The performance of trauma departments is widely audited by applying predictive models that assess probability of survival, and examining the rate of unexpected survivals and deaths. Although the TRISS methodology, a logistic regression modelling technique, is still the de. facto. standard, it is known that neural network models perform better.A key issue when applying neural network models is the selection of input variables. This paper proposes a novel form of sensitivity analysis, which is simpler to apply than existing techniques, and can be used for both numeric and nominal input variables. The technique is applied to the audit survival problem, and used to analyse the TRISS variables. The conclusion discusses the implications for the design of further improved scoring schemes and predictive models.
This study confirms that patients taking insulin are at increased risk of accidents. Among the different types of injury, only low-impact falls were significantly increased. This is most likely related to an increased tendency for insulin-treated patients to fall during a hypoglycemic episode. However, patients with diabetes may also be at higher risk of sustaining a fracture after a fall. The number of car crashes involving drivers with insulin-dependent diabetes is small, and the rate is not significantly greater than that of the background population. Further study of the causes and consequences of falls in diabetic patients is warranted.
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