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Decoding health status transitions of over 200 000 patients with traumatic brain injury from preceding injury to the injury event

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 analysi...

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Autores principales: Mollayeva, Tatyana, Tran, Andrew, Chan, Vincy, Colantonio, Angela, Sutton, Mitchell, Escobar, Michael D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8980052/
https://www.ncbi.nlm.nih.gov/pubmed/35379824
http://dx.doi.org/10.1038/s41598-022-08782-0
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author Mollayeva, Tatyana
Tran, Andrew
Chan, Vincy
Colantonio, Angela
Sutton, Mitchell
Escobar, Michael D.
author_facet Mollayeva, Tatyana
Tran, Andrew
Chan, Vincy
Colantonio, Angela
Sutton, Mitchell
Escobar, Michael D.
author_sort Mollayeva, Tatyana
collection PubMed
description 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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spelling pubmed-89800522022-04-06 Decoding health status transitions of over 200 000 patients with traumatic brain injury from preceding injury to the injury event Mollayeva, Tatyana Tran, Andrew Chan, Vincy Colantonio, Angela Sutton, Mitchell Escobar, Michael D. Sci Rep Article 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. Nature Publishing Group UK 2022-04-04 /pmc/articles/PMC8980052/ /pubmed/35379824 http://dx.doi.org/10.1038/s41598-022-08782-0 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Mollayeva, Tatyana
Tran, Andrew
Chan, Vincy
Colantonio, Angela
Sutton, Mitchell
Escobar, Michael D.
Decoding health status transitions of over 200 000 patients with traumatic brain injury from preceding injury to the injury event
title Decoding health status transitions of over 200 000 patients with traumatic brain injury from preceding injury to the injury event
title_full Decoding health status transitions of over 200 000 patients with traumatic brain injury from preceding injury to the injury event
title_fullStr Decoding health status transitions of over 200 000 patients with traumatic brain injury from preceding injury to the injury event
title_full_unstemmed Decoding health status transitions of over 200 000 patients with traumatic brain injury from preceding injury to the injury event
title_short Decoding health status transitions of over 200 000 patients with traumatic brain injury from preceding injury to the injury event
title_sort decoding health status transitions of over 200 000 patients with traumatic brain injury from preceding injury to the injury event
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8980052/
https://www.ncbi.nlm.nih.gov/pubmed/35379824
http://dx.doi.org/10.1038/s41598-022-08782-0
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