Evidence map›Paper›PMID 41725730›Full record

SynthesisFrontiers in neurology

The second decade of DTI in TBI Part 2: a systematic review of moderate and severe TBI.

Molly F Charney, Simone Glajchen, Shawn Brain, Fahmida Rashid, Sabrina Kentis, Melvin Alexander, Arvind Dev, Jenasis Ortega, Chihiro Okada, Brian Morris and 9 more

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in neurology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

19 authors.

Molly F CharneyDepartment of Neurology, Columbia University Irving Medical Center, New York, NY, United States.
Simone GlajchenDepartment of Radiology, Columbia University Irving Medical Center, New York, NY, United States.
Shawn BrainTouro College of Osteopathic Medicine, New York, NY, United States.
Fahmida RashidDepartment of Radiology, University of California Los Angeles, Los Angeles, CA, United States.
Sabrina KentisAlbert Einstein College of Medicine, Bronx, NY, United States.
Melvin AlexanderAlbert Einstein College of Medicine, Bronx, NY, United States.
Arvind DevAlbert Einstein College of Medicine, Bronx, NY, United States.
Jenasis OrtegaAlbert Einstein College of Medicine, Bronx, NY, United States.
Chihiro OkadaDepartment of Neurology, New York University Langone Hospital, New York, NY, United States.
Brian MorrisDepartment of Neurology, New York University Langone Hospital, New York, NY, United States.
Timothy DarbyDepartment of Radiology, Lennox Hill Hospital, New York, NY, United States.
Taskin ForkanAlbert Einstein College of Medicine, Bronx, NY, United States.
Anthony D YaoDepartment of Radiology, Montefiore Medical Center, New York, NY, United States.
Yuchen DongDepartment of Radiology, Montefiore Medical Center, New York, NY, United States.
Cindy ZhouAlbert Einstein College of Medicine, Bronx, NY, United States.
Emily HuntAlbert Einstein College of Medicine, Bronx, NY, United States.
Jane WeeDepartment of Radiology, University of California Los Angeles, Los Angeles, CA, United States.
Caroline Delbourgo PattonAlbert Einstein College of Medicine, D. Samuel Gottesman Library, Bronx, NY, United States.
Michael L LiptonDepartment of Radiology, Columbia University Irving Medical Center, New York, NY, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Traumatic Brain Injury (TBI) is a pervasive and important public health concern. TBI can range from mild, resulting in headaches and other neurologic symptoms, to severe resulting in coma and death. Diffusion tensor imaging (DTI) offers the ability to assess tissue microstructure at a level inaccessible to classical neuroimaging methods, such as CT and structural MRI. This systematic review aims to explore studies using DTI in moderate-severe TBI (msTBI) during the 2012-2022 decade, which is the second decade of reported use. The use of DTI in mild TBI during this time period is discussed in our companion systematic review. Methods: A systematic literature review was conducted by a medical librarian in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We searched the electronic databases PubMed/MEDLINE, Embase, Cochrane Library, and Web of Science from 2012 through September 28, 2022. Results: One hundred twenty-nine studies of moderate to severe TBI were included, which accounts for 9,609 patients. There were more longitudinal studies in 2012-2022 compared to the prior decade (25.6% vs. 13%). Fractional anisotropy (FA) and mean diffusivity (MD) were the most commonly used DTI measures. Regardless of acquisition techniques and analysis methods, the majority of studies that compared FA between those with msTBI and controls, found lower FA in msTBI patients. Lower FA was associated with worse cognitive outcomes and greater severity of TBI. Conclusion: Since its first decade (2002-2012) of reported use, DTI applications to msTBI have continued to expand in both quantity and scope, including notable increases in longitudinal studies, those employing whole brain analyses, and those addressing clinical and cognitive outcomes. The most salient finding across studies remains similar to 2002-2012, that despite heterogeneity of clinical and technical features of the individual studies, lower FA is consistently identified in msTBI patients compared to controls. Systematic Review Registration: https://www.crd.york.ac.uk/prospero, identifier CRD42022361318.

Indexed as

cognitionDTIneuroimagingreviewTBI

Identifiers

PMID41725730
PMCPMC12920199

What OpenQuestion holds

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Registered trials

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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.