Evidence map›Paper›PMID 25698950›Full record

ReviewFrontiers in human neuroscience2015

Traumatic brain injury detection using electrophysiological methods.

Paul E Rapp, David O Keyser, Alfonso Albano, Rene Hernandez, Douglas B Gibson, Robert A Zambon, W David Hairston, John D Hughes, Andrew Krystal, Andrew S Nichols

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in human neuroscience, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 68 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
68citing papers in PubMed, 3 pooled it
7.1field-weighted citation impact, top 2% 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

68 citing papers in PubMed, 3 syntheses or guidelines pooled it, 168 citations in OpenAlex.

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  10. Impact Induces Phagocytic Defect in Reactive Microglia.bioRxiv : the preprint server for biology · 2025
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8 more citing papers are in PubMed but not listed here.

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

10 authors at 8 institutions in 1 country.

Paul E RappUniformed Services University of the Health Sciences School of Medicine , Bethesda, MD , USA.
David O KeyserUniformed Services University of the Health Sciences School of Medicine , Bethesda, MD , USA.
Alfonso AlbanoBryn Mawr College , Bryn Mawr, PA , USA.
Rene HernandezUS Navy Bureau of Medicine and Surgery , Frederick, MD , USA.
Douglas B GibsonU.S. Army Research Institute , Fort Belvoir, VA , USA.
Robert A ZambonBooz Allen Hamilton Inc. , McLean, VA , USA.
W David HairstonU. S. Army Research Laboratory, Aberdeen Proving Ground , Aberdeen, MD , USA.
John D HughesNaval Medical Research Center , Silver Spring, MD , USA.
Andrew KrystalDuke University , Durham, NC , USA.
Andrew S NicholsBooz Allen Hamilton Inc. , McLean, VA , USA.
Booz Allen Hamilton (United States) · USUniformed Services University of the Health Sciences · USBryn Mawr College · USDEVCOM Army Research Laboratory · USDuke University · USNaval Medical Research Command · USUnited States Army · USUnited States Department of the Navy · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Measuring neuronal activity with electrophysiological methods may be useful in detecting neurological dysfunctions, such as mild traumatic brain injury (mTBI). This approach may be particularly valuable for rapid detection in at-risk populations including military service members and athletes. Electrophysiological methods, such as quantitative electroencephalography (qEEG) and recording event-related potentials (ERPs) may be promising; however, the field is nascent and significant controversy exists on the efficacy and accuracy of the approaches as diagnostic tools. For example, the specific measures derived from an electroencephalogram (EEG) that are most suitable as markers of dysfunction have not been clearly established. A study was conducted to summarize and evaluate the statistical rigor of evidence on the overall utility of qEEG as an mTBI detection tool. The analysis evaluated qEEG measures/parameters that may be most suitable as fieldable diagnostic tools, identified other types of EEG measures and analysis methods of promise, recommended specific measures and analysis methods for further development as mTBI detection tools, identified research gaps in the field, and recommended future research and development thrust areas. The qEEG study group formed the following conclusions: (1) Individual qEEG measures provide limited diagnostic utility for mTBI. However, many measures can be important features of qEEG discriminant functions, which do show significant promise as mTBI detection tools. (2) ERPs offer utility in mTBI detection. In fact, evidence indicates that ERPs can identify abnormalities in cases where EEGs alone are non-disclosing. (3) The standard mathematical procedures used in the characterization of mTBI EEGs should be expanded to incorporate newer methods of analysis including non-linear dynamical analysis, complexity measures, analysis of causal interactions, graph theory, and information dynamics. (4) Reports of high specificity in qEEG evaluations of TBI must be interpreted with care. High specificities have been reported in carefully constructed clinical studies in which healthy controls were compared against a carefully selected TBI population. The published literature indicates, however, that similar abnormalities in qEEG measures are observed in other neuropsychiatric disorders. While it may be possible to distinguish a clinical patient from a healthy control participant with this technology, these measures are unlikely to discriminate between, for example, major depressive disorder, bipolar disorder, or TBI. The specificities observed in these clinical studies may well be lost in real world clinical practice. (5) The absence of specificity does not preclude clinical utility. The possibility of use as a longitudinal measure of treatment response remains. However, efficacy as a longitudinal clinical measure does require acceptable test-retest reliability. To date, very few test-retest reliability studies have been published with qEEG data obtained from TBI patients or from healthy controls. This is a particular concern because high variability is a known characteristic of the injured central nervous system.

Indexed as

EEGevent-related potentialsnon-linear dynamical analysisqEEGtraumatic brain injury

Identifiers

PMID25698950
PMCPMC4316720
OpenAlexW2132029553

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.