Major risk-stratification models fail to predict outcomes in patients with multivessel coronary artery disease undergoing simultaneous hybrid procedure
Background The hybrid procedure for coronary heart disease combines minimally invasive coronary artery bypass grafting (CABG) and percutaneous coronary intervention (PCI) and is an alternative to revascularization treatment. We sought to assess the predictive value of four risk-stratification models...
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Veröffentlicht in: | Chinese medical journal 2013-02, Vol.126 (3), p.450-456 |
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Zusammenfassung: | Background The hybrid procedure for coronary heart disease combines minimally invasive coronary artery bypass grafting (CABG) and percutaneous coronary intervention (PCI) and is an alternative to revascularization treatment. We sought to assess the predictive value of four risk-stratification models for risk assessment of major adverse cardiac and cerebrovascular events (MACCE) in patients with multivessel disease undergoing hybrid coronary revascularization. Methods The data of 120 patients were retrospectively collected and the SYNTAX score, EuroSCORE, SinoSCORE and the Global Risk Classification (GRC) calculated for each patient. The outcomes of interest were 2.7-year incidences of MACCE, including death, myocardial infarction, stroke, and any-vessel revascularization. Results During a mean of 2.7-year follow-up, actuarial survival was 99.17%, and no myocardial infarctions occurred. The discriminatory power (area under curve (AUC)) of the SYNTAX score, EuroSCORE, SinoSCORE and GRC for 2.7-year MACCE was 0.60 (95% confidence interval 0.42-0.77), 0.65 (0.47-0.82), 0.57 (0.39-0.75) and 0.65 (0.46-0.83), respectively. The calibration characteristics of the SYNTAX score, EuroSCORE, SinoSCORE and GRC were 3.92 (P=0.86), 5.39 (P=0.37), 13.81 (P=0.32) and 0.02 (P=0.89), respectively. Conclusions In patients with multivessel disease undergoing a hybrid procedure, the SYNTAX score, EuroSCORE, SinoSCORE and GRC were inaccurate in predicting MACCE. Modifying risk-stratification models to improve the predictive value for a hybrid procedure is needed. |
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ISSN: | 0366-6999 2542-5641 |
DOI: | 10.3760/cma.j.issn.0366-6999.20120712 |