Risk-adjusted predictive models of mortality after index arterial operations using a minimal data set

Abstract

Background: Reducing the data required for a national vascular database (NVD) without compromising the statistical basis of comparative audit is an important goal. This work attempted to model outcomes (mortality and morbidity) from a small and simple subset of the NVD data items, specifically urea, sodium, potassium, haemoglobin, white cell count, age and mode of admission.

Methods: Logistic regression models of risk of adverse outcome were built from the 2001 submission to the NVD using all records that contained the complete data required by the models. These models were applied prospectively against the equivalent data from the 2002 submission to the NVD.

Results: As had previously been found using the P-POSSUM (Portsmouth POSSUM) approach, although elective abdominal aortic aneurysm (AAA) repair and infrainguinal bypass (IIB) operations could be described by the same model, separate models were required for carotid endarterectomy (CEA) and emergency AAA repair. For CEA there were insufficient adverse events recorded to allow prospective testing of the models. The overall mean predicted risk of death in 530 patients undergoing elective AAA repair or IIB operations was 5.6 per cent, predicting 30 deaths. There were 28 reported deaths (chi(2) = 2.75, 4 d.f., P = 0.600; no evidence of lack of fit). Similarly, accurate predictions were obtained across a range of predicted risks as well as for patients undergoing repair of ruptured AAA and for morbidity.

Conclusion: A 'data economic' model for risk stratification of national data is feasible. The ability to use a minimal data set may facilitate the process of comparative audit within the NVD.