Patients with ruptured AAA (rAAA) represent a population with high ICU & hospital mortality. There is little time for complex risk prediction & no prediction tool for those who have survived surgery. This project aimed to review the population presenting to Aberdeen General ICU & identify factors from admission data associated with increased ICU mortality. The SICSAG dataset for all patients with rAAA was reviewed. Bivariate correlation analysis & binary logistic regression were used to calculate relative risks for the variables with the greatest correlation.
The three variables with the strongest correlation were: Hb<9g/dl (RR 2.28), pH<7.2 (RR 3.31) & Prior CPR (RR 2.91). Variables such as age, renal function and vasoactive medication use were not found to correlate well with ICU mortality.
Although predictive in their own right, the presence of 2 or 3 variables is associated with a RR of 3.11 & 3.73, respectively. The dataset only included patients admitted to the ICU, excluding those admitted for palliative care & those who died within 8 hours of admission.The study only looked at variables within the SICSAG dataset and excludes other clinically important variables that may have an influence, such a Open/Endovascular repair and resuscitation fluid volume. As with all predictive tools, the above risk factors should not be used in isolation, but can be used to help identify patients at higher risk of ICU death.