Comparison of risk-scoring methods in predicting the immediate outcome after elective open abdominal aneurysm surgery

Tang, Tjun and Walsh, S.R. and Fanshawe, Thomas and Seppi, V. and Sadat, U. and Hayes, P.D. and Varty, K. and Gaunt, M.E. and Boyle, J.R. (2007) Comparison of risk-scoring methods in predicting the immediate outcome after elective open abdominal aneurysm surgery. European Journal of Vascular and Endovascular Surgery, 34 (5). pp. 505-513. ISSN 1532-2165

Abstract

Background & Objectives The aim of this study was to apply three simple risk - scoring systems to prospectively collected data on all elective open Abdominal Aortic Aneurysm (AAA) operations in the Cambridge Academic Vascular Unit over a 6 - year period (January 1998 to January 2004), to compare their predictive values and to evaluate their validity with respect to prediction of mortality and post-operative complications. Methods 204 patients underwent elective open infra-renal AAA repair. Data were prospectively collected and risk assessment scores were calculated for mortality and morbidity according to the Glasgow Aneurysm Score (GAS), VBHOM (Vascular Biochemistry and Haematology Outcome Models) and Estimation of Physiologic Ability and Surgical Stress (E-PASS). Results The mortality rate was 6.3% (13/204) and 59% (121/204) experienced a post-operative complication (30-day outcome). For GAS, VBHOM and E-PASS the receiver operating characteristics (ROC) curve analysis for prediction of in-hospital mortality showed area under the curve (AUC) of 0.84 (95% confidence interval [CI], 0.76 to 0.92; p < 0.0001), 0.82 (95% CI, 0.68 to 0.95; p = 0.0001) and 0.92 (95% CI, 0.87 to 0.97; p < 0.0001) respectively. There were also significant correlations between post-operative complications and length of hospital stay and each of the three scores, but the correlation was substantially higher in the case of E-PASS. Conclusions All three scoring systems accurately predicted the risk of mortality and morbidity in patients undergoing elective open AAA repair. Among these, E-PASS seemed to be the most accurate predictor in this patient population.