Evidence map›Paper›PMID 33858210›Full record

ReviewJournal of neurotrauma2021

Phenotyping the Spectrum of Traumatic Brain Injury: A Review and Pathway to Standardization.

Mary Jo Pugh, Eamonn Kennedy, Eric M Prager, Jeffrey Humpherys, Kristen Dams-O'Connor, Dallas Hack, Mary Katherine McCafferty, Jessica Wolfe, Kristine Yaffe, Michael McCrea and 4 more

Abstract readReview
In one paragraph

Review in Journal of neurotrauma, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

34 citing papers in PubMed.

  1. Observational
  2. Review
  3. Phenotype discovery of traumatic brain injury segmentations from heterogeneous multi-site data.Proceedings of SPIE--the International Society for Optical Engineering · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Mary Jo PughInformatics, Decision-Enhancement and Analytic Sciences Center, VA Salt Lake City, Salt Lake City, Utah, USA.
Eamonn KennedyInformatics, Decision-Enhancement and Analytic Sciences Center, VA Salt Lake City, Salt Lake City, Utah, USA.
Eric M PragerCohen Veterans Bioscience, New York, New York, USA.
Jeffrey HumpherysInformatics, Decision-Enhancement and Analytic Sciences Center, VA Salt Lake City, Salt Lake City, Utah, USA.
Kristen Dams-O'ConnorDepartment of Rehabilitation and Human Performance, Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Dallas HackCohen Veterans Bioscience, New York, New York, USA.
Mary Katherine McCaffertyInformatics, Decision-Enhancement and Analytic Sciences Center, VA Salt Lake City, Salt Lake City, Utah, USA.
Jessica WolfeCohen Veterans Bioscience, New York, New York, USA.
Kristine YaffeDepartment of Neurology, University of California San Francisco, California, USA.
Michael McCreaDepartment of Neurosurgery, Medical College of Wisconsin, Milwaukee Wisconsin, USA.
Adam R FergusonDepartment of Neurological Surgery, University of California San Francisco, California, USA.
Lee LancashireCohen Veterans Bioscience, New York, New York, USA.
Jamshid GhajarDepartment of Neurosurgery, Stanford University School of Medicine, Stanford, California, USA.
Angela Lumba-BrownDepartment of Emergency Medicine, Stanford University School of Medicine, Stanford, California, USA.

Funding

Maladaptive Plasticity in Spinal Cord Injury: Cellular MechanismsR01NS088475 · NINDS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI FERGUSON, ADAM R · 2015 to 2019
$1.7M
Translational Outcomes Project: Visualizing Syndromic Information and Outcomes for Neurotrauma (TOP-VISION)UG3NS106899 · NINDS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI BEATTIE, MICHAEL S, BRESNAHAN, JACQUELINE C · 2018 to 2019
$480k
NINDS NIH HHS R01 NS088475NINDS NIH HHS UG3 NS106899
6 · The paper itself

Abstract

It is widely appreciated that the spectrum of traumatic brain injury (TBI), mild through severe, contains distinct clinical presentations, variably referred to as subtypes, phenotypes, and/or clinical profiles. As part of the Brain Trauma Blueprint TBI State of the Science, we review the current literature on TBI phenotyping with an emphasis on unsupervised methodological approaches, and describe five phenotypes that appear similar across reports. However, we also find the literature contains divergent analysis strategies, inclusion criteria, findings, and use of terms. Further, whereas some studies delineate phenotypes within a specific severity of TBI, others derive phenotypes across the full spectrum of severity. Together, these facts confound direct synthesis of the findings. To overcome this, we introduce PhenoBench, a freely available code repository for the standardization and evaluation of raw phenotyping data. With this review and toolset, we provide a pathway toward robust, data-driven phenotypes that can capture the heterogeneity of TBI, enabling reproducible insights and targeted care.

Indexed as

Brain Injuries, TraumaticMachine LearningHumansPhenotypeReference Standardsclinical profilesclusteringcomaconcussionmeta-analysisphenotypessubclassificationsubtypestraumatic brain injury

Identifiers

PMID33858210
PMCPMC8917880

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.