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Record W2950424965 · doi:10.82308/2375

Perceptual-cognitive training after pediatric mild traumatic brain injury: Towards a sensitive marker of recovery

2019· article· en· W2950424965 on OpenAlexfundno aff
Laurie‐Ann Corbin‐Berrigan

Bibliographic record

VenueeScholarship@McGill (McGill) · 2019
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsnot available
FundersUniversité de MontréalMcGill University
KeywordsTraumatic brain injuryConcussionMedicinePsychological interventionPhysical medicine and rehabilitationPopulationRehabilitationPhysical therapyInjury preventionCognitionPoison controlPsychologyMedical emergencyPsychiatry

Abstract

fetched live from OpenAlex

Background: Pediatric mild traumatic brain injury (mTBI) has drastically increased in incidence over the past years. This condition can present itself through various forms rendering its diagnosis and management difficult for clinicians working with its population. While most cases recuperate over two to four weeks, about a third of children who sustain an mTBI will experience delayed recovery, and could benefit from rehabilitation interventions. Even after recovery is complete, when children go back to their normal life activities, they are at higher risk of sustaining a second injury than others without a history of such an injury, perhaps because we fail to fully identify subtle deficits. Objective: The overarching goal of this work was to address current research gaps in the clinical management of pediatric mTBI, by following three lines of inquiry. The first line of inquiry consisted of identifying predicting factors of delayed recovery. The second line of inquiry aimed to explore the use of three-dimensional multiple object tracking (3D-MOT) as an intervention for children who experience delayed recovery after mTBI. Finally, the use of 3D-MOT was explored as a mean to detect clinical recovery in pediatric mTBI. Methods and results: The first study consisted of identifying predictors of delayed recovery in children who sought care in a specialized mTBI outpatient clinic (N=213). Results showed that total post-concussion symptom score at their initial visit was a predictor of delayed recovery. The second study used theoretical foundations of 3D-MOT to explore the tolerability and safety of six 3D-MOT training sessions in symptomatic children after mTBI (n=10). To investigate tolerability, protocol adherence and deviations were recorded; safety was evaluated through symptom presentation at each training session. No adverse events were reported, minimal protocol deviations were performed and adherence to the training regimen was predominantly maintained. third study explored differences in 3D-MOT training trajectories between children post-mTBI (n=20) and healthy control children (n=14). This study aimed to explore if learning on this training task occurred similarly across groups. Results demonstrated that both groups improved their task performance over time, however, the gains from initial trainings visits occurred more slowly for the mTBI group. The fourth study compared 3D-MOT training gains in children that had been followed in a specialized mTBI outpatient clinic and had been clinically cleared for return to activities (clinically recovered n=10) to those of healthy controls (n=10). Results demonstrated that clinically recovered individuals performed similarly to controls on 3D-MOT over time. The fifth study compared 3D-MOT training gains in children who had been followed in a specialized mTBI clinic and had been clinically cleared for return to activities (clinically recovered n=10) to those of children with recent history of mTBI and being in various phases of recovery (n=12) recruited through community partnerships. Significant group differences were found in initial training sessions where children with a history of mTBI exhibit lower training gains than clinically recovered children on 3D-MOT. Conclusions: This work revealed that it is possible to predict which children will be more likely to experience delayed recovery after a mTBI, within an outpatient clinical setting. It also demonstrated that perceptual-cognitive training through the use of 3D-MOT was a potentially safe and tolerated intervention for children who experience persisting symptoms. Last, it demonstrated that training differences can be perceived in 3D-MOT across groups of individuals, and that this training task can identify differences between healthy controls and children having a history of mTBI. This work show promising use of 3D-MOT in the management of mTBI and sets ground for future studies using this training paradigm.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.066
GPT teacher head0.312
Teacher spread0.246 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

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