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

Area of Science:

• Cardiothoracic Surgery
• Health Services Research
• Biostatistics

Background:

• Operative mortality prediction is crucial for coronary artery bypass graft surgery (CABG).
• Existing risk models, primarily developed in North America, may not accurately reflect outcomes in different populations.
• The UK population undergoing CABG may have distinct characteristics influencing surgical risk.

Purpose of the Study:

• To evaluate the predictive accuracy of four established risk models for in-hospital mortality following CABG in the United Kingdom.
• To compare the performance of 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.

Main Methods:

• A prospective study was conducted across two UK cardiothoracic centers.
• Data from 1774 patients undergoing CABG were analyzed, including recorded risk factors and in-hospital mortality.
• Predicted mortality was calculated using the STS, PACCN, Parsonnet, and UK Society of Cardiothoracic Surgeons algorithms.

Main Results:

• Observed mortality in the UK cohort was 3.7%.
• Mean predicted mortalities were 1.1% (STS), 1.6% (PACCN), 4.6% (Parsonnet), and 4.7% (UK algorithm).
• The UK Society of Cardiothoracic Surgeons algorithm demonstrated the highest predictive ability (Area Under Curve: 0.75), followed by the Parsonnet score (0.73).

Conclusions:

• Significant demographic differences exist between UK and North American populations undergoing CABG.
• North American risk algorithms (STS, PACCN) show limited utility for predicting mortality in the UK.
• The UK Society of Cardiothoracic Surgeons algorithm is the most suitable among those tested, though its predictive power remains limited, necessitating caution in its application for comparative purposes.