Abstract
OBJECTIVESThe most used mortality risk prediction models in cardiac surgery are the European System for Cardiac Operative Risk Evaluation (ES) and Society of Thoracic Surgeons (STS) score. There is no agreement on which score should be considered more accurate nor which score should be utilized in each population subgroup. We sought to provide a thorough quantitative assessment of these 2 models. METHODSWe performed a systematic literature review and captured information on discrimination, as quantified by the area under the receiver operator curve (AUC), and calibration, as quantified by the ratio of observed-to-expected mortality (O:E). We performed random effects meta-analysis of the performance of the individual models as well as pairwise comparisons and subgroup analysis by procedure type, time and continent.RESULTSThe ES2 {AUC 0.783 [95% confidence interval (CI) 0.765–0.800]; O:E 1.102 (95% CI 0.943–1.289)} and STS [AUC 0.757 (95% CI 0.727–0.785); O:E 1.111 (95% CI 0.853–1.447)] showed good overall discrimination and calibration. There was no significant difference in the discrimination of the 2 models (difference in AUC −0.016; 95% CI −0.034 to −0.002; P = 0.09). However, the calibration of ES2 showed significant geographical variations (P < 0.001) and a trend towards miscalibration with time (P=0.057). This was not seen with STS.CONCLUSIONSES2 and STS are reliable predictors of short-term mortality following adult cardiac surgery in the populations from which they were derived. STS may have broader applications when comparing outcomes across continents as compared to ES2.REGISTRATIONProspero (https://www.crd.york.ac.uk/PROSPERO/) CRD42020220983.
Highlights
Cardiac surgery carries an inherent risk of perioperative mortality and morbidity
There was no significant difference in the discrimination of the 2 models
We report on the original papers and subsequent external validations available and draw comparisons between the models’ discriminatory power, as defined by the area under the receiver operator curve (AUC) or C-statistic, and their calibration, as defined by the ratio of the observed-to-expected mortality (O:E) within 30 days of the operation or the same hospital admission
Summary
Cardiac surgery carries an inherent risk of perioperative mortality and morbidity. This varies considerably depending on the patients’ characteristics, baseline pathology and planned surgical intervention. Prediction models have been created [1,2,3,4,5,6] to quantify this risk. These models are utilized when counselling patients, discussing patients within the multi-disciplinary team, for benchmarking performance and more recently in guidelines for the management of aortic stenosis and deciding between surgical or transcatheter treatments [7, 8]. The most cited models are the European System for Cardiac Operative Risk Evaluation (ES) [1, 2, 9] and the Society of Thoracic Surgeons (STS) score [10, 11]
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