Brain injury : [BI]
-
Brain injury : [BI] · Jan 2016
ReviewParoxysmal sympathetic hyperactivity: Autonomic instability and muscle over-activity following severe brain injury.
Children who suffer from moderate-to-severe brain injury can develop a complicating phenomenon known as paroxysmal sympathetic hyperactivity (PSH), characterized by autonomic instability and identified clinically as a cluster of symptoms that can include recurrent fever without a source of infection, hypertension, tachycardia, tachypnea, agitation, diaphoresis and dystonia. Studies with adults have demonstrated that this cluster of symptoms is associated with poorer clinical outcomes (prolonged hospitalizations, poorer cognitive and motor function). However, there have been limited studies in children with PSH. ⋯ The majority of the research regarding PSH following severe brain injury has been descriptive in nature. Few studies, however, have explored PSH in children with brain injury; therefore, little is known about whether the outcomes of children with PSH are different and, if so, in what ways.
-
Brain injury : [BI] · Jan 2016
Stability of an ERP-based measure of brain network activation (BNA) in athletes: A new electrophysiological assessment tool for concussion.
To determine test-re-test reliabilities of novel Evoked Response Potential (ERP)-based Brain Network Activation (BNA) scores in healthy athletes. ⋯ The wide range of BNA scores observed in this population of healthy athletes suggests that a single BNA score or set of BNA scores from a single after-injury test session may be difficult to interpret in isolation without knowledge of the athlete's own baseline BNA score(s) and/or the results of serial tests performed at additional time points. The stability of each BNA network should be considered when interpreting test-re-test BNA score changes.
-
Brain injury : [BI] · Jan 2016
Prognostic models for prediction of outcomes after traumatic brain injury based on patients admission characteristics.
To identify the best performing prognostic model using admission characteristics to predict mortality at 30 days and functioning outcome at 6-months post-admission in patients with moderate or severe brain injury. ⋯ For clinical decision-making, model-2 is recommended on the basis of good performance in predicting outcomes in patients with moderate or severe TBI in India and other similar countries.
-
Brain injury : [BI] · Jan 2016
Infrascanner in the diagnosis of intracranial lesions in children with traumatic brain injuries.
The number of traumatic injuries among children is increasing. However, so-called mild TBI might result in unfavourable outcomes. Early diagnosis of intracranial haematomas prior to development of serious complications may be a decisive factor for a favourable outcome. InfraScan company developed and brought to the market the Infrascanner model 1000, which is a portable detector of blood collections that operates in the near infrared (NIR) band. ⋯ Infra-scanning might be viewed as a screening technique for intracranial haemorrhages in ambulances and outpatient trauma centres in order to decide on hospitalization, CT scanning and referral to a neurosurgeon. Infra-scanning combined with evaluation of risk factors of intracranial damage might reduce the number of unnecessary radiological examinations.
-
Brain injury : [BI] · Jan 2016
A retrospective cohort study of comorbidity trajectories associated with traumatic brain injury in veterans of the Iraq and Afghanistan wars.
To identify and validate trajectories of comorbidity associated with traumatic brain injury in male and female Iraq and Afghanistan war Veterans (IAV). ⋯ It was found that TBI was most common in PCT-related trajectories, indicating that TBI is commonly comorbid with pain and mental health conditions for both men and women. The relatively young age of this cohort raises important questions regarding how disease burden, including the possibility of neurodegenerative sequelae, will accrue alongside normal age-related decline in individuals with TBI. Additional 'big data' methods and a longer observation period may allow the development of predictive models to identify individuals with TBI that are at-risk for adverse outcomes.