Traumatic Brain Injury (TBI) is a devastating condition in terms of personal, societal and wider economic impact
- prognosis in TBI is difficult but important:
- guides appropriate treatment
- try to limit the proportion of patients left in a persistent vegetative state (PVS)
- aids the family in coming to terms with their loved one’s condition and with future planning
- clinical, physiological variables, radiological predictors and biological markers exist
- all are more useful for prediction at the population level than for guiding decisions concerning individual patients
MRC CRASH study in 2008 (n = 10,000 TBI patients with GCS <15) had these outcomes:
- 1 in 5 dead at 2 weeks
- 1 in 4 dead at 6 months
- 1 in 3 dead or severely disabled at 6 months
Extended Glasgow Outcome Scale is used to classify TBI outcomes, primarily in the research setting:
- Severe disability: lower grade (dependent for ADLs), upper grade (self caring but unable to work)
- Moderate disability: lower grade (able to travel independently and work in sheltered environment), upper grade (able to work in reduced capacity, deficits in speech, memory and personality change)
- Good recovery: lower grade (can participate socially), upper grade (resumption of normal life, minor neurological/psychological deficits)
- age (>40 years, worse with increasing age)
- initial GCS post-resuscitation
- pupil size and reaction to light (i.e fixed and dilated is bad!)
- nature & extent of the intracranial injuries (worst to least, subdural -> extradural -> SAH)
- low-to-middle income countries
- obliteration of third ventricle/basal cisterns (absence of basal cisterns is the strongest predictor of six month mortality)
- midline shift
- petechial haemorrhages
- subarachnoid haemorrhage
- unevacuated hematoma
- brainstem injury
- at 6-8 weeks: injuries to corpus callosum, corona radiata and dorsolateral brainstem predict PVS
- Diffusion tensor imaging
- allows detection of traumatic DI by providing information on integrity of white matter
- correlates with functional outcome at 1 year
- magnetic resonance spectroscopy
- measures brain metabolism and amounts of particular metabolites (creatinine, choline, lactate…)
- correlates with outcome
- SSEPs and cEEG
Primarily experimental at present:
- serum S-100β protein (severe TBI biomarker that most consistently demonstrates the ability to predict injury and outcome in adults)
- neuron-specific enolase (NSE)
- myelin basic protein
- protein degradation products (e.g. spectrin breakdown product, c-tau, and amyloid-beta(1-42))
TBI PROGNOSIS CALCULATORS
These are based on prognostic models that combined data from patients involved in clinical trials to predict clinical outcome, and should be used with caution:
- their outcomes apply to populations — caution is needed if applying them to individual patients
- the models were externally validated against one another — they are yet to be validated on patients not selected from clinical trials
References and Links
- CCC – Traumatic brain injury: Overview
- CCC – Limitations of CT in Traumatic Brain Injury
- CCC – Evoked Potentials in Critical Care
- Predicting outcome after traumatic brain injury: practical prognostic models based on large cohort of international patients. MRC CRASH Trial Collaborators. BMJ 2008;336:425 [Full Text]
- Nichol AD, Toal F, Fedi M, Cooper DJ. Early outcome prediction after severe traumatic brain injury: can multimodal magnetic resonance imaging assist in clinical prognostication for individual patients? Crit Care Resusc. 2011 Mar;13(1):5-8. PubMed PMID: 21355822. [fulltext pdf]
- Stevens RD, Sutter R. Prognosis in severe brain injury. Crit Care Med. 2013 Apr;41(4):1104-23. PMID: 23528755.
- Steyerberg EW, Mushkudiani N, Perel P, Butcher I, Lu J, et al. (2008) Predicting outcome after traumatic brain injury: Development and international validation of prognostic scores based on admission characteristics. PLoS Med 5: e165. doi:10.1371/journal.pmed.0050165.
- Young NH, Andrews PJD (2008) Developing a Prognostic Model for Traumatic Brain Injury—A Missed Opportunity? PLoS Med 5(8): e168. doi:10.1371/journal.pmed.0050168
Chris is an Intensivist and ECMO specialist at the Alfred ICU in Melbourne. He is also the Innovation Lead for the Australian Centre for Health Innovation at Alfred Health, a Clinical Adjunct Associate Professor at Monash University, and the Chair of the Australian and New Zealand Intensive Care Society (ANZICS) Education Committee. He is a co-founder of the Australia and New Zealand Clinician Educator Network (ANZCEN) and is the Lead for the ANZCEN Clinician Educator Incubator programme. He is on the Board of Directors for the Intensive Care Foundation and is a First Part Examiner for the College of Intensive Care Medicine. He is an internationally recognised Clinician Educator with a passion for helping clinicians learn and for improving the clinical performance of individuals and collectives.
After finishing his medical degree at the University of Auckland, he continued post-graduate training in New Zealand as well as Australia’s Northern Territory, Perth and Melbourne. He has completed fellowship training in both intensive care medicine and emergency medicine, as well as post-graduate training in biochemistry, clinical toxicology, clinical epidemiology, and health professional education.
He is actively involved in in using translational simulation to improve patient care and the design of processes and systems at Alfred Health. He coordinates the Alfred ICU’s education and simulation programmes and runs the unit’s education website, INTENSIVE. He created the ‘Critically Ill Airway’ course and teaches on numerous courses around the world. He is one of the founders of the FOAM movement (Free Open-Access Medical education) and is co-creator of LITFL.com, the RAGE podcast, the Resuscitology course, and the SMACC conference.
His one great achievement is being the father of two amazing children.
On Twitter, he is @precordialthump.