Systematic review and meta-analysis of mortality risk prediction models in adult cardiac surgery. Review uri icon

Overview

abstract

  • OBJECTIVES: The 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. METHODS: We 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. RESULTS: The 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. CONCLUSIONS: ES2 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. REGISTRATION: Prospero (https://www.crd.york.ac.uk/PROSPERO/) CRD42020220983.

publication date

  • October 29, 2021

Research

keywords

  • Cardiac Surgical Procedures
  • Surgeons
  • Thoracic Surgery

Identity

PubMed Central ID

  • PMC8557799

Scopus Document Identifier

  • 85119352890

Digital Object Identifier (DOI)

  • 10.1093/icvts/ivab151

PubMed ID

  • 34041539

Additional Document Info

volume

  • 33

issue

  • 5