BACKGROUND: The Society of Thoracic Surgeons National Database Committee is committed to risk stratification and assessment as integral elements in the practice of cardiac operations. The National Cardiac Surgery Database was created to analyze data from subscribing institutions across the country. We analyzed the database for valve replacement procedures with and without coronary artery bypass grafting to determine trends in risk stratification. METHODS: The database contains complete records of 86,580 patients who had valve replacement procedures at the participating institutions between 1986 and 1995, inclusive. The 1995 harvest of data was conducted in late 1996 and available for evaluation in 1997. These records were used to conduct an in-depth analysis of risk factors associated with valve replacement and to provide prediction of operative death by using regression analysis. Regression models were made for six subgroups. RESULTS: Adverse patient risk factors, including diabetes, hypertension and reoperation, but not ventricular function, increased over time. There were trends with regard to increasing age of the various population subsets. The types of prostheses used remained similar over time, with more mechanical prostheses than bioprostheses used for both aortic and mitral valve replacement. There was a trend toward increased use of bioprostheses in aortic replacements and decreased use in mitral replacements between 1991 and 1995 than between 1986 and 1990. The mortality rate was determined by patient subset for primary operation and reoperation and by urgency status. The modeling showed that the predicted and observed mortality correlated for all age groups and within patient subsets. CONCLUSIONS: Risk modeling is a valuable tool for predicting the probability of operative death in any individual patient. This large, multiinstitutional database is capable of determining modern operative risk and should provide standards for acceptable care. The study illustrates the importance of risk stratification for early death both for the patient and the surgeon.
BACKGROUND: The Society of Thoracic Surgeons National Database Committee is committed to risk stratification and assessment as integral elements in the practice of cardiac operations. The National Cardiac Surgery Database was created to analyze data from subscribing institutions across the country. We analyzed the database for valve replacement procedures with and without coronary artery bypass grafting to determine trends in risk stratification. METHODS: The database contains complete records of 86,580 patients who had valve replacement procedures at the participating institutions between 1986 and 1995, inclusive. The 1995 harvest of data was conducted in late 1996 and available for evaluation in 1997. These records were used to conduct an in-depth analysis of risk factors associated with valve replacement and to provide prediction of operative death by using regression analysis. Regression models were made for six subgroups. RESULTS: Adverse patient risk factors, including diabetes, hypertension and reoperation, but not ventricular function, increased over time. There were trends with regard to increasing age of the various population subsets. The types of prostheses used remained similar over time, with more mechanical prostheses than bioprostheses used for both aortic and mitral valve replacement. There was a trend toward increased use of bioprostheses in aortic replacements and decreased use in mitral replacements between 1991 and 1995 than between 1986 and 1990. The mortality rate was determined by patient subset for primary operation and reoperation and by urgency status. The modeling showed that the predicted and observed mortality correlated for all age groups and within patient subsets. CONCLUSIONS: Risk modeling is a valuable tool for predicting the probability of operative death in any individual patient. This large, multiinstitutional database is capable of determining modern operative risk and should provide standards for acceptable care. The study illustrates the importance of risk stratification for early death both for the patient and the surgeon.
Authors: S Al-Ruzzeh; G Asimakopoulos; G Ambler; R Omar; R Hasan; B Fabri; A El-Gamel; A DeSouza; V Zamvar; S Griffin; D Keenan; U Trivedi; M Pullan; A Cale; M Cowen; K Taylor; M Amrani Journal: Heart Date: 2003-04 Impact factor: 5.994
Authors: Benoit de Varennes; Kevin Lachapelle; Renzo Cecere; Patrick Ergina; Dominique Shum-Tim; Christo Tchervenkov; John Sampalis Journal: Can J Cardiol Date: 2007-11 Impact factor: 5.223
Authors: Jocelyn M Beach; Tomislav Mihaljevic; Lars G Svensson; Jeevanantham Rajeswaran; Thomas Marwick; Brian Griffin; Douglas R Johnston; Joseph F Sabik; Eugene H Blackstone Journal: J Am Coll Cardiol Date: 2013-02-26 Impact factor: 24.094