OBJECTIVE: Risk stratification allows preoperative assessment of cardiac surgical risk faced by individual patients and permits retrospective analysis of postoperative complications in the intensive care unit (ICU). The aim of this single-center study was to investigate the prediction of extended ICU stay after cardiac surgery using both the additive and logistic model of the European System for Cardiac Operative Risk Evaluation (EuroSCORE). METHODS: A retrospective observational study was conducted. We collected clinical data of 1562 consecutive patients undergoing cardiac surgery over a 2-year period at the Antwerp University Hospital, Belgium. EuroSCORE values of all patients were obtained. The outcome measure was the duration of ICU stay in days. The predictive performance of EuroSCORE was analyzed by the discriminatory power of a receiver operating characteristic (ROC) curve. Each EuroSCORE value was used as a theoretical cut-off point to predict duration of ICU stay. Three subsequent ICU stays were defined as prolonged: more than 2, 5 and 7 days. ROC curves were constructed for both the additive and logistic model. RESULTS: Patients had a median ICU stay of 2 days and a mean ICU stay of 5.5 days. Median additive EuroSCORE was 5 (range, 0-22) and logistic EuroSCORE was 3.94% (range, 0.00-87.00). In the additive EuroSCORE model, a predictive value of 0.76 for an ICU stay of >7 days, 0.72 for >5 days and 0.67 for >2 days was found. The logistic EuroSCORE model yielded an area under the ROC curve of 0.77, 0.75 and 0.68 for each ICU length of stay, respectively. CONCLUSIONS: In our patient database, prolonged length of stay in the ICU correlated positively with EuroSCORE. The logistic model was more discriminatory than the additive in tracing extended ICU stay. The overall predictive performance of EuroSCORE is acceptable and most likely based on the presence of variables that are risk factors for both mortality and extended ICU stay. Hence, EuroSCORE is a useful predicting tool and provides both surgeons and intensivists with a good estimate of patient risk in terms of ICU stay.
OBJECTIVE: Risk stratification allows preoperative assessment of cardiac surgical risk faced by individual patients and permits retrospective analysis of postoperative complications in the intensive care unit (ICU). The aim of this single-center study was to investigate the prediction of extended ICU stay after cardiac surgery using both the additive and logistic model of the European System for Cardiac Operative Risk Evaluation (EuroSCORE). METHODS: A retrospective observational study was conducted. We collected clinical data of 1562 consecutive patients undergoing cardiac surgery over a 2-year period at the Antwerp University Hospital, Belgium. EuroSCORE values of all patients were obtained. The outcome measure was the duration of ICU stay in days. The predictive performance of EuroSCORE was analyzed by the discriminatory power of a receiver operating characteristic (ROC) curve. Each EuroSCORE value was used as a theoretical cut-off point to predict duration of ICU stay. Three subsequent ICU stays were defined as prolonged: more than 2, 5 and 7 days. ROC curves were constructed for both the additive and logistic model. RESULTS:Patients had a median ICU stay of 2 days and a mean ICU stay of 5.5 days. Median additive EuroSCORE was 5 (range, 0-22) and logistic EuroSCORE was 3.94% (range, 0.00-87.00). In the additive EuroSCORE model, a predictive value of 0.76 for an ICU stay of >7 days, 0.72 for >5 days and 0.67 for >2 days was found. The logistic EuroSCORE model yielded an area under the ROC curve of 0.77, 0.75 and 0.68 for each ICU length of stay, respectively. CONCLUSIONS: In our patient database, prolonged length of stay in the ICU correlated positively with EuroSCORE. The logistic model was more discriminatory than the additive in tracing extended ICU stay. The overall predictive performance of EuroSCORE is acceptable and most likely based on the presence of variables that are risk factors for both mortality and extended ICU stay. Hence, EuroSCORE is a useful predicting tool and provides both surgeons and intensivists with a good estimate of patient risk in terms of ICU stay.
Authors: Aliaksei Pustavoitau; Viachaslau Barodka; Norman E Sharpless; Chad Torrice; Daniel Nyhan; Dan E Berkowitz; Ashish S Shah; Karen J Bandeen Roche; Jeremy D Walston Journal: Exp Gerontol Date: 2015-12-09 Impact factor: 4.032
Authors: Geert Meyfroidt; Fabian Güiza; Dominiek Cottem; Wilfried De Becker; Kristien Van Loon; Jean-Marie Aerts; Daniël Berckmans; Jan Ramon; Maurice Bruynooghe; Greet Van den Berghe Journal: BMC Med Inform Decis Mak Date: 2011-10-25 Impact factor: 2.796