BrainIT collaborative network: analyses from a high time-resolution dataset of head injured patients

Chambers, I; Gregson, B; Citerio, G; Enblad, P; Howells, T; Kiening, K; Mattern, J; Nilsson, P; Piper, I; Ragauskas, A; Sahuquillo, J; Yau, YH

doi:10.1007/978-3-211-85578-2_43

BrainIT collaborative network: analyses from a high time-resolution dataset of head injured patients

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Abstract

Background: The BrainIT project was conceived in 1997 and has grown into an international collaboration with the purpose of gathering high time resolution data from head injured patients utilising standardised methodologies. Materials and methods: From 1998, 22 participating neu-roscience centres collected three main types of information: demographic, physiological data and clinical treatment information. A data collection solution was provided for each centre dependent on their existing facilities and data were collected for the duration of monitoring as defined by the routine care in each centre. On completion of ICP monitoring all personal information was removed and then transferred to Glasgow via the internet where it was converted into a standard format and entered into a central database. Outcome was measured using the extended Glasgow Outcome Score using an interview questionnaire. Findings: Data has been obtained from a total of 349 patients (277 male and 72 female) The age of these patients ranged from 1 to 87 years (median 31); 145 had been involved in a traffic accident and 32 were pedestrians; 78 had suffered a fall; 24 were assaulted and the remaining 70 of other causes. A large amount of physiological data was collected (e.g. BP 2,531 days, ICP 2,212 days in total). This dataset has provided the opportunity to perform unique analysis and these include the statistical features of blood pressure, diurnal variations in ICP, optimal sampling rate determination and a comparison of summary measures of secondary insults. Conclusions This challenging collaboration has brought together a large number of centres and developed a successful clinical research network focussed on improving the treatment of head injured patients. It has successfully collected a vast quantity of high quality data that provides a rich source for analysis and hypothesis testing.