Predicting operative risk for coronary artery surgery in the United Kingdom: a comparison of various risk prediction algorithms

Abstract

Objective: To compare the ability of four risk models to predict operative mortality after coronary artery bypass graft surgery (CABG) in the United Kingdom.

Design: Prospective study.

Setting: Two cardiothoracic centres in the United Kingdom.

Subjects: 1774 patients having CABG.

Main outcome measures: Risk factors were recorded for all patients, along with in-hospital mortality. Predicted mortality was derived from the American Society of Thoracic Surgeons (STS) risk program, Ontario Province risk score (PACCN), Parsonnet score, and the UK Society of Cardiothoracic Surgeons risk algorithm.

Results: There were significant differences (p < 0.05) between the British and American populations from which the STS risk algorithm was derived with respect to most variables. The observed mortality in the British population was 3.7% (65 of 1774). The mean predicted mortality by STS score, PACCN, Parsonnet score, and UK algorithms were 1.1%, 1.6%, 4.6%, and 4.7% respectively. The overall predictive ability of the models as measured by the area under the receiver operating characteristic curve were 0.64, 0.60, 0.73, and 0.75, respectively.

Conclusions: There are differences between the British and American populations for CABG and the North American algorithms are not useful for predicting mortality in the United Kingdom. The UK Society of Cardiothoracic Surgeons algorithm is the best of the models tested but still only has limited predictive ability. Great care must be exercised when using methods of this type for comparisons of units and surgeons.