VBHOM, a data economic model for predicting the outcome after open abdominal aortic aneurysm surgery

Abstract

Abstract Background Vascular Biochemistry and Haematology Outcome Models (VBHOM) adopted the approach of using a minimum data set to model outcome. This study aimed to test such a model on a cohort of patients undergoing open elective and non-elective abdominal aortic aneurysm (AAA) repair. Methods A binary logistic regression model of risk of in-hospital mortality was built from the 2002–2004 submission to the UK National Vascular Database (NVD) (2718 patients). The subset of NVD data items used comprised serum levels of urea, sodium and potassium, haemoglobin, white cell count, sex, age and mode of admission. The model was applied prospectively using Hosmer–Lemeshow methodology to a test data set from the Cambridge Vascular Unit. Results The validation set contained 327 patients, of whom 208 had elective AAA repair and 119 had emergency repair of a ruptured AAA. Outcome following elective and non-elective AAA repair could be described accurately using the same model. The overall mean predicted risk of death was 14·13 per cent, and 48 deaths were predicted. The actual number of deaths was 53 (χ2 = 8·40, 10 d.f., P = 0·590; no evidence of lack of fit). The model also demonstrated good discrimination (c-index = 0·852). Conclusion The VBHOM approach has the advantage of using simple, objective clinical data that are easy to collect routinely. The VBHOM data items potentially allow prediction of risk in an individual patient before aneurysm surgery.