Competing risks after coronary bypass surgeryThe influence of death on reintervention

AbstractObjective: For groups of patients at high risk of death, such as older patients, the actual probability of experiencing a nonfatal event, such as reintervention, must be far smaller than the potential probability were there no attrition by death. Competing risks analysis quantifies the difference. Methods: Multivariable analyses were performed for the competing events death before reintervention, reoperation, and percutaneous transluminal coronary angioplasty in 2001 patients after bilateral internal thoracic artery grafting and in 8123 after single internal thoracic artery grafting. Follow-up was 9.7 ± 3.0 years and 10.8 ± 5.2 years in bilateral and single internal thoracic artery groups, respectively. Results: Patients receiving single grafts experienced shorter survival and more reinterventions (P < .0001). However, other risk factors for death included old age (P < .0001), but risk factors for reintervention included young age (P < .0001). This difference confounds interpretation of event-free survival that is clarified by competing risks analysis. Death reduced the potential benefit of bilateral internal thoracic artery grafting on reintervention by angioplasty from a median of 8.5% to 5.5% at 12 years and by reoperation from 9.3% to 6.8%, with progressively greater erosion of benefit from attrition by death as age increased. Competing risks simulation confirmed that young age was a true risk factor for reintervention, excluding the explanation that it reflected simply passive attrition by death as patients age. Conclusions: Even after accounting for attrition by interim deaths, bilateral versus single internal thoracic artery grafting and older age are associated with fewer reinterventions. However, in high-risk patients, its benefit on freedom from reintervention is eroded considerably by death. (J Thorac Cardiovasc Surg 2000;119:1221-32

Neurologic injury from cardiac surgery—an important but enormously complex phenomenon

AbstractJ Thorac Cardiovasc Surg 2003;125:S28-3

Random survival forests

We introduce random survival forests, a random forests method for the analysis of right-censored survival data. New survival splitting rules for growing survival trees are introduced, as is a new missing data algorithm for imputing missing data. A conservation-of-events principle for survival forests is introduced and used to define ensemble mortality, a simple interpretable measure of mortality that can be used as a predicted outcome. Several illustrative examples are given, including a case study of the prognostic implications of body mass for individuals with coronary artery disease. Computations for all examples were implemented using the freely available R-software package, randomSurvivalForest.Comment: Published in at http://dx.doi.org/10.1214/08-AOAS169 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Analysis of morbid events and risk factors for death after cardiac transplantation

AbstractRisk factors for death after cardiac transplantation performed at the University of Alabana at Birmingham from January 1981 to July 1985 included (by multivariate analysis) higher calculated preoperative pulmonary vascular resistance (early and constant phases), murphology of cardiomyopathy (versus ischemic heart disease) (constant phase only) and black race (constant phase). overall actuarial survival was 71% at 1 year and 48% at 3 years (including azalhioprine and cyclosporine eras). The hazard function for death was highest immediately after operation and declined rapidly thereafter, merging with a constant phase of risk at about 3 months.The most favorable group for long-term survival was the group of white patients with ischemic heart disease and low pulmonary vascular resistance. When such patients had a pulmonary vascular resistance < 3 units m2, the 3 year survival rate exceeded 85%; The most common causes of death were acute rejection (24%) and infection (17%) The risk of infection remained highest during the first several months after any period of augmented immunosuppression