Interleukin-8 predicts fatigue at 12 months post-injury in children with traumatic brain injury


Interleukin‐8 predict fatigue in child TBI
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Journal of neurotrauma

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Mary Ann Liebert

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Mots-clés

  • Fatigue
  • Serum biomarkers
  • Children
  • Glasgow coma scale
  • GCS
  • TBI
  • Traumatic brain injury

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Résumé

Despite many children experiencing fatigue after childhood brain injury, little is known about the predictors of this complaint. To date, traditional indices of traumatic brain injury (TBI) severity have not reliably predicted persisting fatigue (up to 3 years post‐injury). This study aimed to establish if persisting fatigue is predicted by serum biomarker concentrations in child TBI. We examined if acute serum biomarker expression would improve prediction models of 12‐month fatigue based on injury severity. Blood samples were collected from 87 children (1 – 17 years at injury) sustaining mild to severe TBI (GCS range 3‐15; mean 12.43; classified as mild TBI (n=50, 57%) vs moderate/severe TBI n=37, 43%), and presenting to the Emergency Departments (ED) and Pediatric Intensive Care Units (PICU) at one of three tertiary pediatric hospitals (Royal Children’s Hospital (RCH); Hospital for Sick Children (HSC), Toronto St Justine Children’s Hospital (SJH), Montreal). Six serum biomarker concentrations were measured within 24 hours of injury [interleukin‐6 (IL‐6), interleukin‐8 (IL‐8), soluble vascular cell adhesion molecule (SVCAM), S100 calcium binding protein B (S100B), neuron specific enolase (NSE), and soluble neural cell adhesion molecule (sNCAM)]. Fatigue at 12 months post‐injury was measured using the Pediatric Quality of Life Inventory Multidimensional Fatigue Scale (parent report), classified as present/absent using previously derived cut‐points. At 12 months post‐injury, 22% of participants experienced fatigue. A model including interleukin‐8 (IL‐8) was the best serum biomarker for estimating the probability of children experiencing fatigue at 12 months post‐injury. IL‐8 also significantly improved predictive models of fatigue based on severity.

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