Literature DB >> 30256318

Trends in Head Computed Tomography Utilization in Children Presenting to Emergency Departments After Traumatic Head Injury.

Onyinyechi I Ukwuoma1, Veerajalandhar Allareddy2, Veerasathpurush Allareddy3, Sankeerth Rampa4, Jerri A Rose1, Steven L Shein1, Alexandre T Rotta1.   

Abstract

OBJECTIVES: Although closed head injuries occur commonly in children, most do not have a clinically important traumatic brain injury (ciTBI) and do not require neuroimaging. We sought to determine whether the utilization of computed tomography of the head (CT-H) in children presenting to an emergency department (ED) with a closed head injury changed after publication of validated clinical prediction rules to identify children at risk of ciTBI by the Pediatric Emergency Care Applied Research Network (PECARN).
METHODS: We used the nationwide ED sample (2008-2013) to examine children visiting an ED after a mild closed head injury. Multiple patient and hospital characteristics were assessed.
RESULTS: Of the 4,552,071 children presenting to an ED with a mild closed head injury, 1,181,659 (26.0%) underwent CT-H. Care was most commonly received at metropolitan teaching hospitals (43.5%) and varied markedly by geographic region. Overall, there were no significant changes in the nationwide rates of CT-H utilization in the period immediately after publication of the PECARN prediction rules. However, compared with metropolitan teaching hospitals, CT-H utilization increased significantly for patients treated at nonteaching hospitals and at nonmetropolitan hospitals.
CONCLUSIONS: There was no overall reduction in CT-H utilization after publication of the 2009 PECARN prediction rules. However, patients treated at metropolitan teaching hospitals were significantly less likely to undergo CT-H after 2009, suggesting some penetration of the PECARN tool in that setting. Further research should study patterns of CT-H utilization in nonteaching hospitals and nonmetropolitan hospitals to assess challenges for adoption of validated pediatric ciTBI prediction rules.
Copyright © 2018 Wolters Kluwer Health, Inc. All rights reserved.

Entities:  

Year:  2021        PMID: 30256318     DOI: 10.1097/PEC.0000000000001618

Source DB:  PubMed          Journal:  Pediatr Emerg Care        ISSN: 0749-5161            Impact factor:   1.454


  2 in total

1.  Comparison of Machine Learning Optimal Classification Trees With the Pediatric Emergency Care Applied Research Network Head Trauma Decision Rules.

Authors:  Dimitris Bertsimas; Jack Dunn; Dale W Steele; Thomas A Trikalinos; Yuchen Wang
Journal:  JAMA Pediatr       Date:  2019-07-01       Impact factor: 16.193

2.  Intracranial Traumatic Hematoma Detection in Children Using a Portable Near-infrared Spectroscopy Device.

Authors:  Matthew P Kirschen; Sage R Myers; Mark I Neuman; Joseph A Grubenhoff; Rebekah Mannix; Nicholas Stence; Edward Yang; Ashley L Woodford; Tyson Rogers; Anna Nordell; Arastoo Vossough; Mark R Zonfrillo
Journal:  West J Emerg Med       Date:  2021-03-24
  2 in total

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