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Injuries to the blood vessels of the lower extremity are potentially devastating and can result in death, severe disability or limb loss. Delays or errors in treatment decisions may lead to irreversible consequences and worsen outcome. One of the most difficult surgical decisions is whether to attempt salvage or perform an amputation of a severely injured extremity. Accurate risk stratification and outcome prediction, for a given injury pattern, has the potential to improve outcome by reducing delays and errors in decision-making. Predicting the outcome of vascular reconstruction and the projected tissue viability would inform treatment decisions and risks.

The primary aim of the Lower Extremity Vascular Injury Bayesian Network (VBN) is to predict the viability of a traumatic lower extremity with vascular injury after salvage is attempted. The VBN is able to calculate predictions when some of its input variables are unknown. The research is a collaboration between the Risk and Information Management group, Queen Mary University of London , the Trauma Sciences Unit, Barts and the London School of Medicine and Dentistry and the United States Army Institute of Surgical Research (USAISR) .