Beyond mild, moderate, and severe traumatic brain injury: modelling severity from clinical, neuroimaging, and blood-based indicators

Lindsay D Nelson; Brooke E Magnus; John K Yue; Steve Balsis; Christopher J Patrick; Nancy Temkin; Esther L Yuh; Ramon Diaz-Arrastia; Ehri Ryu; Andrew I R Maas; David K Menon; Lindsay Wilson; Geoffrey T Manley; TRACK-TBI Investigators; Ramesh Grandhi; C. Dirk Keene; Christopher Madden; Michael McCrea; Randall Merchant; Pratik Mukherjee; Laura B Ngwenya; Ava Puccio; Claudia Robertson; David  Schnyer; Sabrina R. Taylor; Mary  Vassar

doi:10.1016/j.ebiom.2025.106001

Beyond mild, moderate, and severe traumatic brain injury: modelling severity from clinical, neuroimaging, and blood-based indicators

Lindsay D Nelson^*
, Brooke E Magnus
, John K Yue
, Steve Balsis
, Christopher J Patrick
, Nancy Temkin
, Esther L Yuh
, Ramon Diaz-Arrastia
, Ehri Ryu
, Andrew I R Maas
, David K Menon
, Lindsay Wilson
, Geoffrey T Manley
, TRACK-TBI Investigators
, Ramesh Grandhi
, C. Dirk Keene
, Christopher Madden
, Michael McCrea
, Randall Merchant
, Pratik Mukherjee

Laura B Ngwenya, Ava Puccio, Claudia Robertson, David Schnyer, Sabrina R. Taylor, Mary Vassar

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

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Abstract

BACKGROUND: The conventional clinical approach to characterising traumatic brain injuries (TBIs) as mild, moderate, or severe using the Glasgow Coma Scale (GCS) total score has well-known limitations, prompting calls for more sophisticated strategies.

METHODS: We used item response theory (IRT) to develop a new method for quantifying TBI severity using 24 clinical, head computed tomography, and blood-based biomarker variables familiar to clinicians and researchers. IRT uses individuals' response patterns across indicators to estimate relationships between the indicators and a latent continuum of TBI severity. Model parameters were used to assign severity scores in two large cohorts, and associations with traditional GCS categories and 6-month functional outcomes (Glasgow Outcome Scale-Extended [GOSE]) were tested with correlational and logistic regression analyses.

FINDINGS: In the prospective Transforming Research and Clinical Knowledge in TBI (TRACK-TBI) cohort (N = 2545), modelling showed the 24 indicators index a common latent continuum of TBI severity. IRT enabled us to identify the relative contribution of these features to estimate an individual's TBI severity. Finally, within both the TRACK-TBI derivation sample and an external validation sample (Collaborative European NeuroTrauma Effectiveness Research in TBI [CENTER-TBI]), TBI severity scores generated using this novel IRT-based method incrementally predicted functional (GOSE) outcome better than classic clinical (mild, moderate, severe) or International Mission for Prognosis and Analysis of Clinical Trials in TBI (IMPACT) classification methods.

INTERPRETATION: Our findings directly inform ongoing international efforts to refine and deploy new pragmatic, empirically-supported strategies for characterising TBI, while illustrating a strategy that may be useful to improve staging systems for other diseases.

FUNDING: This secondary analysis project was funded by the U.S. National Institute of Neurological Disorders and Stroke (Grant No. R01 NS110856).

Original language	English
Pages (from-to)	106001
Number of pages	15
Journal	EBioMedicine
Volume	121
DOIs	https://doi.org/10.1016/j.ebiom.2025.106001
Publication status	Published - 4 Nov 2025

Keywords

Humans
Brain Injuries, Traumatic/diagnosis
Male
Female
Biomarkers/blood
Middle Aged
Adult
Neuroimaging/methods
Severity of Illness Index
Tomography, X-Ray Computed
Glasgow Coma Scale
Aged
Glasgow Outcome Scale
Young Adult

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Nelson, L. D., Magnus, B. E., Yue, J. K., Balsis, S., Patrick, C. J., Temkin, N., Yuh, E. L., Diaz-Arrastia, R., Ryu, E., Maas, A. I. R., Menon, D. K., Wilson, L., Manley, G. T., TRACK-TBI Investigators, Grandhi, R., Keene, C. D., Madden, C., McCrea, M., Merchant, R., ... Vassar, M. (2025). Beyond mild, moderate, and severe traumatic brain injury: modelling severity from clinical, neuroimaging, and blood-based indicators. EBioMedicine, 121, 106001. https://doi.org/10.1016/j.ebiom.2025.106001

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title = "Beyond mild, moderate, and severe traumatic brain injury: modelling severity from clinical, neuroimaging, and blood-based indicators",

abstract = "BACKGROUND: The conventional clinical approach to characterising traumatic brain injuries (TBIs) as mild, moderate, or severe using the Glasgow Coma Scale (GCS) total score has well-known limitations, prompting calls for more sophisticated strategies.METHODS: We used item response theory (IRT) to develop a new method for quantifying TBI severity using 24 clinical, head computed tomography, and blood-based biomarker variables familiar to clinicians and researchers. IRT uses individuals' response patterns across indicators to estimate relationships between the indicators and a latent continuum of TBI severity. Model parameters were used to assign severity scores in two large cohorts, and associations with traditional GCS categories and 6-month functional outcomes (Glasgow Outcome Scale-Extended [GOSE]) were tested with correlational and logistic regression analyses.FINDINGS: In the prospective Transforming Research and Clinical Knowledge in TBI (TRACK-TBI) cohort (N = 2545), modelling showed the 24 indicators index a common latent continuum of TBI severity. IRT enabled us to identify the relative contribution of these features to estimate an individual's TBI severity. Finally, within both the TRACK-TBI derivation sample and an external validation sample (Collaborative European NeuroTrauma Effectiveness Research in TBI [CENTER-TBI]), TBI severity scores generated using this novel IRT-based method incrementally predicted functional (GOSE) outcome better than classic clinical (mild, moderate, severe) or International Mission for Prognosis and Analysis of Clinical Trials in TBI (IMPACT) classification methods.INTERPRETATION: Our findings directly inform ongoing international efforts to refine and deploy new pragmatic, empirically-supported strategies for characterising TBI, while illustrating a strategy that may be useful to improve staging systems for other diseases.FUNDING: This secondary analysis project was funded by the U.S. National Institute of Neurological Disorders and Stroke (Grant No. R01 NS110856).",

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author = "Nelson, \{Lindsay D\} and Magnus, \{Brooke E\} and Yue, \{John K\} and Steve Balsis and Patrick, \{Christopher J\} and Nancy Temkin and Yuh, \{Esther L\} and Ramon Diaz-Arrastia and Ehri Ryu and Maas, \{Andrew I R\} and Menon, \{David K\} and Lindsay Wilson and Manley, \{Geoffrey T\} and \{TRACK-TBI Investigators\} and Ramesh Grandhi and Keene, \{C. Dirk\} and Christopher Madden and Michael McCrea and Randall Merchant and Pratik Mukherjee and Ngwenya, \{Laura B\} and Ava Puccio and Claudia Robertson and David Schnyer and Taylor, \{Sabrina R.\} and Mary Vassar and Tony Belli",

year = "2025",

month = nov,

day = "4",

doi = "10.1016/j.ebiom.2025.106001",

language = "English",

volume = "121",

pages = "106001",

journal = "EBioMedicine",

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publisher = "Elsevier",

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Nelson, LD, Magnus, BE, Yue, JK, Balsis, S, Patrick, CJ, Temkin, N, Yuh, EL, Diaz-Arrastia, R, Ryu, E, Maas, AIR, Menon, DK, Wilson, L, Manley, GT, TRACK-TBI Investigators, Grandhi, R, Keene, CD, Madden, C, McCrea, M, Merchant, R, Mukherjee, P, Ngwenya, LB, Puccio, A, Robertson, C, Schnyer, D, Taylor, SR & Vassar, M 2025, 'Beyond mild, moderate, and severe traumatic brain injury: modelling severity from clinical, neuroimaging, and blood-based indicators', EBioMedicine, vol. 121, pp. 106001. https://doi.org/10.1016/j.ebiom.2025.106001

TY - JOUR

T1 - Beyond mild, moderate, and severe traumatic brain injury

T2 - modelling severity from clinical, neuroimaging, and blood-based indicators

AU - Nelson, Lindsay D

AU - Magnus, Brooke E

AU - Yue, John K

AU - Balsis, Steve

AU - Patrick, Christopher J

AU - Temkin, Nancy

AU - Yuh, Esther L

AU - Diaz-Arrastia, Ramon

AU - Ryu, Ehri

AU - Maas, Andrew I R

AU - Menon, David K

AU - Wilson, Lindsay

AU - Manley, Geoffrey T

AU - TRACK-TBI Investigators

AU - Grandhi, Ramesh

AU - Keene, C. Dirk

AU - Madden, Christopher

AU - McCrea, Michael

AU - Merchant, Randall

AU - Mukherjee, Pratik

AU - Ngwenya, Laura B

AU - Puccio, Ava

AU - Robertson, Claudia

AU - Schnyer, David

AU - Taylor, Sabrina R.

AU - Vassar, Mary

AU - Belli, Tony

PY - 2025/11/4

Y1 - 2025/11/4

N2 - BACKGROUND: The conventional clinical approach to characterising traumatic brain injuries (TBIs) as mild, moderate, or severe using the Glasgow Coma Scale (GCS) total score has well-known limitations, prompting calls for more sophisticated strategies.METHODS: We used item response theory (IRT) to develop a new method for quantifying TBI severity using 24 clinical, head computed tomography, and blood-based biomarker variables familiar to clinicians and researchers. IRT uses individuals' response patterns across indicators to estimate relationships between the indicators and a latent continuum of TBI severity. Model parameters were used to assign severity scores in two large cohorts, and associations with traditional GCS categories and 6-month functional outcomes (Glasgow Outcome Scale-Extended [GOSE]) were tested with correlational and logistic regression analyses.FINDINGS: In the prospective Transforming Research and Clinical Knowledge in TBI (TRACK-TBI) cohort (N = 2545), modelling showed the 24 indicators index a common latent continuum of TBI severity. IRT enabled us to identify the relative contribution of these features to estimate an individual's TBI severity. Finally, within both the TRACK-TBI derivation sample and an external validation sample (Collaborative European NeuroTrauma Effectiveness Research in TBI [CENTER-TBI]), TBI severity scores generated using this novel IRT-based method incrementally predicted functional (GOSE) outcome better than classic clinical (mild, moderate, severe) or International Mission for Prognosis and Analysis of Clinical Trials in TBI (IMPACT) classification methods.INTERPRETATION: Our findings directly inform ongoing international efforts to refine and deploy new pragmatic, empirically-supported strategies for characterising TBI, while illustrating a strategy that may be useful to improve staging systems for other diseases.FUNDING: This secondary analysis project was funded by the U.S. National Institute of Neurological Disorders and Stroke (Grant No. R01 NS110856).

AB - BACKGROUND: The conventional clinical approach to characterising traumatic brain injuries (TBIs) as mild, moderate, or severe using the Glasgow Coma Scale (GCS) total score has well-known limitations, prompting calls for more sophisticated strategies.METHODS: We used item response theory (IRT) to develop a new method for quantifying TBI severity using 24 clinical, head computed tomography, and blood-based biomarker variables familiar to clinicians and researchers. IRT uses individuals' response patterns across indicators to estimate relationships between the indicators and a latent continuum of TBI severity. Model parameters were used to assign severity scores in two large cohorts, and associations with traditional GCS categories and 6-month functional outcomes (Glasgow Outcome Scale-Extended [GOSE]) were tested with correlational and logistic regression analyses.FINDINGS: In the prospective Transforming Research and Clinical Knowledge in TBI (TRACK-TBI) cohort (N = 2545), modelling showed the 24 indicators index a common latent continuum of TBI severity. IRT enabled us to identify the relative contribution of these features to estimate an individual's TBI severity. Finally, within both the TRACK-TBI derivation sample and an external validation sample (Collaborative European NeuroTrauma Effectiveness Research in TBI [CENTER-TBI]), TBI severity scores generated using this novel IRT-based method incrementally predicted functional (GOSE) outcome better than classic clinical (mild, moderate, severe) or International Mission for Prognosis and Analysis of Clinical Trials in TBI (IMPACT) classification methods.INTERPRETATION: Our findings directly inform ongoing international efforts to refine and deploy new pragmatic, empirically-supported strategies for characterising TBI, while illustrating a strategy that may be useful to improve staging systems for other diseases.FUNDING: This secondary analysis project was funded by the U.S. National Institute of Neurological Disorders and Stroke (Grant No. R01 NS110856).

KW - Humans

KW - Brain Injuries, Traumatic/diagnosis

KW - Male

KW - Female

KW - Biomarkers/blood

KW - Middle Aged

KW - Adult

KW - Neuroimaging/methods

KW - Severity of Illness Index

KW - Tomography, X-Ray Computed

KW - Glasgow Coma Scale

KW - Aged

KW - Glasgow Outcome Scale

KW - Young Adult

U2 - 10.1016/j.ebiom.2025.106001

DO - 10.1016/j.ebiom.2025.106001

M3 - Article

C2 - 41192220

SN - 2352-3964

VL - 121

SP - 106001

JO - EBioMedicine

JF - EBioMedicine

ER -

Beyond mild, moderate, and severe traumatic brain injury: modelling severity from clinical, neuroimaging, and blood-based indicators

Abstract

Keywords

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