performance of the operating surgeon affects outcomes, and this has led to the publication of surgical results in the public domain. However, the effect of other members of the multidisciplinary team is unknown. We studied the effect of the anaesthetist on mortality after cardiac surgery by analysing data collected prospectively over ten years of consecutive cardiac surgical cases from ten UK centres. Casemix-adjusted outcomes were analysed in models that included random-effects for centre, surgeon and anaesthetist. All cardiac surgical operations for which the EuroSCORE model is appropriate were included, and the primary outcome was in-hospital death up to three months postoperatively. A total of 110 769 cardiac surgical procedures conducted between April 2002 and March 2012 were studied, which included 127 consultant surgeons and 190 consultant anaesthetists. The overwhelming factor associated with outcome was patient risk, accounting for 95.75% of the variation for in-hospital mortality. The impact of the surgeon was moderate (intra-class correlation coefficient 4.00% for mortality), and the impact of the anaesthetist was negligible (0.25%). There was no significant effect of anaesthetist volume above ten cases per year. We conclude that mortality after cardiac surgery is primarily determined by the patient, with small but significant differences between surgeons. Anaesthetists did not appear to affect mortality. These findings do not support public disclosure of cardiac anaesthetists' results, but substantially validate current UK cardiac anaesthetic training and practice. Further research is required to establish the potential effects of very low anaesthetic caseloads and the effect of cardiac anaesthetists on patient morbidity

Creatinine clearance versus serum creatinine as a risk factor in cardiac surgery

BACKGROUND: Renal impairment is one of the predictors of mortality in cardiac surgery. Usually a binarized value of serum creatinine is used to assess the renal function in risk models. Creatinine clearance can be easily estimated by the Cockcroft and Gault equation from serum creatinine, gender, age and body weight. In this work we examine whether this estimation of the glomerular filtration rate can advantageously replace the serum creatinine in the EuroSCORE preoperative risk assessment. METHODS: In a group of 8138 patients out of a total of 11878 patients, who underwent cardiac surgery in our hospital between January 1996 and July 2002, the 18 standard EuroSCORE parameters could retrospectively be determined and logistic regression analysis performed. In all patients scored, creatinine clearance was calculated according to Cockcroft and Gault. The relationship between the predicted and observed 30-days mortality was evaluated in systematically selected intervals of creatinine clearance and significance values computed by employing Monte Carlo methods. Afterwards, risk scoring was performed using a continuous or a categorical value of creatinine clearance instead of serum creatinine. The predictive ability of several risk score models and the individual contribution of their predictor variables were studied using ROC curve analysis. RESULTS: The comparison between the expected and observed 30-days mortalities, which were determined in different intervals of creatinine clearance, revealed the best threshold value of 55 ml/min. A significantly higher 30-days mortality was observed below this threshold and vice versa (both with p < 0.001). The local adaptation of the EuroSCORE is better than the standard EuroSCORE and was further improved by replacing serum creatinine (SC) by creatinine clearance (CC). Differential ROC analysis revealed that CC is superior to SC in providing predictive power within the logistic regression. Variable rank comparison identified CC as the best single variable predictor, even better than the variable age, former number 1, and SC, previously number 9 in the standard set of EuroSCORE variables. CONCLUSION: The renal function is an important determinant of mortality in heart surgery. This risk factor is not well captured in the standard EuroSCORE risk evaluation system. Our study shows that creatinine clearance, calculated according to the Cockcroft and Gault equation, should be applied to estimate the preoperative renal function instead of serum creatinine. This predictor variable replacement gains a significant improvement in the predictive accuracy of the scoring model

The European System for Cardiac Operative Risk Evaluation (EuroSCORE) is not appropriate for withholding surgery in high-risk patients with aortic stenosis: a retrospective cohort study

<p>Abstract</p> <p>Background</p> <p>The European System for Cardiac Operative Risk Evaluation (EuroSCORE) is a widely used risk assessment tool in patients with severe aortic stenosis to determine operability and to select patients for alternative therapies such as transcatheter aortic valve implantation. The objective of this study was to determine the accuracy of the EuroSCORE in predicting mortality following aortic valve replacement (AVR).</p> <p>Methods</p> <p>The logistic EuroSCORE was determined for all consecutive patients that underwent conventional AVR between 1995 and 2005 at our institution. Provincial Vital Statistics were used to determine all-cause mortality. The accuracy of the prognostic risk prediction provided by logistic EuroSCORE was assessed by comparing observed and expected operative mortality.</p> <p>Results</p> <p>During the study period, a total of 1,421 patients underwent AVR including 237 patients (16.7%) that had a logistic EuroSCORE > 20. Among these patients, the mean predicted operative mortality was 38.7% (SD = 18.1). The actual mortality of these patients was significantly lower than that predicted by EuroSCORE (11.4% vs. 38.7%, observed/expected ratio 0.29, 95% CI 0.15–0.52, P < 0.05). The EuroSCORE overestimated mortality within all strata of predicted risk. Although medium-term mortality is significantly higher among patients with EuroSCORE > 20 (log rank P = 0.0001), approximately 60% are alive at five years.</p> <p>Conclusion</p> <p>Actual operative mortality in patients undergoing AVR is significantly lower than that predicted by the logistic EuroSCORE. Additionally, medium-term survival following AVR is acceptable in high-risk patients with EuroSCORE > 20. More accurate risk prediction models are needed for risk-stratifying patients with severe aortic stenosis.</p

Is age an independent determinant of mortality in cardiac surgery as suggested by the EuroSCORE?

BACKGROUND: The proportion of older patients in cardiac surgery is continuously increasing. 37% of patients undergoing heart surgery in Germany in the year 2000 were 70 years of age and older. We have studied the role of age as a determinant of mortality in cardiac surgery in our institutional patient population. METHODS: We have calculated the EuroSCORE and the corresponding age-adjusted EuroSCORE in 8769 patients who underwent heart surgery between January 1996 and January 2002 and collected the information on the occurrence of postoperative complications and 30-days mortality. RESULTS: The multimorbidity increased with ascending age. Both the EuroSCORE and the age-adjusted EuroSCORE values increased significantly with age in the whole group of patients as well as in the group of patients who were alive 30 days after heart surgery. The incidence of postoperative complications and 30-days mortality increased significantly with age. In patients who died within 30 days after surgery, the EuroSCORE increased significantly with age, whereas the age-adjusted EuroSCORE did not. The occurrence of diabetes mellitus, arterial hypertension and atrial fibrillation, i.e., the risk factors not considered by the EuroSCORE, exhibited a significant age dependence in our patients. The univariate analysis identified the significant dependence of 30-days mortality on diabetes and atrial fibrillation. The stepwise logistic regression analysis showed the dependence of mortality on diabetes. CONCLUSIONS: On the background of the well-known age-dependent structural and functional changes of different body organs, our data show that age is a significant risk indicator in cardiac surgery, strongly correlating with morbidity and mortality. Consequently, special preventive and therapeutic measures are required in clinical environment in the case of elderly patients undergoing cardiac surgery

Mechanisms of pulmonary dysfunction after on-pump and off-pump cardiac surgery: a prospective cohort study

BACKGROUND: Pulmonary dysfunction following cardiac surgery is believed to be caused, at least in part, by a lung vascular injury and/or atelectasis following cardiopulmonary bypass (CPB) perfusion and collapse of non-ventilated lungs. METHODS: To test this hypothesis, we studied the postoperative pulmonary leak index (PLI) for (67)Ga-transferrin and (transpulmonary) extravascular lung water (EVLW) in consecutive patients undergoing on-pump (n = 31) and off-pump (n = 8) cardiac surgery. We also studied transfusion history, radiographs, ventilatory and gas exchange variables. RESULTS: The postoperative PLI and EVLW were elevated above normal in 42 and 29% after on-pump surgery and 63 and 37% after off-pump surgery, respectively (ns). Transfusion of red blood cell (RBC) concentrates, PLI, EVLW, occurrence of atelectasis, ventilatory variables and duration of mechanical ventilation did not differ between groups, whereas patients with atelectasis had higher venous admixture and airway pressures than patients without atelectasis (P = 0.037 and 0.049). The PLI related to number of RBC concentrates infused (P = 0.025). CONCLUSION: The lung vascular injury in about half of patients after cardiac surgery is not caused by CPB perfusion but by trauma necessitating RBC transfusion, so that off-pump surgery may not afford a benefit in this respect. However, atelectasis rather than lung vascular injury is a major determinant of postoperative pulmonary dysfunction, irrespective of CPB perfusion

Statistical Primer: Developing and validating a risk prediction model

A risk prediction model is a mathematical equation that uses patient risk factor data to estimate the probability of a patient experiencing a healthcare outcome. Risk prediction models are widely studied in the cardiothoracic surgical literature with most developed using logistic regression. For a risk prediction model to be useful, it must have adequate discrimination, calibration, face validity and clinical usefulness. A basic understanding of the advantages and potential limitations of risk prediction models is vital before applying them in clinical practice. This article provides a brief overview for the clinician on the various issues to be considered when developing or validating a risk prediction model. An example of how to develop a simple model is also included