Evidence map›Paper›PMID 26806406›Full record

ArticleAcademic emergency medicine : official journal of the Society for Academic Emergency Medicine2016

A Novel Tool for Evaluation of Mild Traumatic Brain Injury Patients in the Emergency Department: Does Robotic Assessment of Neuromotor Performance Following Injury Predict the Presence of Postconcussion Symptoms at Follow-up?

Vignesh Subbian, Jonathan J Ratcliff, Joseph J Korfhagen, Kimberly W Hart, Jason M Meunier, George J Shaw, Christopher J Lindsell, Fred R Beyette

Open access · bronzeAbstract read
In one paragraph

Article in Academic emergency medicine : official journal of the Society for Academic Emergency Medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 2 pooled it
2.1field-weighted citation impact, top 13% 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

8 citing papers in PubMed, 2 syntheses or guidelines pooled it, 16 citations in OpenAlex.

  1. Pooled it
  2. Guideline
  3. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 1 institution in 1 country.

Vignesh SubbianDepartment of Electrical Engineering and Computing Systems, University of Cincinnati, Cincinnati, OH.
Jonathan J RatcliffDepartment of Emergency Medicine, University of Cincinnati, Cincinnati, OH.
Joseph J KorfhagenDepartment of Emergency Medicine, University of Cincinnati, Cincinnati, OH.
Kimberly W HartDepartment of Emergency Medicine, University of Cincinnati, Cincinnati, OH.
Jason M MeunierDepartment of Emergency Medicine, University of Cincinnati, Cincinnati, OH.
George J ShawDepartment of Emergency Medicine, University of Cincinnati, Cincinnati, OH.
Christopher J LindsellDepartment of Emergency Medicine, University of Cincinnati, Cincinnati, OH.
Fred R BeyetteDepartment of Electrical Engineering and Computing Systems, University of Cincinnati, Cincinnati, OH.
University of Cincinnati · US

Funding

LCenter for Clinical and Translational Science and TrainingUL1TR001425 · NCATS · UNIVERSITY OF CINCINNATI · PI HEUBI, JAMES E., KISSELA, BRETT M · 2015 to 2024
$37.5M
Cincinnati Center for Clinical and Translational Sciences and TrainingUL1TR000077 · NCATS · UNIVERSITY OF CINCINNATI · PI HEUBI, JAMES E., TSEVAT, JOEL · 2012 to 2014
$9.9M
TrainingU54EB007954 · NIBIB · UNIVERSITY OF CINCINNATI · PI BEYETTE, FRED RICHARD · 2007 to 2011
$9.4M
NCATS NIH HHS 8UL1-TR000077NCATS NIH HHS UL1 TR000077NCATS NIH HHS UL1 TR001425NIBIB NIH HHS 5U54EB007954NIBIB NIH HHS U54 EB007954
6 · The paper itself

Abstract

objectivesPostconcussion symptoms (PCS) are a common complication of mild traumatic brain injury (TBI). Currently, there is no validated clinically available method to reliably predict at the time of injury who will subsequently develop PCS. The purpose of this study was to determine if PCS following mild TBI can be predicted during the initial presentation to an emergency department (ED) using a novel robotic-assisted assessment of neurologic function.

methodsAll patients presenting to an urban ED with a chief complaint of head injury within the preceding 24 hours were screened for inclusion from March 2013 to April 2014. The enrollment criteria were as follows: 1) age of 18 years or greater, 2) ability and willingness to provide written informed consent, 3) blunt head trauma and clinical diagnosis of isolated mild TBI by the treating physician, and 4) blood alcohol level of <100 mg/dL. Eligible mild TBI patients were enrolled and their neuromotor function was assessed in the ED using a battery of five tests that cover a range of proprioceptive, visuomotor, visuospatial, and executive function performance metrics. At 3 weeks postinjury, participants were contacted via telephone to complete the Rivermead Post-Concussion Symptoms Questionnaire to assess the presence of significant PCS.

resultsA total of 66 mild TBI patients were enrolled in the study with 42 of them completing both the ED assessment and the follow-up; 40 patients were included in the analyses. The area under the receiver operating characteristic curve (AUC) for the entire test battery was 0.72 (95% confidence interval [CI] = 0.54 to 0.90). The AUC for tests that primarily measure visuomotor and proprioceptive performance were 0.80 (95% CI = 0.65 to 0.95) and 0.71 (95% CI = 0.53 to 0.89), respectively.

conclusionsThe robotic-assisted test battery has the ability to discriminate between subjects who developed PCS and those who did not. Additionally, poor visuomotor and proprioceptive performance were most strongly associated with subsequent PCS.

Indexed as

AdultBrain InjuriesDiagnostic Techniques, NeurologicalEmergency Service, HospitalFemaleFollow-Up StudiesHead Injuries, ClosedHumansMaleMiddle AgedObserver VariationPost-Concussion SyndromeRoboticsSensitivity and SpecificityUrban PopulationYoung Adult

Identifiers

PMID26806406
PMCPMC4847435
OpenAlexW2264856337

What OpenQuestion holds

Textmetadata
LicenceTDM
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.