Statistical learning of blunt cerebrovascular injury risk factors using the elastic net.
Blunt cerebrovascular injury (BCVI)
Elastic net
Statistical learning
Journal
Emergency radiology
ISSN: 1438-1435
Titre abrégé: Emerg Radiol
Pays: United States
ID NLM: 9431227
Informations de publication
Date de publication:
Oct 2021
Oct 2021
Historique:
received:
25
01
2021
accepted:
19
05
2021
pubmed:
29
5
2021
medline:
26
11
2021
entrez:
28
5
2021
Statut:
ppublish
Résumé
To compare logistic regression to elastic net for identifying and ranking clinical risk factors for blunt cerebrovascular injury (BCVI). Consecutive trauma patients undergoing screening CTA at a level 1 trauma center over a 2-year period. Each internal carotid artery (ICA) and vertebral artery (VA) was independently graded by 2 neuroradiologists using the Denver grading scale. Unadjusted odds ratios were calculated by univariate and adjusted odds ratios by multiple logistic regression with FDR correction. We applied logistic regression with the elastic net penalty and tenfold cross-validation. Total of 467 patients; 73 patients with BCVI. Maxillofacial fracture, basilar skull fracture, and GCS had significant unadjusted odds ratios (OR) for ICA injury and C-spine fracture, spinal ligamentous injury, and age for VA injury. Only transverse foramen fracture had significant adjusted OR for VA injury, with none for ICA injury, after FDR correction. Using elastic net, ICA injury variables included maxillofacial fracture, basilar skull fracture, GCS, and carotid canal fracture. For VA injury, these included cervical spine transverse foramen fracture, ligamentous injury, C1-C3 fractures, posterior element fracture, and vertebral body fracture. Elastic net statistical learning methods identified additional risk factors and outperformed multiple logistic regression for BCVI. Elastic net allows the study of a large number of variables, and is useful when covariates are correlated.
Identifiants
pubmed: 34046756
doi: 10.1007/s10140-021-01949-8
pii: 10.1007/s10140-021-01949-8
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
929-937Informations de copyright
© 2021. American Society of Emergency Radiology.
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