Back to 2016 Annual Symposium Abstacts

Objectives
The clinical decision making utility of scoring algorithms for predicting mortality following ruptured abdominal aortic aneurysms (rAAA) remains unknown. We sought to determine whether adoption of these algorithms would have changed our clinical decision-making and outcomes over a 10-year period.
Methods
Patients admitted with a diagnosis rAAA at a large university hospital were identified from 2005-2014. The Glasgow Aneurysm Score, Hardman Index, Vancouver Score, Edinburgh Ruptured Aneurysm Score, University of Washington (UW) Ruptured Aneurysm Score, Vascular Study Group of New England (VSGNE) rAAA Risk Score, and the Artificial Neural Network (ANN) Score were analyzed for accuracy in predicting mortality. Among patients quantified into the highest risk group (predicted mortality >80% - 85%), we compared the predicted to the actual outcome to determine how well these scores predicted futility.
Results
The cohort comprised 63 patients. Of those, 23 underwent open repair, 36 underwent endovascular repair (EVAR) and 4 patients did not receive repair. Overall mortality was 30% (open repair 26%, EVAR 24%, no repair 100%). With the exception of the Glasgow score, the scores only classified a small percentage of the cohort at the highest risk for mortality (TABLE). In addition, predicted mortality was far greater than actual mortality (80%-100% vs. 57%-67%). Mortality rates for patients not designated into the high-risk cohort ranged from
8-29%. Futility, defined as 100% mortality, was predicted in 5/63 patients with the Hardman Index and 2/63 with the University of Washington score. Of these, surgery was not offered 1/5 and 1/2 patients respectively. If one of these two models were utilized to withhold operative intervention, the mortality of these patients would have been 100%. The actual mortality for these patients was 57% and 50% respectively.
Conclusions
Clinical algorithms for predicting mortality after rAAA were not useful for predicting futility. Most patients with rAAA were not classified in the highest risk group by the clinical decision models. Among patients identified as highest risk, predicted mortality was overestimated compared with actual mortality. These observations suggest that currently published clinical decision algorithms should be used with caution in selecting whom to offer repair for rAAA.

TABLE

Algorithm (n=64)	Number (%) Classified into highest-risk group	Predicted Mortality (%)	Actual Mortality (%)	Estimated % lives saved by offering surgery to the highest risk group
Glasgow	23 (35)	80	70	9
Vancouver	8 (13)	85	63	25
Edinburgh	10 (16)	80	60	20
VSGNE	2 (3)	85	50	50
ANN	3 (5)	85	67	33
Hardman	5 (8)	100	60	40
UW	2 (3)	100	50	50