Evidence map›Paper›PMID 35619112›Full record

ArticleJournal of neuroengineering and rehabilitation2022

Free-living gait does not differentiate chronic mTBI patients compared to healthy controls.

Dylan Powell, Alan Godfrey, Lucy Parrington, Kody R Campbell, Laurie A King, Sam Stuart

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in Journal of neuroengineering and rehabilitation, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06381674 (Wearable Technology to Characterize and Treat mTBI Subtypes), which is not on this map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.1field-weighted citation impact, top 24% 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.

NCT06381674 narecruitingnot on this mapstarted 2024, after this paper: background citation

Wearable Technology to Characterize and Treat mTBI Subtypes: Biofeedback-Based Precision Rehabilitation

TypeinterventionalSponsorOregon Health and Science UniversityRan2024 to 2028Enrolled100ConditionsMild Traumatic Brain Injury, Concussion, Rehabilitation, Balance ImpairmentArmsVestibular therapy for mTBI augmented with audio and visual real-time biofeedback, Vestibular therapy for mTBI
3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 8 citations in OpenAlex.

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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

6 authors at 2 institutions in 3 countries.

Dylan PowellDepartment of Computer and Information Sciences, Northumbria University, Newcastle-upon-Tyne, UK.
Alan GodfreyDepartment of Computer and Information Sciences, Northumbria University, Newcastle-upon-Tyne, UK.
Lucy ParringtonDepartment of Neurology, Oregon Health and Science University, Portland, OR, USA.
Kody R CampbellDepartment of Neurology, Oregon Health and Science University, Portland, OR, USA.
Laurie A KingDepartment of Neurology, Oregon Health and Science University, Portland, OR, USA.
Sam StuartDepartment of Neurology, Oregon Health and Science University, Portland, OR, USA. sam.stuart@northumbria.ac.uk.ORCID 0000-0001-6846-9372
Oregon Health & Science University · USNorthumbria University · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPhysical function remains a crucial component of mild traumatic brain injury (mTBI) assessment and recovery. Traditional approaches to assess mTBI lack sensitivity to detect subtle deficits post-injury, which can impact a patient's quality of life, daily function and can lead to chronic issues. Inertial measurement units (IMU) provide an opportunity for objective assessment of physical function and can be used in any environment. A single waist worn IMU has the potential to provide broad/macro quantity characteristics to estimate gait mobility, as well as more high-resolution micro spatial or temporal gait characteristics (herein, we refer to these as measures of quality). Our recent work showed that quantity measures of mobility were less sensitive than measures of turning quality when comparing the free-living physical function of chronic mTBI patients and healthy controls. However, no studies have examined whether measures of gait quality in free-living conditions can differentiate chronic mTBI patients and healthy controls. This study aimed to determine whether measures of free-living gait quality can differentiate chronic mTBI patients from controls.

methodsThirty-two patients with chronic self-reported balance symptoms after mTBI (age: 40.88 ± 11.78 years, median days post-injury: 440.68 days) and 23 healthy controls (age: 48.56 ± 22.56 years) were assessed for ~ 7 days using a single IMU at the waist on a belt. Free-living gait quality metrics were evaluated for chronic mTBI patients and controls using multi-variate analysis. Receiver operating characteristics (ROC) and Area Under the Curve (AUC) analysis were used to determine outcome sensitivity to chronic mTBI.

resultsFree-living gait quality metrics were not different between chronic mTBI patients and controls (all p > 0.05) whilst controlling for age and sex. ROC and AUC analysis showed stride length (0.63) was the most sensitive measure for differentiating chronic mTBI patients from controls.

conclusionsOur results show that gait quality metrics determined through a free-living assessment were not significantly different between chronic mTBI patients and controls. These results suggest that measures of free-living gait quality were not impaired in our chronic mTBI patients, and/or, that the metrics chosen were not sensitive enough to detect subtle impairments in our sample.

Indexed as

Brain ConcussionAdultAgedGaitHumansMiddle AgedQuality of LifeConcussionGaitInertial measurement unitmTBI

Identifiers

PMID35619112
PMCPMC9137158
OpenAlexW4281569636

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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.