Evidence map›Paper›PMID 38618713›Full record

Trial reportJournal of neurotrauma2024

Predicting Progression of Intracranial Hemorrhage in the Prehospital TXA for TBI Trial.

H E Hinson, Hannah L Radabaugh, Nincheng Li, Toshinori Fukuda, Jeffrey Pollock, Martin Schreiber, Susan Rowell, Adam R Ferguson

Open access · greenAbstract readRandomized Controlled TrialMulticenter StudyClinical Trial, Phase II
PubMed Full text at PMC Publisher
In one paragraph

Trial report in Journal of neurotrauma, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.1field-weighted citation impact, top 23% of its field
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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Machine Learning Approaches to Prognostication in Traumatic Brain Injury.Current neurology and neuroscience reports · 2025
    Review
  2. Review
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

8 authors at 4 institutions in 1 country.

H E HinsonDepartment of Neurology, University of California, San Francisco, California, USA.ORCID 0000-0003-1598-9782
Hannah L RadabaughDepartment of Neurological Surgery, University of California, San Francisco, California, USA.
Nincheng LiDepartment of Radiology, Division of Interventional Radiology University of Massachusetts Chan Medical School, Worcester, Massachusetts, USA.
Toshinori FukudaDepartment of Radiology, Oregon Health and Science University, Portland, Oregon, USA.
Jeffrey PollockDepartment of Radiology, Oregon Health and Science University, Portland, Oregon, USA.
Martin SchreiberDonald D. Trunkey Center for Civilian and Combat Casualty Care, Oregon Health and Science University, Portland, Oregon, USA.
Susan RowellDepartment of Surgery, University of Chicago, Chicago, Illinois, USA.
Adam R FergusonDepartment of Neurological Surgery, University of California, San Francisco, California, USA.
Oregon Health & Science University · USUniversity of California, San Francisco · USUniversity of Chicago · USUniversity of Massachusetts Chan Medical School · US

Funding

Predictors of Low-risk Phenotypes after Traumatic Brain Injury Incorporating Proteomic Biomarker Signatures.K23NS110828 · NINDS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI HINSON, HOLLY ELAINE · 2020 to 2024
$1.0M
NINDS NIH HHS K23 NS110828
6 · The paper itself

Abstract

Progression of intracranial hemorrhage is a common, potentially devastating complication after moderate/severe traumatic brain injury (TBI). Clinicians have few tools to predict which patients with traumatic intracranial hemorrhage on their initial head computed tomography (hCT) scan will progress. The objective of this investigation was to identify clinical, imaging, and/or protein biomarkers associated with progression of intracranial hemorrhage (PICH) after moderate/severe TBI and to create an accurate predictive model of PICH based on clinical features available at presentation. We analyzed a subset of subjects from the phase II double-blind, multi-center, randomized "Prehospital Tranexamic Acid Use for TBI" trial. This subset was limited to the placebo arm of the parent trial with evidence of hemorrhage on the initial hCT and a follow-up hCT 6 h after. PICH was defined as an increase in hemorrhage size by 30% or more, or the development of new hemorrhage in the intra- and extra-axial intracranial vault between the initial and the follow-up hCT. Two independent radiologists evaluated each hCT, and conflicts were adjudicated by a third. Clinical and radiographic characteristics were collected, along with plasma protein biomarkers at admission. Principal component analysis (PCA) was performed, and each principal component (PC) was interrogated for its association with PICH. Finally, expert opinion and recursive feature extraction (RFE) were used to select input features for the construction of several supervised classification models. Their ability to predict PICH was quantified and compared. In this subset of subjects (

Indexed as

Brain Injuries, TraumaticDisease ProgressionAdultAntifibrinolytic AgentsBiomarkersDouble-Blind MethodEmergency Medical ServicesFemaleHumansIntracranial HemorrhagesMaleMiddle AgedPredictive Value of TestsTomography, X-Ray ComputedTranexamic AcidYoung AdultAntifibrinolytic AgentsBiomarkersTranexamic Acidmachine learningprogression of hemorrhagetraumatic brain injury

Identifiers

PMID38618713
PMCPMC11564838
OpenAlexW4394815257

What OpenQuestion holds

Textmetadata
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.