Magnetic Resonance Imaging Findings Are Associated with Long-Term Global Neurological Function or Death after Traumatic Brain Injury in Critically Ill Children.
Adolescent
Algorithms
Brain Injuries, Traumatic
/ complications
Child
Child, Preschool
Critical Illness
Diffuse Axonal Injury
/ diagnostic imaging
Female
Humans
Magnetic Resonance Imaging
Male
Predictive Value of Tests
Prognosis
Prospective Studies
Recovery of Function
Risk Factors
Survival Rate
Time Factors
functional outcomes
magnetic resonance imaging
pediatrics
prediction models
traumatic brain injury
Journal
Journal of neurotrauma
ISSN: 1557-9042
Titre abrégé: J Neurotrauma
Pays: United States
ID NLM: 8811626
Informations de publication
Date de publication:
01 09 2021
01 09 2021
Historique:
pubmed:
1
4
2021
medline:
23
2
2022
entrez:
31
3
2021
Statut:
ppublish
Résumé
The identification of children with traumatic brain injury (TBI) who are at risk of death or poor global neurological functional outcome remains a challenge. Magnetic resonance imaging (MRI) can detect several brain pathologies that are a result of TBI; however, the types and locations of pathology that are the most predictive remain to be determined. Forty-two critically ill children with TBI were recruited prospectively from pediatric intensive care units at five Canadian children's hospitals. Pathologies detected on subacute phase MRIs included cerebral hematoma, herniation, cerebral laceration, cerebral edema, midline shift, and the presence and location of cerebral contusion or diffuse axonal injury (DAI) in 28 regions of interest were assessed. Global functional outcome or death more than 12 months post-injury was assessed using the Pediatric Cerebral Performance Category score. Linear modeling was employed to evaluate the utility of an MRI composite score for predicting long-term global neurological function or death after injury, and nonlinear Random Forest modeling was used to identify which MRI features have the most predictive utility. A linear predictive model of favorable versus unfavorable long-term outcomes was significantly improved when an MRI composite score was added to clinical variables. Nonlinear Random Forest modeling identified five MRI variables as stable predictors of poor outcomes: presence of herniation, DAI in the parietal lobe, DAI in the subcortical white matter, DAI in the posterior corpus callosum, and cerebral contusion in the anterior temporal lobe. Clinical MRI has prognostic value to identify children with TBI at risk of long-term unfavorable outcomes.
Identifiants
pubmed: 33787327
doi: 10.1089/neu.2020.7514
doi:
Types de publication
Journal Article
Multicenter Study
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM