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Sex-specific analysis of traumatic brain injury events: applying computational and data visualization techniques to inform prevention and management

BACKGROUND: The interplay of host, agent, and environment implicated in traumatic brain injury (TBI) events is difficult to account for in hypothesis-driven research. Data-driven analysis of injury data can enable insight into injury events in novel ways. This research dissected complex and multidim...

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Autores principales: Mollayeva, Tatyana, Tran, Andrew, Chan, Vincy, Colantonio, Angela, Escobar, Michael D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8802441/
https://www.ncbi.nlm.nih.gov/pubmed/35094688
http://dx.doi.org/10.1186/s12874-021-01493-6
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author Mollayeva, Tatyana
Tran, Andrew
Chan, Vincy
Colantonio, Angela
Escobar, Michael D.
author_facet Mollayeva, Tatyana
Tran, Andrew
Chan, Vincy
Colantonio, Angela
Escobar, Michael D.
author_sort Mollayeva, Tatyana
collection PubMed
description BACKGROUND: The interplay of host, agent, and environment implicated in traumatic brain injury (TBI) events is difficult to account for in hypothesis-driven research. Data-driven analysis of injury data can enable insight into injury events in novel ways. This research dissected complex and multidimensional data at the time of the TBI event by exploiting data mining and information visualization methods. METHODS: We drew upon population-based decade-long health administrative data collected through the routine operation of the publicly funded health system in Ontario, Canada. We applied a computational approach to categorize health records of 235,003 patients with TBI versus the same number of reference patients without TBI, individually matched based on sex, age, place of residence, and neighbourhood income quantile. We adopted the basic concepts of the Haddon Matrix (host, agent, environment) to organize emerging factors significantly related to TBI versus non-TBI events. To explore sex differences, the data of male and female patients with TBI were plotted on heatmaps and clustered using hierarchical clustering algorithms. RESULTS: Based on detected similarities, the computational technique yielded 34 factors on which individual TBI-event codes were loaded, allowing observation of a set of definable patterns within the host, the agent, and the environment. Differences in the patterns of host, agent and environment were found between male and female patients with TBI, which are currently not identified based on data from injury surveillance databases. The results were internally validated. CONCLUSIONS: The study outlines novel areas for research relevant to TBI and offers insight into how computational and visual techniques can be applied to advance the understanding of TBI event. Results highlight unique aspects of sex differences of the host and agent at the injury event, as well as differences in exposure to adverse social and environmental circumstances, which can be a function of gender, aiding in future studies of injury prevention and gender-transformative care. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12874-021-01493-6.
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spelling pubmed-88024412022-02-02 Sex-specific analysis of traumatic brain injury events: applying computational and data visualization techniques to inform prevention and management Mollayeva, Tatyana Tran, Andrew Chan, Vincy Colantonio, Angela Escobar, Michael D. BMC Med Res Methodol Research BACKGROUND: The interplay of host, agent, and environment implicated in traumatic brain injury (TBI) events is difficult to account for in hypothesis-driven research. Data-driven analysis of injury data can enable insight into injury events in novel ways. This research dissected complex and multidimensional data at the time of the TBI event by exploiting data mining and information visualization methods. METHODS: We drew upon population-based decade-long health administrative data collected through the routine operation of the publicly funded health system in Ontario, Canada. We applied a computational approach to categorize health records of 235,003 patients with TBI versus the same number of reference patients without TBI, individually matched based on sex, age, place of residence, and neighbourhood income quantile. We adopted the basic concepts of the Haddon Matrix (host, agent, environment) to organize emerging factors significantly related to TBI versus non-TBI events. To explore sex differences, the data of male and female patients with TBI were plotted on heatmaps and clustered using hierarchical clustering algorithms. RESULTS: Based on detected similarities, the computational technique yielded 34 factors on which individual TBI-event codes were loaded, allowing observation of a set of definable patterns within the host, the agent, and the environment. Differences in the patterns of host, agent and environment were found between male and female patients with TBI, which are currently not identified based on data from injury surveillance databases. The results were internally validated. CONCLUSIONS: The study outlines novel areas for research relevant to TBI and offers insight into how computational and visual techniques can be applied to advance the understanding of TBI event. Results highlight unique aspects of sex differences of the host and agent at the injury event, as well as differences in exposure to adverse social and environmental circumstances, which can be a function of gender, aiding in future studies of injury prevention and gender-transformative care. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12874-021-01493-6. BioMed Central 2022-01-30 /pmc/articles/PMC8802441/ /pubmed/35094688 http://dx.doi.org/10.1186/s12874-021-01493-6 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Mollayeva, Tatyana
Tran, Andrew
Chan, Vincy
Colantonio, Angela
Escobar, Michael D.
Sex-specific analysis of traumatic brain injury events: applying computational and data visualization techniques to inform prevention and management
title Sex-specific analysis of traumatic brain injury events: applying computational and data visualization techniques to inform prevention and management
title_full Sex-specific analysis of traumatic brain injury events: applying computational and data visualization techniques to inform prevention and management
title_fullStr Sex-specific analysis of traumatic brain injury events: applying computational and data visualization techniques to inform prevention and management
title_full_unstemmed Sex-specific analysis of traumatic brain injury events: applying computational and data visualization techniques to inform prevention and management
title_short Sex-specific analysis of traumatic brain injury events: applying computational and data visualization techniques to inform prevention and management
title_sort sex-specific analysis of traumatic brain injury events: applying computational and data visualization techniques to inform prevention and management
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8802441/
https://www.ncbi.nlm.nih.gov/pubmed/35094688
http://dx.doi.org/10.1186/s12874-021-01493-6
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