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Enregistrement W2950424965 · doi:10.82308/2375

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

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

Notice bibliographique

RevueeScholarship@McGill (McGill) · 2019
Typearticle
Langueen
DomaineMedicine
ThématiqueTraumatic Brain Injury Research
Établissements canadiensnon disponible
Organismes subventionnairesUniversité de MontréalMcGill University
Mots-clésTraumatic brain injuryConcussionMedicinePsychological interventionPhysical medicine and rehabilitationPopulationRehabilitationPhysical therapyInjury preventionCognitionPoison controlPsychologyMedical emergencyPsychiatry

Résumé

récupéré en direct d'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.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,006
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,003
Score d'incertitude au seuil0,008

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,006
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0010,001
Science ouverte0,0010,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,066
Tête enseignante GPT0,312
Écart entre enseignants0,246 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2019
Routes d'admission1
Résumé présentoui

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