ArticleScientific reports2022
Decoding health status transitions of over 200 000 patients with traumatic brain injury from preceding injury to the injury event.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Explainable machine learning of PROGRESS-Plus social factors predicts cognitive trajectories after traumatic brain injury.Scientific reports · 2026Article
- Cognitive reserve and disparities in healthcare usage after traumatic brain injury and stroke: an observational cohort study.Journal of rehabilitation medicine · 2025Observational
- Gender versus sex in predicting outcomes of traumatic brain injury: a cohort study utilizing large administrative databases.Scientific reports · 2023Article
- Integrating unsupervised and supervised learning techniques to predict traumatic brain injury: A population-based study.Intelligence-based medicine · 2023Article
- Developing Brain Injury Resource Facilitation for Acquired Brain Injury: Indications and Unmet Needs.The Journal of head trauma rehabilitationArticle
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Authors and funding
6 authors.
Funding
Abstract
For centuries, the study of traumatic brain injury (TBI) has been centred on historical observation and analyses of personal, social, and environmental processes, which have been examined separately. Today, computation implementation and vast patient data repositories can enable a concurrent analysis of personal, social, and environmental processes, providing insight into changes in health status transitions over time. We applied computational and data visualization techniques to categorize decade-long health records of 235,003 patients with TBI in Canada, from preceding injury to the injury event itself. Our results highlighted that health status transition patterns in TBI emerged along with the projection of comorbidity where many disorders, social and environmental adversities preceding injury are reflected in external causes of injury and injury severity. The strongest associations between health status preceding TBI and health status at the injury event were between multiple body system pathology and advanced age-related brain pathology networks. The interwoven aspects of health status on a time continuum can influence post-injury trajectories and should be considered in TBI risk analysis to improve prevention, diagnosis, and care.
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