Evidence map›Paper›PMID 39212991›Full record

ArticleJAMA network open2024

Automated Measurement of Cerebral Hemorrhagic Contusions and Outcomes After Traumatic Brain Injury in the TRACK-TBI Study.

Samuel B Snider, Nancy R Temkin, Xiaoying Sun, Jacob L Stubbs, Quinn J Rademaker, Amy J Markowitz, Eric S Rosenthal, Ramon Diaz-Arrastia, Michael D Fox, Geoffrey T Manley and 3 more

Abstract read
In one paragraph

Article in JAMA network open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Preservation of anticorrelated brain networks predicts recovery after traumatic brain injury.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
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

13 authors.

Samuel B SniderDivision of Neurocritical Care, Department of Neurology, Brigham and Women's Hospital, Boston, Massachusetts.
Nancy R TemkinDepartment of Neurological Surgery, University of Washington, Seattle.
Xiaoying SunBiostatistics Research Center, Herbert Wertheim School of Public Health, University of California, San Diego.
Jacob L StubbsDepartment of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.
Quinn J RademakerDivision of Neurocritical Care, Department of Neurology, Brigham and Women's Hospital, Boston, Massachusetts.
Amy J MarkowitzDepartment of Neurological Surgery, University of California, San Francisco.
Eric S RosenthalHarvard Medical School, Boston, Massachusetts.
Ramon Diaz-ArrastiaDepartment of Neurology, University of Pennsylvania, Philadelphia.
Michael D FoxHarvard Medical School, Boston, Massachusetts.
Geoffrey T ManleyDepartment of Neurological Surgery, University of California, San Francisco.
Sonia JainBiostatistics Research Center, Herbert Wertheim School of Public Health, University of California, San Diego.
Brian L EdlowHarvard Medical School, Boston, Massachusetts.
TRACK-TBI Investigators

Funding

SNSPD-DCS at 1064 nm for non-invasive monitoring of cerebral perfusion and intracranial pressure in the ICUU01EB034228 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI Maria Angela Franceschini · 2023 to 2026
$2.9M
A Connectome-Based Clinical Trial Platform to Promote Early Recovery of Consciousness after Traumatic ComaDP2HD101400 · NICHD · MASSACHUSETTS GENERAL HOSPITAL · PI EDLOW, BRIAN L. · 2019 to 2019
$2.5M
Predicting Dependency after Traumatic Brain InjuryK23NS136767 · NINDS · BRIGHAM AND WOMEN'S HOSPITAL · PI Samuel Snider · 2024 to 2026
$685k
NIBIB NIH HHS U01 EB034228NICHD NIH HHS DP2 HD101400NINDS NIH HHS K23 NS136767
6 · The paper itself

Abstract

Importance: Because withdrawal of life-sustaining therapy based on perceived poor prognosis is the most common cause of death after moderate or severe traumatic brain injury (TBI), the accuracy of clinical prognoses is directly associated with mortality. Although the location of brain injury is known to be important for determining recovery potential after TBI, the best available prognostic models, such as the International Mission for Prognosis and Analysis of Clinical Trials in TBI (IMPACT) score, do not currently incorporate brain injury location. Objective: To test whether automated measurement of cerebral hemorrhagic contusion size and location is associated with improved prognostic performance of the IMPACT score. Design, Setting, and Participants: This prognostic cohort study was performed in 18 US level 1 trauma centers between February 26, 2014, and August 8, 2018. Adult participants aged 17 years or older from the US-based Transforming Research and Clinical Knowledge in TBI (TRACK-TBI) study with moderate or severe TBI (Glasgow Coma Scale score 3-12) and contusions detected on brain computed tomography (CT) scans were included. The data analysis was performed between January 2023 and February 2024. Exposures: Labeled contusions detected on CT scans using Brain Lesion Analysis and Segmentation Tool for Computed Tomography (BLAST-CT), a validated artificial intelligence algorithm. Main Outcome and Measure: The primary outcome was a Glasgow Outcome Scale-Extended (GOSE) score of 4 or less at 6 months after injury. Whether frontal or temporal lobe contusion volumes improved the performance of the IMPACT score was tested using logistic regression and area under the receiver operating characteristic curve comparisons. Sparse canonical correlation analysis was used to generate a disability heat map to visualize the strongest brainwide associations with outcomes. Results: The cohort included 291 patients with moderate or severe TBI and contusions (mean [SD] age, 42 [18] years; 221 [76%] male; median [IQR] emergency department arrival Glasgow Coma Scale score, 5 [3-10]). Only temporal contusion volumes improved the discrimination of the IMPACT score (area under the receiver operating characteristic curve, 0.86 vs 0.84; P = .03). The data-derived disability heat map of contusion locations showed that the strongest association with unfavorable outcomes was within the bilateral temporal and medial frontal lobes. Conclusions and Relevance: These findings suggest that CT-based automated contusion measurement may be an immediately translatable strategy for improving TBI prognostic models.

Indexed as

Brain Injuries, TraumaticTomography, X-Ray ComputedAdultCohort StudiesFemaleGlasgow Coma ScaleHumansMaleMiddle AgedPrognosis

Identifiers

PMID39212991
PMCPMC11365003

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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.