- Poster presentation
- Open Access
Evaluation of APACHE II, SAPS II and sofa as predictors of mortality in patients over 80 years admitted to ICU
Intensive Care Medicine Experimental volume 3, Article number: A343 (2015)
Evaluate and compare the predictive ability of APACHE II, SAPS II and SOFA in mortality of elderly patients admitted for medical causes in the ICU of the Hospital Universitario de Guadalajara.
Retrospective cohort study. In this study we included patients with at least 80 years admitted to ICU for medical cause, from January-2003 to May 2011. Patients with Ischemic heart disease and arrhythmias were excluded. Logistic regressions analysis was used to calculate the sensitivity, specificity and accuracy as well as the OR probability of mortality. The ability to predict mortality was performed with ROC curves.
There were analyzed 95 patients, 55/95 (58%) males. Median age: 81 years (IQR: 80-83 years). Hospital mortality 52/95 (54.7%). Median APACHE II, SAPS II and SOFA: 23 (IQR 18-29), 7 (IQR: 4-10), 49 (IQR: 40-65).
The sensitivity, specificity and accuracy were respectively 75%, 63% and 69% for APACHE II; 73.1%, 62.8% and 68.4% for SOFA; 73.1%, 76.7% and 74.7% for SAPS II. For every one-point increase in score of APACHE II, SOFA and SAPS II, the possibility of dead increased by 16%, 32% and 13% respectively (p < 0.0001 in all three regressions); coefficient of determination Nagelkerke 0.26, 0.24 and 0.51 respectively. The area under the curve (AUC) of these models was: 0.76 for APACHE II, 0.75 for SOFA and 0.86 for SAPS; the differences between them were statistically significant (p = 0.018).
In our series, the SAPS II is the model that best predicts mortality in patients with at least 80 years admitted to ICU for medical reasons.
About this article
Cite this article
Romo Gonzales, J., Silva Obregón, J., Martin Dal Gesso, C. et al. Evaluation of APACHE II, SAPS II and sofa as predictors of mortality in patients over 80 years admitted to ICU. ICMx 3, A343 (2015) doi:10.1186/2197-425X-3-S1-A343
- Regression Analysis
- Logistic Regression
- Heart Disease
- Cohort Study
- Elderly Patient