Early warning of EUSIG-defined hypotensive events using a Bayesian Artificial Neural Network.
Rob Donald, Tim Howells, Ian Piper, I Chambers, G Citerio, P Enblad, B Gregson, K Kiening, J Mattern, P Nilsson, A Ragauskas, Juan Sahuquillo, R Sinnott, A Stell
Acta Neurochir Suppl | Published : 2012
BACKGROUND: Hypotension is recognized as a potentially damaging secondary insult after traumatic brain injury. Systems to give clinical teams some early warning of likely hypotensive instability could be added to the range of existing techniques used in the management of this group of patients. By using the Edinburgh University Secondary Insult Grades (EUSIG) definitions for -hypotension (systolic arterial pressure <90 mmHg OR mean arterial -pressure <70 mmHg) we collected a group of ∼2,000 events by analyzing the Brain-IT database. We then constructed a Bayesian Artificial Neural Network (an advanced statistical modeling technique) that is able to provide some early warning when trained on ..View full abstract