Currently, there is no risk scores built to predict risk in thoracic aortic surgery. This study aims to develop and internally validate a risk prediction score for patients who require arch reconstruction with hypothermic circulatory arrest.

From 2002 to 2018, data for 2270 patients who underwent aortic arch surgery in 12 institutions in Canada were retrospectively collected. The outcomes modeled included in-hospital mortality and a modified Society of Thoracic Surgeons–defined composite for mortality or major morbidity. Multivariable logistic regression using least absolute shrinkage and selection operator selection method and mixed-effect regression model was used to select the predictors. Internal calibration of the final models is presented with an observed-versus-predicted plot.

There were 182 in-hospital deaths (8.0%), and the incidence of Society of Thoracic Surgeons-defined composite for mortality or major morbidity was 27.9%. Variables that increased risk of mortality are age, chronic obstructive pulmonary disease, atrial fibrillation, peripheral vascular disease, New York Heart Association class ≥III symptoms, acute aortic dissection or rupture, use of elephant trunk, concomitant surgery, and increased cardiopulmonary bypass time, with median c-statistics of 0.85 on internal validation. The c-statistics was 0.77 for the model predicting Society of Thoracic Surgeons–defined composite. Internal assessment shows good overall calibration for both models.

We developed and internally validated a risk score for patients undergoing arch surgery requiring hypothermic circulatory arrest using a multicenter database. Once externally validated, the ARCH (Arch Reconstruction under Circulatory arrest with Hypothermia) score would allow for better patient risk-stratification and aid in the decision-making process for surgeons and patient prior to surgery.