Logistic risk model for mortality following elective abdominal aortic aneurysm repair

Abstract

Background: The aim was to develop a multivariable risk prediction model for 30-day mortality following elective abdominal aortic aneurysm (AAA) repair.

Methods: Data collected prospectively on 2765 consecutive patients undergoing elective open and endovascular AAA repair from September 1999 to October 2009 in the North West of England were split randomly into development (1936 patients) and validation (829) data sets. Logistic regression analysis was undertaken to identify risk factors for 30-day mortality.

Results: Ninety-eight deaths (5·1 per cent) were recorded in the development data set. Variables associated with 30-day mortality included: increasing age (P = 0·005), female sex (P = 0·002), diabetes (P = 0·029), raised serum creatinine level (P = 0·006), respiratory disease (P = 0·031), antiplatelet medication (P < 0·001) and open surgery (P = 0·002). The area under the receiver operating characteristic (ROC) curve for predicted probability of 30-day mortality in the development and validation data sets was 0·73 and 0·70 respectively. Observed versus expected 30-day mortality was 3·2 versus 2·0 per cent (P = 0·272) in low-risk, 6·1 versus 5·1 per cent (P = 0·671) in medium-risk and 11·1 versus 10·7 per cent (P = 0·879) in high-risk patients.

Conclusion: This multivariable model for predicting 30-day mortality following elective AAA repair can be used clinically to calculate patient-specific risk and is useful for case-mix adjustment. The model predicted well across all risk groups in the validation data set.