A model for prediction of failure in amputation of the lower limb

A logistic regression analysis of eighteen variables in eighty-three lower limb amputations was performed in order to predict stump failure. Five variables were identified as having a significant effect on the logistic model: Age had an inverse relation to failure rate (p less than 0.005). This effect was mediated through a subgroup of 23 patients who had had a vascular operation (p less than 0.02), as this group had a higher failure rate and were younger than those without previous vascular surgery. Furthermore, the surgical experience (p less than 0.005) was of major importance for stump failure. Experienced surgeons had a failure rate of 2% while less experienced had a rate of 29% (p less than 0.001). In addition, it was confirmed that the higher the skin perfusion pressure (p less than 0.05) and the amputation level, (p less than 0.05) the better the healing. A model including "skin perfusion pressure," "previous vascular surgery," "amputation level" and "surgical experience" had a good predictive capability with a misclassification rate of 0.08-0.11. Therefore it is suggested that a logistic model including these variables could be a helpful tool to predict the risk of stump failure.