Interobserver Agreement for the Computed Tomography Severity Grading Scales for Acute 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:
15 06 2020
Historique:
pubmed: 31 1 2020
medline: 8 10 2021
entrez: 31 1 2020
Statut: ppublish

Résumé

The purpose of this study was to determine the interobserver variability among providers of different specialties and levels of experience across five established computed tomography (CT) scoring systems for acute traumatic brain injury (TBI). One hundred cases were selected at random from a retrospective population of adult patients transported to our emergency department and subjected to a non-contrast head CT due to suspicion of TBI. Eight neuroradiologists and neurosurgeons in trainee (residents and fellows) and attending roles independently scored each non-contrast head CT scan on the Marshall, Rotterdam, Helsinki, Stockholm, and NeuroImaging Radiological Interpretation System (NIRIS) head CT scales. Interobserver variability of scale scores-overall and by specialty and level of training-was quantified using the intraclass correlation coefficient (ICC), and agreement with respect to National Institutes of Health Common Data Elements (NIH CDEs) was assessed using Cohen's kappa. All CT severity scoring systems showed high interobserver agreement as evidenced by high ICCs, ranging from 0.75-0.89. For all scoring systems, neuroradiologists (ICC range from 0.81-0.94) tended to have higher interobserver agreement than neurosurgeons (ICC range from 0.63-0.76). For all scoring systems, attendings (ICC range from 0.76-0.89) had similar interobserver agreement to trainees (ICC range from 0.73-0.89). Agreement with respect to NIH CDEs was high for ascertaining presence/absence of hemorrhage, skull fracture, and mass effect, with estimated kappa statistics of least 0.89. Acute TBI CT scoring systems demonstrate high interobserver agreement. These results provide scientific rigor for future use of these systems for the classification of acute TBI.

Identifiants

pubmed: 31996087
doi: 10.1089/neu.2019.6871
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1445-1451

Auteurs

Sean Creeden (S)

Department of Radiology, Stanford University, Stanford, California, USA.

Victoria Y Ding (VY)

Department of Medicine, Stanford University, Stanford, California, USA.

Jonathon J Parker (JJ)

Department of Neurosurgery, Stanford University, Stanford, California, USA.

Bin Jiang (B)

Department of Radiology, Stanford University, Stanford, California, USA.

Ying Li (Y)

Department of Radiology, Stanford University, Stanford, California, USA.

Bryan Lanzman (B)

Department of Radiology, Stanford University, Stanford, California, USA.

Austin Trinh (A)

Department of Radiology, Stanford University, Stanford, California, USA.

Alexander Khalaf (A)

Department of Radiology, Stanford University, Stanford, California, USA.

Dylan Wolman (D)

Department of Radiology, Stanford University, Stanford, California, USA.

Casey H Halpern (CH)

Department of Neurosurgery, Stanford University, Stanford, California, USA.

Derek Boothroyd (D)

Department of Medicine, Stanford University, Stanford, California, USA.

Max Wintermark (M)

Department of Radiology, Stanford University, Stanford, California, USA.

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