Evidence map›Paper›PMID 41158728›Full record

ArticleTrauma surgery & acute care open2025

Traumatic brain injury (TBI) triage tool for low-risk patients: standardizing TBI care at a Level 1 trauma center.

Joshua A Villarreal, Mitchell Anderson, Kris Gallegos, Odette Harris, Karen Hirsch, Angela Lumba-Brown, Shashank Ravi, Kimberly Seifert, David Spain, Kristan Staudenmayer and 2 more

Abstract read
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In one paragraph

Article in Trauma surgery & acute care open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors.

Joshua A VillarrealDepartment of Surgery, Stanford University, Stanford, California, USA.ORCID https://orcid.org/0000-0001-6380-4880
Mitchell AndersonReno School of Medicine, University of Nevada, Reno, Nevada, USA.ORCID https://orcid.org/0009-0005-7475-3915
Kris GallegosDepartment of Surgery, Stanford University School of Medicine, Stanford, California, USA.
Odette HarrisDepartment of Neurosurgery, Stanford University, Stanford, California, USA.
Karen HirschDepartment of Neurology, Stanford University School of Medicine, Stanford, California, USA.
Angela Lumba-BrownDepartment of Emergency Medicine, Stanford University School of Medicine, Stanford, California, USA.
Shashank RaviDepartment of Emergency Medicine, Stanford University School of Medicine, Stanford, California, USA.
Kimberly SeifertDepartment of Radiology, Stanford University School of Medicine, Stanford, California, USA.
David SpainDepartment of Surgery, Stanford University, Stanford, California, USA.ORCID https://orcid.org/0000-0002-0477-7613
Kristan StaudenmayerDepartment of Surgery, Stanford University, Stanford, California, USA.ORCID https://orcid.org/0000-0001-5336-376X
Zachary ThrelkeldDepartment of Neurology, Stanford University School of Medicine, Stanford, California, USA.
Joseph D ForresterDepartment of Surgery, Stanford University School of Medicine, Stanford, California, USA.ORCID https://orcid.org/0000-0002-8558-6180

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Traumatic brain injury (TBI) remains a major healthcare burden, especially among older adults. Existing triage protocols, such as the Brain Injury Guidelines, may not be universally applicable due to institutional and implementation barriers. We evaluated the impact of a novel, evidence-based TBI triage tool-developed by a multidisciplinary team using high-risk and low-risk criteria-on hospital resource utilization at a high-volume Level 1 trauma center. The triage tool stratified patients into high-risk or low-risk pathways based on age, clinical criteria, and radiographic findings. We hypothesized that implementation would reduce intensive care unit (ICU) patient days and repeat head CT scans. Methods: We conducted a retrospective pre-post implementation study at an American College of Surgeons-verified Level 1 trauma center. The pre-implementation group included patients retrospectively categorized as low-risk from January to November 2021. The post implementation group included patients prospectively triaged as low-risk from January 2023 to June 2024. The triage tool was created through consensus from all relevant clinical stakeholders. Patient demographics, clinical outcomes, and hospital resource use were compared using Fisher's exact test, χ², and Mann-Whitney U tests. Results: A total of 145 patients were included (62 pre-implementation, 83 post implementation). Groups were well matched by demographics and clinical factors. Post implementation, 188 ICU-patient-days were projected to be saved, and ICU length of stay was significantly reduced (median (IQR): 1 (0-2) vs 0 (0-0) days; p<0.001). 38 repeat CT head scans were avoided, with overall scan frequency reduced (median (IQR): 2 (2-2) vs 2 (1-2); p<0.001). There were no neurosurgical interventions, in-hospital deaths, or 30-day readmissions in either group. Conclusion: Implementation of a multidisciplinary, risk-based TBI triage tool significantly reduced unnecessary ICU stays and repeat head CTs without observed adverse patient outcomes in the low-risk cohort. This approach represents a scalable, value-based model for improving TBI care and optimizing resource utilization. Level of evidence: Level III.

Indexed as

implementationresource utilizationtraumatic brain injury

Identifiers

PMID41158728
PMCPMC12557746

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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.