Abstract
Background: The study was designed to evaluate the Acute Physiology
And Chronic Health Evaluation (APACHE) II risk scoring system in
abdominal aortic aneurysm (AAA) surgery. The aim was to create an
APACHE-based risk stratification model for postoperative death. Methods:
Prospective postoperative APACHE II data were collected from patients
undergoing AAA repair over a 9-year interval from 24 intensive care
units (ICUs) in the Thames region. A multilevel logistic regression
model (APACHE-AAA) for in-hospital mortality was developed to adjust
for both case mix and the variation in outcome between ICUs. Results:
A total of 1896 patients were studied. The in-hospital mortality
rate among the 1289 patients who had elective AAA repair was 9.6
(95 per cent confidence interval (c.i.) 8.0 to 11.2) per cent and
that among the 605 patients who had an emergency repair was 46.9
(95 per cent c.i. 43.0 to 50.9) per cent. Four independent predictors
of death were identified: age (odds ratio (OR) 1.05 (95 per cent
c.i. 1.03 to 1.07) per year increase), Acute Physiology Score (OR
1.14 (95 per cent c.i. 1.12 to 1.17) per unit increase), emergency
operation (OR 4.86 (95 per cent c.i. 3.64 to 6.52)) and chronic health
dysfunction (OR 1.43 (95 per cent c.i. 1.04 to 1.97)). The APACHE-AAA
model was internally valid, as shown by calibration (Hosmer-Lemeshow
C statistic: x(2) = 6.14, 8 d.f., P = 0.632), discrimination properties
(area under receiver-operator characteristic curve 0.845) and subgroup
analysis. There was no significant variation in outcome between hospitals.
Conclusion: APACHE-AAA was shown to be an accurate risk-stratification
model that could be used to quantify the risk of death after AAA
surgery. It might also be used to determine the relative impact of
ICU over high-dependency unit care
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