Evidence Based Diagnostics and Treatment Planning Solution for Traumatic Brain Injuries

Overview

Adult patients, age ≥ 18 years, with clinically diagnosed mild, moderate or severe brain trauma will be asked to participate in the study. This prospective database will consist of 400 subjects with TBI, 200 from both TUCH and Cambridge Addenbrooke's Hospital. In addition, 100 controls will be recruited, with 50 from both centres.This study is a prospective clinical observational study with detailed data collecting. All patients will be treated according to the accepted, standardized, existing guidelines that are based on national and international recommendations. New treatment interventions will NOT be evaluated during the data acquisition for this study.

Aim in this study is to collect large amounts of data in adult subject population, who have suffered mild, moderate or severe brain trauma. This data will be added up to the existing large TBI databases from IMPACT as well as to the retrospective brain trauma data sets collected at the Turku University Hospital after the year 1995 and to the prospectively collected existing data set from the University of Cambridge. Data will contain patient characteristics, injury mechanisms, and patients' physiological status and findings immediately after the incident as well as through the processes of diagnostics, emergency treatment and in-hospital care. All data during these phases will follow the recommendations of Common Data Elements (advanced version) in TBI studies by the IMPACT investigators. Immediate head CT will be performed according to the existing guidelines, and head MRI with modern techniques as soon as the patient's wellbeing will allow the imaging to be done. During the intensive care unit (ICU) visit a database of EEG signals will be collected and the relevant information components will be extracted to provide inputs for the care decision algorithm. The aim is to investigate the feasibility of continuous EEG monitoring on the detection of epileptic seizures and other adverse events to enable rapid intervention during the patient's ICU stay and to improve outcome prediction. The investigators will also search new metabolomic, lipidomic, and genetic biomarkers related to TBIs through analyzing blood samples drawn in different time points. Based on all these factors, simulation models will be brought up as to help clinicians determine the earliest possible prognosis and to decide, whether patient would benefit from a particular care during the acute phase of a TBI.