Toward a New Multi-Dimensional Classification of Traumatic Brain Injury: A Collaborative European NeuroTrauma Effectiveness Research for Traumatic Brain Injury StudyShow others and affiliations
Number of Authors: 2352020 (English)In: Journal of Neurotrauma, ISSN 0897-7151, E-ISSN 1557-9042, Vol. 37, no 7, p. 1002-1010Article in journal (Refereed) Published
Abstract [en]
Traumatic brain injury (TBI) is currently classified as mild, moderate, or severe TBI by trichotomizing the Glasgow Coma Scale (GCS). We aimed to explore directions for a more refined multidimensional classification system. For that purpose, we performed a hypothesis-free cluster analysis in the Collaborative European NeuroTrauma Effectiveness Research for TBI (CENTER-TBI) database: a European all-severity TBI cohort (n = 4509). The first building block consisted of key imaging characteristics, summarized using principal component analysis from 12 imaging characteristics. The other building blocks were demographics, clinical severity, secondary insults, and cause of injury. With these building blocks, the patients were clustered into four groups. We applied bootstrap resampling with replacement to study the stability of cluster allocation. The characteristics that predominantly defined the clusters were injury cause, major extracranial injury, and GCS. The clusters consisted of 1451, 1534, 1006, and 518 patients, respectively. The clustering method was quite stable: the proportion of patients staying in one cluster after resampling and reclustering was 97.4% (95% confidence interval [CI]: 85.6-99.9%). These clusters characterized groups of patients with different functional outcomes: from mild to severe, 12%, 19%, 36%, and 58% of patients had unfavorable 6 month outcome. Compared with the mild and the upper intermediate cluster, the lower intermediate and the severe cluster received more key interventions. To conclude, four types of TBI patients may be defined by injury mechanism, presence of major extracranial injury and GCS. Describing patients according to these three characteristics could potentially capture differences in etiology and care pathways better than with GCS only.
Place, publisher, year, edition, pages
Mary Ann Liebert, 2020. Vol. 37, no 7, p. 1002-1010
Keywords [en]
GCS, classification, clustering, prospective
National Category
Neurology
Identifiers
URN: urn:nbn:se:oru:diva-81160DOI: 10.1089/neu.2019.6764ISI: 000524528800009PubMedID: 31672086Scopus ID: 2-s2.0-85083076089OAI: oai:DiVA.org:oru-81160DiVA, id: diva2:1423950
2020-04-162020-04-162021-02-09Bibliographically approved