OBJECTIVE: This study examined the association between hospital mortality and five illness-severity scoring systems evaluated at different time points in the intensive care unit (ICU) as well as clinical variables as predictors in critically ill patients supported by extracorporeal membrane oxygenation (ECMO) and acute dialysis. METHODS: This multicenter prospective observational study included 104 patients who received ECMO support and acute dialysis from January 2002 to December 2006. Patients' demographic, clinical and laboratory variables were analyzed as predictors of survival. The SAPS 2, APACHE II, SOFA, MODS, and SAPS 3 scores upon ICU admission and at acute dialysis commencement were evaluated to predict the patient's hospital mortality. RESULTS: Hospital mortality for the study group was 76% (79/104). Among the five scoring systems, only SAPS 3 score showed a significant difference between survivors and non-survivors either upon ICU admission (p=0.038) or at dialysis commencement (p=0.001). SAPS 3 score at dialysis commencement showed the best discrimination ability by using the area under the receiver operating characteristic curve (SOFA, 0.55; SAPS 2, 0.56; MODS, 0.58; APACHE II, 0.59; and SAPS 3, 0.73). Multiple logistic regression analysis indicated that SAPS 3 score at dialysis commencement (OR: 1.070, 95% CI: 1.016-1.216) and IABP usage before ECMO (OR: 4.181, 95% CI: 1.448-12.075) were two independent risk factors for hospital mortality. CONCLUSIONS: Among five common ICU scoring systems evaluated at different time points, SAPS 3 at dialysis commencement is the best risk adjustment systems to predict hospital mortality in critically ill patients supported by ECMO and acute dialysis. Furthermore, the SAPS 3 score at dialysis commencement and IABP usage before ECMO are two major independent predictors for hospital mortality in patients supported by ECMO and acute dialysis.
OBJECTIVE: This study examined the association between hospital mortality and five illness-severity scoring systems evaluated at different time points in the intensive care unit (ICU) as well as clinical variables as predictors in critically illpatients supported by extracorporeal membrane oxygenation (ECMO) and acute dialysis. METHODS: This multicenter prospective observational study included 104 patients who received ECMO support and acute dialysis from January 2002 to December 2006. Patients' demographic, clinical and laboratory variables were analyzed as predictors of survival. The SAPS 2, APACHE II, SOFA, MODS, and SAPS 3 scores upon ICU admission and at acute dialysis commencement were evaluated to predict the patient's hospital mortality. RESULTS: Hospital mortality for the study group was 76% (79/104). Among the five scoring systems, only SAPS 3 score showed a significant difference between survivors and non-survivors either upon ICU admission (p=0.038) or at dialysis commencement (p=0.001). SAPS 3 score at dialysis commencement showed the best discrimination ability by using the area under the receiver operating characteristic curve (SOFA, 0.55; SAPS 2, 0.56; MODS, 0.58; APACHE II, 0.59; and SAPS 3, 0.73). Multiple logistic regression analysis indicated that SAPS 3 score at dialysis commencement (OR: 1.070, 95% CI: 1.016-1.216) and IABP usage before ECMO (OR: 4.181, 95% CI: 1.448-12.075) were two independent risk factors for hospital mortality. CONCLUSIONS: Among five common ICU scoring systems evaluated at different time points, SAPS 3 at dialysis commencement is the best risk adjustment systems to predict hospital mortality in critically illpatients supported by ECMO and acute dialysis. Furthermore, the SAPS 3 score at dialysis commencement and IABP usage before ECMO are two major independent predictors for hospital mortality in patients supported by ECMO and acute dialysis.
Authors: Sarah E Siegelaar; Maartje Hickmann; Joost B L Hoekstra; Frits Holleman; J Hans DeVries Journal: Crit Care Date: 2011-09-13 Impact factor: 9.097
Authors: Sung Woo Lee; Mi-Yeon Yu; Hajeong Lee; Shin Young Ahn; Sejoong Kim; Ho Jun Chin; Ki Young Na Journal: PLoS One Date: 2015-10-15 Impact factor: 3.240
Authors: Jonathan E Millar; Jonathon P Fanning; Charles I McDonald; Daniel F McAuley; John F Fraser Journal: Crit Care Date: 2016-11-28 Impact factor: 9.097