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Validation of bleeding classifications in coronary artery bypass grafting
- Publication Year :
- 2017
-
Abstract
- Perioperative bleeding is a determinant of poor outcome in patients undergoing coronary artery bypass grafting (CABG), but there is a lack of adequate stratification of its severity. The ability of the European registry of Coronary Artery Bypass Grafting (E-CABG), Universal Definition of Perioperative Bleeding (UDPB), Study of Platelet Inhibition and Patient Outcomes (PLATO), Clopidogrel and Aspirin Optimal Dose Usage to Reduce Recurrent Events−Seventh Organization to Assess Strategies in Ischemic Syndromes (CURRENT-OASIS 7), Efficacy and Safety of Subcutaneous Enoxaparin in Non-Q Wave Coronary Events (ESSENCE), and SafeTy and Efficacy of Enoxaparin in Percutaneous coronary intervention patients, an internationaL randomized Evaluation (STEEPLE) bleeding classifications to predict early mortality, stroke, acute kidney injury (AKI) stage 3, and deep sternal wound infection/mediastinitis was investigated in 3,730 patients from the prospective, multicentre E-CABG registry. Increasing grades of the E-CABG, UDPB, PLATO, and CURRENT-OASIS 7 classifications were associated with increasing risks of early mortality, had similar receiver-operating characteristic area under the curves (>0.7), and were predictive also when adjusted for EuroSCORE II. The E-CABG and UDPB classifications had satisfactory area under the curves (>0.6) in predicting stroke, AKI stage 3, and deep sternal wound infection/mediastinitis even when adjusted for EuroSCORE II. The PLATO and CURRENT-OASIS 7 classifications had similar predictive ability for stroke and AKI stage 3 as confirmed by multivariate analysis adjusted for EuroSCORE II but showed inferior ability in predicting severe wound infection compared to the E-CABG and UDPB classifications. The STEEPLE and ESSENCE classifications had a poor ability of predicting all these adverse events. Decision curve analysis showed a benefit of the E-CABG bleeding classification over the other classifications in predicting all adverse events. In concl
Details
- Database :
- OAIster
- Notes :
- application/pdf, English
- Publication Type :
- Electronic Resource
- Accession number :
- edsoai.on1126539113
- Document Type :
- Electronic Resource