A comparison of the national surgical quality improvement program and the society of thoracic surgery cardiac surgery preoperative risk models: A cohort study.

Abstract

Cardiac surgery prediction models and outcomes from the ACS-NSQIP have not been reported. We sought to develop preoperative prediction models and estimates of postoperative outcomes for cardiac surgery using the ACS-NSQIP and compare these to the Society of Thoracic Surgeons Adult Cardiac Surgery Database (STS-ACSD). In a retrospective analysis of the ACS-NSQIP data (2007-2018), cardiac operations were identified using cardiac surgeon primary specialty and sorted into cohorts of coronary artery bypass grafting (CABG) only, valve surgery only, and valve+CABG operations using CPT codes. Prediction models were created using backward selection of the 28 nonlaboratory preoperative variables in ACS-NSQIP. Rates of 9 postoperative outcomes and performance statistics of these models were compared to published STS 2018 data. Of 28,912 cardiac surgery patients, 18,139 (62.8%) were CABG only, 7,872 (27.2%) were valve only, and 2,901 (10.0%) were valve+CABG. Most outcome rates were similar between the ACS-NSQIP and STS-ACSD, except for lower rates of prolonged ventilation and composite morbidity and higher reoperation rates in ACS-NSQIP (all P<0.0001). For all 27 comparisons (9 outcomes x 3 operation groups), the c-indices for the ACS-NSQIP models were lower by an average of ~0.05 than the reported STS models. The ACS-NSQIP preoperative risk models for cardiac surgery were almost as accurate as the STS-ACSD models. Slight differences in c-indexes could be due to more predictor variables in STS-ACSD models or the use of more disease- and operation-specific risk variables in the STS-ACSD models.