A predictive model of outcomes during cerebral aneurysm coiling

Background: Benchmarking of complications is necessary in the context of the developing path to accountable care. We attempted to create a predictive model of negative outcomes in patients undergoing cerebral aneurysm coiling (CACo). Methods: We performed a retrospective cohort study involving patients who underwent CACo from 2005 to 2009 and who were registered in the Nationwide Inpatient Sample database. A model for outcome prediction based on individual patient characteristics was developed. Results: Of the 10 607 patients undergoing CACo, 6056 presented with unruptured aneurysms (57.1%) and 4551 with subarachnoid hemorrhage (42.9%). The respective inpatient postoperative risks were 0.3%, 5.7%, 1.8%, 0.8%, 0.5%, 0.2%, 1.9%, and 0.1% for unruptured aneurysms, and 13.8%, 52.8%, 4.9%, 36.7%, 1%, 2.9%, 2.3%, and 0.8% for ruptured aneurysms for death, unfavorable discharge, stroke, treated hydrocephalus, cardiac complications, deep vein thrombosis, pulmonary embolism, and acute renal failure. Multivariate analysis identified risk factors independently associated with the above outcomes. A validated model for outcome prediction based on individual patient characteristics was developed. The accuracy of the model was estimated by the area under the receiver operating characteristic curve, and it was found to have good discrimination. Conclusions: The presented model can aid in the prediction of the incidence of postoperative complications, and can be used as an adjunct in tailoring the treatment of cerebral aneurysms.