Amaze: a randomized controlled trial of adjunct surgery for atrial fibrillation.

OBJECTIVES: Atrial fibrillation (AF) reduces survival and quality of life (QoL). It can be treated at the time of major cardiac surgery using ablation procedures ranging from simple pulmonary vein isolation to a full maze procedure. The aim of this study is to evaluate the impact of adjunct AF surgery as currently performed on sinus rhythm (SR) restoration, survival, QoL and cost-effectiveness. METHODS: In a multicentre, Phase III, pragmatic, double-blinded, parallel-armed randomized controlled trial, 352 cardiac surgery patients with >3 months of documented AF were randomized to surgery with or without adjunct maze or similar AF ablation between 2009 and 2014. Primary outcomes were SR restoration at 1 year and quality-adjusted life years at 2 years. Secondary outcomes included SR at 2 years, overall and stroke-free survival, medication, QoL, cost-effectiveness and safety. RESULTS: More ablation patients were in SR at 1 year [odds ratio (OR) 2.06, 95% confidence interval (CI) 1.20-3.54; P = 0.009]. At 2 years, the OR increased to 3.24 (95% CI 1.76-5.96). Quality-adjusted life years were similar at 2 years (ablation - control -0.025, P = 0.6319). Significantly fewer ablation patients were anticoagulated from 6 months postoperatively. Stroke rates were 5.7% (ablation) and 9.1% (control) (P = 0.3083). There was no significant difference in stroke-free survival [hazard ratio (HR) = 0.99, 95% CI 0.64-1.53; P = 0.949] nor in serious adverse events, operative or overall survival, cardioversion, pacemaker implantation, New York Heart Association, EQ-5D-3L and SF-36. The mean additional ablation cost per patient was £3533 (95% CI £1321-£5746). Cost-effectiveness was not demonstrated at 2 years. CONCLUSIONS: Adjunct AF surgery is safe and increases SR restoration and costs but not survival or QoL up to 2 years. A continued follow-up will provide information on these outcomes in the longer term. Study registration: ISRCTN82731440 (project number 07/01/34).

The current role of EuroSCORE.

The current status of risk modeling is briefly reviewed with emphasis on the role of EuroSCORE in the current era.

Death in low-risk cardiac surgery: the failure to achieve a satisfactory cardiac outcome (FIASCO) study.

Death in low-risk patients is not studied as frequently as it is in other cardiac patients. We, therefore, sought to determine why some low-risk patients die after cardiac surgery. All low-risk patients (EuroSCORE

Impact of cardiothoracic resident turnover on mortality after cardiac surgery: a dynamic human factor.

BACKGROUND: The study was designed to determine whether cardiac surgical outcomes are affected during times of major turnover of cardiothoracic resident surgical staff and at the beginning versus the end of their training periods. METHODS: This observational cohort study analyzed data from cardiac operations between April 1996 and March 2006 at a single institution. In-hospital mortality and other outcomes were compared between operations done during months of major change in resident staff rotation (July, August, January, February, n = 5,517) and the rest of the year (n = 10,773). We also compared outcomes at the beginning and end of surgical rotation for cardiothoracic residents. Adjustment was made for EuroSCORE (European System for Cardiac Operative Risk Evaluation), year of operation, and surgeon resident status. Analyses were done within surgery procedure subgroups of isolated coronary artery bypass graft surgery (CABG) and complex operations (CABG combined with other procedures). RESULTS: Patient populations in the groups were similar. After risk adjustment, there was a significant increase in hospital mortality for the complex cases during months of resident staff change compared with rest of the year (odds ratio 1.3, 95% confidence interval: 1.3, 1.4; p = 0.02). There was, however, no significant difference in mortality for the CABG only cases (odds ratio 1.1, 95% confidence interval: 0.8, 1.4; p = 0.61). Risk-adjusted mortality after operations done by residents was the same at the start and finish of their surgical rotation. During the change months, the surgery time was 2.2 minutes longer on average in CABG operations (95% confidence interval: 0.3, 4.0; p = 0.02), and no different in combined cases. CONCLUSIONS: Periods of major change in resident surgical staff are associated with increased risk-adjusted in-hospital mortality after complex cardiac operations but not after CABG alone.

Risk factor identification and mortality prediction in cardiac surgery using artificial neural networks.

OBJECTIVE: The artificial neural network model is a nonlinear technology useful for complex pattern recognition problems. This study aimed to develop a method to select risk variables and predict mortality after cardiac surgery by using artificial neural networks. METHODS: Prospectively collected data from 18,362 patients undergoing cardiac surgery at 128 European institutions in 1995 (the European System for Cardiac Operative Risk Evaluation database) were used. Models to predict the operative mortality were constructed using artificial neural networks. For calibration a sixfold cross-validation technique was used, and for testing a fourfold cross-testing was performed. Risk variables were ranked and minimized in number by calibrated artificial neural networks. Mortality prediction with 95% confidence limits for each patient was obtained by the bootstrap technique. The area under the receiver operating characteristics curve was used as a quantitative measure of the ability to distinguish between survivors and nonsurvivors. Subgroup analysis of surgical operation categories was performed. The results were compared with those from logistic European System for Cardiac Operative Risk Evaluation analysis. RESULTS: The operative mortality was 4.9%. Artificial neural networks selected 34 of the total 72 risk variables as relevant for mortality prediction. The receiver operating characteristics area for artificial neural networks (0.81) was larger than the logistic European System for Cardiac Operative Risk Evaluation model (0.79; P = .0001). For different surgical operation categories, there were no differences in the discriminatory power for the artificial neural networks (P = .15) but significant differences were found for the logistic European System for Cardiac Operative Risk Evaluation (P = .0072). CONCLUSIONS: Risk factors in a ranked order contributing to the mortality prediction were identified. A minimal set of risk variables achieving a superior mortality prediction was defined. The artificial neural network model is applicable independent of the cardiac surgical procedure.

Cardiac surgery risk models: a position article.

Differences in medical outcomes may result from disease severity, treatment effectiveness, or chance. Because most outcome studies are observational rather than randomized, risk adjustment is necessary to account for case mix. This has usually been accomplished through the use of standard logistic regression models, although Bayesian models, hierarchical linear models, and machine-learning techniques such as neural networks have also been used. Many factors are essential to insuring the accuracy and usefulness of such models, including selection of an appropriate clinical database, inclusion of critical core variables, precise definitions for predictor variables and endpoints, proper model development, validation, and audit. Risk models may be used to assess the impact of specific predictors on outcome, to aid in patient counseling and treatment selection, to profile provider quality, and to serve as the basis of continuous quality improvement activities.

Outcomes in emergency redo cardiac surgery: cost, benefit and risk assessment.

Emergency redo surgery is rare, but may be required in patients with conditions such as endocarditis, unstable angina and acute aortic dissection. To date there are no published data on the outcome of these difficult patients. Prospective consecutive data were collected from a single institution on 65 patients (51 male) undergoing coronary artery bypass grafts (27), mitral valve replacement or repair (13), aortic valve replacement (7), aortic surgery (13), and other (combined procedures) (5). Indications for surgery were unstable angina (12), endocarditis (11), resuscitation/catheter lab complications (11), torn prosthetic leaflet (6), aortic dissection (4), paraprosthetic leak (2), other (19). Mean ITU stay was 45 h (0-284) and hospital stay was 13.3 days (0-68). There were 14 intra-operative deaths and 14 further in-hospital deaths (overall mortality 43%). Predicted mortality rates were 26% (Parsonnet), 11% (EuroSCORE) and 31% (EuroSCORE logistic). Mean hospital cost per patient was 18,299 euros (or 32,147 euros per hospital survivor). In conclusion, the mortality in these difficult patients is very high, however, often no other treatment option is available. More sophisticated models, such as EuroSCORE logistic, may allow better prediction of risk in very high risk cases.