Open AccessPrediction of in-hospital death following aortic valve replacement: a new accurate model
Author(s) -
Matthew Richardson,
Neil Howell,
Nick Freemantle,
Ben Bridgewater,
Duilio Pagano
Publication year - 2012
Publication title -
european journal of cardio-thoracic surgery
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.303
H-Index - 133
eISSN - 1873-734X
pISSN - 1010-7940
DOI - 10.1093/ejcts/ezs457
Subject(s) - medicine , aortic valve replacement , euroscore , logistic regression , cardiac surgery , framingham risk score , cardiology , stenosis , risk assessment , surgery , computer security , disease , computer science
Aortic valve replacement (AVR) is accepted as the standard treatment for severe symptomatic aortic valve stenosis and regurgitation. As novel treatments are introduced for patients at high risk for conventional surgery, it is important to have models that accurately predict procedural risk. The aim of this study was to develop and validate a risk-stratification model to predict in-hospital risk of death for patients undergoing AVR and to compare the model with existing algorithms.
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