Conditional probability of multiple coronary graft failure.
To assess the potential capability of using artery-specific factors to predict the success of coronary bypass grafting, we classified each graft according to the type of graft (mammary, single vein, or multiple skip vein), the degree of obstruction in the native coronary artery, and the size of the grafted artery. The mean patency rates for each category of graft were determined by performing early postoperative (mean 6.6 months) arteriograms in 354 patients. We found that mammary arteries gave the best results for every graft category. Skip vein grafts had a higher mean patency rate than single vein grafts for arteries with obstructions between 70% and 90% and lumina less than 2.0 mm in diameter. The results for vein and skip grafts were equivalent for the category with arteries greater than 2.0 mm and obstruction greater than 90%. Vein grafts produced better results than skip grafts for the remaining categories. Patients were classified into subgroups according to the number of actually observed graft failures. The probabilities that specific numbers of grafts would fail were calculated for each patient. These probabilities were based upon the observed patency rates for the category appropriate for each graft and the hypothesis that individual grafts within a patient fail independently. We observed an excess number of patients with no failures or multiple failures than would be expected according to the hypothesis of independent failure and category-specific patency rates. Conversely, there were fewer patients than expected who had single failures. Therefore, we postulate that there may also be global factors which influence early graft patency.
D003201:Computers; D001026:Coronary Artery Bypass / Q000379:methods*; D003327:Coronary Disease / Q000601:surgery; D005069:Evaluation Studies as Topic; D005500:Follow-Up Studies; D006801:Humans; D008323:Mammary Arteries / Q000637:transplantation; D011183:Postoperative Complications; D011336:Probability; D013997:Time Factors