Cargando…
Sub-classifying patients with mild traumatic brain injury: A clustering approach based on baseline clinical characteristics and 90-day and 180-day outcomes
BACKGROUND: The current classification of traumatic brain injury (TBI) into “mild”, “moderate”, or “severe” does not adequately account for the patient heterogeneity that still exists within each of these categories. The objective of this study was to identify “sub-groups” of mild TBI (mTBI) patient...
Autores principales: | , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6040703/ https://www.ncbi.nlm.nih.gov/pubmed/29995912 http://dx.doi.org/10.1371/journal.pone.0198741 |
_version_ | 1783338877570777088 |
---|---|
author | Si, Bing Dumkrieger, Gina Wu, Teresa Zafonte, Ross Valadka, Alex B. Okonkwo, David O. Manley, Geoffrey T. Wang, Lujia Dodick, David W. Schwedt, Todd J. Li, Jing |
author_facet | Si, Bing Dumkrieger, Gina Wu, Teresa Zafonte, Ross Valadka, Alex B. Okonkwo, David O. Manley, Geoffrey T. Wang, Lujia Dodick, David W. Schwedt, Todd J. Li, Jing |
author_sort | Si, Bing |
collection | PubMed |
description | BACKGROUND: The current classification of traumatic brain injury (TBI) into “mild”, “moderate”, or “severe” does not adequately account for the patient heterogeneity that still exists within each of these categories. The objective of this study was to identify “sub-groups” of mild TBI (mTBI) patients based on data available at the time of the initial post-TBI patient evaluation and to determine if the sub-grouping correlates with patient outcomes at 90 and 180 days post-TBI. METHODS: Data from patients in the TRACK-TBI Pilot dataset who had a Glasgow Coma Scale (GCS) score of 13 to 15 at arrival to the Emergency Department and a closed head injury were included. Considering 53 clinical variables that are typically available during the initial evaluation of the patient with mild TBI, sparse heirarchial clustering with cluster quality assessment was used to identify the optimal number of patient sub-groups. Patient sub-groups were then compared for ten outcomes measured at 90 or 180 days post-TBI. RESULTS: Amongst the 485 patients with mTBI, optimal clustering was based on the inclusion of 12 clinical variables that divided the patients into 5 mild TBI sub-groups. Clinical variables driving the sub-clustering included: gender, employment status, marital status, TBI due to falling, brain CT scan result, systolic blood pressure, diastolic blood pressure, administration of IV fluids in the Emergency Department, alcohol use, tobacco use, history of neurologic disease, and history of psychiatric disease. These 5 mild TBI sub-groups differed in their 90 day and 180 day outcomes within several domains including global outcomes, persistence of TBI-related symptoms, and neuropsychological impairment. CONCLUSIONS: Sub-groups of patients with mTBI can be identified according to clinical variables that are relatively easy to obtain at the time of initial patient evaluation. A patient’s sub-group assignment is associated with multidimensional patient outcomes at 90 and 180 days. These findings support the notion that there are clinically meaningful subgroups of patients amongst those currently classified as having mTBI. |
format | Online Article Text |
id | pubmed-6040703 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-60407032018-07-19 Sub-classifying patients with mild traumatic brain injury: A clustering approach based on baseline clinical characteristics and 90-day and 180-day outcomes Si, Bing Dumkrieger, Gina Wu, Teresa Zafonte, Ross Valadka, Alex B. Okonkwo, David O. Manley, Geoffrey T. Wang, Lujia Dodick, David W. Schwedt, Todd J. Li, Jing PLoS One Research Article BACKGROUND: The current classification of traumatic brain injury (TBI) into “mild”, “moderate”, or “severe” does not adequately account for the patient heterogeneity that still exists within each of these categories. The objective of this study was to identify “sub-groups” of mild TBI (mTBI) patients based on data available at the time of the initial post-TBI patient evaluation and to determine if the sub-grouping correlates with patient outcomes at 90 and 180 days post-TBI. METHODS: Data from patients in the TRACK-TBI Pilot dataset who had a Glasgow Coma Scale (GCS) score of 13 to 15 at arrival to the Emergency Department and a closed head injury were included. Considering 53 clinical variables that are typically available during the initial evaluation of the patient with mild TBI, sparse heirarchial clustering with cluster quality assessment was used to identify the optimal number of patient sub-groups. Patient sub-groups were then compared for ten outcomes measured at 90 or 180 days post-TBI. RESULTS: Amongst the 485 patients with mTBI, optimal clustering was based on the inclusion of 12 clinical variables that divided the patients into 5 mild TBI sub-groups. Clinical variables driving the sub-clustering included: gender, employment status, marital status, TBI due to falling, brain CT scan result, systolic blood pressure, diastolic blood pressure, administration of IV fluids in the Emergency Department, alcohol use, tobacco use, history of neurologic disease, and history of psychiatric disease. These 5 mild TBI sub-groups differed in their 90 day and 180 day outcomes within several domains including global outcomes, persistence of TBI-related symptoms, and neuropsychological impairment. CONCLUSIONS: Sub-groups of patients with mTBI can be identified according to clinical variables that are relatively easy to obtain at the time of initial patient evaluation. A patient’s sub-group assignment is associated with multidimensional patient outcomes at 90 and 180 days. These findings support the notion that there are clinically meaningful subgroups of patients amongst those currently classified as having mTBI. Public Library of Science 2018-07-11 /pmc/articles/PMC6040703/ /pubmed/29995912 http://dx.doi.org/10.1371/journal.pone.0198741 Text en © 2018 Si et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Si, Bing Dumkrieger, Gina Wu, Teresa Zafonte, Ross Valadka, Alex B. Okonkwo, David O. Manley, Geoffrey T. Wang, Lujia Dodick, David W. Schwedt, Todd J. Li, Jing Sub-classifying patients with mild traumatic brain injury: A clustering approach based on baseline clinical characteristics and 90-day and 180-day outcomes |
title | Sub-classifying patients with mild traumatic brain injury: A clustering approach based on baseline clinical characteristics and 90-day and 180-day outcomes |
title_full | Sub-classifying patients with mild traumatic brain injury: A clustering approach based on baseline clinical characteristics and 90-day and 180-day outcomes |
title_fullStr | Sub-classifying patients with mild traumatic brain injury: A clustering approach based on baseline clinical characteristics and 90-day and 180-day outcomes |
title_full_unstemmed | Sub-classifying patients with mild traumatic brain injury: A clustering approach based on baseline clinical characteristics and 90-day and 180-day outcomes |
title_short | Sub-classifying patients with mild traumatic brain injury: A clustering approach based on baseline clinical characteristics and 90-day and 180-day outcomes |
title_sort | sub-classifying patients with mild traumatic brain injury: a clustering approach based on baseline clinical characteristics and 90-day and 180-day outcomes |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6040703/ https://www.ncbi.nlm.nih.gov/pubmed/29995912 http://dx.doi.org/10.1371/journal.pone.0198741 |
work_keys_str_mv | AT sibing subclassifyingpatientswithmildtraumaticbraininjuryaclusteringapproachbasedonbaselineclinicalcharacteristicsand90dayand180dayoutcomes AT dumkriegergina subclassifyingpatientswithmildtraumaticbraininjuryaclusteringapproachbasedonbaselineclinicalcharacteristicsand90dayand180dayoutcomes AT wuteresa subclassifyingpatientswithmildtraumaticbraininjuryaclusteringapproachbasedonbaselineclinicalcharacteristicsand90dayand180dayoutcomes AT zafonteross subclassifyingpatientswithmildtraumaticbraininjuryaclusteringapproachbasedonbaselineclinicalcharacteristicsand90dayand180dayoutcomes AT valadkaalexb subclassifyingpatientswithmildtraumaticbraininjuryaclusteringapproachbasedonbaselineclinicalcharacteristicsand90dayand180dayoutcomes AT okonkwodavido subclassifyingpatientswithmildtraumaticbraininjuryaclusteringapproachbasedonbaselineclinicalcharacteristicsand90dayand180dayoutcomes AT manleygeoffreyt subclassifyingpatientswithmildtraumaticbraininjuryaclusteringapproachbasedonbaselineclinicalcharacteristicsand90dayand180dayoutcomes AT wanglujia subclassifyingpatientswithmildtraumaticbraininjuryaclusteringapproachbasedonbaselineclinicalcharacteristicsand90dayand180dayoutcomes AT dodickdavidw subclassifyingpatientswithmildtraumaticbraininjuryaclusteringapproachbasedonbaselineclinicalcharacteristicsand90dayand180dayoutcomes AT schwedttoddj subclassifyingpatientswithmildtraumaticbraininjuryaclusteringapproachbasedonbaselineclinicalcharacteristicsand90dayand180dayoutcomes AT lijing subclassifyingpatientswithmildtraumaticbraininjuryaclusteringapproachbasedonbaselineclinicalcharacteristicsand90dayand180dayoutcomes |