Determinants of prognosis in neurocatastrophes

Kamal Sharma, Robert David Stevens

Research output: Contribution to journalReview articlepeer-review

Abstract

A neurocatastrophe or severe brain injury (SBI) is a central nervous system insult associated with a high likelihood of death or severe disability. While many etiologic processes may lead to SBI, the most common and best-studied clinical paradigms are traumatic brain injury and anoxic-ischemic encephalopathy following cardiac arrest. Clinical phenotypes following SBI include acute and chronic disorders of consciousness as well as a range of cognitive and behavioral impairments. A fundamental task for medical teams working in the acute phase is to estimate SBI recovery probabilities with the highest degree of accuracy possible. Predictions made on the basis of single features or variables lack discrimination and are generally supplanted by multivariable models that combine clinical, imaging, and laboratory data into tractable scoring systems. Yet existing scores fail to classify outcomes with the accuracy that would support individual patient-level decision making. Improved prognostication will likely depend on the use of molecular and imaging data that capture unique biologic features in individual patients with SBI. The integration of these additional layers of information will require iterative computational approaches.

Original languageEnglish (US)
Pages (from-to)379-395
Number of pages17
JournalHandbook of Clinical Neurology
Volume140
DOIs
StatePublished - 2017

Keywords

  • anoxic-ischemic encephalopathy
  • coma
  • intracerebral hemorrhage
  • minimally conscious state
  • outcome prediction
  • prognosis
  • subarachnoid hemorrhage
  • traumatic brain injury
  • vegetative state

ASJC Scopus subject areas

  • Medicine(all)
  • Neurology
  • Clinical Neurology

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